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Lee SW, Lee EH, Choi IC. An ensemble machine learning approach to predict postoperative mortality in older patients undergoing emergency surgery. BMC Geriatr 2023; 23:262. [PMID: 37131138 PMCID: PMC10155414 DOI: 10.1186/s12877-023-03969-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 04/13/2023] [Indexed: 05/04/2023] Open
Abstract
BACKGROUND Prediction of preoperative frailty risk in the emergency setting is a challenging issue because preoperative evaluation cannot be done sufficiently. In a previous study, the preoperative frailty risk prediction model used only diagnostic and operation codes for emergency surgery and found poor predictive performance. This study developed a preoperative frailty prediction model using machine learning techniques that can be used in various clinical settings with improved predictive performance. METHODS This is a national cohort study including 22,448 patients who were older than 75 years and visited the hospital for emergency surgery from the cohort of older patients among the retrieved sample from the Korean National Health Insurance Service. The diagnostic and operation codes were one-hot encoded and entered into the predictive model using the extreme gradient boosting (XGBoost) as a machine learning technique. The predictive performance of the model for postoperative 90-day mortality was compared with those of previous frailty evaluation tools such as Operation Frailty Risk Score (OFRS) and Hospital Frailty Risk Score (HFRS) using the receiver operating characteristic curve analysis. RESULTS The predictive performance of the XGBoost, OFRS, and HFRS for postoperative 90-day mortality was 0.840, 0.607, and 0.588 on a c-statistics basis, respectively. CONCLUSIONS Using machine learning techniques, XGBoost to predict postoperative 90-day mortality, using diagnostic and operation codes, the prediction performance was improved significantly over the previous risk assessment models such as OFRS and HFRS.
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Affiliation(s)
- Sang-Wook Lee
- Department of Anesthesiology and Pain Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Seoul, 05505, Songpa-gu, Republic of Korea
| | - Eun-Ho Lee
- University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Seoul, 05505, Songpa-gu, Republic of Korea
| | - In-Cheol Choi
- Department of Anesthesiology and Pain Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88 Olympic-ro 43-gil, Seoul, 05505, Songpa-gu, Republic of Korea.
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Elsamadicy AA, Koo AB, Sherman JJZ, Sarkozy M, Reeves BC, Craft S, Sayeed S, Sandhu MRS, Hersh AM, Lo SFL, Shin JH, Mendel E, Sciubba DM. Association of frailty with healthcare resource utilization after open thoracic/thoracolumbar posterior spinal fusion for adult spinal deformity. Eur Spine J 2023:10.1007/s00586-023-07635-2. [PMID: 36949143 DOI: 10.1007/s00586-023-07635-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 02/24/2023] [Accepted: 03/04/2023] [Indexed: 03/24/2023]
Abstract
PURPOSE The Hospital Frailty Risk Score (HFRS) is a frailty-identifying metric developed using ICD-10-CM codes. While other studies have examined frailty in adult spinal deformity (ASD), the HFRS has not been assessed in this population. The aim of this study was to utilize the HFRS to investigate the impact of frailty on outcomes in ASD patients undergoing posterior spinal fusion (PSF). METHODS A retrospective study was performed using the 2016-2019 National Inpatient Sample database. Adults with ASD undergoing elective PSF were identified using ICD-10-CM codes. Patients were categorized into HFRS-based frailty cohorts: Low (HFRS < 5) and Intermediate-High (HFRS ≥ 5). Patient demographics, comorbidities, intraoperative variables, and outcomes were assessed. Multivariate regression analyses were used to determine whether HFRS independently predicted extended length of stay (LOS), non-routine discharge, and increased cost. RESULTS Of the 7500 patients identified, 4000 (53.3%) were in the Low HFRS cohort and 3500 (46.7%) were in the Intermediate-High HFRS cohort. On average, age increased progressively with increasing HFRS scores (p < 0.001). The frail cohort experienced more postoperative adverse events (p < 0.001), greater LOS (p < 0.001), accrued greater admission costs (p < 0.001), and had a higher rate of non-routine discharge (p < 0.001). On multivariate analysis, Intermediate-High HFRS was independently associated with extended LOS (OR: 2.58, p < 0.001) and non-routine discharge (OR: 1.63, p < 0.001), though not increased admission cost (OR: 1.01, p = 0.929). CONCLUSION Our study identified HFRS to be significantly associated with prolonged hospitalizations and non-routine discharge. Other factors that were found to be associated with increased healthcare resource utilization include age, Hispanic race, West hospital region, large hospital size, and increasing number of AEs.
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Affiliation(s)
- Aladine A Elsamadicy
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.
| | - Andrew B Koo
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Josiah J Z Sherman
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Margot Sarkozy
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Benjamin C Reeves
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Samuel Craft
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Sumaiya Sayeed
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Mani Ratnesh S Sandhu
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Andrew M Hersh
- Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Sheng-Fu Larry Lo
- Department of Neurosurgery, Zucker School of Medicine at Hofstra, Long Island Jewish Medical Center and North Shore University Hospital, Northwell Health, Manhasset, NY, USA
| | - John H Shin
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ehud Mendel
- Department of Neurosurgery, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Daniel M Sciubba
- Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of Neurosurgery, Zucker School of Medicine at Hofstra, Long Island Jewish Medical Center and North Shore University Hospital, Northwell Health, Manhasset, NY, USA
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Subramaniam A, Ueno R, Tiruvoipati R, Srikanth V, Bailey M, Pilcher D. Comparison of the predictive ability of clinical frailty scale and hospital frailty risk score to determine long-term survival in critically ill patients: a multicentre retrospective cohort study. Crit Care 2022; 26:121. [PMID: 35505435 PMCID: PMC9063154 DOI: 10.1186/s13054-022-03987-1] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 04/09/2022] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The Clinical Frailty Scale (CFS) is the most commonly used frailty measure in intensive care unit (ICU) patients. The hospital frailty risk score (HFRS) was recently proposed for the quantification of frailty. We aimed to compare the HFRS with the CFS in critically ill patients in predicting long-term survival up to one year following ICU admission. METHODS In this retrospective multicentre cohort study from 16 public ICUs in the state of Victoria, Australia between 1st January 2017 and 30th June 2018, ICU admission episodes listed in the Australian and New Zealand Intensive Care Society Adult Patient Database registry with a documented CFS, which had been linked with the Victorian Admitted Episode Dataset and the Victorian Death Index were examined. The HFRS was calculated for each patient using the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes that represented pre-existing conditions at the time of index hospital admission. Descriptive methods, Cox proportional hazards and area under the receiver operating characteristic (AUROC) were used to investigate the association between each frailty score and long-term survival up to 1 year, after adjusting for confounders including sex and baseline severity of illness on admission to ICU (Australia New Zealand risk-of-death, ANZROD). RESULTS 7001 ICU patients with both frailty measures were analysed. The overall median (IQR) age was 63.7 (49.1-74.0) years; 59.5% (n = 4166) were male; the median (IQR) APACHE II score 14 (10-20). Almost half (46.7%, n = 3266) were mechanically ventilated. The hospital mortality was 9.5% (n = 642) and 1-year mortality was 14.4% (n = 1005). HFRS correlated weakly with CFS (Spearman's rho 0.13 (95% CI 0.10-0.15) and had a poor agreement (kappa = 0.12, 95% CI 0.10-0.15). Both frailty measures predicted 1-year survival after adjusting for confounders, CFS (HR 1.26, 95% CI 1.21-1.31) and HFRS (HR 1.08, 95% CI 1.02-1.15). The CFS had better discrimination of 1-year mortality than HFRS (AUROC 0.66 vs 0.63 p < 0.0001). CONCLUSION Both HFRS and CFS independently predicted up to 1-year survival following an ICU admission with moderate discrimination. The CFS was a better predictor of 1-year survival than the HFRS.
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Affiliation(s)
- Ashwin Subramaniam
- Department of Intensive Care, Frankston Hospital, Peninsula Health, 2 Hastings Road, VIC, 3199, Frankston, Australia.
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia.
- Peninsula Clinical School, Monash University, Frankston, VIC, Australia.
| | - Ryo Ueno
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Department of Intensive Care, Eastern Health, Box Hill, VIC, Australia
| | - Ravindranath Tiruvoipati
- Department of Intensive Care, Frankston Hospital, Peninsula Health, 2 Hastings Road, VIC, 3199, Frankston, Australia
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Peninsula Clinical School, Monash University, Frankston, VIC, Australia
| | - Velandai Srikanth
- Peninsula Clinical School, Monash University, Frankston, VIC, Australia
- Department of Geriatric Medicine, Peninsula Health, Frankston, VIC, Australia
- National Centre for Healthy Ageing, Melbourne, Australia
| | - Michael Bailey
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
| | - David Pilcher
- Australian and New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, VIC, Australia
- Centre for Outcome and Resource Evaluation, Australian and New Zealand Intensive Care Society, Melbourne, VIC, Australia
- Department of Intensive Care, Alfred Hospital, Melbourne, VIC, Australia
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Ushida K, Shimizu A, Hori S, Yamamoto Y, Momosaki R. Hospital Frailty Risk Score Predicts Outcomes in Chronic Obstructive Pulmonary Disease Exacerbations. Arch Gerontol Geriatr 2022; 100:104658. [PMID: 35190332 DOI: 10.1016/j.archger.2022.104658] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/09/2022] [Accepted: 02/10/2022] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Patients with chronic obstructive pulmonary disease (COPD) are at high risk for frailty and prone to complications after admission for an acute exacerbation. We aim to investigate the association between frailty risk and functional outcomes in patients with acute exacerbations of COPD, using a nationwide database. METHODS This retrospective cohort study included patients with acute exacerbations of COPD who were admitted by ambulance. We assessed frailty using the Hospital Frailty Risk Score (HFRS) and compared the outcomes between low frailty risk (HFRS < 5) and frailty at risk (HFRS ≥ 5) groups. The primary outcome was prolonged hospitalization (≥30 days). The secondary outcomes were in-hospital mortality, readmission (≤90 days), poor activities of daily living (ADL) at discharge, and difficulty in returning home. RESULTS There were 3,396 eligible patients (mean age, 75.9 ± 11.2 years; 20.4% female). The rate of frailty at risk patients was 14.0%. Frailty at risk patients were significantly higher rates of prolonged hospitalization (32.9% vs. 17.5%), more in-hospital mortality (16.4% vs. 12.5%), more difficulty in returning home (34.6% vs. 22.9%), and poorer ADL at discharge (8.7% vs. 12.4%) than those of low frailty risk. Multivariate analysis with adjusted covariates showed that HFRS was independently associated with prolonged hospitalization (odds ratio, 2.0; 95% confidence interval, 1.4-2.9). CONCLUSIONS HFRS can be used to predict the outcome of patients with acute exacerbations of COPD. This finding supports the validity of using the HFRS in clinical practice with patients with acute exacerbations of COPD.
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Affiliation(s)
- Kenta Ushida
- Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, 514-8507, Japan.
| | - Akio Shimizu
- Department of Nutrition, Hamamatsu City Rehabilitation Hospital, Hamamatsu, 443-8127, Japan
| | - Shinsuke Hori
- Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, 514-8507, Japan
| | - Yoshinori Yamamoto
- Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, 514-8507, Japan
| | - Ryo Momosaki
- Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, 514-8507, Japan
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Shimizu A, Maeda K, Fujishima I, Kayashita J, Mori N, Okada K, Uno C, Shimizu M, Momosaki R. Hospital Frailty Risk Score predicts adverse events in older patients with hip fractures after surgery: Analysis of a nationwide inpatient database in Japan. Arch Gerontol Geriatr 2021; 98:104552. [PMID: 34653923 DOI: 10.1016/j.archger.2021.104552] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/17/2021] [Accepted: 10/05/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Frailty may predict adverse events in patients with hip fractures. This study aimed to investigate the association between frailty and adverse events in patients with hip fractures after surgery using information from Japanese health insurance. METHODS This retrospective cohort study included patients with hip fractures aged ≥ 65 years using a nationwide database in Japan. We examined the relationship of the frailty risk, which was defined using the Hospital Frailty Risk Score (HFRS), with in-hospital mortality, complications such as delirium and pneumonia, and functional outcomes. We used descriptive analysis, logistic regression, and linear regression analysis to estimate the association between the HFRS and outcomes in patients with hip fracture. RESULTS We analysed data from 36,192 patients with hip fractures after surgery (mean age: 83.6 ± 6.7 years, female: 79.5%). The proportions of low, intermediate, and high risk of frailty were 68.4%, 28.1%, and 3.5%, respectively. The frailty risk was independently associated with in-hospital mortality (intermediate risk: odds ratio [OR] 1.385, P < 0.001; high risk: OR 1.572; P < 0.001) and the occurrence of complications. Furthermore, each frailty risk was negatively associated with the Barthel Index score at discharge (intermediate risk: coefficient -11.919, P < 0.001; high risk: coefficient -18.044; P < 0.001). CONCLUSIONS The HFRS could predict adverse events, including in-hospital mortality, in Japanese older patients with hip fractures. This finding supports the validity of using the HFRS in clinical practice for patients with hip fractures.
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Affiliation(s)
- Akio Shimizu
- Department of Nutrition, Hamamatsu City Rehabilitation Hospital, Hamamatsu, 443-8127, Japan; Department of Palliative and Supportive Medicine, Graduate School of Medicine, Aichi Medical University, Nagakute, 480-1195, Japan; Department of Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan; Institute of Health and Nutrition Nagoya University of Arts and Sciences, Nisshin, 470-0196, Japan.
| | - Keisuke Maeda
- Department of Palliative and Supportive Medicine, Graduate School of Medicine, Aichi Medical University, Nagakute, 480-1195, Japan; Department of Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Ichiro Fujishima
- Department of Rehabilitation Medicine, Hamamatsu City Rehabilitation Hospital, Hamamatsu, 443-8127, Japan
| | - Jun Kayashita
- Department of Health Sciences, Faculty of Human Culture and Science, Prefectural University of Hiroshima, Hiroshima, 734-8558, Japan
| | - Naoharu Mori
- Department of Palliative and Supportive Medicine, Graduate School of Medicine, Aichi Medical University, Nagakute, 480-1195, Japan
| | - Kiwako Okada
- Institute of Health and Nutrition Nagoya University of Arts and Sciences, Nisshin, 470-0196, Japan
| | - Chiharu Uno
- Institute of Health and Nutrition Nagoya University of Arts and Sciences, Nisshin, 470-0196, Japan; Department of Community Health and Geriatrics, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan
| | - Miho Shimizu
- Department of Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, 466-8550, Japan
| | - Ryo Momosaki
- Department of Rehabilitation Medicine, Mie University Graduate School of Medicine, Tsu, 514-8507, Japan
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