Systematic Review With Meta-Analyses and Critical Appraisal of Clinical Prediction Rules for Pulmonary Tuberculosis in Hospitals (original) (raw)
ABSTRACTBackgroundMany children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Diagnostic challenges in children include low bacterial burden, challenges around specimen collection, and limited access to diagnostic expertise. Algorithms that guide decisions to initiate tuberculosis treatment in resource-limited settings could help to close the persistent childhood tuberculosis treatment gap. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies conducted to date have been small and localised, with limited generalizability.MethodsWe collated individual participant data including clinical, bacteriological, and radiologic information from prospective diagnostic studies in high-tuberculosis incidence settings enrolling children <10 years with presumptive pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing...
Evaluation of Clinical Parameters to Predict Mycobacterium tuberculosis in Inpatients
Archives of Internal Medicine, 2000
Background: Respiratory isolation has been recommended for all patients with suspected tuberculosis (TB) to avoid transmission to other patients and health care personnel. In implementing these guidelines, patients with and without TB are frequently isolated, significantly increasing hospital costs. The objective of this study was to derive a clinical rule to predict the need for respiratory isolation of patients with suspected TB. Methods: To identify potential predictors of the need for isolation, 56 inpatients with sputum cultures positive for TB were retrospectively compared with 56 controls who were isolated on admission to the hospital based on clinically suspected TB but whose sputum cultures tested negative for TB. Variables analyzed included TB risk factors, clinical symptoms, and findings from physical examination and chest radiography. Results: Multivariate analysis revealed that the following factors were significantly associated with a culture positive for TB: presence of TB risk factors or symptoms (odds ratio [OR], 7.9 [95% confidence interval (CI), 4.4-24.2]), a positive purified protein derivative tuberculin test result (OR, 13.2 [95% CI, 4.4-40.7]), high temperature (OR, 2.8 [95% CI, 1.1-8.3]), and upper-lobe disease on chest radiograph (OR, 14.6 [95% CI, 3.7-57.5]). Shortness of breath (OR, 0.2 [95% CI, 0.12-0.53]) and crackles noted during the physical examination (OR, 0.29 [95% CI, 0.15-0.57]) were negative predictors of TB. A scoring system was developed using these variables. A patient's total score of 1 or higher indicated the need for respiratory isolation, accurately predicting a culture positive for TB (98% sensitivity [95% CI, 95%-100%]; 46% specificity [95% CI, 33%-59%]). Conclusion: Among inpatients with suspected active pulmonary TB, a prediction rule based on clinical and chest radiographic findings accurately identified patients requiring respiratory isolation.
Predicting the outcome of therapy for pulmonary tuberculosis
2000
Patients vary considerably in their response to treatment of pulmonary tuberculosis. Although several studies have indicated that adverse outcomes are more likely in those patients with delayed sputum sterilization, few tools are available to identify those patients prospectively. In this study, multivariate models were developed to predict the response to therapy in a prospectively recruited cohort of 42 HIV-uninfected subjects with drug-sensitive tuberculosis. The cohort included 2 subjects whose initial response was followed by drug-sensitive relapse. The total duration of culture positivity was best predicted by a model that included sputum M. tuberculosis antigen 85 concentration on Day 14 of therapy, days-to-positive in BACTEC on Day 30, and the baseline radiographic extent of disease (R ϭ 0.63). A model in which quantitative AFB microscopy replaced BACTEC also performed adequately (R ϭ 0.58). Both models predicted delayed clearance of bacilli in both relapses (Ͼ 85th percentile of all subjects) using information collected during the first month of therapy. Stratification of patients according to anticipated response to therapy may allow TB treatment to be individualized, potentially offering superior outcomes and greater efficiency in resource utilization, and aiding in the conduct of clinical trials.
BMC Public Health
Background: Delays in diagnosis and treatment of pulmonary tuberculosis are a major setback to global tuberculosis control. There is currently no global evidence on the average delays thus, the most important contributor to total delay is unknown. We aimed to estimate average delay measures and to investigate sources for heterogeneity among studies assessing delay measures. Methods: Systematic review of studies reporting mean (± standard deviation) or median (interquartile range, IQR) of patient, doctor, diagnostic, treatment, health system and/or total delays in journal articles indexed in PubMed. We pooled mean delays using random-effects inverse variance meta-analysis, investigated for variations in pooled estimates in subgroup analyses and explored for sources of heterogeneity using pre-specified explanatory variables. Results: The systematic review included 198 studies (831,724 patients) from 78 countries. The median number of patients per study was 243 (IQR; 160-458) patients. Overall, the pooled mean total delay was 87.6 (95% CI: 81.4-93.9) days. The most important and largest contributor to total delay was patient delay with a pooled mean delay of 81 (95% CI: 70-92) days followed by doctor's delay and treatment delay with pooled mean delays of 29.5 (95% CI: 25.9-33.0) and 7.9 (95% CI: 6.9-8.9) days respectively. There was considerable heterogeneity in all pooled analyses (I 2 > 95%). In the meta-regression models of mean delays, studies excluding extra-pulmonary tuberculosis patients reported increased mean doctor's delay by 45 days on average, non-use of chest x-ray and conducting studies in high income countries decreased mean treatment delay by 20 and 22 days on average, respectively. Conclusion: Strategies to address patients' delay could have important implications for the success of the global tuberculosis control programmes.
BMC Pulmonary Medicine, 2012
Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.
Predicting Mycobacterium tuberculosis in patients with community-acquired pneumonia
European Respiratory Journal, 2013
The 22 risk factors suggested by the Centers for Disease Control and Prevention (CDC) to predict patients at risk for Mycobacterium tuberculosis have not been evaluated in hospitalised patients with community-acquired pneumonia (CAP). We evaluated which of the CDC risk factors best predict M. tuberculosis in these patients. To our knowledge, this is the first time a score has been developed assessing these risk factors. This was a secondary analysis of 6976 patients hospitalised with CAP enrolled in the Community-Acquired Pneumonia Organization International Cohort Study. Using Poisson regression, we selected the subset of risk factors that best predicted the presence of CAP due to M. tuberculosis. This subset was compared to the CDC risk factors using receiver operating characteristic (ROC) curve analysis. Five risk factors were found to best predict CAP due to M. tuberculosis: night sweats, haemoptysis, weight loss, M. tuberculosis exposure and upper lobe infiltrate. The area under the ROC curve for all CDC risk factors was 71% and 89% for the subset of five risk factors. The CDC-suggested risk factors are poor at predicting the presence of M. tuberculosis in hospitalised patients with CAP. With a subset of five risk factors identified in this study, we developed a new score, which will improve our capacity to isolate patients at risk of CAP due to M. tuberculosis at the time of hospitalisation. @ERSpublications New scores developed from a subset of CDC risk factors predicts M. tuberculosis in patients hospitalised with CAP http://ow.ly/qf1F2 For editorial comments see page 10.
Predictors for Identifying the Most Infectious Pulmonary Tuberculosis Patient
Journal of the Formosan Medical Association, 2008
Tuberculosis (TB) persists as a major cause of human mortality and morbidity, affecting almost a third of the world's population. 1 Sputum microscopy and sputum culture has been advocated as two useful diagnostic tools for pulmonary TB. However, only a few TB-control programs in low-income countries have access to culture facilities in their primary-care diagnostic centers. Moreover, culture for acid-fast bacilli (AFB) takes 6-8 weeks to be interpretable, which limits the usefulness of culture as a first-line diagnostic test. Under these circumstances, sputum smear examination for AFB is the most useful diagnostic test for pulmonary TB.
Scientific Reports, 2018
Background: There is uncertainty regarding which factors are associated with in-hospital mortality among patients with pulmonary TB (PTB). The aim of this systematic review and meta-analysis is to identify predictors of in-hospital mortality among patients with PTB. Methods: We searched MEDLINE, EMBASE, and Global Health, for cohort and case-control studies that reported risk factors for inhospital mortality in PTB. We pooled all factors that were assessed for an association, and presented relative associations as pooled odds ratios (ORs). Results: We identified 2,969 records, of which we retrieved 51 in full text; 11 cohort studies that evaluated 5,468 patients proved eligible. Moderate quality evidence suggested an association with co-morbid malignancy and in-hospital mortality (OR 1.85; 95% CI 1.01-3.40). Low quality evidence showed no association with positive sputum smear (OR 0.99; 95% CI 0.40-2.48), or male sex (OR 1.09, 95% CI 0.84-1.41), and very low quality evidence showed no association with diabetes mellitus (OR 1.31, 95% IC 0.38-4.46), and previous TB infection (OR 2.66, 95% CI 0.48-14.87). Conclusion: Co-morbid malignancy was associated with increased risk of in-hospital death among pulmonary TB patients. There is insufficient evidence to confirm positive sputum smear, male sex, diabetes mellitus, and previous TB infection as predictors of in-hospital mortality in TB patients.