Infrared thermal screening, via the use of handheld non-contact infrared thermometers (NCITs) and thermal scanners, has been widely implemented all over the world. We performed a systematic review and meta-analysis to investigate its diagnostic accuracy for the detection of fever. We searched PubMed, Embase, the Cochrane Library, medRxiv, bioRxiv, ClinicalTrials.gov, COVID-19 Open Research Dataset, COVID-19 research database, Epistemonikos, EPPI-Centre, World Health Organization International Clinical Trials Registry Platform, Scopus and Web of Science databases for studies where a non-contact infrared device was used to detect fever against a reference standard of conventional thermometers. Forest plots and Hierarchical Summary Receiver Operating Characteristics curves were used to describe the pooled summary estimates of sensitivity, specificity and diagnostic odds ratio. From a total of 1063 results, 30 studies were included in the qualitative synthesis, of which 19 were included in the meta-analysis. The pooled sensitivity and specificity were 0.808 (95%CI 0.656–0.903) and 0.920 (95%CI 0.769–0.975), respectively, for the NCITs (using forehead as the site of measurement), and 0.818 (95%CI 0.758–0.866) and 0.923 (95%CI 0.823–0.969), respectively, for thermal scanners. The sensitivity of NCITs increased on use of rectal temperature as the reference. The sensitivity of thermal scanners decreased in a disease outbreak/pandemic setting. Changes approaching statistical significance were also observed on the exclusion of neonates from the analysis. Thermal screening had a low positive predictive value, especially at the initial stage of an outbreak, whereas the negative predictive value (NPV) continued to be high even at later stages. Thermal screening has reasonable diagnostic accuracy in the detection of fever, although it may vary with changes in subject characteristics, setting, index test and the reference standard used. Thermal screening has a good NPV even during a pandemic. The policymakers must take into consideration the factors surrounding the screening strategy while forming ad-hoc guidelines.

Background: The association of serum prolactin (PRL) with diabetes is still uncertain, with a paucity of data in the south Indian population. This study aims to compare the serum PRL levels between type 2 diabetes mellitus (T2DM) patients and normoglycaemic volunteers and correlate the serum PRL level with fasting plasma glucose (FPG), postprandial plasma glucose (PPG), glycated haemoglobin (HbA1c) levels, and the lipid profile in the study population. Methods: This was a comparative cross-sectional study among 112 T2DM participants and 112 healthy volunteers in a tertiary care centre in India. All participants were tested for FPG, PPG, HbA1c, fasting serum lipid profile, and serum PRL, which were compared between T2DM patients and healthy volunteers. Results: The serum PRL in T2DM patients was significantly lower compared to healthy volunteers (8.67 ± 4.37 vs. 13.76 ± 6.55 ng/ml, P < 0.001). FPG, PPG, and HbA1c correlated inversely with serum PRL in our study population. On multivariable logistic regression adjusted for age and sex, a higher serum PRL level within the physiological range was protective for T2DM (adjusted odds ratio: 0.83, 95% CI: 0.77-0.90, P < 0.001). Serum PRL levels were inversely correlated with serum total cholesterol, low-density lipoprotein cholesterol, and triglycerides, but not with high-density lipoprotein cholesterol. Conclusions: A high serum PRL within the physiological range was inversely associated with the prevalence of T2DM in the south Indian population. Serum PRL also correlated inversely with glycaemic and blood lipid parameters. Larger longitudinal studies are required to further validate the association of serum PRL with various components of metabolic syndrome in the south Indian population.

Byssinosis is an occupational lung disease affecting textile workers exposed to cotton, jute and hemp dust. It causes symptoms like cough, breathlessness, and wheezing which is more during Mondays. Diagnosis is mainly clinical. The true burden of byssinosis in India remains unknown, and this systematic review and meta-analysis (SR-MA) aims to estimate its prevalence among textile industry workers in India. This study was registered in PROSPERO. The search spanned from January 2000 to September 2023, focusing on observational studies that met specific criteria. Two independent reviewers screened the literature, extracted relevant data, and assessed the risk of bias. Statistical analysis included a random effects model, assessment of heterogeneity and publication bias. Eighteen studies (5678 individuals) were included in the analysis. Byssinosis diagnosis was based on Schilling’s criteria in the majority of studies. Seven studies had low risk of bias, three had high risk, and the rest were moderate. There was no significant publication bias. The pooled prevalence of byssinosis was 24% (95% CI = 13%-36%) with high heterogeneity (I ² = 99.02%). Sub-group analysis of studies with low risk of bias showed a prevalence of 20% (95% CI = 11% - 29%). Extrapolation of these findings to India suggests that about 10 million people are affected by byssinosis. The authors recommend development and practice of tailored health surveillance guidelines and the promotion of respiratory protective equipment (RPE) among those employed in textile industries.