Efficacy and safety of vitamin D in tuberculosis patients: a systematic review and meta-analysis

Evidence from the basic research and epidemiological studies indicates a beneficial effect of vitamin D in the treatment of tuberculosis (TB). However, the evidence from randomized controlled trials (RCTs) is inconsistent. This systematic review and meta-analysis was performed to synthesize evidence regarding role of vitamin D versus placebo for the management of TB. We searched PubMed and Cochrane Clinical Trial Registry for RCTs comparing vitamin D versus placebo for the treatment of TB. RCTs enrolling adult patients with TB receiving vitamin D in addition to standard treatment were included. Data were pooled using random effects model. The study was conducted according to PRISMA guidelines and protocol was registered with PROSPERO (CRD42016052841). Of 605 identified references, 12 RCTs were included. The overall risk of bias in included studies was low or unclear. There was no significant difference between vitamin D and placebo group for any outcomes of efficacy (time to culture conversion, time to smear conversion, rate of culture conversion, and rate of smear conversion) or safety (mortality, serious adverse events, and nonserious adverse events) Vitamin D administered with standard treatment has no beneficial effect in the TB patients as compared to the placebo.</p

Additional file 1 of Is telemedicine a holy grail in healthcare policy: clinicians’ and patients’ perspectives from an Apex Institution in Western India

Additional file 1 Supplementary Table 1. Association of perception of doctors regarding delivering telemedicine services with socio-demographic variables. Supplementary Table 2. Association of perception of the patient regarding receiving telemedicine services with socio-demographic variables

Sociodemographic and behavioral characteristics of the study participants (n = 942).

Sociodemographic and behavioral characteristics of the study participants (n = 942).</p

Statistical comparison of all the ROC curves of IDRS and CBAC scores.

Statistical comparison of all the ROC curves of IDRS and CBAC scores.</p

Sensitivity, specificity, PPV, NPV, LR⁺, LR^-, accuracy, and Youden’s index of IDRS and CBAC scores to diagnose Met S.

Sensitivity, specificity, PPV, NPV, LR+, LR-, accuracy, and Youden’s index of IDRS and CBAC scores to diagnose Met S.</p

Area Under the Curve (AUC) and level of significance for ROC curves.

Area Under the Curve (AUC) and level of significance for ROC curves.</p

Fig 2 -

ROC curves for depicting prediction ability of Met S with IDRS and CBAC score for Metabolic Syndrome (2a: ROC curves for Males, 2b: ROC curves for Females, 2c: ROC curves for total participants).</p

Flow chart depicting screening of the study participants for Metabolic Syndrome.

Flow chart depicting screening of the study participants for Metabolic Syndrome.</p

Data sheet.

BackgroundIndian Diabetic Risk Score (IDRS) and Community Based Assessment Checklist (CBAC) are easy, inexpensive, and non-invasive tools that can be used to screen people for Metabolic Syndrome (Met S). The study aimed to explore the prediction abilities of IDRS and CBAC tools for Met S.MethodsAll the people of age ≥30 years attending the selected rural health centers were screened for Met S. We used the International Diabetes Federation (IDF) criteria to diagnose the Met S. ROC curves were plotted by taking Met S as dependent variables, and IDRS and CBAC scores as independent/prediction variables. Sensitivity (SN), specificity (SP), Positive and Negative Predictive Value (PPV and NPV), Likelihood Ratio for positive and negative tests (LR+ and LR-), Accuracy, and Youden’s index were calculated for different IDRS and CBAC scores cut-offs. Data were analyzed using SPSS v.23 and MedCalc v.20.111.ResultsA total of 942 participants underwent the screening process. Out of them, 59 (6.4%, 95% CI: 4.90–8.12) were found to have Met S. Area Under the Curve (AUC) for IDRS in predicting Met S was 0.73 (95%CI: 0.67–0.79), with 76.3% (64.0%-85.3%) sensitivity and 54.6% (51.2%-57.8%) specificity at the cut-off of ≥60. For the CBAC score, AUC was 0.73 (95%CI: 0.66–0.79), with 84.7% (73.5%-91.7%) sensitivity and 48.8% (45.5%-52.1%) specificity at the cut-off of ≥4 (Youden’s Index, 2.1). The AUCs of both parameters (IDRS and CBAC scores) were statistically significant. There was no significant difference (p = 0.833) in the AUCs of IDRS and CBAC [Difference between AUC = 0.00571].ConclusionThe current study provides scientific evidence that both IDRS and CBAC have almost 73% prediction ability for Met S. Though CBAC holds relatively greater sensitivity (84.7%) than IDRS (76.3%), the difference in prediction abilities is not statistically significant. The prediction abilities of IDRS and CBAC found in this study are inadequate to qualify as Met S screening tools.</div

Additional file 1 of Recalibrating the Non-Communicable Diseases risk prediction tools for the rural population of Western India

Additional file 1: Table 1. Sociodemographic characteristics of the study population (n=942)