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Larson, N.B., McDonnell, S., Albright, L.C., Teerlink, C., Stanford, J., Ostrander, E.A., et al. (2016) Post Hoc Analysis for Detecting Individual Rare Variant Risk Associations Using Probit Regression Bayesian Variable Selection Methods in Case-Control Sequencing Studies. Genetic Epidemiology, 40, 461-469.
https://doi.org/10.1002/gepi.21983

has been cited by the following article:

• TITLE: Validating a Prognostic Model for Mortality of Psychogeriatric Inpatients

  AUTHORS: Isabelle Moebs, Chris Gale, Esther Abeln, Annalise Seifert, Yoram Barak

  KEYWORDS: Psychogeriatric, Mortality, Prediction

  JOURNAL NAME: Open Journal of Psychiatry, Vol.13 No.1, January 10, 2023

  ABSTRACT: Background: To validate a predictive scoring system for 1-year mortality among psychogeriatric inpatients admitted for acute psychiatric care. Methods: Computerized data were extracted from the District Health Board Database for a university affiliated general hospital. A geriatric risk scoring system developed in the USA was employed to validate mortality within 1-year of hospital discharge. Results: Among 125 psychogeriatric inpatients who were discharged in 2017, [mean age 82.8 (±8.9) years, 82 (65.6%) women] 33 died within 1-year [26.4% of the sample, mean age, 87.7 (±11.1) years, 25 (75.7%) women]. Levine’s mortality index predicted death. A post hoc probit analysis found two factors significantly associated with predicted mortality: metastatic cancer (Chi-square = 5.6; p Conclusions: A geriatric 1-year mortality scoring system accurately predicted mortality among psychogeriatric inpatients. Predicting psychogeriatric mortality should be considered a guideline for ensuring quality of care and appropriate discharge and advanced care planning.