Model Prediksi Mortalitas 30 Hari Pasien Usia Lanjut di Ruang Rawat Akut Geriatri Menggunakan Domain Pendekatan Paripurna Pasien Geriatri

Noto Dwimartutie, Siti Setiati, Edy Rizal Wahyudi, Kuntjoro Harimurti

Abstract

Pendahuluan. Mortalitas pasien usia lanjut yang dirawat cukup tinggi. Penelitian ini bertujuan untuk mendapatkan dan menentukan performa model prediksi mortalitas 30 hari pasien usia lanjut yang dirawat di ruang rawat akut (RRA) geriatri menggunakan domain pendekatan paripurna pasien geriatri (P3G).

Metode. Penelitian kohort retrospektif ini menggunakan status rekam medis pasien usia lanjut (> 60 tahun) yang dirawat di RRA geriatri. Prediktor yang dianalisis meliputi usia, jenis kelamin, delirium, komorbiditas (CIRS-G), kadar albumin, status fungsional (ADL Barthel), status kognitif, status psikoafektif, dan status nutrisi (MNA). Analisis multivariat dengan cox regression dilakukan untuk mendapatkan hazard ratio (HR) dan untuk mengembangkan model prediksi. Kemampuan kalibrasi model prediksi ditentukan dengan uji Hosmer-Lemeshow dan kemampuan diskriminasinya ditentukan dengan menghitung area under the receiver-operating-characteristic curve (AUC).

Hasil. Terdapat 530 subjek dengan median usia 69 tahun (rentang 60-96 tahun). Mortalitas 30 hari didapatkan sebesar 28,1%. Delirium (HR 4,11 [(IK 95% 1,83-9,11]), kadar albumin < 3 mg/dl (HR 2,18 [IK 95% 1,23-3,85]), ADL Barthel < 9 (HR 2,21 [IK 95% 1,23-3,85]), dan malnutrisi (MNA < 17) (HR 1,77 [IK 95% 1,19-2,63]) merupakan prediktor bermakna mortalitas 30 hari. Model prediksi mortalitas dikelompokkan menjadi risiko rendah (4,4%), risiko sedang (24,8%), dan risiko tinggi (64,3%). Uji Hosmer-Lemeshow menunjukkan presisi yang baik (p = 0,409) dan AUC menunjukkan kemampuan diskriminasi yang baik (84,3% [IK 95% 80,7-87,9]).

Simpulan. Model prediksi mortalitas 30 hari berdasarkan domain P3G memiliki presisi dan kemampuan diskriminasi yang baik.                           

Kata Kunci: Domain P3G, model prediksi, mortalitas, usia lanjut

 

Prediction Model of 30-Day Mortality in Elderly Patients Admitted to Geriatric Acute Ward Using Comprehensive Geriatric Assessment Domain

Introduction. Mortality of hospitalized elderly patients remains high. This study aimed to develop and to determine the performance of a prediction model for 30-day mortality in elderly patients hospitalized in geriatric acute ward using comprehensive geriatric assessment (CGA) domain.

Methods. A retrospective cohort study was conducted using medical records of elderly patients (> 60 years) hospitalized in acute geriatric ward. Nine predictors (age, sex, delirium, comorbidity, albumin level, comorbidity [CIRS-G], psycho-affective status, cognitive status, and nutrition status [MNA]) were analyzed. Multivariate analysis using cog regression of significant predictors was done to determine hazard ratio (HR) for each predictor and to develop prediction model. The model’s calibration performance and its discrimination ability were respectively determined by Hosmer-Lemeshow test and area under the receiver-operating-characteristic curve (AUC).

Results. There were 530 subjects with the median age was 69 (range 60-96)) years old. The 30-day mortality was 28.1%. Delirium (HR 4.11 [95% CI 1.83-9.11]), albumin < 3 mg/dl (HR 2,18 [95% CI 1.23-3.85]), Barthel index < 9 (HR 2.21 [95%CI 1.23-3.85]), and malnutrition (MNA < 17) (HR 1,77 (95% CI 1.19-2.63)] were significant predictors of 30-day mortality. Prediction model of mortality was stratified into 3 groups: lower risk (4.4%), medium risk (24.8%), and high risk (64.3%). The Hosmer-Lemeshow showed good precision (p = 0.409) and the AUC revealed good discrimination ability (84.3% [95% CI 80.7-87.9]).

Conclusion.  Prediction model of 30-day mortality based on CGA domain has good precision and discrimination ability.


 

Keywords

CGA domain, elderly, mortality, prediction model

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