OBJECTIVES:During the COVID-19 pandemic, individuals from non-White and with poorer socio-economic status (SES) had higher rates of mortality than their counterparts. The hypothesis that these individuals had more severe respiratory failure at the time of first presentation to hospital was tested. STUDY DESIGN:Observational cross-sectional study using routinely collected physiological measurements. METHODS:The study population consisted of all individuals admitted to Nottingham University Hospitals NHS Trust from 1 February 2020 and 31 December 2021. Severity of respiratory failure was measured by the oxygen saturation fraction ratio (SFR, oxygen%/inspired oxygen concentration%). RESULTS:Patients from the areas of highest quintiles of deprivation had an adjusted SFR of 12.6 (95 % confidence intervals [CI]: 7.4 to 17.8) units lower than patients from areas of the lowest deprivation. Patients from an Asian ethnic group has a lower SFR than those from a White ethnic group (-10.9 units; 95 % CI: -19.1 to -2.7). Sensitivity analysis adjusting for the measurement error of pulse oximetry by ethnicity increased this differential for Asian and Black ethnic groups. CONCLUSIONS:These data suggest that individuals from both non-White ethnic groups and poorer SES are sicker at the time of presentation to hospital with COVID-19 infection. Public health strategies are required to understand these observations and counter them with appropriate interventions. These may vary from proximal factors such as enhanced access to healthcare to more distal ones including building trust in modern medical treatments. These data are from one centre and hence should be interpretated cautiously particular with generalisability to other healthcare settings.

Background:Understanding the reasons for delays in leaving hospital once an in-patient is considered ready for discharge is important to inform the development of interventions to improve patient flow through resource-stressed healthcare systems. Aims:To identify risk factors for delayed discharge from hospital during the COVID-19 pandemic. Methods:The study population was all patients admitted with COVID-19 infection from February 2020 to September 2021 to a large UK teaching hospital. Results:Data were available from 7929 admission events with a median delay of 0.20 days from being considered medically safe for discharge and the discharge date. Age older than 60 years (+2.23 days), White ethnicity (+1.58 days compared to SE Asian), living in an area of increased affluence (+0.13 days per decile decrease in deprivation) and having two or more comorbidities (+1.82 days; compared to no comorbidities) were associated with delayed discharge.There was a total potential saving of over 22,000 bed-days if all patients had been discharged when they were considered medically safe. Conclusions:Early identification of patients at an increased risk of a delayed discharge may allow development of appropriate anticipatory interventions, and inform policymakers to help identify and minimise bottlenecks at the institutional level.

Few studies have explored the variability of the oxygen-haemoglobin dissociation curve in vivo.96,428 blood gas measurements were obtained (80,376 arterial, 6,959 venous) from a cohort of 7,656 patients who were admitted to a large UK teaching hospital between 1 February 2020 and 31 December 2021 for a Covid-19 related admission with a positive PCR. There was consistent variation of the distribution of the oxygen-haemoglobin curve across most oxygen saturation strata with typical values at 91-92% saturation (mean 8.1kPa, standard deviation sd 0.6 kPa or 60.8mmHg sd 4.5mmHg), with the exception of the highest strata of oxygen saturation of 99-100% (mean 17.7 kPa, sd 8.1kPa or 132mmHg sd 60.8).The higher oxygen partial pressures at higher oxygen saturations are a concern in view of the increased mortality observed in RCTs of higher oxygen saturation targets. However, the observational study design precludes any attribution of causality.

Background Pulse oximetry measures oxygen saturation non-invasively by using differential absorption of infrared signals which are dependent on the oxyhaemoglobin:deoxyhaemoglobin ratio. We tested the hypothesis that pulse oximetry error in measurements of blood oxygen saturations may be associated with blood haemoglobin levels.Methods The study design was an observational study of all adult patients admitted to a large teaching hospital with suspected or confirmed COVID-19 infection from February 2020 to December 2021 who had arterial blood gases (ABG) drawn. The pulse oximetry reading was compared with the arterial saturation on the ABG and the measurement error was determined according to the ABG haemoglobin. A secondary analysis was performed among a subset of patients with venous haemoglobins drawn within 24 hours, comparing measurement error between ABG arterial saturation and pulse oximetry readings between those with normal (150 g/L) and low (70 g/L) haemoglobins.Results The analysis used 5922 paired oxygen saturations from 3994 patients with contemporaneous haemoglobin measurements by ABG. A 1 g/L decrease in blood haemoglobin was associated with an 0.021% (95% CI: +0.008% to +0.033%) increase in the measurement error (in the direction of a falsely elevated reading.). In the 1086 patients who had had a venous haemoglobin there was a 0.055% (95% CI: +0.020% to +0.090%) increase in the measurement error of oxygen saturation per 1 g/L decrease in blood haemoglobin. The measurement error was thus greater in those with anaemia than in those with normal haemoglobin.Conclusion As blood haemoglobin decreases, the oxygen saturation measurement derived from a pulse oximeter reads erroneously higher than the true value measured by ABG. While this study was confined to patients with COVID-19, physicians should be aware of this potential discrepancy among all patients with haemorrhage or known anaemia

In England and Wales there was excess mortality from Covid-19 infection in individuals whose forebears originated outside the UK, often in Africa or South East Asia [1]. The reasons for this are still unclear. We suggest that the use of oxygen saturations derived from pulse oximetry to guide treatment may have been a contributory factor. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of Interest: All authors have nothing to disclose.

Background Pulse oximeters are widely used to monitor blood oxygen saturations, although concerns exist that they are less accurate in individuals with pigmented skin. Aims This study aimed to determine if patients with pigmented skin were more severely unwell at the period of transfer to intensive care units (ICUs) than individuals with White skin. Methods Using data from a large teaching hospital, measures of clinical severity at the time of transfer of patients with COVID-19 infection to ICUs were assessed, and how this varied by ethnic group. Results Data were available on 748 adults. Median pulse oximetry demonstrated similar oxygen saturations at the time of transfer to ICUs (Kruskal-Wallis test, P = 0.51), although median oxygen saturation measurements from arterial blood gases at this time demonstrated lower oxygen saturations in patients classified as Indian/Pakistani ethnicity (91.6%) and Black/Mixed ethnicity (93.0%), compared to those classified as a White ethnicity (94.4%, Kruskal-Wallis test, P = 0.005). There were significant differences in mean respiratory rates in these patients (P < 0.0001), ranging from 26 breaths/min in individuals with White ethnicity to 30 breaths/min for those classified as Indian/Pakistani ethnicity and 31 for those who were classified as Black/Mixed ethnicity. Conclusions These data are consistent with the hypothesis that differential measurement error for pulse oximeter readings negatively impact on the escalation of clinical care in individuals from other than White ethnic groups. This has implications for healthcare in Africa and South-East Asia and may contribute to differences in health outcomes across ethnic groups globally.

Journal of Medical VirologyVolume 95, Issue 6 e28837 LETTER TO THE EDITOR Maximal temperature varies by sex and ethnic group in hospital in-patients with Covid-19 infection Colin J. Crooks, Colin J. Crooks Nottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, UK NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorJoe West, Joe West NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK East Midlands Academic Health Science Network, University of Nottingham, Nottingham, UKSearch for more papers by this authorTasso Gazis, Tasso Gazis Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorMark Simmonds, Mark Simmonds Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorDominick Shaw, Dominick Shaw Nottingham University Hospitals NHS Trust, Nottingham, UK Division of Respiratory Medicine, School of Medicine, University of Nottingham, Nottingham, UKSearch for more papers by this authorTimothy R. Card, Timothy R. Card NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UKSearch for more papers by this authorAndrew W. Fogarty, Corresponding Author Andrew W. Fogarty [email protected] orcid.org/0000-0001-9426-977X NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK Correspondence Andrew W. Fogarty, Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham NG5 1PB, UK. Email: [email protected]Search for more papers by this author Colin J. Crooks, Colin J. Crooks Nottingham Digestive Diseases Centre, School of Medicine, University of Nottingham, Nottingham, UK NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorJoe West, Joe West NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK East Midlands Academic Health Science Network, University of Nottingham, Nottingham, UKSearch for more papers by this authorTasso Gazis, Tasso Gazis Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorMark Simmonds, Mark Simmonds Nottingham University Hospitals NHS Trust, Nottingham, UKSearch for more papers by this authorDominick Shaw, Dominick Shaw Nottingham University Hospitals NHS Trust, Nottingham, UK Division of Respiratory Medicine, School of Medicine, University of Nottingham, Nottingham, UKSearch for more papers by this authorTimothy R. Card, Timothy R. Card NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UKSearch for more papers by this authorAndrew W. Fogarty, Corresponding Author Andrew W. Fogarty [email protected] orcid.org/0000-0001-9426-977X NIHR Nottingham Biomedical Research Centre (BRC), Nottingham University Hospitals NHS Trust, University of Nottingham, Nottingham, UK Nottingham University Hospitals NHS Trust, Nottingham, UK Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham, UK Correspondence Andrew W. Fogarty, Population and Lifespan Sciences, School of Medicine, University of Nottingham, Nottingham NG5 1PB, UK. Email: [email protected]Search for more papers by this author First published: 11 June 2023 https://doi.org/10.1002/jmv.28837Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. REFERENCES 1Mohamed MO, Gale CP, Kontopantelis E, et al. Sex differences in mortality rates and underlying conditions for COVID-19 deaths in england and wales. Mayo Clin Proc. 2020; 95(10): 2110-2124. doi:10.1016/j.mayocp.2020.07.009 2Crooks CJ, West J, Fogarty A, et al. Predicting need for escalation of care or death from repeated daily clinical observations and laboratory results in patients with severe acute respiratory syndrome coronavirus 2. Am J Epidemiol. 2022; 191: 1944-1953. 3Sue K. The science behind “man flu”. BMJ (Clinical research ed.). 2017; 359:j5560. doi:10.1136/bmj.j5560 4McGann KP, Marion GS, Spangler JS. The influence of gender and race on mean body temperature in a population of healthy older adults. Arch Fam Med. 1993; 2(12): 1265-1267. [published Online First: 1993/12/01]. doi:10.1001/archfami.2.12.1265 5Demetriou CA, Achilleos S, Quattrocchi A, et al. Impact of the COVID-19 pandemic on total, sex- and age-specific all-cause mortality in 20 countries worldwide during 2020: results from the C-MOR project. Int J Epidemiol. 2022; 52(3): 664-676. doi:10.1093/ije/dyac170 Volume95, Issue6June 2023e28837 ReferencesRelatedInformation

AIMS:The study tests the hypothesis that a higher acute systemic inflammatory response was associated with a larger decrease in blood hemoglobin levels in patients with Coronavirus 2019 (COVID-19) infection.METHODS:All patients with either suspected or confirmed COVID-19 infection admitted to a busy UK hospital from February 2020 to December 2021 provided data for analysis. The exposure of interest was maximal serum C-reactive protein (CRP) level after COVID-19 during the same admission.RESULTS:A maximal serum CRP >175mg/L was associated with a decrease in blood haemoglobin (-5.0 g/L, 95% confidence interval: -5.9 to -4.2) after adjustment for covariates, including the number of times blood was drawn for analysis. Clinically, for a 55-year-old male patient with a maximum haemoglobin of 150 g/L who was admitted for a 28-day admission, a peak CRP >175 mg/L would be associated with an 11 g/L decrease in blood haemoglobin, compared with only 6 g/L if the maximal CRP was <4 mg/L.CONCLUSIONS:A higher acute systemic inflammatory response is associated with larger decreases in blood haemoglobin levels in patients with COVID-19. This represents an example of anaemia of acute inflammation, and a potential mechanism by which severe disease can increase morbidity and mortality.

OBJECTIVE:To explore the associations between arterial pO2, pCO2 and pH and how these are modified by age. METHODS:An analysis of 2598 patients admitted with a diagnosis of Covid-19 infection to a large UK teaching hospital. RESULTS:There were inverse associations for arterial pO2, pCO2 and pH with respiratory rate. The effects of pCO2 and pH on respiratory rate were modified by age; older patients had higher respiratory rates at higher pCO2 (p = 0.004) and lower pH (p = 0.007) values. CONCLUSIONS:This suggests that ageing is associated with complex changes in the physiological feedback loops that control respiratory rate. As well as having clinical relevance, this may also impact on the use of respiratory rate in early warning scores across the age range.

OBJECTIVE:To determine the maximal response of the temperature and inflammatory response to SARS-CoV-2 infection and how these are modified by age.METHODS:Participants were patients admitted to hospital with SARS-CoV-2 infection. For each participant, the maximal temperature and serum C-reactive protein (CRP) were identified and stratified by age. In a secondary analysis, these were compared in patients treated before and after dexamethasone.RESULTS:Mean maximal temperature varied by age (p<0.001; ANOVA) with the highest mean maximal temperature of 37.3°C observed in patients aged 30-49 years and decreasing maximal mean temperatures in the older age groups, with the lowest measure of 36.8°C observed in individuals aged 90-99 years. The mean maximal serum CRP also varied across age groups (p<0.001; ANOVA) and increased with age across all age categories from 34.5 mg/dL (95% confidence interval (CI) 22.0-47.0) for individuals aged 20-29 years to 77.6 mg/dL (95% CI 72.0-83.2) in those aged 80-89 years. After dexamethasone became standard treatment for COVID-19 pneumonia, mean maximal CRP decreased by 17 mg/dL (95% CI -22 to -11).CONCLUSION:Age modifies both maximal temperature and systemic inflammatory response in patients with SARS-CoV-2 infection.

Background Radiographic severity may help predict patient deterioration and outcomes from COVID-19 pneumonia. Purpose To assess the reliability and reproducibility of three chest radiograph reporting systems (radiographic assessment of lung edema [RALE], Brixia, and percentage opacification) in patients with proven SARS-CoV-2 infection and examine the ability of these scores to predict adverse outcomes both alone and in conjunction with two clinical scoring systems, National Early Warning Score 2 (NEWS2) and International Severe Acute Respiratory and Emerging Infection Consortium: Coronavirus Clinical Characterization Consortium (ISARIC-4C) mortality. Materials and Methods This retrospective cohort study used routinely collected clinical data of patients with polymerase chain reaction–positive SARS-CoV-2 infection admitted to a single center from February 2020 through July 2020. Initial chest radiographs were scored for RALE, Brixia, and percentage opacification by one of three radiologists. Intra- and interreader agreement were assessed with intraclass correlation coefficients. The rate of admission to the intensive care unit (ICU) or death up to 60 days after scored chest radiograph was estimated. NEWS2 and ISARIC-4C mortality at hospital admission were calculated. Daily risk for admission to ICU or death was modeled with Cox proportional hazards models that incorporated the chest radiograph scores adjusted for NEWS2 or ISARIC-4C mortality. Results Admission chest radiographs of 50 patients (mean age, 74 years ± 16 [standard deviation]; 28 men) were scored by all three radiologists, with good interreader reliability for all scores, as follows: intraclass correlation coefficients were 0.87 for RALE (95% CI: 0.80, 0.92), 0.86 for Brixia (95% CI: 0.76, 0.92), and 0.72 for percentage opacification (95% CI: 0.48, 0.85). Of 751 patients with a chest radiograph, those with greater than 75% opacification had a median time to ICU admission or death of just 1–2 days. Among 628 patients for whom data were available (median age, 76 years [interquartile range, 61–84 years]; 344 men), opacification of 51%–75% increased risk for ICU admission or death by twofold (hazard ratio, 2.2; 95% CI: 1.6, 2.8), and opacification greater than 75% increased ICU risk by fourfold (hazard ratio, 4.0; 95% CI: 3.4, 4.7) compared with opacification of 0%–25%, when adjusted for NEWS2 score. Conclusion Brixia, radiographic assessment of lung edema, and percentage opacification scores all reliably helped predict adverse outcomes in SARS-CoV-2 infection. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Little in this issue.

Be aware that pulse oximeters overestimate oxygen saturation measurements in patients with hypoxaemia, and that this error is larger in individuals from black and Asian ethnic groupshttps://bit.ly/3fCeJP7

As pulse oximeters are now so widely used, it is important to identify any patient groups in whom they may also have a systematic bias that may impair the delivery of medical care to these individuals. One group would be tobacco smokers [1–3], as the inhaled carbon monoxide modifies the haemoglobin molecule within 1–2 min of inhaling tobacco smoke [4], and the subsequent increase in blood carboxyhaemoglobin levels modifies the pulse oximetry signal [5]. This was reported in a series of 16 patients with carbon monoxide poisoning from 1994 which resulted in higher pulse oximetry measurements than the true values, with the comment that this phenomenon may also extend to oxygen saturation measured in smokers as well [6]. To date, no robust real-world clinical data on acutely unwell patients exist to clarify the impact of smoking status and blood carboxyhaemoglobin levels on the measurement error of oxygen saturation by pulse oximeters. There is substantial measurement error in pulse oximetry readings of oxygen saturation below 90% which is not due to smoking status https://bit.ly/3RunKtL The authors would like to thank an anonymous reviewer whose insightful comments changed the whole outcome of this analysis.

The structure of pulse oximeters has changed tremendously over time, but inaccurate readings of oxygen saturation in black patients have not improved across 32 years and manufacturers do not report efforts to resolve the problemhttps://bit.ly/3KYc7Zo

We don't have reliable data on whether these patients were ventilated or not, as the electronic data that we had access to excluded the period of time when patients were admitted to intensive care. For those patients with a paired pulse oximeter and ABG reading with a reading of<85% arterial saturations (unique patients n=644), 287 (45%) were labelled as eligible for escalation to ICU and of these 143 (50%) were admitted to ICU within 24 h of the blood gas measurement, and 172 (60%) were admitted to ITU at any point during the whole admission period. Response to letter.

Abstract We compared the performance of prognostic tools for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using parameters fitted either at the time of hospital admission or across all time points of an admission. This cohort study used clinical data to model the dynamic change in prognosis of SARS-CoV-2 at a single hospital center in the United Kingdom, including all patients admitted from February 1, 2020, to December 31, 2020, and then followed up for 60 days for intensive care unit (ICU) admission, death, or discharge from the hospital. We incorporated clinical observations and blood tests into 2 time-varying Cox proportional hazards models predicting daily 24- to 48-hour risk of admission to the ICU for those eligible for escalation of care or death for those ineligible for escalation. In developing the model, 491 patients were eligible for ICU escalation and 769 were ineligible for escalation. Our model had good discrimination of daily risk of ICU admission in the validation cohort (n = 1,141; C statistic: C = 0.91, 95% confidence interval: 0.89, 0.94) and our score performed better than other scores (National Early Warning Score 2, International Severe Acute Respiratory and Emerging Infection Comprehensive Clinical Characterisation Collaboration score) calculated using only parameters measured on admission, but it overestimated the risk of escalation (calibration slope = 0.7). A bespoke daily SARS-CoV-2 escalation risk prediction score can predict the need for clinical escalation better than a generic early warning score or a single estimation of risk calculated at admission.