Several studies have proposed that the neutrophil–lymphocyte ratio (NLR) is one of the various biomarkers that can be useful in assessing COVID-19 disease-related outcomes. Our systematic review analyzes the relationship between on-admission NLR values and COVID-19 severity and mortality. Six different severity criteria were used. A search of the literature in various databases was conducted from 1 January 2020 to 1 May 2021. We calculated the pooled standardized mean difference (SMD) for the collected NLR values. A meta-regression analysis was performed, looking at the length of hospitalization and other probable confounders, such as age, gender, and comorbidities. A total of sixty-four studies were considered, which included a total of 15,683 patients. The meta-analysis showed an SMD of 3.12 (95% CI: 2.64–3.59) in NLR values between severe and non-severe patients. A difference of 3.93 (95% CI: 2.35–5.50) was found between survivors and non-survivors of the disease. Upon summary receiver operating characteristics analysis, NLR showed 80.2% (95% CI: 74.0–85.2%) sensitivity and 75.8% (95% CI: 71.3–79.9%) specificity for the prediction of severity and 78.8% (95% CI: 73.5–83.2%) sensitivity and 73.0% (95% CI: 68.4–77.1%) specificity for mortality, and was not influenced by age, gender, or co-morbid conditions. Conclusion: On admission, NLR predicts both severity and mortality in COVID-19 patients, and an NLR > 6.5 is associated with significantly greater the odds of mortality.

There is a need for biomarkers to predict outcomes, including mortality, in interstitial lung disease (ILD). Krebs von den Lungen-6 (KL-6) and surfactant protein D (SP-D) are associated with lung damage and fibrosis in all ILDs and are related to important clinical outcomes. Though these two biomarkers have been associated with ILD outcomes, there are no studies that have evaluated their predictive potential in combination. This study aims to determine whether KL-6 and SP-D are linked to poor disease outcomes and mortality. Additionally, we plan to examine whether changes in KL-6 and SP-D concentrations correspond with changes in lung function and whether serial measurements improve their predictive potential to identify disease progression and mortality. Forty-four patients with ILD participated in a prospective 6-month longitudinal observational study. ILD patients who succumbed had the highest KL-6 levels (3990.4 U/mL (3490.0–4467.6)) and highest SP-D levels (256.1 ng/mL (217.9–260.0)), followed by those who deteriorated: KL-6 levels 1357.0 U/mL (822.6–1543.4) and SP-D levels 191.2 ng/mL (152.8–210.5). The generalized linear model (GLM) analysis demonstrated that changes in forced vital capacity (FVC), diffusing capacity of lungs for carbon monoxide (DLCO), forced expiratory volume in 1 s (FEV1), and partial pressure of arterial oxygen (PaO₂) were correlated to changes in KL6 (p = 0.016, 0.014, 0.027, 0.047) and SP-D (p = 0.008, 0.012, 0.046, 0.020), respectively. KL-6 (odds ratio (OR): 2.87 (1.06–7.79)) and SPD (OR: 1.76 (1.05–2.97)) were independent predictors of disease progression, and KL-6 (hazard ratio (HR): 3.70 (1.46–9.41)) and SPD (HR: 2.58 (1.01–6.59)) were independent predictors of death by Cox regression analysis. Combined biomarkers (KL6 + SPD + CT + FVC) had the strongest ability to predict disease progression (AUC: 0.797) and death (AUC: 0.961), on ROC analysis. Elevated KL-6 and SPD levels are vital biomarkers for predicting the severity, progression, and outcomes of ILD. High baseline levels or an increase in levels over a six-month follow-up despite treatment indicate a poor prognosis. Combining KL6 and SPD with conventional measures yields a more potent prognostic indicator. Clinical studies are needed to test additional interventions, and future research will determine if this combined biomarker benefits different ethnicities globally.

Telemedicine is a promising solution to the challenges of delivering equitable and quality primary healthcare, especially in LMICs. This review evaluated peer-reviewed literature on telehealth interventions in Indian primary care published from Jan 1, 2011 to Dec 31, 2021, from PubMed, Scopus, TRIP, Google Scholar, Indian Kanoon, and Cochrane database The majority of Indian studies focus on key health issues like maternal and child health, mental health, diabetes, infectious diseases, and hypertension, mainly through patient education, monitoring, and diagnostics. Yet, there's a lack of research on telemedicine's cost-effectiveness, communication among providers, and the role of leadership in its quality and accessibility. The current research has gaps, including small sample sizes and inconsistent methodologies, which hamper the evaluation of telemedicine's effectiveness. India's varied healthcare landscape, technological limitations, and social factors further challenge telemedicine's adoption. Despite regulatory efforts, issues like the digital divide and data privacy persist. Addressing these challenges with a context-aware, technologically driven approach is crucial for enhancing healthcare through telemedicine in India.

To achieve herd immunity to a disease, a large portion of the population needs to be vaccinated, which is possible only when there is broad acceptance of the vaccine within the community. Thus, policymakers need to understand how the general public will perceive the vaccine. This study focused on the degree of COVID-19 vaccine hesitancy and refusal and explored sociodemographic correlations that influence vaccine hesitancy and refusal. A cross-sectional online survey was conducted among the adult population of India. The survey consisted of basic demographic questions and questions from the Vaccination Attitudes Examination (VAX) Scale. Multinomial logistical regression was used to identify correlates of vaccine hesitancy and refusal. Of the 1582 people in the study, 9% refused to become vaccinated and 30.8% were hesitant. We found that both hesitancy and refusal predictors were nearly identical (lower socioeconomic status, female gender, and older age groups), except for three groups (subjects aged 45–64 years, those with approximate income <10,000 INR/month, and those residing in rural households) that showed slightly higher odds of vaccine hesitancy than refusal. We need to address the underlying sociodemographic determinants and formulate public awareness programs to address specific subgroups that are at higher risk of rejecting the vaccine and convert those who are undecided or hesitant into those willing to accept the vaccine.

Medication errors (MEs) are a major public health concern as they are detrimental to patient safety, compromise patients' confidence in the healthcare system, increase healthcare costs, and adversely affect the patient's quality of life. This is especially true in low to middle-income countries where the significance of MEs is largely undervalued. This study aims to investigate the prevalence of MEs and analyze the causes, medicines involved, reporting, and severity of MEs in a tertiary care setting. A prospective observational study was conducted from March 2020 to February 2021 in a tertiary care teaching hospital in South India. The data was collected after reviewing patient medical records, by interviewing patients and healthcare professionals. National Coordinating Council for Medication Error Reporting and Prevention (NCC MERP) index was used to evaluate MEs. A total of 557 MEs were identified from 3798 patients with a prevalence of 14.6%. Prescribing errors were the most commonly observed ME followed by errors related to documentation of medical records, administration-related errors, and dispensing errors. Lack of time for documentation of medication records, shift change and work overload were common causes of MEs. The majority of MEs were category A and B of the NCC MERP severity index. Antibiotics and proton pump inhibitors were the most common medicines involved in MEs. Prescribing and documentation errors were most prevalent. Implementation of systems like strict adherence to treatment guidelines, computerized provider order entry (CPOE), barcode medication administration, and closed-loop electronic medication management systems may greatly help reduce MEs. All healthcare institutions should undertake routine audits to determine the prevalence and causes of medication errors.