Age effect on the prediction of risk of prolonged length hospital stay in older patients visiting the emergency department: results from a large prospective geriatric cohort study.

BACKGROUND: With the rapid growth of elderly patients visiting the Emergency Department (ED), it is expected that there will be even more hospitalisations following ED visits in the future. The aim of this study was to examine the age effect on the performance criteria of the 10-item brief geriatric assessment (BGA) for the prolonged length of hospital stay (LHS) using artificial neural networks (ANNs) analysis. METHODS: Based on an observational prospective cohort study, 1117 older patients (i.e., aged ≥ 65 years) ED users were admitted to acute care wards in a University Hospital (France) were recruited. The 10-items of BGA were recorded during the ED visit and prior to discharge to acute care wards. The top third of LHS (i.e., ≥ 13 days) defined the prolonged LHS. Analysis was successively performed on participants categorized in 4 age groups: aged ≥ 70, ≥ 75, ≥ 80 and ≥ 85 years. Performance criteria of 10-item BGA for the prolonged LHS were sensitivity, specificity, positive predictive value [PPV], negative predictive value [NPV], likelihood ratios [LR], area under receiver operating characteristic curve [AUROC]). The ANNs analysis method was conducted using the modified multilayer perceptron (MLP). RESULTS: Values of criteria performance were high (sensitivity> 89%, specificity≥ 96%, PPV > 87%, NPV > 96%, LR+ > 22; LR- ≤ 0.1 and AUROC> 93), regardless of the age group. CONCLUSIONS: Age effect on the performance criteria of the 10-item BGA for the prediction of prolonged LHS using MLP was minimal with a good balance between criteria, suggesting that this tool may be used as a screening as well as a predictive tool for prolonged LHS.

Precipitants of Delirium in Older Inpatients Admitted in Surgery for Post-Fall Hip Fracture: An Observational Study.

BACKGROUND: Hip fractures precipitate several acute adverse outcomes in elderly people, thus leading to chronic adverse outcomes. OBJECTIVES: The objective of our study was to examine the clinical characteristics associated with incident delirium in community dwelling elderly individuals who have a hip fracture. DESIGN: Retrospective observational cohort study. SETTING: Data was collected from an academic tertiary hospital affiliated with McGill University. PARTICIPANTS: 114 elderly individuals who were above 65 years of age, who underwent surgery for a fractured hip. MEASUREMENTS: The main outcome variable was incident delirium, which was assessed by chart reviews of notes and observations recorded by nurses and physicians when patients were admitted post operatively to the surgical unit. Covariates included age, sex, length of stay, delay to surgery, number of medical comorbidities, number of medications and hip fracture location, and were extracted from medical records. Baseline mobility and functional status, preoperative cognitive impairment, postoperative complications, regular psychotropic medications, psychotropic medications in hospital, and location of discharge were also assessed through chart review. RESULTS: The results demonstrated that 17.5% of participants with a diagnosis of delirium had a longer length of hospitalization (p = 0.01), a lower baseline functional status (p = 0.03) and pre-operative cognitive impairment (p = 0.01). Patients receiving new psychotropic medications in hospital were more likely to have delirium (OR = 4.6, p = 0.01) which was independent of pre-operative cognitive impairment. CONCLUSION: We have shown that an association exists between psychotropic medication prescription and incident delirium in patients with hip fractures, even when adjusting for cognitive impairment. Hence, the prescription of psychotropic drugs should be judicious in these patients so as minimize the risk of adverse outcomes.

Falls Risk Prediction for Older Inpatients in Acute Care Medical Wards: Is There an Interest to Combine an Early Nurse Assessment and the Artificial Neural Network Analysis?

BACKGROUND: Identification of the risk of falls is important among older inpatients. This study aims to examine performance criteria (i.e.; sensitivity, specificity, positive predictive value, negative predictive value and accuracy) for fall prediction resulting from a nurse assessment and an artificial neural networks (ANNs) analysis in older inpatients hospitalized in acute care medical wards. METHODS: A total of 848 older inpatients (mean age, 83.0±7.2 years; 41.8% female) admitted to acute care medical wards in Angers University hospital (France) were included in this study using an observational prospective cohort design. Within 24 hours after admission of older inpatients, nurses performed a bedside clinical assessment. Participants were separated into non-fallers and fallers (i.e.; ≥1 fall during hospitalization stay). The analysis was conducted using three feed forward ANNs (multilayer perceptron [MLP], averaged neural network, and neuroevolution of augmenting topologies [NEAT]). RESULTS: Seventy-three (8.6%) participants fell at least once during their hospital stay. ANNs showed a high specificity, regardless of which ANN was used, and the highest value reported was with MLP (99.8%). In contrast, sensitivity was lower, with values ranging between 98.4 to 14.8%. MLP had the highest accuracy (99.7). CONCLUSIONS: Performance criteria for fall prediction resulting from a bedside nursing assessment and an ANNs analysis was associated with a high specificity but a low sensitivity, suggesting that this combined approach should be used more as a diagnostic test than a screening test when considering older inpatients in acute care medical ward.