Clinical Section: Research Article

Lee S.-W.a· Kim K.-S.b· Park S.-W.b· Kim J.b· Choi J.-H.b· Lee S.a· Joung K.-W.a· Choi I.-C.a

Author affiliations

aDepartment of Anesthesiology and Pain Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
bDepartment of Anesthesiology and Pain Medicine, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Republic of Korea

Log in to MyKarger to check if you already have access to this content.

Buy FullText & PDF Unlimited re-access via MyKarger Unrestricted printing, no saving restrictions for personal use read more

CHF 38.00 *
EUR 35.00 *
USD 39.00 *

Select

KAB

Buy a Karger Article Bundle (KAB) and profit from a discount!

If you would like to redeem your KAB credit, please log in.

Save over 20% compared to the individual article price.

Learn more

Rent/Cloud Rent for 48h to view Buy Cloud Access for unlimited viewing via different devices Synchronizing in the ReadCube Cloud Printing and saving restrictions apply Rental: USD 8.50
Cloud: USD 20.00

Select

Subscribe Access to all articles of the subscribed year(s) guaranteed for 5 years Unlimited re-access via Subscriber Login or MyKarger Unrestricted printing, no saving restrictions for personal use read more

Subcription rates

Select

* The final prices may differ from the prices shown due to specifics of VAT rules.

Article / Publication Details

First-Page Preview

Received: December 08, 2021
Accepted: April 23, 2022
Published online: May 16, 2022

Number of Print Pages: 9
Number of Figures: 4
Number of Tables: 2

ISSN: 0304-324X (Print)
eISSN: 1423-0003 (Online)

For additional information: https://www.karger.com/GER

Abstract

Background: Predicting preoperative frailty risk in emergency surgery is difficult with limited information because preoperative evaluation is not commonly performed properly. A recent study attempted to predict preoperative frailty risk using only diagnostic and surgical codes that can be extracted from the electronic medical records system. Objective: This study aimed to validate whether the prediction model of preoperative frailty risk presented in the previous study is well applied to other medical hospitals’ data. Methods: This is a retrospective cohort study including 1,557 patients (≥75 years old) who were admitted to a single institution for emergency operations between January 1, 2010, and December 31, 2019, for study analysis. The Charlson comorbidity index, Hospital Frailty Risk Score, and the recently developed Operation Frailty Risk Score (OFRS) were calculated using the patient’s diagnostic and operation codes. The predictive performances of these calculated risk scores and the American Society of Anesthesiologists-Physical Status classification for postoperative 90-day mortality were compared by using the receiver operating characteristic curve analysis. Findings: The predictive performance of the OFRS, Charlson comorbidity index, American Society of Anesthesiologists-Physical Status, and Hospital Frailty Risk Score for postoperative 90-day mortality was 0.81, 0.630, 0.699, and 0.549 on a c-statistics basis, respectively. Conclusions: The OFRS using diagnostic and operation codes may show the best predictive performance for 90-day mortality compared to other risk scores, and it can be the clinically applicable model to evaluate the preoperative frailty risk in elderly patients undergoing emergency surgery.

© 2022 S. Karger AG, Basel

References Black M, Bowman M. Nutrition and healthy aging. Clin Geriatr Med. 2020 Nov;36(4):655–69. Lim BG, Lee IO. Anesthetic management of geriatric patients. Korean J Anesthesiol. 2020 Feb;73(1):8–29. Chan SP, Ip KY, Irwin MG. Peri-operative optimisation of elderly and frail patients: a narrative review. Anaesthesia. 2019 Jan;74(Suppl 1):80–9. Joseph B, Zangbar B, Pandit V, Fain M, Mohler MJ, Kulvatunyou N, et al. Emergency general surgery in the elderly: too old or too frail? J Am Coll Surg. 2016 May;222(5):805–13. Castell MV, Sánchez M, Julián R, Queipo R, Martín S, Otero Á. Frailty prevalence and slow walking speed in persons age 65 and older: implications for primary care. BMC Fam Pract. 2013 Jun 19;14:86. Dudzinska-Griszek J, Szuster K, Szewieczek J. Grip strength as a frailty diagnostic component in geriatric inpatients. Clin Interv Aging. 2017;12:1151–7. Jung HW, Jang IY, Lee CK, Yu SS, Hwang JK, Jeon C, et al. Usual gait speed is associated with frailty status, institutionalization, and mortality in community-dwelling rural older adults: a longitudinal analysis of the aging study of pyeongchang rural area. Clin Interv Aging. 2018;13:1079–89. Reeve TE 4th, Ur R, Craven TE, Kaan JH, Goldman MP, Edwards MS, et al. Grip strength measurement for frailty assessment in patients with vascular disease and associations with comorbidity, cardiac risk, and sarcopenia. J Vasc Surg. 2018 May;67(5):1512–20. Arjunan A, Peel NM, Hubbard RE. Gait speed and frailty status in relation to adverse outcomes in geriatric rehabilitation. Arch Phys Med Rehabil. 2019 May;100(5):859–64. Choi JY, Kim KI, Choi Y, Ahn SH, Kang E, Oh HK, et al. Comparison of multidimensional frailty score, grip strength, and gait speed in older surgical patients. J Cachexia Sarcopenia Muscle. 2020 Apr;11(2):432–40. Lee SW, Nam JS, Kim YJ, Kim MJ, Choi JH, Lee EH, et al. Predictive model for the assessment of preoperative frailty risk in the elderly. J Clin Med. 2021 Oct 8;10(19):4612. ASA physical status classification system. 2014. Mayhew D, Mendonca V, Murthy BVS. A review of ASA physical status: historical perspectives and modern developments. Anaesthesia. 2019 Mar;74(3):373–9. Gilbert T, Neuburger J, Kraindler J, Keeble E, Smith P, Ariti C, et al. Development and validation of a Hospital Frailty Risk Score focusing on older people in acute care settings using electronic hospital records: an observational study. Lancet. 2018 May 5;391(10132):1775–82. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. Romano PS, Roos LL, Jollis JG. Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. J Clin Epidemiol. 1993 Oct;46(10):1075–90; discussion 1081–90 Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, et al. Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data. Med Care. 2005 Nov;43(11):1130–9. Roos LL, Stranc L, James RC, Li J. Complications, comorbidities, and mortality: improving classification and prediction. Health Serv Res. 1997 Jun;32(2):229–42; discussion 239–42. Kim KH. [Comparative study on three algorithms of the ICD-10 Charlson comorbidity index with myocardial infarction patients]. J Prev Med Public Health. 2010 Jan;43(1):42–9. Lee J, Lee JS, Park SH, Shin SA, Kim K. Cohort profile: the National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea. Int J Epidemiol. 2017 Apr 1;46(2):e15. McCusker J, Bellavance F, Cardin S, Trépanier S, Verdon J, Ardman O. Detection of older people at increased risk of adverse health outcomes after an emergency visit: the ISAR screening tool. J Am Geriatr Soc. 1999 Oct;47(10):1229–37. Soong J, Poots AJ, Scott S, Donald K, Bell D. Developing and validating a risk prediction model for acute care based on frailty syndromes. BMJ Open. 2015 Oct 21;5(10):e008457. Shinall MC Jr, Arya S, Youk A, Varley P, Shah R, Massarweh NN, et al. Association of preoperative patient frailty and operative stress with postoperative mortality. JAMA Surg. 2020 Jan 1;155(1):e194620. Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, et al. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005 Aug 30;173(5):489–95. Rodacki ALF, Boneti Moreira N, Pitta A, Wolf R, Melo Filho J, Rodacki CLN, et al. Is handgrip strength a useful measure to evaluate lower limb strength and functional performance in older women? Clin Interv Aging. 2020;15:1045–56. Article / Publication Details

First-Page Preview

Received: December 08, 2021
Accepted: April 23, 2022
Published online: May 16, 2022

Number of Print Pages: 9
Number of Figures: 4
Number of Tables: 2

ISSN: 0304-324X (Print)
eISSN: 1423-0003 (Online)

For additional information: https://www.karger.com/GER

Copyright / Drug Dosage / Disclaimer Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher.
Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug.
Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.