Diabetic foot ulcer is a debilitating complication of long‐standing diabetes mellitus. Patients lose their earning potential, face repeated hospitalizations, and are forced to bear heavy treatment costs. This places an enormous financial burden on the patients and their families. This study seeks to ascertain the out‐of‐pocket expenditure among these patients and correlate it with their risk factor profile. In this hospital‐based cross‐sectional study, a total of 154 patients with diabetic foot ulcers or amputations have been studied with an elaborate patient questionnaire and relevant clinical examinations. The costs incurred and the risk factors of the patients were analyzed for statistical association. The median total annual out‐of‐pocket expenditure for the management of diabetic foot ulcers among the study participants was found to be ₹29 775 (₹9650–₹81 120) ($378.14 [$122.56–$1030.22]). Out of the total expenditure, 58.49% went towards direct medical costs, 5.64% towards direct non‐medical costs, and 35.88% for indirect costs. Medications, ulcer dressing and periodic debridement have accounted for 79.26% of direct medical costs. Transportation (61.37%) and patient's loss of income (89.45%) account for the major costs under the direct non‐medical and indirect cost categories, respectively. A high ulcer grade and area, long ulcer duration, and past history of ulcers have higher expenditure. Patients seeking treatment from private establishments and those engaged in professional/skilled occupations have higher expenses. Adequate dressing of foot ulcers and proper footwear are associated with lower treatment expenditure. 68.8% of the participants have faced catastrophic expenditure due to treatment costs of diabetic foot ulcers. Adequate glycaemic control and proper foot care are necessary. Patients must seek medical care at the earliest in case of foot ulceration. Clinicians must provide proper wound care, institute effective antibiotics, and manage the complications. Government and insurance schemes are required to alleviate the patients' financial burden.

Systemic sclerosis-associated pulmonary arterial hypertension (SSc-PAH) is a life-threatening vascular complication of SSc, marked by high morbidity and mortality. Early diagnosis remains a major challenge due to nonspecific symptoms and the limitations of conventional tools such as echocardiography (ECHO), pulmonary function tests (PFTs), and serum biomarkers. This review evaluates the emerging role of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), in improving the diagnostic landscape of SSc-PAH. A comprehensive literature search was conducted across PubMed, Scopus, IEEE Xplore, Embase and Google Scholar to identify studies involving AI applications in SSc, pulmonary arterial hypertension (PAH), and their intersection. Evidence indicates that AI models can assist interpretation across modalities, including heart sounds, ECGs, chest X-rays (CXRs), ECHOs, CT pulmonary angiography (CTPA), and omics-based biomarkers. While several models show encouraging diagnostic performance, their accuracy varies by dataset and modality, and most require external validation against right heart catheterization (RHC)-confirmed cohorts. Integrating multimodal data through AI frameworks may enhance early recognition and individualized risk stratification; however, these tools remain exploratory. Future work should emphasize harmonized hemodynamic definitions, transparent validation protocols, and SSc-specific datasets to ensure clinical applicability and reproducibility.

Background: Several studies have reported a reduced risk of COVID-19-related mortality in patients taking antidiabetic medications. This is an umbrella review, meta-analysis, and Bayesian sensitivity assessment of SGLT2 inhibitors (SGLT2is) in COVID-19 patients with type 2 diabetes mellitus (T2DM). Methods: A search was conducted on the MEDLINE (PubMed), EMBASE, Cochrane, and ClinicalTrials.gov databases on 5/12/2023. We performed an umbrella review of systematic reviews and meta-analyses on the effects of SGLT2is in T2DM patients with COVID-19 and critically appraised them using AMSTAR 2.0. Trials investigating SGLT2i use in COVID-19 patients post-hospitalisation and observational studies on prior SGLT2i use among COVID-19 patients were included in the meta-analysis, adhering to the PRISMA guidelines. Results: SGLT2is exhibited significantly lower odds of mortality (OR 0.67, 95% CI 0.53–0.84) and hospitalisation (OR 0.84, 0.75–0.94) in COVID-19 patients with T2DM. Bayesian sensitivity analyses corroborated most of the findings, with differences observed in hospitalisation and mortality outcomes. SGLT-2 inhibitors showed an OR of 1.20 (95% CI 0.64–2.27) for diabetic ketoacidosis. Publication bias was observed for hospitalisation, but not for mortality. The GRADE assessment indicated a low to very low quality of evidence because of the observational studies included. Conclusions: The prophylactic use of SGLT2is reduces mortality and hospitalisation among COVID-19 patients, particularly in patients with diabetes. The utility of SGLT2is after hospitalisation is uncertain and warrants further investigation. A limited efficacy has been observed under critical conditions. Individualised assessment is crucial before integration into COVID-19 management.

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Purpose: To assess the presence and quantity of CD34+ hematopoietic stem cells in patients with Alzheimer’s disease (AD) through a meta-analysis. Methods: A systematic search of the databases identified the observational and interventional studies reporting baseline CD34+ cell counts in AD patients. The data on mean counts and the measures of variation were extracted. Standardized mean differences (SMDs) were calculated using common and random effects models to compare the CD34+ cell counts between the AD patients and controls. Heterogeneity among the studies was evaluated using tau², tau, and I² statistics. The risk of bias was assessed using the Newcastle–Ottawa Scale and the ROBINS-I tool. Patients: Five studies were included, comprising four observational studies and one open-label trial, with a total of 271 participants (139 AD patients and 132 controls). Results: The meta-analysis indicated an increase in CD34+ cell counts of the AD patients when compared to the controls. The common effects model showed a moderate SMD of 0.2964 (95% CI:0.0490–0.5437). However, the random effects model yielded a non-significant SMD of 0.2326 (95% CI: −0.4832–0.9484). Significant heterogeneity was observed among the studies (I² = 87.1%, p < 0.0001). Conclusion: AD patients may exhibit higher circulating CD34+ cell counts than the controls, but substantial heterogeneity and potential biases limit definitive conclusions.

This letter examines the potential relationship between the highly toxic herbicide paraquat (PQ) and Parkinson's disease (PD). Despite animal studies implicating PQ as a causative factor for PD, the evidence is insufficient due to limited human research on this topic. There is a pressing need for human autopsy-based studies in PQ poisoning fatalities to comprehend paraquat's neuropathology. Further studies are crucial to assess the morbidity in paraquat poisoning survivors, potentially shedding light on clinical links with PD. Although current research hasn't definitively established a causal connection, the absence of evidence shouldn't discourage ongoing investigation. The pursuit of understanding the PQ-PD connection necessitates unwavering commitment from the scientific community.