Arundhati Barua

Alzheimer's disease (AD) is the leading cause of dementia globally, typified by insidious cognitive impairment underlain by amyloid-β plaques, neurofibrillary tangles, and neurodegeneration. Accumulating evidence shows these pathophysiological changes start years to decades before symptom onset, highlighting an urgent need for preclinical detection and prognostication. Biomarkers have revolutionized the field with the ability to measure amyloid deposition, tau pathology, and neuronal damage in vivo. The AT(N) framework has reconceptualized AD as a biologically based continuum, merging biomarkers across modalities. Cerebrospinal fluid and imaging assessments, including amyloid/tau PET and MRI-based volumetry, are still gold standards but are constrained by invasiveness and expense. New developments in blood-based biomarkers, particularly plasma phosphorylated tau (p-tau217, p-tau231), Aβ42/Aβ40 ratio, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP), have proved to be highly accurate in identifying preclinical disease and forecasting cognitive decline. Head-to-head comparisons show that plasma p-tau217 is equally effective as tau PET in forecasting progression in cognitively unimpaired individuals, and repeated testing enhances prognostic precision. Multimodal biomarker integration provides greater predictive power, but standardization, diversity of populations, and preclinical diagnosis ethical issues persist. Potential future advances involve validation in large and heterogeneous cohorts, longitudinal follow-up, and incorporation of new markers like synaptic and inflammatory proteins. In summary, biomarkers are revolutionizing early diagnosis and prognosis of AD, making possible earlier intervention and therapeutic customization.

Background: Cardiorenal Syndrome (CRS) represents a bidirectional interplay between cardiac and renal dysfunction, where impairment of one organ precipitates or exacerbates dysfunction in the other. It is commonly encountered in heart failure (HF) patients and is associated with poor prognosis. Despite increasing awareness, data on the clinical outcomes and prognostic predictors of CRS in Indian populations remain limited. Objective: To evaluate the prevalence, risk factors, and six-month clinical outcomes of CRS in patients with heart failure admitted to a tertiary care hospital, and to identify predictors of mortality Methods: This prospective observational study included 70 patients with heart failure (≥12 years) admitted to D. Y. Patil Hospital, Navi Mumbai (2023–2024). Patients were classified into CRS and non-CRS groups based on consensus diagnostic criteria. Demographic, clinical, biochemical, and echocardiographic parameters were recorded. Patients were followed for six months to assess survival and rehospitalization. Statistical analyses were performed using SPSS version 26.0, with logistic regression to identify independent mortality predictors. Results: Among 70 HF patients, 48 (68.5%) had CRS. The mean age was 60.53 ± 15.55 years, with a male predominance (62.5%). The most common comorbidities were hypertension (63.9%) and diabetes mellitus (50%). Type I CRS was the most frequent subtype (54.1%). Six-month mortality was significantly higher in CRS patients (29.2%) compared to non-CRS patients (0%) (p 2000 pg/mL) (OR 3.8, p=0.008), reduced LVEF (2 mg/dL (OR 2.5, p=0.046), and eGFR Conclusion: CRS was highly prevalent among heart failure patients and strongly associated with increased mortality and poor outcomes. Reduced ejection fraction, elevated NT-proBNP, and renal dysfunction were key predictors of death. Early detection, vigilant monitoring of renal and cardiac function, and timely interventions are vital to improving prognosis in this high-risk group.