Automatic Cough Classification for Tuberculosis Screening in a Real-World Environment

Objective: The automatic discrimination between the coughing sounds produced by patients with tuberculosis (TB) and those produced by patients with other lung ailments. Approach: We present experiments based on a dataset of 1358 forced cough recordings obtained in a developing-world clinic from 16 patients with confirmed active pulmonary TB and 35 patients suffering from respiratory conditions suggestive of TB but confirmed to be TB negative. Using nested cross-validation, we have trained and evaluated five machine learning classifiers: logistic regression (LR), support vector machines (SVM), k-nearest neighbour (KNN), multilayer perceptrons (MLP) and convolutional neural networks (CNN). Main Results: Although classification is possible in all cases, the best performance is achieved using LR. In combination with feature selection by sequential forward selection (SFS), our best LR system achieves an area under the ROC curve (AUC) of 0.94 using 23 features selected from a set of 78 high-resolution mel-frequency cepstral coefficients (MFCCs). This system achieves a sensitivity of 93\% at a specificity of 95\% and thus exceeds the 90\% sensitivity at 70\% specificity specification considered by the World Health Organisation (WHO) as a minimal requirement for a community-based TB triage test. Significance: The automatic classification of cough audio sounds, when applied to symptomatic patients requiring investigation for TB, can meet the WHO triage specifications for the identification of patients who should undergo expensive molecular downstream testing. This makes it a promising and viable means of low cost, easily deployable frontline screening for TB, which can benefit especially developing countries with a heavy TB burden.Comment: This paper has been accepted in Physiological Measurement (2021

Clinical utility of C-reactive protein-based triage for presumptive pulmonary tuberculosis in South African adults.

BACKGROUND: Identification of an accurate, low-cost triage test for pulmonary TB among people presenting to healthcare facilities is an urgent global research priority. We assessed the diagnostic accuracy and clinical utility of C-reactive protein (CRP) for TB triage among symptomatic adult outpatients, irrespective of HIV status. METHODS: We prospectively enrolled adults reporting at least one (for people with HIV) or two (for people without HIV) symptoms of cough, fever, night sweats, or weight loss at two TB clinics in Cape Town, South Africa. Participants provided sputum for culture and Xpert MTB/RIF Ultra. We evaluated the diagnostic accuracy of CRP (measured using a laboratory-based assay) against a TB-culture reference standard as the area under the receiver operating characteristic curve (AUROC), and sensitivity and specificity at pre-specified thresholds. We assessed clinical utility using decision curve analysis and benchmarked against WHO recommendations. RESULTS: Of 932 included individuals, 255 (27%) had culture-confirmed pulmonary TB and 389 (42%) were living with HIV. CRP demonstrated an AUROC of 0·80 (95% confidence interval 0·77-0·83), with sensitivity 93% (89-95%) and specificity 54% (50-58%) using a primary cut-off of ≥10 mg/L. Performance was similar among people with HIV to those without. In decision curve analysis, CRP-based triage offered greater clinical utility than confirmatory testing for all up to a number willing to test threshold of 20 confirmatory tests per true positive pulmonary TB case diagnosed (threshold probability 5%). If it is possible to perform more confirmatory tests than this, a 'confirmatory test for all' strategy performed better. CONCLUSIONS: CRP achieved the WHO-defined sensitivity, but not specificity, targets for a triage test for pulmonary TB and showed evidence of clinical utility among symptomatic outpatients, irrespective of HIV status. FUNDING: South African Medical Research Council, EDCTP2, Royal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, Royal College of Physicians

Thiopurine monotherapy is effective in ulcerative colitis but significantly less so in Crohn’s disease: long-term outcomes for 11 928 patients in the UK inflammatory bowel disease bioresource

Objective: Thiopurines are widely used as maintenance therapy in inflammatory bowel disease (IBD) but the evidence base for their use is sparse and their role increasingly questioned. Using the largest series reported to date, we assessed the long-term effectiveness of thiopurines in ulcerative colitis (UC) and Crohn’s disease (CD), including their impact on need for surgery. Design: Outcomes were assessed in 11 928 patients (4968 UC, 6960 CD) in the UK IBD BioResource initiated on thiopurine monotherapy with the intention of maintaining medically induced remission. Effectiveness was assessed retrospectively using patient-level data and a definition that required avoidance of escalation to biological therapy or surgery while on thiopurines. Analyses included overall effectiveness, time-to-event analysis for treatment escalation and comparison of surgery rates in patients tolerant or intolerant of thiopurines. Results: Using 68 132 patient-years of exposure, thiopurine monotherapy appeared effective for the duration of treatment in 2617/4968 (52.7%) patients with UC compared with 2378/6960 (34.2%) patients with CD (p<0.0001). This difference was corroborated in a multivariable analysis: after adjusting for variables including treatment era, thiopurine monotherapy was less effective in CD than UC (OR 0.47, 95% CI 0.43 to 0.51, p<0.0001). Thiopurine intolerance was associated with increased risk of surgery in UC (HR 2.44, p<0.0001); with a more modest impact on need for surgery in CD (HR=1.23, p=0.0015). Conclusion: Thiopurine monotherapy is an effective long-term treatment for UC but significantly less effective in CD

Diagnostic yield of urine lipoarabinomannan and sputum tuberculosis tests in people living with HIV: a systematic review and meta-analysis of individual participant data

BACKGROUND: Sputum is the most widely used sample to diagnose active tuberculosis, but many people living with HIV are unable to produce sputum. Urine, in contrast, is readily available. We hypothesised that sample availability influences the diagnostic yield of various tuberculosis tests. METHODS: In this systematic review and meta-analysis of individual participant data, we compared the diagnostic yield of point-of-care urine-based lipoarabinomannan tests with that of sputum-based nucleic acid amplification tests (NAATs) and sputum smear microscopy (SSM). We used microbiologically confirmed tuberculosis based on positive culture or NAAT from any body site as the denominator and accounted for sample provision. We searched PubMed, Web of Science, Embase, African Journals Online, and clinicaltrials.gov from database inception to Feb 24, 2022 for randomised controlled trials, cross-sectional studies, and cohort studies that assessed urine lipoarabinomannan point-of-care tests and sputum NAATs for active tuberculosis detection in participants irrespective of tuberculosis symptoms, HIV status, CD4 cell count, or study setting. We excluded studies in which recruitment was not consecutive, systematic, or random; provision of sputum or urine was an inclusion criterion; less than 30 participants were diagnosed with tuberculosis; early research assays without clearly defined cutoffs were tested; and humans were not studied. We extracted study-level data, and authors of eligible studies were invited to contribute deidentified individual participant data. The main outcomes were the tuberculosis diagnostic yields of urine lipoarabinomannan tests, sputum NAATs, and SSM. Diagnostic yields were predicted using Bayesian random-effects and mixed-effects meta-analyses. This study is registered with PROSPERO, CRD42021230337. FINDINGS: We identified 844 records, from which 20 datasets and 10 202 participants (4561 [45%] male participants and 5641 [55%] female participants) were included in the meta-analysis. All studies assessed sputum Xpert (MTB/RIF or Ultra, Cepheid, Sunnyvale, CA, USA) and urine Alere Determine TB LAM (AlereLAM, Abbott, Chicago, IL, USA) in people living with HIV aged 15 years or older. Nearly all (9957 [98%] of 10 202) participants provided urine, and 82% (8360 of 10 202) provided sputum within 2 days. In studies that enrolled unselected inpatients irrespective of tuberculosis symptoms, only 54% (1084 of 1993) of participants provided sputum, whereas 99% (1966 of 1993) provided urine. Diagnostic yield was 41% (95% credible interval [CrI] 15-66) for AlereLAM, 61% (95% Crl 25-88) for Xpert, and 32% (95% Crl 10-55) for SSM. Heterogeneity existed across studies in the diagnostic yield, influenced by CD4 cell count, tuberculosis symptoms, and clinical setting. In predefined subgroup analyses, all tests had higher yields in symptomatic participants, and AlereLAM yield was higher in those with low CD4 counts and inpatients. AlereLAM and Xpert yields were similar among inpatients in studies enrolling unselected participants who were not assessed for tuberculosis symptoms (51% vs 47%). AlereLAM and Xpert together had a yield of 71% in unselected inpatients, supporting the implementation of combined testing strategies. INTERPRETATION: AlereLAM, with its rapid turnaround time and simplicity, should be prioritised to inform tuberculosis therapy among inpatients who are HIV-positive, regardless of symptoms or CD4 cell count. The yield of sputum-based tuberculosis tests is undermined by people living with HIV who cannot produce sputum, whereas nearly all participants are able to provide urine. The strengths of this meta-analysis are its large size, the carefully harmonised denominator, and the use of Bayesian random-effects and mixed-effects models to predict yields; however, data were geographically restricted, clinically diagnosed tuberculosis was not considered in the denominator, and little information exists on strategies for obtaining sputum samples. FUNDING: FIND, the Global Alliance for Diagnostics

Tuberculosis screening among ambulatory people living with HIV: a systematic review and individual participant data meta-analysis.

BackgroundThe WHO-recommended tuberculosis screening and diagnostic algorithm in ambulatory people living with HIV is a four-symptom screen (known as the WHO-recommended four symptom screen [W4SS]) followed by a WHO-recommended molecular rapid diagnostic test (eg Xpert MTB/RIF [hereafter referred to as Xpert]) if W4SS is positive. To inform updated WHO guidelines, we aimed to assess the diagnostic accuracy of alternative screening tests and strategies for tuberculosis in this population.MethodsIn this systematic review and individual participant data meta-analysis, we updated a search of PubMed (MEDLINE), Embase, the Cochrane Library, and conference abstracts for publications from Jan 1, 2011, to March 12, 2018, done in a previous systematic review to include the period up to Aug 2, 2019. We screened the reference lists of identified pieces and contacted experts in the field. We included prospective cross-sectional, observational studies and randomised trials among adult and adolescent (age ≥10 years) ambulatory people living with HIV, irrespective of signs and symptoms of tuberculosis. We extracted study-level data using a standardised data extraction form, and we requested individual participant data from study authors. We aimed to compare the W4SS with alternative screening tests and strategies and the WHO-recommended algorithm (ie, W4SS followed by Xpert) with Xpert for all in terms of diagnostic accuracy (sensitivity and specificity), overall and in key subgroups (eg, by antiretroviral therapy [ART] status). The reference standard was culture. This study is registered with PROSPERO, CRD42020155895.FindingsWe identified 25 studies, and obtained data from 22 studies (including 15 666 participants; 4347 [27·7%] of 15 663 participants with data were on ART). W4SS sensitivity was 82% (95% CI 72-89) and specificity was 42% (29-57). C-reactive protein (≥10 mg/L) had similar sensitivity to (77% [61-88]), but higher specificity (74% [61-83]; n=3571) than, W4SS. Cough (lasting ≥2 weeks), haemoglobin (2), and lymphadenopathy had high specificities (80-90%) but low sensitivities (29-43%). The WHO-recommended algorithm had a sensitivity of 58% (50-66) and a specificity of 99% (98-100); Xpert for all had a sensitivity of 68% (57-76) and a specificity of 99% (98-99). In the one study that assessed both, the sensitivity of sputum Xpert Ultra was higher than sputum Xpert (73% [62-81] vs 57% [47-67]) and specificities were similar (98% [96-98] vs 99% [98-100]). Among outpatients on ART (4309 [99·1%] of 4347 people on ART), W4SS sensitivity was 53% (35-71) and specificity was 71% (51-85). In this population, a parallel strategy (two tests done at the same time) of W4SS with any chest x-ray abnormality had higher sensitivity (89% [70-97]) and lower specificity (33% [17-54]; n=2670) than W4SS alone; at a tuberculosis prevalence of 5%, this strategy would require 379 more rapid diagnostic tests per 1000 people living with HIV than W4SS but detect 18 more tuberculosis cases. Among outpatients not on ART (11 160 [71·8%] of 15 541 outpatients), W4SS sensitivity was 85% (76-91) and specificity was 37% (25-51). C-reactive protein (≥10 mg/L) alone had a similar sensitivity to (83% [79-86]), but higher specificity (67% [60-73]; n=3187) than, W4SS and a sequential strategy (both test positive) of W4SS then C-reactive protein (≥5 mg/L) had a similar sensitivity to (84% [75-90]), but higher specificity than (64% [57-71]; n=3187), W4SS alone; at 10% tuberculosis prevalence, these strategies would require 272 and 244 fewer rapid diagnostic tests per 1000 people living with HIV than W4SS but miss two and one more tuberculosis cases, respectively.InterpretationC-reactive protein reduces the need for further rapid diagnostic tests without compromising sensitivity and has been included in the updated WHO tuberculosis screening guidelines. However, C-reactive protein data were scarce for outpatients on ART, necessitating future research regarding the utility of C-reactive protein in this group. Chest x-ray can be useful in outpatients on ART when combined with W4SS. The WHO-recommended algorithm has suboptimal sensitivity; Xpert for all offers slight sensitivity gains and would have major resource implications.FundingWorld Health Organization

Automatic Tuberculosis and COVID-19 cough classification using deep learning

We present a deep learning based automatic cough classifier which can discriminate tuberculosis (TB) coughs from COVID-19 coughs and healthy coughs. Both TB and COVID-19 are respiratory disease, have cough as a predominant symptom and claim thousands of lives each year. The cough audio recordings were collected at both indoor and outdoor settings and also uploaded using smartphones from subjects around the globe, thus contain various levels of noise. This cough data include 1.68 hours of TB coughs, 18.54 minutes of COVID-19 coughs and 1.69 hours of healthy coughs from 47 TB patients, 229 COVID-19 patients and 1498 healthy patients and were used to train and evaluate a CNN, LSTM and Resnet50. These three deep architectures were also pre-trained on 2.14 hours of sneeze, 2.91 hours of speech and 2.79 hours of noise for improved performance. The class-imbalance in our dataset was addressed by using SMOTE data balancing technique and using performance metrics such as F1-score and AUC. Our study shows that the highest F1-scores of 0.9259 and 0.8631 have been achieved from a pre-trained Resnet50 for two-class (TB vs COVID-19) and three-class (TB vs COVID-19 vs healthy) cough classification tasks, respectively. The application of deep transfer learning has improved the classifiers' performance and makes them more robust as they generalise better over the cross-validation folds. Their performances exceed the TB triage test requirements set by the world health organisation (WHO). The features producing the best performance contain higher order of MFCCs suggesting that the differences between TB and COVID-19 coughs are not perceivable by the human ear. This type of cough audio classification is non-contact, cost-effective and can easily be deployed on a smartphone, thus it can be an excellent tool for both TB and COVID-19 screening