Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Making cough count in tuberculosis care.

ABSTRACT: Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.

SUBMITTER: Zimmer AJ

PROVIDER: S-EPMC9258463 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Making cough count in tuberculosis care.

Zimmer Alexandra J AJ Ugarte-Gil César C Pathri Rahul R Dewan Puneet P Jaganath Devan D Cattamanchi Adithya A Pai Madhukar M Grandjean Lapierre Simon S

Communications medicine 20220706

Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, su ...[more]

PMID: 35814294

Similar Datasets

Comment: Making data count.

Project description: Not available

| S-EPMC4550906 | biostudies-literature

Cough dynamics in adults receiving tuberculosis treatment.

Project description:Cough is a characteristic symptom of tuberculosis, is the main cause of transmission, and is used to assess treatment response. We aimed to identify the best measure of cough severity and characterize changes during initial tuberculosis therapy. We conducted a prospective cohort of recently diagnosed ambulatory adult patients with pulmonary tuberculosis in two tertiary hospitals in Lima, Peru. Pre-treatment and five times during the first two months of treatment, a vibrometer was used to capture 4-hour recordings of involuntary cough. A total of 358 recordings from 69 participants were analyzed using a computer algorithm. Total time spent coughing (seconds per hour) was a better predictor of microbiologic indicators of disease severity and treatment response than the frequency of cough episodes or cough power. Patients with prior tuberculosis tended to cough more than patients without prior tuberculosis, and patients with tuberculosis and diabetes coughed more than patients without diabetes co-morbidity. Cough characteristics were similar regardless of HIV co-infection and for drug-susceptible versus drug-resistant tuberculosis. Tuberculosis treatment response may be meaningfully assessed by objectively monitoring the time spent coughing. This measure demonstrated that cough was increased in patients with TB recurrence or co-morbid diabetes, but not because of drug resistance or HIV co-infection.

| S-EPMC7279573 | biostudies-literature

Experiences of implementing the 'Making Every Contact Count' initiative into a UK integrated care system: an interview study.

Project description:BackgroundThe 'Making Every Contact Count' (MECC) approach is in line with the current National Health Service (NHS) strategy to improve and prevent health conditions in England. Despite its importance and value for preventative healthcare, implementation of MECC varies. The aim of this study was to explore the barriers and facilitators of implementing MECC and MECC training into an integrated care system (ICS).MethodsRemote semi-structured interviews were conducted with staff across an ICS in the North West of England who were involved in implementing and delivering MECC across the region. Data were analysed initially using an inductive thematic analysis approach and then interpreted using the 'Capability, Opportunity, Motivation = Behaviour' (COM-B) model of behaviour change.ResultsWe interviewed nine stakeholders and identified three superordinate themes: (1) macro-level barriers and facilitators, e.g. funding; (2) organizational level barriers and facilitators, e.g. time and resource; and (3) individual-level barriers/facilitators for both MECC trainers and MECC agents.ConclusionsMECC has potential to meet the needs of the public's health, but barriers to its implementation exist. MECC must be successfully embedded into organizations and regions in which it is implemented, which relies on further development of an appropriate infrastructure including sustainable funding and a shift in culture to value preventative healthcare.

| S-EPMC10689001 | biostudies-literature

A dataset of Solicited Cough Sound for Tuberculosis Triage Testing.

Project description:Cough is a common and commonly ignored symptom of lung disease. Cough is often perceived as difficult to quantify, frequently self-limiting, and non-specific. However, cough has a central role in the clinical detection of many lung diseases including tuberculosis (TB), which remains the leading infectious disease killer worldwide. TB screening currently relies on self-reported cough which fails to meet the World Health Organization (WHO) accuracy targets for a TB triage test. Artificial intelligence (AI) models based on cough sound have been developed for several respiratory conditions, with limited work being done in TB. To support the development of an accurate, point-of-care cough-based triage tool for TB, we have compiled a large multi-country database of cough sounds from individuals being evaluated for TB. The dataset includes more than 700,000 cough sounds from 2,143 individuals with detailed demographic, clinical and microbiologic diagnostic information. We aim to empower researchers in the development of cough sound analysis models to improve TB diagnosis, where innovative approaches are critically needed to end this long-standing pandemic.

| S-EPMC11489852 | biostudies-literature

Mycobacterium tuberculosis Sulfolipid-1 Activates Nociceptive Neurons and Induces Cough.

Project description:Pulmonary tuberculosis, a disease caused by Mycobacterium tuberculosis (Mtb), manifests with a persistent cough as both a primary symptom and mechanism of transmission. The cough reflex can be triggered by nociceptive neurons innervating the lungs, and some bacteria produce neuron-targeting molecules. However, how pulmonary Mtb infection causes cough remains undefined, and whether Mtb produces a neuron-activating, cough-inducing molecule is unknown. Here, we show that an Mtb organic extract activates nociceptive neurons in vitro and identify the Mtb glycolipid sulfolipid-1 (SL-1) as the nociceptive molecule. Mtb organic extracts from mutants lacking SL-1 synthesis cannot activate neurons in vitro or induce cough in a guinea pig model. Finally, Mtb-infected guinea pigs cough in a manner dependent on SL-1 synthesis. Thus, we demonstrate a heretofore unknown molecular mechanism for cough induction by a virulent human pathogen via its production of a complex lipid.

| S-EPMC7102531 | biostudies-literature

Protocol for studying cough frequency in people with pulmonary tuberculosis.

Project description:Cough is a key symptom of tuberculosis (TB) as well as the main cause of transmission. However, a recent literature review found that cough frequency (number of coughs per hour) in patients with TB has only been studied once, in 1969. The main aim of this study is to describe cough frequency patterns before and after the start of TB treatment and to determine baseline factors that affect cough frequency in these patients. Secondarily, we will evaluate the correlation between cough frequency and TB microbiological resolution.This study will select participants with culture confirmed TB from 2 tertiary hospitals in Lima, Peru. We estimated that a sample size of 107 patients was sufficient to detect clinically significant changes in cough frequency. Participants will initially be evaluated through questionnaires, radiology, microscopic observation drug susceptibility broth TB-culture, auramine smear microscopy and cough recordings. This cohort will be followed for the initial 60 days of anti-TB treatment, and throughout the study several microbiological samples as well as 24 h recordings will be collected. We will describe the variability of cough episodes and determine its association with baseline laboratory parameters of pulmonary TB. In addition, we will analyse the reduction of cough frequency in predicting TB cure, adjusted for potential confounders.Ethical approval has been obtained from the ethics committees at each participating hospital in Lima, Peru, Asociación Benéfica PRISMA in Lima, Peru, the Universidad Peruana Cayetano Heredia in Lima, Peru and Johns Hopkins University in Baltimore, USA. We aim to publish and disseminate our findings in peer-reviewed journals. We also expect to create and maintain an online repository for TB cough sounds as well as the statistical analysis employed.

| S-EPMC4853990 | biostudies-other

Dynamics of Cough Frequency in Adults Undergoing Treatment for Pulmonary Tuberculosis.

Project description:BackgroundCough is the major determinant of tuberculosis transmission. Despite this, there is a paucity of information regarding characteristics of cough frequency throughout the day and in response to tuberculosis therapy. Here we evaluate the circadian cycle of cough, cough frequency risk factors, and the impact of appropriate treatment on cough and bacillary load.MethodsWe prospectively evaluated human immunodeficiency virus-negative adults (n = 64) with a new diagnosis of culture-proven, drug-susceptible pulmonary tuberculosis immediately prior to treatment and repeatedly until treatment day 62. At each time point, participant cough was recorded (n = 670) and analyzed using the Cayetano Cough Monitor. Consecutive coughs at least 2 seconds apart were counted as separate cough episodes. Sputum samples (n = 426) were tested with microscopic-observation drug susceptibility broth culture, and in culture-positive samples (n = 252), the time to culture positivity was used to estimate bacillary load.ResultsThe highest cough frequency occurred from 1 pm to 2 pm, and the lowest from 1 am to 2 am (2.4 vs 1.1 cough episodes/hour, respectively). Cough frequency was higher among participants who had higher sputum bacillary load (P < .01). Pretreatment median cough episodes/hour was 2.3 (interquartile range [IQR], 1.2-4.1), which at 14 treatment days decreased to 0.48 (IQR, 0.0-1.4) and at the end of the study decreased to 0.18 (IQR, 0.0-0.59) (both reductions P < .001). By 14 treatment days, the probability of culture conversion was 29% (95% confidence interval, 19%-41%).ConclusionsCoughs were most frequent during daytime. Two weeks of appropriate treatment significantly reduced cough frequency and resulted in one-third of participants achieving culture conversion. Thus, treatment by 2 weeks considerably diminishes, but does not eliminate, the potential for airborne tuberculosis transmission.

| S-EPMC5399950 | biostudies-literature

TBscreen: A passive cough classifier for tuberculosis screening with a controlled dataset.

Project description:Recent respiratory disease screening studies suggest promising performance of cough classifiers, but potential biases in model training and dataset quality preclude robust conclusions. To examine tuberculosis (TB) cough diagnostic features, we enrolled subjects with pulmonary TB (N = 149) and controls with other respiratory illnesses (N = 46) in Nairobi. We collected a dataset with 33,000 passive coughs and 1600 forced coughs in a controlled setting with similar demographics. We trained a ResNet18-based cough classifier using images of passive cough scalogram as input and obtained a fivefold cross-validation sensitivity of 0.70 (±0.11 SD). The smartphone-based model had better performance in subjects with higher bacterial load {receiver operating characteristic-area under the curve (ROC-AUC): 0.87 [95% confidence interval (CI): 0.87 to 0.88], P < 0.001} or lung cavities [ROC-AUC: 0.89 (95% CI: 0.88 to 0.89), P < 0.001]. Overall, our data suggest that passive cough features distinguish TB from non-TB subjects and are associated with bacterial burden and disease severity.

| S-EPMC10776005 | biostudies-literature

Shared Decision Making for the Emergency Provider: Engaging Patients When Seconds Count.

Project description:IntroductionPhysicians need to be able to communicate the myriad of management options clearly to patients and engage them in their health care decisions, even in the fast-paced environment of the emergency department. Shared decision making (SDM) is an effective communication strategy for physicians to share diagnostic uncertainty, avoid potentially harmful tests, and solicit patients' preferences for their care. Role-playing with just-in-time feedback is an effective method to learn and practice SDM before having these conversations with patients.MethodsThis flipped classroom workshop featured precourse materials and an in-class session incorporating a short lecture outlining a framework for SDM, followed by role-playing through patient scenarios. Learners took turns playing the physician or patient role and received feedback on their communication skills while in the physician role. A faculty examiner subsequently assessed skill attainment using a simulated patient encounter and checklist of critical actions.ResultsThe workshop was an interactive and effective way to teach SDM to 28 PGY 1 and PGY 2 emergency medicine residents. Two months after attending the workshop, over 75% of the first-year residents were able to complete all the elements of the SDM process in a simulated patient encounter; four residents required no prompting by the examiner.DiscussionA communications workshop that incorporates role-playing with different patient encounters is an interactive way to teach SDM for the emergency setting. Residents early in their clinical training can benefit from learning and practicing SDM in a simulated setting.

| S-EPMC7449574 | biostudies-literature

Making Pastoralists Count: Geospatial Methods for the Health Surveillance of Nomadic Populations.

Project description:Nomadic pastoralists are among the world's hardest-to-reach and least served populations. Pastoralist communities are difficult to capture in household surveys because of factors including their high degree of mobility over remote terrain, fluid domestic arrangements, and cultural barriers. Most surveys use census-based sampling frames which do not accurately capture the demographic and health parameters of nomadic populations. As a result, pastoralists are "invisible" in population data such as the Demographic and Health Surveys (DHS). By combining remote sensing and geospatial analysis, we developed a sampling strategy designed to capture the current distribution of nomadic populations. We then implemented this sampling frame to survey a population of mobile pastoralists in southwest Ethiopia, focusing on maternal and child health (MCH) indicators. Using standardized instruments from DHS questionnaires, we draw comparisons with regional and national data finding disparities with DHS data in core MCH indicators, including vaccination coverage, skilled birth attendance, and nutritional status. Our field validation demonstrates that this method is a logistically feasible alternative to conventional sampling frames and may be used at the population level. Geospatial sampling methods provide cost-affordable and logistically feasible strategies for sampling mobile populations, a crucial first step toward reaching these groups with health services.

| S-EPMC6726942 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data