TY - JOUR
T1 - Validation and Recalibration of Modified Mayo Delirium Prediction Tool in a Hospitalized Cohort
AU - Pagali, Sandeep R.
AU - Fischer, Karen M.
AU - Kashiwagi, Deanne T.
AU - Schroeder, Darrell R.
AU - Philbrick, Kemuel L.
AU - Lapid, Maria I.
AU - Pignolo, Robert J.
AU - Burton, M. Caroline
N1 - Funding Information:
Funding: Dr. Sandeep Pagali received funding to support this work by the small grants program of the Mayo Clinic Center for Clinical and Translational Science , made possible by Clinical and Translation Science Awards Grant Number UL1 TR000135 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH). Dr. Robert Pignolo is supported by the Robert and Arlene Kogod Professorship in Geriatric Medicine . The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official view of NIH or any other entity.
Publisher Copyright:
© 2022 Academy of Consultation-Liaison Psychiatry
PY - 2022/11/1
Y1 - 2022/11/1
N2 - Background: Delirium prediction can augment and optimize care of older adults. Mayo Delirium Prediction (MDP) tool is a robust tool, developed from a large retrospective data set. The MDP tool predicts delirium risk for hospitalized older adults, within 24 hours of hospital admission, based on risk factor information available from electronic health record. Objective: We intend to validate the prediction performance of this tool and optimize the tool for clinical use. Methods: This is an observational cohort study conducted at Mayo Clinic Hospitals, Rochester, MN. All hospitalized older adults (age >50 years) from December 2019 to June 2020 were included. Patients with an admitting diagnosis of substance use disorder were excluded. The original MDP tool was modified to adjust for the fall risk variable as a binary variable that will facilitate broader applicability across different fall risk tools. The modified MDP tool was validated in the retrospective derivation and validation data set which yielded similar prediction capability (area under the receiver operating curve = 0.85 and 0.83, respectively). Diagnosis of delirium was captured by flowsheet diagnosis of delirium documented by nursing staff in the medical record. Predictive variable data were collected daily. Results: A total of 8055 patients were included in the study (median age 71 y). Delirium prediction of the modified MDP tool compared to delirium occurrence was 4% in the low-risk group, 17.8% in the medium-risk group, and 45.3% in the high-risk group (area under receiver operating curve of 0.80). Recalibration of the tool was attempted to further optimize the tool which resulted in both simplification and increased performance (area under receiver operating curve 0.82). The simplified tool was able to predict delirium in hospitalized patients admitted to both medical and surgical services. Conclusions: Validation of the modified MDP tool revealed good prediction capabilities. Recalibration resulted in simplification with increased performance of the tool in both medical and surgical hospitalized patients.
AB - Background: Delirium prediction can augment and optimize care of older adults. Mayo Delirium Prediction (MDP) tool is a robust tool, developed from a large retrospective data set. The MDP tool predicts delirium risk for hospitalized older adults, within 24 hours of hospital admission, based on risk factor information available from electronic health record. Objective: We intend to validate the prediction performance of this tool and optimize the tool for clinical use. Methods: This is an observational cohort study conducted at Mayo Clinic Hospitals, Rochester, MN. All hospitalized older adults (age >50 years) from December 2019 to June 2020 were included. Patients with an admitting diagnosis of substance use disorder were excluded. The original MDP tool was modified to adjust for the fall risk variable as a binary variable that will facilitate broader applicability across different fall risk tools. The modified MDP tool was validated in the retrospective derivation and validation data set which yielded similar prediction capability (area under the receiver operating curve = 0.85 and 0.83, respectively). Diagnosis of delirium was captured by flowsheet diagnosis of delirium documented by nursing staff in the medical record. Predictive variable data were collected daily. Results: A total of 8055 patients were included in the study (median age 71 y). Delirium prediction of the modified MDP tool compared to delirium occurrence was 4% in the low-risk group, 17.8% in the medium-risk group, and 45.3% in the high-risk group (area under receiver operating curve of 0.80). Recalibration of the tool was attempted to further optimize the tool which resulted in both simplification and increased performance (area under receiver operating curve 0.82). The simplified tool was able to predict delirium in hospitalized patients admitted to both medical and surgical services. Conclusions: Validation of the modified MDP tool revealed good prediction capabilities. Recalibration resulted in simplification with increased performance of the tool in both medical and surgical hospitalized patients.
KW - Mayo delirium prediction
KW - delirium
KW - prediction tool
KW - validation
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U2 - 10.1016/j.jaclp.2022.05.006
DO - 10.1016/j.jaclp.2022.05.006
M3 - Article
C2 - 35660677
AN - SCOPUS:85133248122
SN - 2667-2979
VL - 63
SP - 521
EP - 528
JO - Journal of the Academy of Consultation-Liaison Psychiatry
JF - Journal of the Academy of Consultation-Liaison Psychiatry
IS - 6
ER -