National and regional prevalence of gestational diabetes mellitus in India: a systematic review and Meta-analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is frequently misdiagnosed during pregnancy. There is an abundance of evidence, but little is known regarding the regional prevalence estimates of GDM in India. This systematic review and meta-analysis aims to provide valuable insights into the national and regional prevalence of GDM among pregnant women in India. METHODS: We conducted an initial article search on PubMed, Scopus, Google Scholar, and ShodhGanga searches to identify quantitative research papers (database inception till 15th June,2022). This review included prevalence studies that estimated the occurrence of GDM across different states in India. RESULTS: Two independent reviewers completed the screening of 2393 articles, resulting in the identification of 110 articles that met the inclusion criteria, which collectively provided 117 prevalence estimates. Using a pooled estimate calculation (with an Inverse square heterogeneity model), the pooled prevalence of GDM in pregnant women was estimated to be 13%, with a 95% confidence interval (CI) ranging from 9 to 16%.. In India, Diabetes in Pregnancy Study of India (DIPSI) was the most common diagnostic criteria used, followed by International Association of Diabetes and Pregnancy Study Groups (IADPSG) and World Health Organization (WHO) 1999. It was observed that the rural population has slightly less prevalence of GDM at 10.0% [6.0-13.0%, I2=96%] when compared to the urban population where the prevalence of GDM was 12.0% [9.0-16.0%, I2 = 99%]. CONCLUSIONS: This review emphasizes the lack of consensus in screening and diagnosing gestational diabetes mellitus (GDM), leading to varied prevalence rates across Indian states. It thoroughly examines the controversies regarding GDM screening by analyzing population characteristics, geographic variations, diagnostic criteria agreement, screening timing, fasting vs. non-fasting approaches, cost-effectiveness, and feasibility, offering valuable recommendations for policy makers. By fostering the implementation of state-wise screening programs, it can contribute to improving maternal and neonatal outcomes and promoting healthier pregnancies across the country.

Recalibrating the Non-Communicable Diseases risk prediction tools for the rural population of Western India.

BACKGROUND: The aim of the present study was to recalibrate the effectiveness of Indian Diabetes Risk Score (IDRS) and Community-Based Assessment Checklist (CBAC) by opportunistic screening of Diabetes Mellitus (DM) and Hypertension (HT) among the people attending health centres, and estimating the risk of fatal and non-fatal Cardio-Vascular Diseases (CVDs) among them using WHO/ISH charts. METHODS: All the people aged ≥ 30 years attending the health centers were screened for DM and HT. Weight, height, waist circumference, and hip circumferences were measured, and BMI and Waist-Hip Ratio (WHR) were calculated. Risk categorization of all participants was done using IDRS, CBAC, and WHO/ISH risk prediction charts. Individuals diagnosed with DM or HT were started on treatment. The data was recorded using Epicollect5 and was analyzed using SPSS v.23 and MedCalc v.19.8. ROC curves were plotted for DM and HT with the IDRS, CBAC score, and anthropometric parameters. Sensitivity (SN), specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV), Accuracy and Youden's index were calculated for different cut-offs of IDRS and CBAC scores. RESULTS: A total of 942 participants were included for the screening, out of them, 9.2% (95% CI: 7.45-11.31) were diagnosed with DM for the first time. Hypertension was detected among 25.7% (95% CI: 22.9-28.5) of the participants. A total of 447 (47.3%) participants were found with IDRS score ≥ 60, and 276 (29.3%) with CBAC score > 4. As much as 26.1% were at moderate to higher risk (≥ 10%) of developing CVDs. Area Under the Curve (AUC) for IDRS in predicting DM was 0.64 (0.58-0.70), with 67.1% SN and 55.2% SP (Youden's Index 0.22). While the AUC for CBAC was 0.59 (0.53-0.65). For hypertension both the AUCs were 0.66 (0.62-0.71) and 0.63 (0.59-0.67), respectively. CONCLUSIONS: IDRS was found to have the maximum AUC and sensitivity thereby demonstrating its usefulness as compared to other tools for screening of both diabetes and hypertension. It thus has the potential to expose the hidden NCD iceberg. Hence, we propose IDRS as a useful tool in screening of Diabetes and Hypertension in rural India.

Predictive ability of complete blood count, mean platelet ratio, mean platelet volume, and neutrophil/lymphocyte ratio for severe pneumonia among RT-PCR or radiologically proven COVID-19 patients.

Background: Immuno-inflammatory markers related to white blood cells, and platelets are shown to be associated with COVID-19 infection, and considered to be independent markers for clinical outcomes and mortality. The present study aimed to study the predictive value of these hematologic parameters in progression of COVID-19 to severe pneumonia. Methods: This was an analytical cross-sectional study conducted among RT-PCR or radiologically proven COVID-19 patients in a tertiary care hospital in Rajasthan. Semi-structured questionnaire was used to collect the epidemiological information of the patients with COVID-19. Complete blood count and other laboratory parameters were also studied among the patients. Results: Mean age of participants in the study was 52 years, with about 70% being males. Cough and breathlessness were the most common symptoms among the patients. It was found that the parameters related to white blood cells were significantly different between patients with COVID-19 infection and severe pneumonia (except absolute monocyte count). NLR was significantly higher among those with severe pneumonia. In the univariate analysis, age (OR - 1.02), NLR (OR - 1.16), and albumin (OR - 0.45) were found to be significant predictors of progression to severe pneumonia. In the final model, adjusted for confounders, only NLR and albumin levels significantly predicted progression to severe pneumonia among COVID-19 patients. Conclusion: The study consolidates the predictive ability of NLR for severe pneumonia. It is an important finding, as health facilities with limited access to laboratory investigations can rely on simple markers in routine practice to predict the progression of COVID-19 infection to severe pneumonia.

Enabling Readiness of a School to Reopen During a Pandemic - A Field Experience.

Modeling studies indicate that the closure of schools during the coronavirus disease (COVID-19) pandemic may not be well grounded for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, as evidences indicate that children are less affected by this virus, and the clinical attack rates in the 0-19 age group are low. Experts also opine that school closures might have negative effects on the scholastic abilities of children and also an adverse impact on the economy and health care system, considering the responsibilities conferred upon the parents. Also, in a developing country like India, it is difficult for the rural population to afford distance online learning, which brings into importance the reopening of schools in a safe environment to avoid adversities such as increased drop-outs in the upcoming academic year, loss of in-person benefits such as mid-day meal scheme. This study highlights a field experience in relation to readiness assessment of a rural school in the Jodhpur district of Rajasthan, India, for a safe reopening to accept students in a safe and conducive atmosphere, which shall help prevent transmission of the virus in the schools among the children. In this regard, an indigenous readiness checklist has been developed to achieve the purpose, which assesses the readiness in 3 domains: (1) procedural readiness; (2) supplies, sanitation, and infrastructure-related; and (3) education and training.