Anaemia in elderly patients represents a significant health concern worldwide, contributing to increased morbidity, hospitalisation, and mortality. The condition’s complex aetiology in this population makes early detection challenging, highlighting the need for effective predictive models. To address this, a recent retrospective cohort study analysed demographic, clinical, and laboratory data from 864 elderly inpatients. The study aimed to identify the key factors contributing to anaemia and develop an accurate predictive model to facilitate early intervention and improve patient outcomes.
Key Predictors of Anaemia
The study identified several significant predictors associated with anaemia in elderly patients. Advanced age was strongly correlated with increased risk, reflecting the progressive physiological changes in blood production and iron metabolism. Elevated levels of inflammatory markers, particularly C-reactive protein (CRP) and activated partial thromboplastin time (APTT), indicated the role of chronic inflammation and coagulation disturbances in anaemia development. Lower concentrations of albumin, calcium, and 25-Hydroxyvitamin D [25(OH)D] suggested nutritional deficiencies and impaired metabolic processes as contributing factors. Furthermore, the presence of multiple drug resistance (MDR) emerged as a notable risk factor, likely due to its impact on treatment complexity and patient resilience.
Model Performance and Accuracy
Using multivariate logistic regression, the researchers developed a predictive model integrating these demographic and laboratory parameters. The model demonstrated exceptional performance with an area under the receiver operating characteristic curve (AUC) of 0.955, indicating a very high level of accuracy in predicting anaemia risk among elderly inpatients. Calibration analysis further confirmed the model’s reliability across different patient subgroups, making it a promising clinical tool for real-world application.
Clinical Implications
The findings highlight the multifactorial nature of anaemia in elderly patients and underscore the importance of comprehensive evaluation beyond routine blood counts. Early detection of at-risk individuals allows clinicians to implement timely nutritional, pharmacological, and supportive interventions to mitigate complications.
Reference
Bi S et al. Influential factors and predictive model of anemia in hospitalized elderly patients. Sci Rep. 2025;15:35324.
