Predicting mortality in patients diagnosed with advanced dementia presenting at an acute care hospital: the PROgnostic Model for Advanced DEmentia (PRO-MADE)

• Published in: BMC geriatrics Vol. 23; no. 1; p. 255
• Main Authors: Kaur, Palvinder, Kannapiran, Palvannan, Ng, Sheryl Hui Xian, Chu, Jermain, Low, Zhi Jun, Ding, Yew Yoong, Tan, Woan Shin, Hum, Allyn
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 28.04.2023; BioMed Central; BMC
• Subjects: Accuracy and precision; Activities of Daily Living; Acute care setting; Advanced dementia; Aged, 80 and over; Care and treatment; Comorbidity; Death & dying; Dementia; Dementia - diagnosis; Dementia - epidemiology; Dementia - therapy; Dementia disorders; Diagnosis; Disease; Dysphagia; Forecasts and trends; Geriatrics; Hospitals; Humans; Male; Management; Medical prognosis; Mortality; Older people; One-year mortality; Palliation; Palliative care; Palliative treatment; Patients; Primary care; Prognosis; Prognostication; Retrospective Studies; Services; Singapore; Ulcers; Variables; Singapore; One-year mortality; Palliative care; Prognostication; Acute care setting; Advanced dementia
• DOI: 10.1186/s12877-023-03945-8
• ISSN: 1471-2318

Challenges in prognosticating patients diagnosed with advanced dementia (AD) hinders timely referrals to palliative care. We aim to develop and validate a prognostic model to predict one-year all-cause mortality (ACM) in patients with AD presenting at an acute care hospital. This retrospective cohort study utilised administrative and clinical data from Tan Tock Seng Hospital (TTSH). Patients admitted to TTSH between 1st July 2016 and 31st October 2017 and identified to have AD were included. The primary outcome was ACM within one-year of AD diagnosis. Multivariable logistic regression was used. The PROgnostic Model for Advanced Dementia (PRO-MADE) was internally validated using a bootstrap resampling of 1000 replications and externally validated on a more recent cohort of AD patients. The model was evaluated for overall predictive accuracy (Nagelkerke's R and Brier score), discriminative [area-under-the-curve (AUC)], and calibration [calibration slope and calibration-in-the-large (CITL)] properties. A total of 1,077 patients with a mean age of 85 (SD: 7.7) years old were included, and 318 (29.5%) patients died within one-year of AD diagnosis. Predictors of one-year ACM were age > 85 years (OR:1.87; 95%CI:1.36 to 2.56), male gender (OR:1.62; 95%CI:1.18 to 2.22), presence of pneumonia (OR:1.75; 95%CI:1.25 to 2.45), pressure ulcers (OR:2.60; 95%CI:1.57 to 4.31), dysphagia (OR:1.53; 95%CI:1.11 to 2.11), Charlson Comorbidity Index ≥ 8 (OR:1.39; 95%CI:1.01 to 1.90), functional dependency in ≥ 4 activities of daily living (OR: 1.82; 95%CI:1.32 to 2.53), abnormal urea (OR:2.16; 95%CI:1.58 to 2.95) and abnormal albumin (OR:3.68; 95%CI:2.07 to 6.54) values. Internal validation results for optimism-adjusted Nagelkerke's R , Brier score, AUC, calibration slope and CITL were 0.25 (95%CI:0.25 to 0.26), 0.17 (95%CI:0.17 to 0.17), 0.76 (95%CI:0.76 to 0.76), 0.95 (95% CI:0.95 to 0.96) and 0 (95%CI:-0.0001 to 0.001) respectively. When externally validated, the model demonstrated an AUC of 0.70 (95%CI:0.69 to 0.71), calibration slope of 0.64 (95%CI:0.63 to 0.66) and CITL of -0.27 (95%CI:-0.28 to -0.26). The PRO-MADE attained good discrimination and calibration properties. Used synergistically with a clinician's judgement, this model can identify AD patients who are at high-risk of one-year ACM to facilitate timely referrals to palliative care.