Development and validation of a prediction model for functional decline in older medical inpatients. (July 2018)
- Record Type:
- Journal Article
- Title:
- Development and validation of a prediction model for functional decline in older medical inpatients. (July 2018)
- Main Title:
- Development and validation of a prediction model for functional decline in older medical inpatients
- Authors:
- Takada, Toshihiko
Fukuma, Shingo
Yamamoto, Yosuke
Tsugihashi, Yukio
Nagano, Hiroyuki
Hayashi, Michio
Miyashita, Jun
Azuma, Teruhisa
Fukuhara, Shunichi - Abstract:
- Highlights: A model to assess the risk of functional decline in older medical inpatients. The model demonstrated better diagnostic performance than existing models. Further clinical impact studies would be expected to quantify the model. Abstract: Objective: To prevent functional decline in older inpatients, identification of high-risk patients is crucial. The aim of this study was to develop and validate a prediction model to assess the risk of functional decline in older medical inpatients. Methods: In this retrospective cohort study, patients ≥65 years admitted acutely to medical wards were included. The healthcare database of 246 acute care hospitals (n = 229, 913) was used for derivation, and two acute care hospitals (n = 1767 and 5443, respectively) were used for validation. Data were collected using a national administrative claims and discharge database. Functional decline was defined as a decline of the Katz score at discharge compared with on admission. Results: About 6% of patients in the derivation cohort and 9% and 2% in each validation cohort developed functional decline. A model with 7 items, age, body mass index, living in a nursing home, ambulance use, need for assistance in walking, dementia, and bedsore, was developed. On internal validation, it demonstrated a c-statistic of 0.77 (95% confidence interval (CI) = 0.767–0.771) and good fit on the calibration plot. On external validation, the c-statistics were 0.79 (95% CI = 0.77–0.81) and 0.75 (95%Highlights: A model to assess the risk of functional decline in older medical inpatients. The model demonstrated better diagnostic performance than existing models. Further clinical impact studies would be expected to quantify the model. Abstract: Objective: To prevent functional decline in older inpatients, identification of high-risk patients is crucial. The aim of this study was to develop and validate a prediction model to assess the risk of functional decline in older medical inpatients. Methods: In this retrospective cohort study, patients ≥65 years admitted acutely to medical wards were included. The healthcare database of 246 acute care hospitals (n = 229, 913) was used for derivation, and two acute care hospitals (n = 1767 and 5443, respectively) were used for validation. Data were collected using a national administrative claims and discharge database. Functional decline was defined as a decline of the Katz score at discharge compared with on admission. Results: About 6% of patients in the derivation cohort and 9% and 2% in each validation cohort developed functional decline. A model with 7 items, age, body mass index, living in a nursing home, ambulance use, need for assistance in walking, dementia, and bedsore, was developed. On internal validation, it demonstrated a c-statistic of 0.77 (95% confidence interval (CI) = 0.767–0.771) and good fit on the calibration plot. On external validation, the c-statistics were 0.79 (95% CI = 0.77–0.81) and 0.75 (95% CI = 0.73–0.77) for each cohort, respectively. Calibration plots showed good fit in one cohort and overestimation in the other one. Conclusions: A prediction model for functional decline in older medical inpatients was derived and validated. It is expected that use of the model would lead to early identification of high-risk patients and introducing early intervention. … (more)
- Is Part Of:
- Archives of gerontology and geriatrics. Volume 77(2018)
- Journal:
- Archives of gerontology and geriatrics
- Issue:
- Volume 77(2018)
- Issue Display:
- Volume 77, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 77
- Issue:
- 2018
- Issue Sort Value:
- 2018-0077-2018-0000
- Page Start:
- 184
- Page End:
- 188
- Publication Date:
- 2018-07
- Subjects:
- TRIPOD transparent reporting of a multivariable prediction model for individual prognosis or diagnosis -- MDV medical data vision -- DPC diagnosis-procedure combination -- ADL activities of daily living -- BMI body mass index -- AIC akaike information criterion -- ISAR-HP identification of seniors at risk – hospitalized patients
Decision support techniques -- Frail elderly -- Inpatients -- Prognosis -- Rehabilitation
Aging -- Periodicals
Geriatrics -- Periodicals
Gerontology -- Periodicals
Electronic journals
305.26 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01674943 ↗
http://www.elsevier.com/wps/find/journaldescription.cws%5Fhome/506044/description#description ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01674943 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01674943 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.archger.2018.05.011 ↗
- Languages:
- English
- ISSNs:
- 0167-4943
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1634.401000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6739.xml