RATIONALE: Periods of intense coughing (bouts, bursts, fits, epochs) are particularly problematic for coughers but not well reflected in simple tabulations of daily cough frequency. Traditional definitions of cough bouts rely on arbitrary parameters: fixed inter-cough intervals and minimum cough counts, which may not accurately characterize the true pattern and impact of cough. This study examines the effects of varying bout definitions on cough pattern assessment using continuous cough monitoring. METHODS: Two chronic coughers’ data, collected via continuous cough monitoring over two weeks with time stamped cough events, were analyzed to understand how different definitions of cough bouts influence measurement outcomes. Bout definitions were varied using inter-cough intervals of 2, 4, and 6 seconds and minimum cough counts of 2, 4, and 6. Daily bout counts, coughs per bout, and bout duration were examined for each parameter set to assess how these variations reflect different cough patterns. RESULTS: Varying the inter-cough interval and minimum cough count significantly altered the resulting metrics for cough bout counts, duration, and frequency. Short inter-cough intervals and low cough count thresholds inflated bout frequency, particularly for the participant coughing frequently but briefly. In contrast, longer inter-cough intervals and higher minimum cough counts revealed more sustained coughing episodes, emphasizing the diverse coughing patterns – and potentially the severity of cough experienced – between individuals. In panel A, the dashed lines indicate the average daily cough count over the two-week period: 1,420 coughs/d for participant-1 and 691 coughs/d for participant-2. Panels B and C highlight that participant 1 primarily coughs twice in rapid succession, while participant 2 tends to cough in longer-duration waves, suggesting the possibility that the cough experience may be more severe for participant-2. CONCLUSIONS: Measuring periods of intense coughing may better capture the patient's experience and improve the correlation between objective and subjective cough measurement. Arbitrary cough bout definitions can misrepresent cough severity by either overestimating or underestimating coughing patterns, depending on the selected parameters. Continuous cough monitoring offers a nuanced understanding of cough dynamics and may support refined bout metrics that more accurately reflect clinical needs. Further research may establish standardized, evidence-based parameters for cough bout definitions that account for individual coughing patterns and patient experience, enhancing their application in clinical studies and therapeutic evaluations. The frequency and pattern of bout/count discrepancies observed in these two patients will be explored in a cohort of patients, and will be presented at the event.

Background: The ability to passively and continuously monitor coughing for prolonged periods of time would significantly improve cough management and research. To date there is no automated clinically validated cough monitor that can be routinely used in clinical care and research. Here we describe the validation of such an automated cough monitor. Methods: This multicenter observational study compared the results of the Hyfe CoughMonitor wrist-worn device with manually counted coughs in subjects with a variety of etiologies as they went about their usual daily activities. We collected 24 h of continuous sounds from subjects while they simultaneously wore a CoughMonitor and an audio recorder. Coughs were labelled by multiple trained annotators who listened to the continuous audio recordings using validated methodology. The time stamps of these human-detected coughs were compared to those of the CoughMonitor to determine the system’s overall performance using event-to-event and hourly rate correlation analyses. Results: Over the 546 h monitored, 4,454 cough events were recorded; The overall sensitivity was 90.4% (95% CI of 88.3–92.2%). The overall false positive rate was 1.03 false positives per hour (95% CI of 0.84 to 1.24). The overall correlation between manual and CoughMonitor measured hourly coughing was high (Pearson correlation coefficient of 0.99). Two case studies of long-term monitoring of patients with chronic cough are presented. Conclusion: The present analysis of cough events demonstrated that the Hyfe CoughMonitor accurately reflects them with a high sensitivity and a low false positive rate. Future studies should focus on its potential role in the management of patients with cough in clinical practice. Registration Clinicaltrials.gov, NCT05723159.

BACKGROUND:Malaria control and elimination is threatened by the spread of insecticide resistance and behavioral adaptation of vectors. Whether mass administration of ivermectin, a broad-spectrum antiparasitic drug that also kills mosquitoes feeding on treated persons, can reduce malaria transmission is unclear. METHODS:We conducted a cluster-randomized trial in Kwale, a county in coastal Kenya in which malaria is highly endemic and coverage and use of insecticide-treated nets are high. Clusters of household areas were randomly assigned in a 1:1 ratio to receive mass administration of ivermectin (400 μg per kilogram of body weight) or albendazole (400 mg, active control) once a month for 3 consecutive months at the beginning of the "short rains" season. Children 5 to 15 years of age were tested for malaria infection monthly for 6 months after the first round of treatment. The two primary outcomes were the cumulative incidence of malaria infection (assessed among children 5 to 15 years of age) and of adverse events (assessed among all eligible participants). Analyses were performed with generalized estimating equations in accordance with the intention-to-treat principle. RESULTS:A total of 84 clusters comprising 28,932 eligible participants underwent randomization. The baseline characteristics of the participants were similar in the trial groups. Six months after the first round of treatment, the incidence of malaria infection was 2.20 per child-year at risk in the ivermectin group and 2.66 per child-year at risk in the albendazole group; the adjusted incidence rate ratio (ivermectin vs. albendazole) was 0.74 (95% confidence interval [CI], 0.58 to 0.95, P = 0.02). The incidence of serious adverse events per 100 treatments did not differ significantly between the trial groups (incidence rate ratio, 0.63; 95% CI, 0.21 to 1.91). CONCLUSIONS:Among children 5 to 15 years of age who were living in an area with high coverage and use of bed nets, ivermectin, administered once a month for 3 consecutive months, resulted in a 26% lower incidence of malaria infection than albendazole. No safety concerns were identified. (Funded by Unitaid; BOHEMIA ClinicalTrials.gov number, NCT04966702; Pan African Clinical Trial Registry number, PACTR202106695877303.).

RATIONALE: Accurate assessment of cough frequency is essential for evaluating cough as a symptom, as a disease indicator and as a biomarker in the development of novel therapeutics. Traditional monitoring durations (e.g., 24 hours) fail to capture the variability in cough frequency observed in real-world conditions, potentially leading to skewed results in clinical studies. This study evaluates the optimal monitoring duration to achieve reliable estimates of cough frequency, proposing a 7-day monitoring standard based on statistical modeling of continuous cough data. METHODS: Using real-world cough data from over 30 individuals with problematic cough, monitored for at least 20 hours per day over 60 days, we analyzed daily and hourly cough frequency distributions. The data revealed that daily cough counts do not fit conventional statistical distributions, complicating analysis. However, hourly cough counts showed a robust fit to zero-inflated negative binomial (ZINB) distributions, enabling more reliable modeling. We used ZINB-based simulations to model 504 hours (21 days) of cough data across various frequency profiles, calculating the minimum monitoring duration needed to achieve consistent estimates of hourly cough frequency within 20% of true values. RESULTS: Simulations demonstrated that most individuals, especially those with a coefficient of variation (CV) between 0.8 and 1.65, reached stable cough frequency estimates within a 7-day (168 hours) monitoring period (Figure 1). Subjects with lower variability (CV < 1) required fewer days, while those with higher variability (CV > 1.65) needed closer to 8 days for reliable data. Across all profiles, 7 days was sufficient to capture accurate cough frequency for 83% of participants, suggesting it as a potentially pragmatic balance between scientific rigor and operational feasibility. CONCLUSION: A 7-day monitoring duration provides a robust, standardized timeframe for assessing cough frequency in clinical studies, offering a significant improvement over the traditional 24-hour period. This duration captures inter- and intra-individual cough variability, enhancing the accuracy of cough-related endpoints in research. While future work may explore tailored monitoring durations for specific populations, a 7-day period is recommended as the default for most studies involving cough frequency assessment.

Prompt diagnosis is critical for tuberculosis (TB) control, as it enables early treatment which in turn, reduces transmission and improves treatment outcomes. We investigated the impact on TB diagnosis of introducing Xpert Ultra as the frontline diagnostic test, combined with an innovative active-case finding (ACF) strategy (based on Xpert Ultra semi-quantitative results and spatial parameters), in a semi-rural district of Southern Mozambique. From January-December 2018 we recruited incident TB-cases (index cases, ICs) and their household contacts (HCs). Recruitment of close community contacts (CCs) depended on IC´s Xpert Ultra results, and the population density of their area. TB-contacts, either symptomatic or people living with HIV, were asked to provide a spot sputum for lab-testing. Trends on TB case notification were compared to the previous years and to those of two districts in the south of the Maputo province (control area), using an interrupted time series analysis with and without control (CITS/ITS). A total of 1010 TB ICs (37.1% laboratory-confirmed) were recruited; 3165 HCs and 4730 CCs were screened for TB. Eighty-nine additional TB cases were identified through the ACF intervention (52.8% laboratory-confirmed). The intervention increased by 8.2% all forms of TB cases detected in 2018. Xpert Ultra trace positive results accounted for a high proportion of laboratory confirmations in the ACF cohort (51.1% vs 13.7% of those passively diagnosed). The Number Needed to Screen to find a TB case differed widely among HCs (55) and CCs (153). During the intervention period, a reversal of the previous negative trend in lab-confirmed case notifications was observed in the district. However, the CITS model did not show any statistically significant difference compared to the control area. Paediatric population benefited the most from the ACF strategy and HCs screening seemed an effective intervention to find microbiological confirmed cases in early stages of the disease.

The ability to passively and continuously monitor coughing would significantly improve cough management and research. To date there is no automated clinically validated cough monitor that can be routinely used in clinical care and research. Here we describe the validation of such an automated cough monitor. To assess the overall performance of the Hyfe Cough Monitoring System when used by individuals with problematic cough, under common living conditions This multicenter observational study compared the results of the Hyfe CoughMonitor wrist-worn device with manually counted coughs in subjects with a variety of etiologies as they went about their usual daily activities. We collected 24 hours of continuous sounds from subjects while they simultaneously wore a CoughMonitor and an audio recorder. Coughs were labelled by multiple trained annotators who listened to the continuous audio recordings using validated methodology. The time stamps of these human-detected coughs were compared to those of the CoughMonitor to determine the system’s overall performance using event-to-event and hourly rate correlation analyses. Over the 546 hours monitored, 4454 cough events were recorded; The overall sensitivity was 90.4% (95% CI of 88.3% to 92.2%). The overall false positive rate was 1.03 false positives per hour (95% CI of 0.84 to 1.24). The overall correlation between manual and CoughMonitor measured hourly coughing was high (Pearson correlation coefficient of 0.99 with OLS slope 0.94 and OLS intercept 0.68). The present analysis of cough events demonstrated that the Hyfe CoughMonitor accurately reflects them with a high sensitivity and a low false positive rate. Future studies should confirm its potential role in the management of patients with cough in clinical practice. Clinicaltrials.gov: NCT05723159

BackgroundTreatment of chronic cough remains a challenge. We hypothesised that inhaled alkaline hypertonic divalent salts (alkaline HDS) might provide relief for refractory chronic cough by laryngeal and tracheal hydration.MethodsWe conducted an exploratory, single-blinded, nasal saline-controlled study in 12 refractory chronic cough patients to examine cough suppression efficacy of an alkaline HDS composition (SC001) at pH 8 or pH 9 administered by nasal inhalation. As control, we used nasal saline with the same hand-held pump spray aerosol device. Each subject was monitored continuously using a digital cough monitor watch for 1 week of baseline, 1 week of control treatment and 1 week of active treatment.ResultsBaseline daily cough rates ranged from 4 to 34 coughs·h−1with mean visual analogue score 65±17 pre- and post-baseline testing. Control-adjusted efficacy of cough rate reduction ranged from 15% (p=0.015) (from Day 1) to 23% (p=0.002) (from Day 3). Control-adjusted efficacy was highest with SC001 pH 9 (n=5), ranging from 25% (p=0.03) (from Day 1) to 35% (p=0.02) (from Day 3), and lowest for SC001 pH 8 (n=7), ranging from 9% (p=0.08) (from Day 1) to 16% (p=0.02) (from Day 3). Hourly cough counts and visual analogue score correlated for baseline (r=0.254, p=0.02) and control (r=0.299, p=0.007) monitoring weeks. Treatment improved this correlation (r=0.434, p=0.00006). No adverse events were reported.ConclusionsAlkaline (pH 9) HDS aerosol is a promising treatment for refractory chronic cough and should be further evaluated.

PurposeWe determined the cough counts and their variability in subjects with persistent cough for 30 days.MethodsThe Hyfe cough tracker app uses the mobile phone microphone to monitor sounds and recognizes cough with artificial intelligence-enabled algorithms. We analyzed the daily cough counts including the daily predictability rates of 97 individuals who monitored their coughs over 30 days and had a daily cough rate of at least 5 coughs per hour.ResultsThe mean (median) daily cough rates varied from 6.5 to 182 (6.2 to 160) coughs per hour, with standard deviations (interquartile ranges) varying from 0.99 to 124 (1.30 to 207) coughs per hour among all subjects. There was a positive association between cough rate and variability, as subjects with higher mean cough rates (OLS) have larger standard deviations. The accuracy of any given day for predicting all 30 days is the One Day Predictability for that day, defined as the percentage of days when cough frequencies fall within that day's 95% confidence interval. Overall Predictability was the mean of the 30-One Day Predictability percentages and ranged from 95% (best predictability) to 30% (least predictability).ConclusionThere is substantial within-day and day-to-day variability for each subject with persistent cough recorded over 30 days. If confirmed in future studies, the clinical significance and the impact on the use of cough counts as a primary end-point of cough interventions of this variability need to be assessed.

This study evaluated the feasibility and utility of longitudinal cough frequency monitoring with the Hyfe Cough Tracker, a mobile application equipped with cough-counting artificial intelligence algorithms, in real-world patients with chronic cough. Patients with chronic cough (> 8-week duration) were monitored continuously for cough frequency with the Hyfe app for at least one week. Cough was also evaluated using the Leicester Cough Questionnaire (LCQ) and daily cough severity scoring (0–10). The study analyzed adherence rate, the correlation between objective cough frequency and subjective scores, day-to-day variability, and patient experience. Of 65 subjects consecutively recruited, 43 completed the study. The median cough monitoring duration was 13.9 days, with a median adherence of 91

Background: Recent developments in the field of artificial intelligence and acoustics have made it possible to objectively monitor cough in clinical and ambulatory settings. We hypothesized that clinical prognosis tools could be derived from objectively measured COVID-19 cough time patterns to rapidly identify patients at high risk of unfavorable clinical outcomes. Methods: Between December 2020 and June 2021, patients hospitalized with COVID-19 were enrolled at University of Florida Health Shands (n=98) and the Centre Hospitalier de l’Université de Montréal (n=25). Patients’ cough was continuously monitored digitally along with clinical severity of disease until hospital discharge, intubation, or death. The natural history of cough in severe COVID-19 disease was described and logistic models fitted on cough time patterns were used to predict clinical outcomes. Findings: In both cohorts, higher coughing rates were associated with more favorable clinical outcomes. The transitional cough rate, or maximum cough rate per hour predicting unfavorable outcomes, was 3·40 and the AUC for cough frequency as a predictor of unfavorable outcomes was 0·761. The initial 6h (0·792) and 24h (0·719) post-enrolment observation periods showed similar predictive value. Interpretation: Digital cough monitoring could be used as a prognosis biomarker to predict unfavorable clinical outcomes in COVID-19 disease. With early sampling periods showing good predictive value, this digital biomarker could be combined with clinical and paraclinical evaluation and is well adapted for triaging patients in overwhelmed or resources-limited health programs. Funding Information: This study was funded by the Patrick J McGovern Foundation (grant name: 'Early diagnosis of COVID-19 by utilizing Artificial Intelligence and Acoustic Monitoring') and by internal funding from the Emerging Pathogens Institute at the University of Florida. SGL is supported by the Fonds de Recherche en Santé Québec. Declaration of Interests: Authors disclose no financial or personal relationships with other people or organizations that could inappropriately influence this work. MR, PN, JB and PMS are employees of Hyfe Inc. Ethics Approval Statement: This study has received ethics board approval from the Centre de Recherche du Centre Hospitalier de l’Université de Montréal and the Emerging Pathogens Institute. All patients provided signed informed consent.

Cough is one of the most common reasons that individuals seek health care, and yet it is largely unmeasured in clinical medicine and practice.New technology that unobtrusively monitors cough holds great promise in continually monitoring cough.Detecting a change in cough rates would be easy if people coughed like metronomes.In reality, chronic coughers have good and bad days, hours, and minutes.This stochastic nature of cough raises challenges in detecting statistically significant changes in cough frequency.Here we describe statistical properties of cough monitoring data and suggest a method to detect changes in its frequency.

Research question What is the impact of the duration of cough monitoring on its accuracy in detecting changes in the cough frequency? Materials and methods This is a statistical analysis of a prospective cohort study. Participants were recruited in the city of Pamplona (Northern Spain), and their cough frequency was passively monitored using smartphone-based acoustic artificial intelligence software. Differences in cough frequency were compared using a one-tailed Mann–Whitney U test and a randomisation routine to simulate 24-h monitoring. Results 616 participants were monitored for an aggregated duration of over 9 person-years and registered 62 325 coughs. This empiric analysis found that an individual's cough patterns are stochastic, following a binomial distribution. When compared to continuous monitoring, limiting observation to 24 h can lead to inaccurate estimates of change in cough frequency, particularly in persons with low or small changes in rate. Interpretation Detecting changes in an individual's rate of coughing is complicated by significant stochastic variability within and between days. Assessing change based solely on intermittent sampling, including 24-h, can be misleading. This is particularly problematic in detecting small changes in individuals who have a low rate and/or high variance in cough pattern.

Rare inactivating mutations in BRCA1, BRCA2, ATM, TP53 and CHEK2 confer relative risks for breast cancer between about 2 and more than 10, but more common variants in these genes are generally considered of little or no clinical significance. Under the polygenic model for breast cancer carriers of multiple low-penetrance alleles are at high risk, but few such alleles have been reliably identified. We analysed 1037 potentially functional single nucleotide polymorphisms (SNPs) in candidate cancer genes in 473 women with two primary breast cancers and 2463 controls. Twenty-five of these SNPs were in BRCA1, BRCA2, ATM, TP53 and CHEK2. Among the 1037 SNPs there were a few significant findings, but hardly more than would be expected in this large experiment. There was, however, a significant trend in risk with increasing numbers of variant alleles for the 25 SNPs in BRCA1, BRCA2, ATM, TP53 and CHEK2 (P(trend) = 0.005). For the 21 of these with minor allele frequency <10% this trend was highly significant (P(trend) = 0.00004, odds ratio for 3 or more SNPs = 2.90, 95% CI 1.69-4.97). The individual effects of most of these risk alleles were undetectably small even in this well powered study, but the risk conferred by multiple variants is readily detectable and makes a substantial contribution to susceptibility. A risk score incorporating a suitably weighted sum of all potentially functional variants in these and a few other candidate genes may provide clinically useful identification of women at high genetic risk.

The Gly388Arg polymorphism in the fibroblast growth factor receptor 4 (FGFR4) gene has been reported to influence prognosis in a wide variety of cancer types. To determine whether Gly388Arg is a marker for lung cancer prognosis, we genotyped 619 lung cancer patients with incident disease and examined the relationship between genotype and overall survival. While we employed a comprehensive set of statistical tests, including those sensitive to the detection of differences in early survival, our data provide little evidence to support the tenet that the FGFR4 Gly388Arg polymorphism is a clinically useful marker for lung cancer prognosis.

Functional nonsynonymous single-nucleotide polymorphisms (nsSNPs) of folate metabolism genes can influence the methylation of tumour suppressor genes, thereby potentially impacting on tumour behaviour. To investigate whether such polymorphisms influence lung cancer survival, we genotyped 14 nsSNPs mapping to methylene-tetrahydrofolate reductase (MTHFR), methionine synthase (MTR), methionine synthase reductase (MTRR); DNA methyltransferase (DNMT2), methylenetetrahydrofolate dehydrogenase (MTHFD1) and methenyltetrahydrofolate synthetase (MTHFS) in 619 Caucasian women with incident disease, 465 with non-small cell (NSCLC) and 154 with small cell lung cancer (SCLC). The most significant association detected was with MTHFS Thr202Ala, with carriers of variant alleles having a worse prognosis (hazard ratio (HR)=1.49; 95% confidence interval: 1.14-1.94). Associations were also detected between overall survival (OS) in SCLC and homozygosity for MTHFR 222Val (HR=1.92; 1.03-3.58) and between OS from NSCLC and MTRR 175Leu carrier status (HR=1.36; 1.06-1.75). While there is evidence that variation in the folate metabolism genes may influence prognosis from lung cancer, current data are insufficiently robust to distinguish individual patient outcome.