Sri Harsha Chalasani

Background: During parenteral administration, liquid drug formulations come into direct and often prolonged contact with the polymeric materials of the delivery pathway, including bags, administration sets, extension tubing, syringes, and catheters. This contact can cause sorption, leaching, precipitation, degradation, and visible incompatibility, which may reduce the delivered dose or introduce contaminants. Relevant evidence is scattered across individual studies and is not captured by existing drug compatibility databases, and no structured resource currently exists to support the assessment of drug-device material compatibility. Objective: To systematically map the available evidence on drug–device material compatibility in parenteral administration, characterize the drug, formulation, device, material, and administration factors reported in relation to compatibility outcomes, and to structure and harmonize the extracted evidence into a modelling-ready database of drug, formulation, device, material, experimental condition, and compatibility outcome data. Eligibility Criteria: Studies reporting original data on the compatibility of a parenterally administered drug substance or product with a medical-device material through at least one mechanism (sorption, leaching, precipitation, degradation, or visual incompatibility) will be included. The context is parenteral administration via medical devices, such as infusion sets, syringes, catheters, infusion containers, pumps, and extension sets. No date restriction will be applied; only English-language records reporting extractable original data will be included. Sources of Evidence: PubMed/MEDLINE, Scopus, and Web of Science will be searched, along with grey-literature sources, including Google Scholar, the FDA and EMA databases, and conference proceedings. Data Collection: Records will be screened in two stages: title and abstract, followed by full text, against the predefined population-concept-context criteria, using Rayyan to manage deduplication and screening. Data will be extracted using a standardized form, summarized descriptively, and presented in tables and an evidence map. Extracted data will be curated into a standardized, modelling-ready database containing drug, formulation, device, material, experimental condition, and compatibility outcome data. Conclusion: This review will produce a structured map of the available evidence on drug–device material compatibility in parenteral administration, together with a curated, modelling-ready database of the extracted compatibility data.

Background: Medication safety is a critical concern in geriatric care, with high rates of polypharmacy and potentially inappropriate medications among older adult patients in India. The EldenCare application was developed as a digital clinical decision support tool to address these challenges through evidence-based screening and collaborative medication management. Objective: To evaluate the reliability and feasibility of the EldenCare system in supporting safe medication practices among older adults. Methods: This prospective observational study was conducted over 10 days with 22 healthcare professionals and 15 simulated patient profiles. Reliability assessment included the validation of automated clinical calculations (creatinine clearance and glomerular filtration rate) and the evaluation of drug-related problem (DRP) detection. Feasibility was measured using the System Usability Scale (SUS), AttrakDiff Mini questionnaire, and Technology Acceptance Model. A companion mobile application was also evaluated by 15 Android users based on 11 key features. Results: The EldenCare system received positive usability ratings (SUS: 72.82 ± 9.83) and high acceptance scores (perceived usefulness: 5.86 ± 0.65; perceived ease of use: 6.02 ± 0.60) from healthcare professionals, with no significant differences between physicians and clinical pharmacists ( P > .05). However, significant technical limitations were identified: (1) none of the 25 test cases for clinical calculations fell within the acceptable ±2% error margin; (2) DRP detection showed inadequate accuracy across all categories (53.42% overall, range: 61.64% to 76.02%, all below the predetermined 95% threshold); and (3) the patient mobile application’s medication and appointment reminder notifications failed after 3 days. Conclusion: EldenCare shows promising potential through high user acceptance but requires substantial technical refinement before clinical implementation. Future development should focus on algorithm accuracy, medication database mapping, and notification reliability to enhance medication safety in older adults.

Background: Falls are among the most prevalent and significant problems leading to disability, particularly in older adults. Although many studies have reported various predictors for fall among older adults, the evidence remains scattered across different types of predictors. A comprehensive synthesis of clinical, biomarker, and physical performance-based predictors is needed to inform evidence-based fall prevention strategies and fall risk assessment tools for older adults. Objective: To determine which clinical, biomarker, and physical performance indicators are most frequently reported fall predictors among older adults. Methods: Following the PRISMA guidelines, we will conduct a systematic review that includes three databases: PubMed, Embase, and Scopus. The proposed review will include prospective and retrospective cohort, case-control, cross-sectional, and randomized controlled trials that report predictor associations. Study types such as literature reviews, letters to the editor, pilot studies, and short communications will be excluded from the review. We will narratively synthesize the findings and, when suitable, perform random-effects meta-analyses to calculate pooled effect sizes (odds ratios, hazard ratios, risk ratios) for associations between predictors and falls. Subgroup analyses will be performed to investigate heterogeneity based on setting, age, and sex. The protocol was registered in PROSPERO (CRD420251119800).

Introduction: The Defined Daily Dose (DDD) is a statistical metric for quantifying drug utilization that does not always align with the Prescribed Daily Dose (PDD). This study aimed to identify the discrepancies between prescribed daily dose (PDD) and defined daily dose (DDD) among congestive heart failure (CHF) patients. methods: A single-center, prospective observational study was conducted among patients with heart failure at the outpatient Cardiology Department over a period of three months. All eligible prescrip-tions containing guideline-directed medical therapy (GDMT) were included, irrespective of the pa-tient’s sex, and for those aged ≥18 years with New York Heart Association (NYHA) class I–III heart failure. Standard definitions of DDD and PDD were employed. A drug registry was curated on an ad hoc basis that encompassed all relevant patient and medication data, from which DDD and PDD were computed. results: A total of 84 eligible patients [63 (75%) males and 21 (25%) females] with a mean age of 60.08 ± 10.11 years were recruited to the study with consent. The majority (94%) were diagnosed with heart failure with reduced ejection fraction (HFrEF), 44% were de novo, and 48% belonged to NYHA class III. A total of 685 medicines were used among participants, with an average of 8.2 (mean 10.54). However, only 37% of medicines were from GDMT, where the most commonly prescribed drugs per patient were β-blockers (89%; n = 253), followed by 68% of SGLT2 inhibitors, 67% of ARNI, and 50% of MRA. The average PDD: DDD ratio for four-pillar therapy ranged from 0.23 (β-Blockers) to 0.33 (MRA) and 1 (SGLT2-i). Except for GDMT, the PDD was 0.06 DDD for Enoxap-arin, 1.14 DDD for Glimepiride, and 2.0 DDD for Rosuvastatin. discussion: The PDDs were lower than the DDDs for most of the prescribed drugs. These discrep-ancies do not necessarily relate to real-time patient characteristics. conclusion: The variability of PDD and DDD for most drugs suggests the need for further monitor-ing to optimize patient care.

The cumulative effects of multiple medications with anticholinergic and sedative properties, referred to as anticholinergic and sedative burdens, can result in adverse effects in older adults. This study aimed to evaluate the exposure of older adult patients to anticholinergic and sedative medications. This cross-sectional study included older adult patients (aged ≥60 years) admitted to the geriatric inpatient wards. The anticholinergic burden was assessed using the CRIDECO scale, and the Drug Burden Index (DBI) quantified the cumulative anticholinergic and sedative burden. The data obtained were categorically assessed and are represented as [n (%)]. The associations between medication burden and health outcomes were analyzed using appropriate tests. The mean age of the participants in the study cohort was 72.80±7.41 years. Among the participants, 29.17% were administered at least one anticholinergic medication, with a mean cumulative Anticholinergic Cognitive Burden (ACB) score of 2.49±2.00. The majority (94.34%) had a cumulative DBI score of ≥1, with a mean DBI score of 3.14±1.55. Linear regression analysis demonstrated that both ACB and DBI were significant predictors of the length of hospitalization (ACB: p=0.002; DBI: p=0.001), whereas only DBI was associated with the Charlson Comorbidity Index (p=0.001). Logistic regression revealed that ACB scores significantly predicted cognitive decline (p=0.047). This study highlights the high prevalence of anticholinergic and sedative medication use among hospitalized older adult patients and its association with adverse health outcomes. Regular medication reviews and targeted deprescribing strategies are essential to reduce the medication burden in this vulnerable population.