Background Limited evidence exists to guide Elexacaftor-Tezacaftor-Ivacaftor (ETI) use in adults with cystic fibrosis (awCF) and preserved lung function (ppFEV1 >90%). To address the resulting variability in prescribing practices, we conducted a European survey among a group of adult CF centres aiming at identifying factors influencing ETI initiation decisions in adults with preserved lung function. Methods Between April and June 2024, we invited 25 ECFS prescribers from 25 adult CF centres to participate in a web-based survey to explore factors influencing ETI initiation in adults with CF and ppFEV₁ >90%. The survey questionnaire collected data on centre characteristics, prescribing ETI attitudes, and the impact of specific clinical variables on ETI prescription decision in this subgroup. Results Twenty-three CF specialists (92%) responded. Most specialists (69.6%) favoured early treatment initiation in all eligible patients. A key factors influencing ETI initiation decisions was the presence of respiratory symptoms. In adults with preserved lung function, however, microbiological and imaging features emerged as the most influential factors driving treatment decision. While patient willingness and symptoms strongly encouraged ETI use, factors like age over 50, a history of mental health issues, and pregnancy desire resulted in conflicting prescribing attitudes among centers. Conclusions Although several disease markers more consistently support the decision to initiate ETI in individuals with preserved lung function, the absence of clear clinical guidance contributes to heterogeneous prescribing practices across centres. This highlights the need for longitudinal studies to clarify the long-term outcomes of ETI in this population.

Background: Although cystic fibrosis (CF) standards of care have been produced and regularly updated, they are not specifically targeting at the adult population. The ECFS Standards of Care Project established an international task force of experts to identify quality standards for adults with CF and assess their adherence. Methods: This study was composed of two phases. In the first one, a task force of international experts derived from published guidelines and graded ten quality standards for adult CF care using a modified Delphi methodology. In the second phase, an international audit was conducted among adult CF centers to retrospectively validate the quality statements and monitor adherence. Results: The task force identified 10 quality standards specific to the care of adults with CF, mainly based on the 2018 ECFS standards of care. 14 adult CF centers participated in the audit, which showed that most quality standards for the management of CF in adults are met across Europe. Heterogeneity in adherence to standards was found across centers according to geographical setting and centers' characteristics . Conclusions: The identification of quality standards is a valuable resource for the standardization and monitoring of care delivery across centers taking care of adults with CF.

Introduction. One third of people with CF in the UK are co-infected by both Staphylococcus aureus and Pseudomonas aeruginosa. Chronic bacterial infection in CF contributes to the gradual destruction of lung tissue, and eventually respiratory failure in this group.Gap Statement. The contribution of S. aureus to cystic fibrosis (CF) lung decline in the presence or absence of P. aeruginosa is unclear. Defining the molecular and phenotypic characteristics of a range of S. aureus clinical isolates will help further under-stand its pathogenic capabilities.Aim. Our objective was to use molecular and phenotypic tools to characterise twenty -five clinical S. aureus isolates collected from mono-and coinfection with P. aeruginosa from people with CF at the Royal Victoria Infirmary, Newcastle upon Tyne.Methodology. Genomic DNA was extracted and sequenced. Multilocus sequence typing was used to construct phylogeny from the seven housekeeping genes. A pangenome was calculated using Roary, and cluster of Orthologous groups were assigned using eggNOG-mapper which were used to determine differences within core, accessory, and unique genomes. Characterisa-tion of sequence type, clonal complex, agr and spa types was carried out using PubMLST, eBURST, AgrVATE and spaTyper, respectively. Antibiotic resistance was determined using Kirby -Bauer disc diffusion tests. Phenotypic testing of haemolysis was carried out using ovine red blood cell agar plates and mucoid phenotypes visualised using Congo red agar.Results. Clinical strains clustered closely based on agr type, sequence type and clonal complex. COG analysis revealed statisti-cally significant enrichment of COG families between core, accessory and unique pangenome groups. The unique genome was significantly enriched for replication, recombination and repair, and defence mechanisms. The presence of known virulence genes and toxins were high within this group, and unique genes were identified in 11 strains. Strains which were isolated from the same patient all surpassed average nucleotide identity thresholds, however, differed in phenotypic traits. Antimicrobial resistance to macrolides was significantly higher in the coinfection group.Conclusion. There is huge variation in genetic and phenotypic capabilities of S. aureus strains. Further studies on how these may differ in relation to other species in the CF lung may give insight into inter-species interactions.

Palliative and supportive care are integral components of a comprehensive cystic fibrosis (CF) service and aim to maintain optimal health and well-being throughout the person's life span. Specialist palliative care provides additional knowledge and skills in mitigating complex symptoms and in supporting the CF team in meeting the needs of people with CF. Symptom control, holistic support, advance care planning and end-of-life care are key aspects of palliative care, and often run in parallel with disease-modifying treatments and consideration of potential lung transplantation. Services need to be flexible to meet the individual person's needs and wishes. In integrated models of care, both CF and palliative specialists combine to bring their knowledge and skills to provide optimal, holistic care.

Studies of microbiota reveal inter-relationships between the microbiomes of the gut and lungs. This relationship may influence the progression of lung disease, particularly in patients with cystic fibrosis (CF), who often experience extraoesophageal reflux (EOR). Despite identifying this relationship, it is not well characterised. Our hypothesis is that the gastric and lung microbiomes in CF are related, with the potential for aerodigestive pathophysiology. We evaluated gastric and sputum bacterial communities by culture and 16S rRNA gene sequencing in 13 CF patients. Impacts of varying levels of bile acids, pepsin and pH on patient isolates of Pseudomonas aeruginosa (Pa) were evaluated. Clonally related strains of Pa and NTM were identified in gastric and sputum samples from patients with symptoms of EOR. Bacterial diversity was more pronounced in sputa compared to gastric juice. Gastric and lung bile and pepsin levels were associated with Pa biofilm formation. Analysis of the aerodigestive microbiomes of CF patients with negative sputa indicates that the gut can be a reservoir of Pa and NTM. This combined with the CF patient’s symptoms of reflux and potential aspiration, highlights the possibility of communication between microorganisms of the gut and the lungs. This phenomenon merits further research.

ABSTRACT Introduction One third of people with CF in the UK are co-infected by both Staphylococcus aureus and Pseudomonas aeruginosa . Chronic bacterial infection in CF contributes to the gradual destruction of lung tissue, and eventually respiratory failure in this group. Gap Statement The contribution of S. aureus to cystic fibrosis (CF) lung decline in the presence or absence of P. aeruginosa is unclear. Defining the molecular and phenotypic characteristics of a range of S. aureus clinical isolates will help further understand its pathogenic capabilities. Aim Our objective was to use molecular and phenotypic tools to characterise twenty-five clinical S. aureus isolates collected from mono- and coinfection with P. aeruginosa from people with CF at the Royal Victoria Infirmary, Newcastle upon Tyne. Methodology Genomic DNA was extracted and sequenced. Multilocus sequence typing was used to construct phylogeny from the seven housekeeping genes. A pangenome was calculated using Roary. and cluster of Orthologous groups were assigned using eggNOG-mapper which were used to determine differences within core, accessory, and unique genomes. Characterisation of sequence type, clonal complex, agr and spa types was carried out using PubMLST, eBURST, AgrVATE and spaTyper, respectively. Antibiotic resistance was determined using Kirby Bauer disk diffusion tests. Phenotypic testing of haemolysis was carried out using ovine red blood cell agar plates and mucoid phenotypes visualised using Congo red agar. Results Clinical strains clustered closely based on agr type, sequence type and clonal complex. COG analysis revealed statistically significant enrichment of COG families between core, accessory and unique pangenome groups. The unique genome was significantly enriched for replication, recombination and repair, and defence mechanisms. The presence of known virulence genes and toxins were high within this group, and unique genes were identified in 11 strains. Strains which were isolated from the same patient all surpassed average nucleotide identity thresholds, however, differed in phenotypic traits. Antimicrobial resistance to macrolides was significantly higher in the coinfection group. Conclusion There is huge variation in genetic and phenotypic capabilities of S. aureus strains. Further studies on how these may differ in relation to other species in the CF lung may give insight into inter-species interactions. Data summary The assembled GenBank (gbk) files for all clinical isolates in this study have been deposited in ENA under the study accession PRJEB56184, accession numbers for each of the twenty-five clinical isolates have been provided in Table S1. The reference strains were collected from the NCBI BioSample database ( www.ncbi.nlm.nih.gov/biosample ): MRSA_252 (NC_002952.2), HO 5096 0412 (NC_017763.1), ST398 (NC_017333.1) and NCTC8325 (NC_007795.1).

The authors regret an error has occurred in the description and calculation of dose-weighted composite MPR (dwcMPR) for participants on multiple medicines. We described dose-weighting according to the number of dispensed inhaled medications. In fact, the dose-weighting should be based on the number of prescribed inhaled medications to ensure there is no gap between the cMPR and electronic data capture (EDC) adherence if someone has indeed used all the medicines that were supplied. Therefore, the first step to calculate dwcMPR should have been: calculate the total prescribed doses of medicine by adding up of all individual values of daily prescribed dose × days.We have now re-calculated the relevant values for the difference between dwcMPR and unadjusted EDC adherence, and the cost of excess supply using this method. We have also repeated the relevant analyses. A summary of the updated results are as follow:1.Table 1 (demographics) – Median % dwcMPR 67 (IQR 39 to 91)2.Figure 1 (Bland-Altman plot of dwcMPR versus EDC adherence) – Mean difference 10% (limits of agreement -38% to 59%). An updated Figure 1 is attached.3.Table 2 (dwcMPR versus EDC adherence discrepancy and excess supply cost) – Discrepancy median 9% (IQR -2% to 21%). Mean excess supply cost for overall cohort £822 (95% CI £587 to £1057). The total excess supply cost was £226,104 among the 275 adults. An updated Table 2 is attached.Table 2dwcMPR versus EDC adherence discrepancy; and excess supply cost.†Estimates of excess supply cost are highly conservative because of contingency, see ‘Discussion’ paragraph 6. Excess supply cost was calculated as the cost of excess medicine box(es) delivered or collected after accounting for the discrepancy between EDC adherence and dwcMPR with 20% contingency. For example, if a person has an excess supply of 83 aztreonam nebules, the excess supply cost was calculated as “0” because each box of aztreonam has 84 nebules.,‡Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.ResultsDiscrepancy between dwcMPR and EDC adherence Median (IQR)9% (–2 to 21%) Mean (95% CI)10% (7 to 13%)Discrepancy between dwcMPR and EDC adherence in different adherence levels EDC adherence <50%, Median (IQR)15% (6 to 30%) EDC adherence 50 to <80%, Median (IQR)5% (–9 to 17%) EDC adherence ≥80%, Median (IQR)2% (–11 to 11%)Discrepancy between dwcMPR with 20% contingency and EDC adherence Median (IQR)–2% (–16 to 14%) Mean (95% CI)–1% (–4 to 3%)Excess supply cost in £ for the overall cohort Median (IQR)0 (0 to 760) Mean (95% CI)822 (587 to 1,057)Excess supply cost in £ according to the source of recruitment, mean (95% CI) Learning health system1,201 (590 to 1,812) Usual care arm of the ACtiF trial713 (446 to 979) Intervention arm of the ACtiF trial583 (313 to 853)Excess supply cost in £ according to age categories, mean (95% CI) ≤18 years594 (96 to 1,091) 19 to 25 years1,515 (977 to 2,055) 26 to 34 years447 (236 to 658) ≥35 years409 (0 to 831)Excess supply cost in £ according to gender, mean (95% CI) Male908 (522 to 1,293) Female731 (467 to 996)Excess supply cost in £ according to P. aeruginosa status, mean (95% CI) Not chronic732 (427 to 1,037) Chronic infection886 (545 to 1,227)Excess supply cost in £ according to %FEV1 categories, mean (95% CI) <40%704 (219 to 1,188) 40 to 69.9%917 (564 to 1,270) ≥70%767 (351 to 1,183)Excess supply cost in £ according to source of inhaled medicine supply, mean (95% CI) Hospital1,020 (504 to 1,536) Homecare only1,086 (644 to 1,527) ≥2 supply sources559 (230 to 887)Excess supply cost in £ according to number of inhaled medicines, mean (95% CI) 1 medicine only595 (319 to 870) ≥2 different medicines878 (593 to 1,163)Excess supply cost in £ according to prescription of inhaled antibiotics, mean (95% CI)d Only on inhaled mucolytic452 (246 to 658) ≥1 inhaled antibiotic964 (649 to 1,278)Excess supply cost in £ according to use of expensive antibiotics, mean (95% CI) Neither inhaled aztreonam nor levofloxacin819 (564 to 1,074) On inhaled aztreonam and/or levofloxacin836 (215 to 1,457)Excess supply cost in £ according to unadjusted EDC adherence, mean (95% CI) <50%1,540 (1,078 to 2,001) 50 to <80%422 (125 to 718) ≥80%82 (15 to 148)† Estimates of excess supply cost are highly conservative because of contingency, see ‘Discussion’ paragraph 6. Excess supply cost was calculated as the cost of excess medicine box(es) delivered or collected after accounting for the discrepancy between EDC adherence and dwcMPR with 20% contingency. For example, if a person has an excess supply of 83 aztreonam nebules, the excess supply cost was calculated as “0” because each box of aztreonam has 84 nebules.‡ Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3. Open table in a new tab 4.Table 3 (results from linear regression models) – With excess supply cost in £ as the outcome, the unadjusted regression coefficient for unadjusted EDC adherence was -739 (95% CI -986 to -491) and the adjusted regression coefficient was -660 (95% CI -908 to -410). Similar to the initial analyses, excess supply cost was higher among those with EDC adherence <50%, aged 19-25 years and on inhaled antibiotics rather than mucolytics only. An updated Table 3 is attached.Table 3Summary of the excess supply cost results from linear regression models.†Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.VariableExcess supply cost in £Unadjusted regression coefficient (95% CI)P-valueAdjusted regression coefficient ‡Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2. (95% CI)P-valueUnadjusted EDC adherence AEDC adherence category was analysed as an ordinal variable because Table 2 showed a step-wise reduction in excess supply cost with increasing level of adherence category. For the univariate analysis, an increase in one level of adherence category (e.g. from <50% to 50–79%) was associated with a decrease of £739 (95% CI £491–986) in excess supply cost. For the multivariate analysis, an increase in one level of adherence category was associated with a decrease of £660 (95% CI £411–908) in excess supply cost, all else being equal.–739 (–986 to –491)<0.001–660 (–908 to –411)<0.001Age <19 years or >25 years BAge was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: ≤18 years, 26–34 years and ≥35 years. (reference)Age 19 to 25 years1,072 (595 to 1,548)<0.001790 (324 to 1,256)<0.001Only on inhaled mucolytic ‡Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2. (reference)≥1 inhaled antibiotic476 (–38 to 990)0.069586 (111 to 1,062)0.0161 medicine only (reference)≥2 different medicines283 (–309 to 876)0.347Source of recruitment Learning health system (reference) Usual care arm of the ACtiF trial–488 (–1,166 to 191)–618 (–1,251 to 16)0.1580.056 Intervention arm of the ACtiF trialMale (reference)Female–177 (–648 to 295)0.526Not chronic P. aeruginosa (reference)Chronic P. aeruginosa infection154 (–324 to 632)0.470%FEV1 <40% or ≥70% C%FEV1 was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: <40% and ≥70%. (reference)%FEV1 40 to 69.9%157 (–325 to 638)0.552≥2 medicine supply sources DThe source of inhaled medicine supply was dichotomised because Table 2 showed similar amount of excess supply cost for those who received all supply from hospital only and all supply via homecare only. In an exploratory multiple regression analysis accounting for EDC adherence level and age 19–25 years, source of inhaled medicine supply was not associated with excess supply cost in £ (adjusted regression coefficient of 432, 95% CI -6 to 869, p-value 0.053. The source of inhaled medicine supply reached statistical significance in the univariate analysis because those receiving supply from a single source have somewhat lower EDC adherence level compared to those receiving supply from ≥2 sources (median 48%, IQR 19–84% vs median 64%, IQR 28–87%, Mann-Whitney p-value 0.064). (reference)Supply from hospital only or homecare only504 (35 to 972)0.035Neither aztreonam nor levofloxacin (reference)On inhaled aztreonam and/or levofloxacin17 (–594 to 628)0.956† Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.‡ Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2.A EDC adherence category was analysed as an ordinal variable because Table 2 showed a step-wise reduction in excess supply cost with increasing level of adherence category. For the univariate analysis, an increase in one level of adherence category (e.g. from <50% to 50–79%) was associated with a decrease of £739 (95% CI £491–986) in excess supply cost. For the multivariate analysis, an increase in one level of adherence category was associated with a decrease of £660 (95% CI £411–908) in excess supply cost, all else being equal.B Age was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: ≤18 years, 26–34 years and ≥35 years.C %FEV1 was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: <40% and ≥70%.D The source of inhaled medicine supply was dichotomised because Table 2 showed similar amount of excess supply cost for those who received all supply from hospital only and all supply via homecare only. In an exploratory multiple regression analysis accounting for EDC adherence level and age 19–25 years, source of inhaled medicine supply was not associated with excess supply cost in £ (adjusted regression coefficient of 432, 95% CI -6 to 869, p-value 0.053. The source of inhaled medicine supply reached statistical significance in the univariate analysis because those receiving supply from a single source have somewhat lower EDC adherence level compared to those receiving supply from ≥2 sources (median 48%, IQR 19–84% vs median 64%, IQR 28–87%, Mann-Whitney p-value 0.064). Open table in a new tab 5.Figure 2 (tree-based analysis) – Similar to the initial analyses, excess supply cost was higher among those with EDC adherence <50%, aged 19-25 years and on inhaled antibiotics rather than mucolytics only. An updated Figure 2 is attached.Figure 2Tree-based diagram † summarising excess supply cost ‡ according to different subgroups Ω.Show full caption† The tree-based method is an efficient approach to look inside the “black box” of regression analysis and allows the comparison of excess supply cost between clinically meaningful subgroups. EDC adherence level (the covariate most strongly associated with excess supply cost) was used for the first ‘layer’ division of the study sample, age (the next strongest associated covariate) was used for the second ‘layer’ and prescription of inhaled antibiotic (the other associated covariate) was used for the third ‘layer’. For all divisions, similar categories used in the multiple regression analysis were applied, i.e. <50% versus 50 to <80% versus ≥80% for EDC adherence level; 19 to 25 years versus <19 years or >25 years for age; and prescribed ≥1 inhaled antibiotic versus on mucolytic only for the prescription of inhaled medicines.‡ Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3. The minimum value for excess supply cost was “0”, as stated in the ‘Methods’. Therefore, if the confidence interval returned a negative value due to imprecise estimate from small sample sizes, the lower limit of the confidence interval was summarised as “0”.Ω Statistical tests were not performed for subgroups with sample size <20 due to imprecise estimate from the small sample size. These subgroups are marked in grey.A For the comparison of excess supply cost between three subgroups in this ‘layer’, ANOVA p-value was <0.001.B For the comparison of excess supply cost between five subgroups with sample size ≥20 in this ‘layer’, ANOVA p-value was <0.001 i T-test p-value = 0.007 ii T-test p-value = 0.130.C For the comparison of excess supply cost between six subgroups with sample size ≥20 in this ‘layer’, ANOVA p-value was <0.001 iii T-test p-value = 0.081 iv T-test p-value = 0.346.View Large Image Figure ViewerDownload Hi-res image Download (PPT)6.Appendix A (participants with skewed MPR data) – the details for skewed MPR data and the values of dwcMPR, ‘standard’ composite MPR (i.e. a mean of all individual MPR) and unadjusted EDC adherence are now tabulated in Table S3 (attached). Where MPR data were skewed, EDC adherence is more similar to dwcMPR compared to ‘standard’ cMPR.Table S3Details of participants with skewed MPR data; and a comparison between unadjusted EDC adherence, dwcMPR and ‘standard’ cMPR.Details of skewed MPR data †The skewed (i.e. excessively high or excessively low) MPR reflect the fact that on occasion, lack of system optimisation in medicine management can create quite marked over-supply. Most of the excessively skewed MPR occurred in short-term prescriptions, for example a salbutamol prescription for only 20 days in Person #2. In the extant CF literature, composite MPR (cMPR) is calculated simply as a mean of all individual MPR [1,2]. That means the skewed individual MPR data can have a disproportionate impact on the cMPR. For example, salbutamol MPR of >2000% for Person #2 resulted in ‘standard’ cMPR of 445%. With dose-weighting, short-term prescriptions by the virtue of fewer prescribed doses are given a lower weight compared to longer-term prescriptions. For example, the salbutamol for Person #2 was only given a weight of 0.021 (out of 1.000) because five other medications were prescribed for longer durations (dornase alfa for 365 days, colistimethate for 162 days, hypertonic saline for 365 days, tobramycin for 141 days and aztreonam lysine for 40 days). As a result, dwcMPR is more resistant to skewed MPR data and more accurately reflect the overall amount of supplied medications.Unadjusted EDC adherencedwcMPR‘Standard’ cMPRPerson #1 – this person was only prescribed salbutamol for 5 days but one box (10 days’ worth of supply) was supplied, hence MPR for salbutamol was 200%.90%115%142%Person #2– salbutamol prescription was for only 20 days but 12 months of supplies (48 boxes) were delivered, hence MPR for salbutamol was >2000%.78%90%445%Person #3 – salbutamol prescription was for only 30 days but 6 months of supplies (27 boxes) were delivered, hence MPR for salbutamol was 900%.73%119%278%Person #4 – MPR for hypertonic saline was 190%.2%139%139%Person #5 – MPR for salbutamol was 99% compared to MPR for hypertonic saline of 5%.33%30%52%Person #6 – MPR for dornase alfa was 36% compared to MPR for colistimethate of 6%.5%18%21%Person #7– unable to find evidence for the supply of piperacillin-tazobactam post hospital admission although the prescription was continued, hence MPR for piperacillin-tazobactam was only 5%.19%56%55%Person #8 – tobramycin prescription was stopped after 2 days but one box was supplied, hence MPR for tobramycin was 1400%.24%76%297%Person #9 – this person was only prescribed colistin for 18 days but on-going supply resulted in an MPR of 570% for colistin.39%57%203%† The skewed (i.e. excessively high or excessively low) MPR reflect the fact that on occasion, lack of system optimisation in medicine management can create quite marked over-supply. Most of the excessively skewed MPR occurred in short-term prescriptions, for example a salbutamol prescription for only 20 days in Person #2. In the extant CF literature, composite MPR (cMPR) is calculated simply as a mean of all individual MPR 1Quittner A.L. Zhang J. Marynchenko M. Chopra P.A. Signorovitch J. Yushkina Y. Rieckert K.A.. Pulmonary medication adherence and health-care use in cystic fibrosis.Chest. 2014; 146: 142-151Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar, 2Eakin M.N. Bilderback A. Boyle M.P. Mogayzel P.J. Riekert K.A.. Longitudinal association between medication adherence and lung health in people with cystic fibrosis.J Cyst Fibros. 2011; 10: 258-264Abstract Full Text Full Text PDF PubMed Scopus (152) Google Scholar. That means the skewed individual MPR data can have a disproportionate impact on the cMPR. For example, salbutamol MPR of >2000% for Person #2 resulted in ‘standard’ cMPR of 445%. With dose-weighting, short-term prescriptions by the virtue of fewer prescribed doses are given a lower weight compared to longer-term prescriptions. For example, the salbutamol for Person #2 was only given a weight of 0.021 (out of 1.000) because five other medications were prescribed for longer durations (dornase alfa for 365 days, colistimethate for 162 days, hypertonic saline for 365 days, tobramycin for 141 days and aztreonam lysine for 40 days). As a result, dwcMPR is more resistant to skewed MPR data and more accurately reflect the overall amount of supplied medications. Open table in a new tab In Appendix C, we calculated the minimum excess supply cost based on the assumption that more expensive medications were used first and maximum excess supply cost based on the assumption that cheaper medications were used first. The minimum and maximum excess supply costs were calculated directly from the total doses of supplied medications without the need to calculate a composite MPR. Therefore, the results in Appendix C are unaffected.Overall, the reduction in excess supply cost (mean £822, 95% CI £587-1057 with the revised method vs mean £1124, 95% CI £855-1394 with the method as originally described) does not alter the conclusions of the paper. MPR provides information about medicine supply but over-estimates actual medicine use. The excess supply cost was highest among those with lowest EDC adherence. Our study provides a conservative estimate of excess inhaled medicines supply cost among adults with CF in the UK. Importantly, the lowest excess supply cost of £1,325/patient/year among those with EDC adherence <50%, suggests there are potential annual savings of around £2.5 million.The authors would like to apologise for any inconvenience caused. The authors regret an error has occurred in the description and calculation of dose-weighted composite MPR (dwcMPR) for participants on multiple medicines. We described dose-weighting according to the number of dispensed inhaled medications. In fact, the dose-weighting should be based on the number of prescribed inhaled medications to ensure there is no gap between the cMPR and electronic data capture (EDC) adherence if someone has indeed used all the medicines that were supplied. Therefore, the first step to calculate dwcMPR should have been: calculate the total prescribed doses of medicine by adding up of all individual values of daily prescribed dose × days. We have now re-calculated the relevant values for the difference between dwcMPR and unadjusted EDC adherence, and the cost of excess supply using this method. We have also repeated the relevant analyses. A summary of the updated results are as follow:1.Table 1 (demographics) – Median % dwcMPR 67 (IQR 39 to 91)2.Figure 1 (Bland-Altman plot of dwcMPR versus EDC adherence) – Mean difference 10% (limits of agreement -38% to 59%). An updated Figure 1 is attached.3.Table 2 (dwcMPR versus EDC adherence discrepancy and excess supply cost) – Discrepancy median 9% (IQR -2% to 21%). Mean excess supply cost for overall cohort £822 (95% CI £587 to £1057). The total excess supply cost was £226,104 among the 275 adults. An updated Table 2 is attached.Table 2dwcMPR versus EDC adherence discrepancy; and excess supply cost.†Estimates of excess supply cost are highly conservative because of contingency, see ‘Discussion’ paragraph 6. Excess supply cost was calculated as the cost of excess medicine box(es) delivered or collected after accounting for the discrepancy between EDC adherence and dwcMPR with 20% contingency. For example, if a person has an excess supply of 83 aztreonam nebules, the excess supply cost was calculated as “0” because each box of aztreonam has 84 nebules.,‡Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.ResultsDiscrepancy between dwcMPR and EDC adherence Median (IQR)9% (–2 to 21%) Mean (95% CI)10% (7 to 13%)Discrepancy between dwcMPR and EDC adherence in different adherence levels EDC adherence <50%, Median (IQR)15% (6 to 30%) EDC adherence 50 to <80%, Median (IQR)5% (–9 to 17%) EDC adherence ≥80%, Median (IQR)2% (–11 to 11%)Discrepancy between dwcMPR with 20% contingency and EDC adherence Median (IQR)–2% (–16 to 14%) Mean (95% CI)–1% (–4 to 3%)Excess supply cost in £ for the overall cohort Median (IQR)0 (0 to 760) Mean (95% CI)822 (587 to 1,057)Excess supply cost in £ according to the source of recruitment, mean (95% CI) Learning health system1,201 (590 to 1,812) Usual care arm of the ACtiF trial713 (446 to 979) Intervention arm of the ACtiF trial583 (313 to 853)Excess supply cost in £ according to age categories, mean (95% CI) ≤18 years594 (96 to 1,091) 19 to 25 years1,515 (977 to 2,055) 26 to 34 years447 (236 to 658) ≥35 years409 (0 to 831)Excess supply cost in £ according to gender, mean (95% CI) Male908 (522 to 1,293) Female731 (467 to 996)Excess supply cost in £ according to P. aeruginosa status, mean (95% CI) Not chronic732 (427 to 1,037) Chronic infection886 (545 to 1,227)Excess supply cost in £ according to %FEV1 categories, mean (95% CI) <40%704 (219 to 1,188) 40 to 69.9%917 (564 to 1,270) ≥70%767 (351 to 1,183)Excess supply cost in £ according to source of inhaled medicine supply, mean (95% CI) Hospital1,020 (504 to 1,536) Homecare only1,086 (644 to 1,527) ≥2 supply sources559 (230 to 887)Excess supply cost in £ according to number of inhaled medicines, mean (95% CI) 1 medicine only595 (319 to 870) ≥2 different medicines878 (593 to 1,163)Excess supply cost in £ according to prescription of inhaled antibiotics, mean (95% CI)d Only on inhaled mucolytic452 (246 to 658) ≥1 inhaled antibiotic964 (649 to 1,278)Excess supply cost in £ according to use of expensive antibiotics, mean (95% CI) Neither inhaled aztreonam nor levofloxacin819 (564 to 1,074) On inhaled aztreonam and/or levofloxacin836 (215 to 1,457)Excess supply cost in £ according to unadjusted EDC adherence, mean (95% CI) <50%1,540 (1,078 to 2,001) 50 to <80%422 (125 to 718) ≥80%82 (15 to 148)† Estimates of excess supply cost are highly conservative because of contingency, see ‘Discussion’ paragraph 6. Excess supply cost was calculated as the cost of excess medicine box(es) delivered or collected after accounting for the discrepancy between EDC adherence and dwcMPR with 20% contingency. For example, if a person has an excess supply of 83 aztreonam nebules, the excess supply cost was calculated as “0” because each box of aztreonam has 84 nebules.‡ Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3. Open table in a new tab 4.Table 3 (results from linear regression models) – With excess supply cost in £ as the outcome, the unadjusted regression coefficient for unadjusted EDC adherence was -739 (95% CI -986 to -491) and the adjusted regression coefficient was -660 (95% CI -908 to -410). Similar to the initial analyses, excess supply cost was higher among those with EDC adherence <50%, aged 19-25 years and on inhaled antibiotics rather than mucolytics only. An updated Table 3 is attached.Table 3Summary of the excess supply cost results from linear regression models.†Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.VariableExcess supply cost in £Unadjusted regression coefficient (95% CI)P-valueAdjusted regression coefficient ‡Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2. (95% CI)P-valueUnadjusted EDC adherence AEDC adherence category was analysed as an ordinal variable because Table 2 showed a step-wise reduction in excess supply cost with increasing level of adherence category. For the univariate analysis, an increase in one level of adherence category (e.g. from <50% to 50–79%) was associated with a decrease of £739 (95% CI £491–986) in excess supply cost. For the multivariate analysis, an increase in one level of adherence category was associated with a decrease of £660 (95% CI £411–908) in excess supply cost, all else being equal.–739 (–986 to –491)<0.001–660 (–908 to –411)<0.001Age <19 years or >25 years BAge was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: ≤18 years, 26–34 years and ≥35 years. (reference)Age 19 to 25 years1,072 (595 to 1,548)<0.001790 (324 to 1,256)<0.001Only on inhaled mucolytic ‡Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2. (reference)≥1 inhaled antibiotic476 (–38 to 990)0.069586 (111 to 1,062)0.0161 medicine only (reference)≥2 different medicines283 (–309 to 876)0.347Source of recruitment Learning health system (reference) Usual care arm of the ACtiF trial–488 (–1,166 to 191)–618 (–1,251 to 16)0.1580.056 Intervention arm of the ACtiF trialMale (reference)Female–177 (–648 to 295)0.526Not chronic P. aeruginosa (reference)Chronic P. aeruginosa infection154 (–324 to 632)0.470%FEV1 <40% or ≥70% C%FEV1 was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: <40% and ≥70%. (reference)%FEV1 40 to 69.9%157 (–325 to 638)0.552≥2 medicine supply sources DThe source of inhaled medicine supply was dichotomised because Table 2 showed similar amount of excess supply cost for those who received all supply from hospital only and all supply via homecare only. In an exploratory multiple regression analysis accounting for EDC adherence level and age 19–25 years, source of inhaled medicine supply was not associated with excess supply cost in £ (adjusted regression coefficient of 432, 95% CI -6 to 869, p-value 0.053. The source of inhaled medicine supply reached statistical significance in the univariate analysis because those receiving supply from a single source have somewhat lower EDC adherence level compared to those receiving supply from ≥2 sources (median 48%, IQR 19–84% vs median 64%, IQR 28–87%, Mann-Whitney p-value 0.064). (reference)Supply from hospital only or homecare only504 (35 to 972)0.035Neither aztreonam nor levofloxacin (reference)On inhaled aztreonam and/or levofloxacin17 (–594 to 628)0.956† Results exclude nine participants with skewed MPR data. Further explanation for the skewed MPR data is provided in Table S3.‡ Adjusted R2 of the multiple regression model = 0.155. Unadjusted EDC adherence category and age category were included in the multiple regression analysis because both covariates reached statistical significance in the univariate analysis. Prescription of inhaled antibiotic were also included as a covariate because those prescribed inhaled antibiotics have substantially higher EDC adherence level compared to those who were not (median 61%, IQR 26–86% vs median 45%, IQR 13–83%, Mann-Whitney p-value 0.042). Therefore the lack of statistical significance in the univariate analysis of inhaled antibiotics prescription was simply due to confounding by adherence level rather than a genuine lack of association. This result is in keeping with the result for lowest excess supply cost in Appendix C Table 2.A EDC adherence category was analysed as an ordinal variable because Table 2 showed a step-wise reduction in excess supply cost with increasing level of adherence category. For the univariate analysis, an increase in one level of adherence category (e.g. from <50% to 50–79%) was associated with a decrease of £739 (95% CI £491–986) in excess supply cost. For the multivariate analysis, an increase in one level of adherence category was associated with a decrease of £660 (95% CI £411–908) in excess supply cost, all else being equal.B Age was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: ≤18 years, 26–34 years and ≥35 years.C %FEV1 was dichotomised because Table 2 showed similar amount of excess supply cost for the following categories: <40% and ≥70%.D The source of inhaled medicine supply was dichotomised because Table 2 showed similar amount of excess supply cost for those who received all supply from hospital only and all supply via homecare only. In an exploratory multiple regression analysis accounting for EDC adherence level and age 19–25 years, source of inhaled medicine supply was not associated with excess supply cost in £ (adjusted regression coefficient of 432, 95% CI -6 to 869, p-value 0.053. The source of inhaled medicine supply reached statistical significance in the univariate analysis because those receiving supply from a single source have somewhat lower EDC adherence level compared to those receiving supply from ≥2 sources (median 48%, IQR 19–84% vs median 64%, IQR 28–87%, Mann-Whitney p-value 0.064). Open table in a new tab 5.Figure 2 (tree-based analysis) – Similar to the initial analyses, excess supply cost was higher among those with EDC adherence <50%, aged 19-25 years and on inhaled antibiotics rather than mucolytics only. An updated Figure 2 is attached.6.Appendix A (participants with skewed MPR data) – the details for skewed MPR data and the values of dwcMPR, ‘standard’ composite MPR (i.e. a mean of all individual MPR) and unadjusted EDC adherence are now tabulated in Table S3 (attached). Where MPR data were skewed, EDC adherence is more similar to dwcMPR compared to ‘standard’ cMPR.Table S3Details of participants with skewed MPR data; and a comparison between unadjusted EDC adherence, dwcMPR and ‘standard’ cMPR.Details of skewed MPR data †The skewed (i.e. excessively high or excessively low) MPR reflect the fact that on occasion, lack of system optimisation in medicine management can create quite marked over-supply. Most of the excessively skewed MPR occurred in short-term prescriptions, for example a salbutamol prescription for only 20 days in Person #2. In the extant CF literature, composite MPR (cMPR) is calculated simply as a mean of all individual MPR [1,2]. That means the skewed individual MPR data can have a disproportionate impact on the cMPR. For example, salbutamol MPR of >2000% for Person #2 resulted in ‘standard’ cMPR of 445%. With dose-weighting, short-term prescriptions by the virtue of fewer prescribed doses are given a lower weight compared to longer-term prescriptions. For example, the salbutamol for Person #2 was only given a weight of 0.021 (out of 1.000) because five other medications were prescribed for longer durations (dornase alfa for 365 days, colistimethate for 162 days, hypertonic saline for 365 days, tobramycin for 141 days and aztreonam lysine for 40 days). As a result, dwcMPR is more resistant to skewed MPR data and more accurately reflect the overall amount of supplied medications.Unadjusted EDC adherencedwcMPR‘Standard’ cMPRPerson #1 – this person was only prescribed salbutamol for 5 days but one box (10 days’ worth of supply) was supplied, hence MPR for salbutamol was 200%.90%115%142%Person #2– salbutamol prescription was for only 20 days but 12 months of supplies (48 boxes) were delivered, hence MPR for salbutamol was >2000%.78%90%445%Person #3 – salbutamol prescription was for only 30 days but 6 months of supplies (27 boxes) were delivered, hence MPR for salbutamol was 900%.73%119%278%Person #4 – MPR for hypertonic saline was 190%.2%139%139%Person #5 – MPR for salbutamol was 99% compared to MPR for hypertonic saline of 5%.33%30%52%Person #6 – MPR for dornase alfa was 36% compared to MPR for colistimethate of 6%.5%18%21%Person #7– unable to find evidence for the supply of piperacillin-tazobactam post hospital admission although the prescription was continued, hence MPR for piperacillin-tazobactam was only 5%.19%56%55%Person #8 – tobramycin prescription was stopped after 2 days but one box was supplied, hence MPR for tobramycin was 1400%.24%76%297%Person #9 – this person was only prescribed colistin for 18 days but on-going supply resulted in an MPR of 570% for colistin.39%57%203%† The skewed (i.e. excessively high or excessively low) MPR reflect the fact that on occasion, lack of system optimisation in medicine management can create quite marked over-supply. Most of the excessively skewed MPR occurred in short-term prescriptions, for example a salbutamol prescription for only 20 days in Person #2. In the extant CF literature, composite MPR (cMPR) is calculated simply as a mean of all individual MPR 1Quittner A.L. Zhang J. Marynchenko M. Chopra P.A. Signorovitch J. Yushkina Y. Rieckert K.A.. Pulmonary medication adherence and health-care use in cystic fibrosis.Chest. 2014; 146: 142-151Abstract Full Text Full Text PDF PubMed Scopus (147) Google Scholar, 2Eakin M.N. Bilderback A. Boyle M.P. Mogayzel P.J. Riekert K.A.. Longitudinal association between medication adherence and lung health in people with cystic fibrosis.J Cyst Fibros. 2011; 10: 258-264Abstract Full Text Full Text PDF PubMed Scopus (152) Google Scholar. That means the skewed individual MPR data can have a disproportionate impact on the cMPR. For example, salbutamol MPR of >2000% for Person #2 resulted in ‘standard’ cMPR of 445%. With dose-weighting, short-term prescriptions by the virtue of fewer prescribed doses are given a lower weight compared to longer-term prescriptions. For example, the salbutamol for Person #2 was only given a weight of 0.021 (out of 1.000) because five other medications were prescribed for longer durations (dornase alfa for 365 days, colistimethate for 162 days, hypertonic saline for 365 days, tobramycin for 141 days and aztreonam lysine for 40 days). As a result, dwcMPR is more resistant to skewed MPR data and more accurately reflect the overall amount of supplied medications. Open table in a new tab In Appendix C, we calculated the minimum excess supply cost based on the assumption that more expensive medications were used first and maximum excess supply cost based on the assumption that cheaper medications were used first. The minimum and maximum excess supply costs were calculated directly from the total doses of supplied medications without the need to calculate a composite MPR. Therefore, the results in Appendix C are unaffected. Overall, the reduction in excess supply cost (mean £822, 95% CI £587-1057 with the revised method vs mean £1124, 95% CI £855-1394 with the method as originally described) does not alter the conclusions of the paper. MPR provides information about medicine supply but over-estimates actual medicine use. The excess supply cost was highest among those with lowest EDC adherence. Our study provides a conservative estimate of excess inhaled medicines supply cost among adults with CF in the UK. Importantly, the lowest excess supply cost of £1,325/patient/year among those with EDC adherence <50%, suggests there are potential annual savings of around £2.5 million. The authors would like to apologise for any inconvenience caused. Using a learning health system to understand the mismatch between medicines supply and actual medicines use among adults with cystic fibrosisJournal of Cystic FibrosisVol. 21Issue 2PreviewInhaled medicines (antibiotics and mucolytics) reduce the risk of exacerbations and slow lung function decline in cystic fibrosis [1,2]. However, real-world low adherence results in preventable morbidity and mortality [3–7]. Full-Text PDF

Background: Patients with pulmonary fibrosis attending interstitial lung disease (ILD) clinics undergo assessment to classify their condition into one of the recognised subtypes, including fibrosing hypersensitivity pneumonitis (fHP) & connective tissue disease (CTD)-ILD. Questions seeking symptoms relevant to CTD and an immunology panel, including autoantibodies relevant to rheumatological conditions, are commonly employed. Two single centre retrospective studies in patients with established fHP suggest worse outcomes when positive autoantibody screens are present. Pigeon fanciers gain significant pleasure from their sport, and perform a classical natural experiment given their reluctance to stop exposure, but are at high risk for developing fHP. Studying this group should improve understanding of how common autoimmunity is in fHP, and whether it correlates with the development of fHP. This may aid understanding of how fHP develops without identifiable exposure/s. Methods: The BPF-GILD study commenced in 2019, and continues to recruit from the pigeon fancier community. A standard questionnaire is completed for each participant by clinicians, including a panel of questions usually employed within ILD clinics for symptoms relevant to CTD. In addition they perform lung function and provide blood for genetic and immunological testing. CTD questionnaire positivity was defined as at least one positive response. Results: To date 353 subjects have been enrolled. Just over 1/3 have a positive CTD questionnaire. Conclusions: Pigeon fanciers commonly express CTD symptoms. The development of auto-antibody positivity and evolution of fHP should be further explored in this group.

Background: Pigeon fanciers are at increased risk of Hypersensitivity Pneumonitis (HP), a common interstitial lung disease (ILD). Connective tissue disease (CTD) is also associated with development of ILD, and CTD symptoms are common in pigeon fanciers without CTD. How this links to their risk of ILD is unclear. Single cell RNA sequencing (scRNAseq) can allow unbiased identification of relevant novel pathways. Objectives: We aimed to map monocyte molecular heterogeneity among pigeon fanciers to test the hypothesis that distinct phenotypes associate with HP/ILD or CTD symptoms. Methods: Blood monocytes from fanciers categorised as ‘no symptoms’ post pigeon exposure (n=15), previous acute HP/fibrosing ILD (HP/ILD)(n=10), symptoms of CTD (n=12) or ‘post exposure’ symptoms (n=15) were prepared for scRNA-seq. 130,000 cells (500 immune-gene panel) were analysed per subject. Results: Following agnostic integration (SCTransform algorithm), 5 clusters in classic (CD14hiCD16neg), 3 in non-classic (CD14loCD16hi), and 4 in intermediate (CD14+CD16+) monocytes were identified across all groups. Differences in relative proportions were significant for those with CTD symptoms: an intermediate cluster (dominant gene IFITM2pos) was higher, and a classic cluster (S100A12hi) was lower compared to those without CTD symptoms. Among 15 differentially expressed genes GNAI2 was significantly upregulated (+2.7) in HP/ILD vs CTD. Conclusions: GNAI2 encodes G-protein Gαi2 which modulates GPCR chemokine receptor responses. Relative expression levels may determine recruitment of selective monocyte clusters to different tissue sites for local pathogenesis or resolution, and may be relevant for the evolution of disease in patients with HP.

We are delighted to bring you volume 54, issue 3 for the Journal of the Association of Chartered Physiotherapists in Respiratory care.The volume starts with Stefania Spiliopoulou who reports on an observational evaluation of intensive care rehabilitation outcomes in COVID-19 compared to other respiratory viruses.King et al then presents a single centre, retrospective valuation on the rapid adoption of the ICS/FICM guidance for prone positioning in adult critical care with mechanically ventilated patients.The third article is by Mansell et al and is an evaluation of observational outcomes of patients with COVID-19 who received a tracheostomy during the first pandemic surge.Bass et al then present a randomised controlled trail to investigate if an online exercise platform is an acceptable tool to promote exercise participation in adults with cystic fibrosis.Following this, Banks et al report on a service evaluation on home monitoring and self-management for adult patients with cystic fibrosis during the COVID-19 pandemic.Tom Walker reports on an evaluation on the attendance and completion of cardiac rehabilitation following heart transplantation, and Drover et al report on their findings from a survey exploring the incidence of chest infection in wind musicians.As part of the Therapies in Critical Care Workforce Project, Twose et al present a scoping review on the role and staffing in critical care.The volume also includes a further output from the ACPRC editorial board, led by Dr. Una Jones.The editorial board is tasked with leading the scoping, commissioning, co-ordination, and delivery of all new ACPRC guidance documents and resources and in this publication, Cork et al present a scoping review on airway clearance techniques for the intubated adult.The final article is a systematic review and thematic synthesis protocol on life after critical illness by King et al.As always, we hope that you enjoy reading this issue of the ACPRC journal, and that you are inspired to write up and submit your work.

Background Triple CFTR modulator therapy (elexacaftor/tezacaftor/ivacaftor) improves lung function, weight, exacerbation rates and quality of life in people with Cystic Fibrosis. CF is a multisystem disease and there is increasing interest in the extrapulmonary effects of CFTR modulators. Chronic rhinosinusitis and gastroesophageal reflux are common in people with CF and cause a high level of sino-nasal and laryngopharyngeal symptoms. We assessed the effect of triple CFTR modulator therapy on these symptoms in a cohort of patients with advanced CF lung disease. Method In a prospective study, we used the Sino-Nasal Outcome Test (SNOT), the Reflux Symptom Index (RSI) and the Hull Airway Reflux Questionnaire (HARQ) as patient-reported outcome measures (PROMs) to assess the effect of triple CFTR modulators on sino-nasal and laryngoesophageal reflux symptoms. Questionnaires, lung function and weight were recorded at baseline before starting treatment and after 6 months on treatment. Results 32 patients (23 male) starting elexacaftor/tezacaftor/ivacaftor were studied. Their baseline characteristics were mean age 34.3 (range 20–65) years, FEV1% predicted 24.8 (11–40), weight 63.2 kg (35–99.8) and BMI 21.28 kg/m2 (13.2–31.1). All patients continued with treatment throughout the study period. At 6 months there was an improvement in mean FEV1% predicted of 8.63 and BMI 2.6 kg/m2. Patient reported outcome measures showed significant improvement (table 1): median scores RSI 10, HARQ 19.5 and SNOT 16 (p<0.001 for all outcomes). Discussion This study shows significant improvement in lung function, weight and sino-nasal and laryngopharyngeal reflux PROMs in patients with advanced CF. The SNOT-20, RSI and HARQ scores showed improvement that exceeded recognised clinically significant changes in these metrics.

Background Studies in separate cohorts suggest possible discrepancies between inhaled medicines supplied (median 50-60%) and medicines used (median 30-40%). We performed the first study that directly compares CF medicine supply against use to identify the cost of excess medicines supply. Methods This cross-sectional study included participants from 12 UK adult centres with ≥1 year of continuous adherence data from data-logging nebulisers. Medicine supply was measured as medication possession ratio (MPR) for a 1-year period from the first suitable supply date. Medicine use was measured as electronic data capture (EDC) adherence over the same period. The cost of excess medicines was calculated as whole excess box(es) supplied after accounting for the discrepancy between EDC adherence and MPR with 20% contingency. Results Among 275 participants, 133 (48.4%) were females and mean age was 30 years (95% CI 29-31 years). Median EDC adherence was 57% (IQR 23-86%), median MPR was 74% (IQR 46-96%) and the discrepancy between measures was median 14% (IQR 2-29%). Even with 20% contingency, mean potential cost of excess medicines was £1,124 (95% CI £855-1,394), ranging from £183 (95% CI £29-338) for EDC adherence ≥80% to £2,017 (95% CI £1,507-2,526) for EDC adherence <50%. Conclusions This study provides a conservative estimate of excess inhaled medicines supply cost among adults with CF in the UK. The excess supply cost was highest among those with lowest EDC adherence, highlighting the importance of adherence support and supplying medicine according to actual use. MPR provides information about medicine supply but over-estimates actual medicine use.

Background People with CF were considered to be extremely vulnerable to COVID-19 and were advised on 23rd March 2020 to 'shield' (stay at home; no outside contacts). Methods In July an e-mail survey was sent to 137 CF adults to determine how strictly they had shielded, how they had coped and the effect on wellbeing and mental health (GAD-7 & PHQ-9). Treatment adherence (measured with 'chipped nebulisers'- CFHealthHub) and levels of anxiety and depression pre- and during shielding were compared in a subgroup that consented to being identified. Changes were compared with the Wilcoxon rank test. Results 63 (46%) responded; 19 replied anonymously and 44 (25 men) gave their identity. Mean age (range) was 32.7 (17.5–64) years, FEV12.1 (0.57–4.86) L, BMI 22.8 (16.4–28.6) kg/m2 and 33 were on CFTR modulator treatment. Fifty-nine (94%) reported adherence to shielding 'all the time'/'often'. Most (76%) found this difficult, reporting a negative impact on exercise, social support, independence, sleep and daily routines. Most were not concerned about shielding being relaxed but 44% worried that others might not adhere to social distancing with risks of COVID-19 infection (43%). Adherence rates during COVID were available in 42 patients, with a median of 91% (interquartile range 84% to 100%). In 28 patients, pre-COVID adherence results were available, with a median difference of 0 (IQR -4 to 8). In 41 patients with complete data, there was a significant difference in the median pre-COVID versus during-COVID anxiety score (pre= 2, IQR 0.5–6 compared to during =5, IQR 1–11; p=0.002). 'Clinically significant' (mild-severe) anxiety rose from 27% pre-COVID to 54% during COVID. In 43 patients with complete data there was no difference in median pre-COVID versus during-COVID depression scores (pre= 3, IQR 1–10 compared to during= 3, IQR 2–12; p=0.09). Conclusions These CF patients showed high compliance with shielding, and high rates of adherence with medication, and none developed COVID-19. They coped well, with low depression scores, but negative impacts were reported on exercise, social support, and daily routines. Anxiety levels significantly increased during shielding, and 7 patients requested a psychology consultation from this survey.

BackgroundIn hospitalised patients with exacerbation of Chronic Obstructive Pulmonary Disease, European and British guidelines endorse oxygen target saturations of 88%–92%, with adjustment to 94%–98% if carbon dioxide levels are normal. We assessed the impact of admission oxygen saturation level and baseline carbon dioxide on inpatient mortality.MethodsPatients were identified from the prospective Dyspnoea, Eosinopenia, Consolidation, Acidaemia and Atrial Fibrillation (DECAF) derivation study (December 2008–June 2010) and the mixed methods DECAF validation study (January 2012 to May 2014). In six UK hospitals, of 2645 patients with COPD exacerbation, 1027 patients were in receipt of supplemental oxygen at admission. All had a clinical history of COPD and obstructive spirometry. These patients were subdivided into the following groups: admission oxygen saturations of 87% or less, 88%–92%, 93%–96% or 97%–100%. Inpatient mortality was calculated for each group and expressed as ORs. The DECAF score and National Early Warning Score 2 (excluding oxygen saturation) were used in binary logistic regression to adjust for baseline risk.ResultsIn patients with COPD receiving supplemental oxygen, oxygen saturations above 92% were associated with higher mortality and an adverse dose–response. Compared with the 88%–92% group, the adjusted risk of death (OR) in the 93%–96% and 97%–100% groups was 1.98 (95% CI 1.09 to 3.60, p=0.025) and 2.97 (95% CI 1.58 to 5.58, p=0.001). In the subgroup with normocapnia, the mortality signal remained significant in both the 93%–96% and 97%–100% groups.ConclusionsInpatient mortality was lowest in those with oxygen saturations of 88%–92%. Even modest elevations in oxygen saturations above this range (93%–96%) were associated with an increased risk of death. A similar mortality trend was seen in both patients with hypercapnia and normocapnia. This shows that the practice of setting different target saturations based on carbon dioxide levels is not justified. Treating all patients with COPD with target saturations of 88%–92% will simplify prescribing and should improve outcome.Trial registration numberUKCRN ID 14214.

Background Cystic Fibrosis (CF) is a life-limiting illness. Audit of the care of patients dying of CF has not been published to date. Methods Newcastle and Oxford teams adapted the National Audit of Care at the End of Life and agreed additional questions that were particularly pertinent for patients dying as a consequence of their CF. Data were extracted and analysed for 15 patients. Results On recognition that the patient was dying, the CF teams were less good at reviewing the need for physiological observations (50% vs national 70%) but better at reviewing the need for capillary blood glucose monitoring, oxygen support and intravenous antibiotics compared with the national average for all patients. On recognition that the patient was dying, the CF teams were better at assessing pain (87% vs national 80%) and breathlessness (93% vs national 73%), but less good at assessing nausea and vomiting (47% vs national 74%). There was documented evidence that 100% of families and 64% of patients were aware that the patient was at risk of dying. Conclusion Comparing care of this sample of patients dying with CF against the national data is a useful first step in understanding that many aspects of care are of high quality. This audit identifies the need to offer earlier conversations to patients as their voices may be missing from the conversation. Undertaking a national audit would provide a more reliable and a fuller picture.

Cystic fibrosis (CF) arises from mutations in the CF transmembrane conductance regulator ( CFTR) gene, resulting in progressive and life-limiting respiratory disease. R751L is a rare CFTR mutation that is poorly characterized. Our aims were to describe the clinical and molecular phenotypes associated with R751L. Relevant clinical data were collected from three heterozygote individuals harboring R751L (2 patients with G551D/R751L and 1 with F508del/R751L). Assessment of R751L-CFTR function was made in primary human bronchial epithelial cultures (HBEs) and Xenopus oocytes. Molecular properties of R751L-CFTR were investigated in the presence of known CFTR modulators. Although sweat chloride was elevated in all three patients, the clinical phenotype associated with R751L was mild. Chloride secretion in F508del/R751L HBEs was reduced compared with non-CF HBEs and associated with a reduction in sodium absorption by the epithelial sodium channel (ENaC). However, R751L-CFTR function in Xenopus oocytes, together with folding and cell surface transport of R751L-CFTR, was not different from wild-type CFTR. Overall, R751L-CFTR was associated with reduced sodium chloride absorption but had functional properties similar to wild-type CFTR. This is the first report of R751L-CFTR that combines clinical phenotype with characterization of functional and biological properties of the mutant channel. Our work will build upon existing knowledge of mutations within this region of CFTR and, importantly, inform approaches for clinical management. Elevated sweat chloride and reduced chloride secretion in HBEs may be due to alternative non-CFTR factors, which require further investigation.

Temperate bacteriophages are a common feature of Pseudomonas aeruginosa genomes, but their role in chronic lung infections is poorly understood. This study was designed to identify the diverse communities of mobile P. aeruginosa phages by employing novel metagenomic methods, to determine cross infectivity, and to demonstrate the influence of phage infection on antimicrobial susceptibility. Mixed temperate phage populations were chemically mobilized from individual P. aeruginosa, isolated from patients with cystic fibrosis (CF) or bronchiectasis (BR). The infectivity phenotype of each temperate phage lysate was evaluated by performing a cross-infection screen against all bacterial isolates and tested for associations with clinical variables. We utilized metagenomic sequencing data generated for each phage lysate and developed a novel bioinformatic approach allowing resolution of individual temperate phage genomes. Finally, we used a subset of the temperate phages to infect P. aeruginosa PAO1 and tested the resulting lysogens for their susceptibility to antibiotics. Here, we resolved 105 temperate phage genomes from 94 lysates that phylogenetically clustered into 8 groups. We observed disease-specific phage infectivity profiles and found that phages induced from bacteria isolated from more advanced disease infected broader ranges of P. aeruginosa isolates. Importantly, when infecting PAO1 in vitro with 20 different phages, 8 influenced antimicrobial susceptibility. This study shows that P. aeruginosa isolated from CF and BR patients harbors diverse communities of inducible phages, with hierarchical infectivity profiles that relate to the progression of the disease. Temperate phage infection altered the antimicrobial susceptibility of PAO1 at subinhibitory concentrations of antibiotics, suggesting they may be precursory to antimicrobial resistance. IMPORTANCE Pseudomonas aeruginosa is a key opportunistic respiratory pathogen in patients with cystic fibrosis and non-cystic fibrosis bronchiectasis. The genomes of these pathogens are enriched with mobile genetic elements including diverse temperate phages. While the temperate phages of the Liverpool epidemic strain have been shown to be active in the human lung and enhance fitness in a rat lung infection model, little is known about their mobilization more broadly across P. aeruginosa in chronic respiratory infection. Using a novel metagenomic approach, we identified eight groups of temperate phages that were mobilized from 94 clinical P. aeruginosa isolates. Temperate phages from P. aeruginosa isolated from more advanced disease showed high infectivity rates across a wide range of P. aeruginosa genotypes. Furthermore, we showed that multiple phages altered the susceptibility of PAO1 to antibiotics at subinhibitory concentrations.