Predictors for detecting chronic respiratory diseases in community surveys: A pilot cross-sectional survey in four South and South East Asian low- and middle-income countries

Hanafi, Nik Sherina; Khoo, Ee Ming; Parker, Richard; Ghorpade, Deesha; Salvi, Sundeep; Bakar, Ahmad Ihsan Abu; Chinna, Karuthan; Das, Deepa; Habib, Mansur; Hussein, Norita; Isaac, Rita; Islam, Mohammad Shahidul; Khan, Mohsin Saeed; Liew, Su May; Pang, Yong Kek; Paul, Biswajit; Saha, Samir K.; Wong, Li Ping; Yusuf, Osman; Yusuf, Shahida O; Juvekar, Sanjay; Pinnock, Hilary

doi:10.7189/jogh.11.04065

Cited by 5 publications

(6 citation statements)

References 22 publications

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“…A relevance of the symptom cough for the diagnosis of chronic obstructive airway diseases other than COPD (ie, asthma and OAD) cannot be inferred from the inconsistent results of the rather small studies presented here [37,[39][40][41][42][43]. Others report a stronger association of clinical symptoms and asthma [61]. However, they highlight wheezing and thoracic tightness, not cough, as the strongest predictors.…”

Section: Principal Findings and Comparison With Prior Workmentioning

confidence: 55%

“…The combination of symptoms such as "cough and dyspnea" and "chronic cough and phlegm," in turn, led to higher ORs through further specification [29,31]. Nevertheless, other authors report age and spirometry predicting COPD rather than the detection of clinical symptoms [61]. A relevance of the symptom cough for the diagnosis of chronic obstructive airway diseases other than COPD (ie, asthma and OAD) cannot be inferred from the inconsistent results of the rather small studies presented here [37,[39][40][41][42][43].…”

Section: Principal Findings and Comparison With Prior Workmentioning

confidence: 98%

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Identifying Existing Evidence to Potentially Develop a Machine Learning Diagnostic Algorithm for Cough in Primary Care Settings: Scoping Review

Cummerow,

Wienecke,

Engler

et al. 2023

J Med Internet Res

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Background Primary care is known to be one of the most complex health care settings because of the high number of theoretically possible diagnoses. Therefore, the process of clinical decision-making in primary care includes complex analytical and nonanalytical factors such as gut feelings and dealing with uncertainties. Artificial intelligence is also mandated to offer support in finding valid diagnoses. Nevertheless, to translate some aspects of what occurs during a consultation into a machine-based diagnostic algorithm, the probabilities for the underlying diagnoses (odds ratios) need to be determined. Objective Cough is one of the most common reasons for a consultation in general practice, the core discipline in primary care. The aim of this scoping review was to identify the available data on cough as a predictor of various diagnoses encountered in general practice. In the context of an ongoing project, we reflect on this database as a possible basis for a machine-based diagnostic algorithm. Furthermore, we discuss the applicability of such an algorithm against the background of the specifics of general practice. Methods The PubMed, Scopus, Web of Science, and Cochrane Library databases were searched with defined search terms, supplemented by the search for gray literature via the German Journal of Family Medicine until April 20, 2023. The inclusion criterion was the explicit analysis of cough as a predictor of any conceivable disease. Exclusion criteria were articles that did not provide original study results, articles in languages other than English or German, and articles that did not mention cough as a diagnostic predictor. Results In total, 1458 records were identified for screening, of which 35 articles met our inclusion criteria. Most of the results (11/35, 31%) were found for chronic obstructive pulmonary disease. The others were distributed among the diagnoses of asthma or unspecified obstructive airway disease, various infectious diseases, bronchogenic carcinoma, dyspepsia or gastroesophageal reflux disease, and adverse effects of angiotensin-converting enzyme inhibitors. Positive odds ratios were found for cough as a predictor of chronic obstructive pulmonary disease, influenza, COVID-19 infections, and bronchial carcinoma, whereas the results for cough as a predictor of asthma and other nonspecified obstructive airway diseases were inconsistent. Conclusions Reliable data on cough as a predictor of various diagnoses encountered in general practice are scarce. The example of cough does not provide a sufficient database to contribute odds to a machine learning–based diagnostic algorithm in a meaningful way.

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Section: Principal Findings and Comparison With Prior Workmentioning

confidence: 55%

Section: Principal Findings and Comparison With Prior Workmentioning

confidence: 98%

Identifying Existing Evidence to Potentially Develop a Machine Learning Diagnostic Algorithm for Cough in Primary Care Settings: Scoping Review

Cummerow,

Wienecke,

Engler

et al. 2023

J Med Internet Res

View full text Add to dashboard Cite

show abstract

“… 29 Agarwal et al studied the diagnosis of asthma in four Asian LMICs through a cross-sectional survey and reported that language was a barrier to healthcare access in diverse regions and that the quality of spirometry measurements was difficult to assess in the field. 30 The study also found that evaluating patient history, along with the presence of key symptoms (wheezing and chest tightness) was the most reliable method for diagnosing asthma. 30 These findings illustrated the difficulty of diagnosing asthma in a low-resource environment, while pointing toward evidence-based clinical adaptations to meet patient needs.…”

Section: Discussionmentioning

confidence: 89%

Global Burden of Asthma, and Its Impact on Specific Subgroups: Nasal Polyps, Allergic Rhinitis, Severe Asthma, Eosinophilic Asthma

Rabe,

Loke,

Gurjar

et al. 2023

JAA

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Background The complex nature of asthma has resulted in a poor understanding of its epidemiology, particularly in low-and middle-income countries (LMIC). Clinical subgroups, such as patients with severe asthma, eosinophilic asthma, allergic rhinitis, or nasal polyps, experience additional barriers to care. Methods Prevalence estimates for asthma and key clinical subgroups were extracted from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 and from a targeted literature review conducted through PubMed in October of 2021. National estimates were calculated and the roles of potential explanatory factors were explored through qualitative analysis. Results In total, 162 publications from 69 countries were included. Across continents, asthma prevalence values ranged from 3.44% (Asia), 3.67% (Africa), 4.90% (South America), 5.69% (Europe), 8.29% (North America), to 8.33% (Oceania). Globally, of those with asthma, 26.70% had severe asthma, 30.99% had eosinophilic asthma, 48.95% had allergic rhinitis, and 7.0% to 25.40% had nasal polyps. Countries with higher air quality, income status, and healthcare access and quality reported a higher asthma prevalence. Conclusion Asthma prevalence values were low in LMICs, potentially indicating health system deficiencies resulting in low diagnosis and reporting. The prevalence of eosinophilic asthma and severe asthma phenotypes was high in many countries, although the prevalence estimates of all asthma subgroups were quite variable.

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“…The equations for the Indian population, using the current standardisation of spirometry, have been published recently. 11 This gap in primary care has led to the advent of innovative digital "Make in India" solutions like Briota PFT in a Box™. This unique point of care solution includes a handheld digital spirometer SpiroPRO®, AI (Artificial Intelligence) first clinical decision support system software CDSS and remote spirometry verification.…”

Section: Discussionmentioning

confidence: 99%

“…Informed by the literature review conducted, 10,11 a range of validated questionnaires that had previously been used in LMICs to detect CRDs were considered. A participant with a high-risk score for Group A was further administered Group B questionnaire (Supplementary file 2 questionnaire B).…”

Section: Questionnairementioning

confidence: 99%

Using spirometry for screening and diagnosis of chronic respiratory diseases in primary health care: findings from a community health project in rural India

Sakhare,

Chitte,

Munje

et al. 2024

Journal of Global Health Reports

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Background Chronic respiratory diseases (CRDs) such as Chronic obstructive pulmonary disease (COPD), Asthma and post-tuberculosis lung disease (PTLD) are a growing public health concern in India. Early diagnosis and management of CRDs require a good quality spirometry test, a technician to conduct spirometry and a chest physician to interpret the results. In India, these are not available at the primary care level. This study reports the feasibility of a large-scale CRD diagnosis and management program in primary care using a unique point-of-care spirometry solution, Briota PFT in a Box™. # Methods A community-based cross-sectional study was conducted among 15,602 adults in Dindori Taluka (subdivision), Nashik, Maharashtra state. This study was part of a holistic CRD diagnosis and management program SAVE™ (Spirometry Assisted Virtually Early). Make In India point of care solution Briota PFT in a Box™ was used. A House‐to‐house community-based assessment checklist (CBAC) survey, 4-parameter spirometry test, 15-parameter pre and post-bronchodilator spirometry test and a software-assisted medical examination by the medical officer at primary care were conducted. Software was used to generate CRD diagnosis and lung health score (LHS™). The diagnosis was verified by the chest physician. Confirmed diagnosed patients were provided treatment and offered a patient support program. Interviews were conducted with the patients, nurses, doctors and public health officials for understanding feasibility and documenting learning from program SAVE™. # Results Out of 15,602 adults surveyed, total 4,937 (31.6%) were identified as “CRD high risk”. 1231 participants based on medical examination, spirometry tests and software analysis were identified as CRD candidates by medical officers at primary care. 1154 participants out of 15,602 (7.4%) were confirmed diagnosed as CRD patients post independent evaluation by chest physicians. At the time of follow-up, 537 patients (75% of 712 patients enrolled in patient support program) reported improvement in symptoms and high satisfaction with the program. District health officer, Medical officers, nurses, Accredited Social Health Activist (ASHA) from the primary health care centers confirmed ease of use and feasibility of using Briota PFT in a Box™ in program SAVE™. Outcome and learning from program SAVE™ was documented and submitted to Ministry of Health and Family Welfare Government of India. # Conclusions CRD diagnosis and management in large scale settings in primary healthcare level using a point of care spirometry solution Briota PFT in a Box™ is highly feasible.

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Predictors for detecting chronic respiratory diseases in community surveys: A pilot cross-sectional survey in four South and South East Asian low- and middle-income countries

Cited by 5 publications

References 22 publications

Identifying Existing Evidence to Potentially Develop a Machine Learning Diagnostic Algorithm for Cough in Primary Care Settings: Scoping Review

Identifying Existing Evidence to Potentially Develop a Machine Learning Diagnostic Algorithm for Cough in Primary Care Settings: Scoping Review

Global Burden of Asthma, and Its Impact on Specific Subgroups: Nasal Polyps, Allergic Rhinitis, Severe Asthma, Eosinophilic Asthma

Using spirometry for screening and diagnosis of chronic respiratory diseases in primary health care: findings from a community health project in rural India

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