Gupta A, Singh O, Juneja D. Clinical prediction scores predicting weaning failure from invasive mechanical ventilation: Role and limitations. World J Crit Care Med 2024; 13(4): 96482 [DOI: 10.5492/wjccm.v13.i4.96482]
Corresponding Author of This Article
Deven Juneja, DNB, FRCP, MBBS, Director, Institute of Critical Care Medicine, Max Super Specialty Hospital, 1 Press Enclave Road, Saket, New Delhi 110017, India. devenjuneja@gmail.com
Research Domain of This Article
Critical Care Medicine
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Crit Care Med. Dec 9, 2024; 13(4): 96482 Published online Dec 9, 2024. doi: 10.5492/wjccm.v13.i4.96482
Clinical prediction scores predicting weaning failure from invasive mechanical ventilation: Role and limitations
Anish Gupta, Omender Singh, Deven Juneja
Anish Gupta, Institute of Critical Care Medicine, Max Hospital, Gurugram 122022, Haryana, India
Omender Singh, Deven Juneja, Institute of Critical Care Medicine, Max Super Specialty Hospital, New Delhi 110017, India
Author contributions: Gupta A and Juneja D conceived the study, performed data acquisition, carried out the majority of writing, and prepared the tables; Singh O provided inputs in writing of the paper and reviewed the manuscript.
Conflict-of-interest statement: All authors declare that they have no conflicts of interest to disclose.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Deven Juneja, DNB, FRCP, MBBS, Director, Institute of Critical Care Medicine, Max Super Specialty Hospital, 1 Press Enclave Road, Saket, New Delhi 110017, India. devenjuneja@gmail.com
Received: May 7, 2024 Revised: August 27, 2024 Accepted: August 30, 2024 Published online: December 9, 2024 Processing time: 176 Days and 15.6 Hours
Abstract
Invasive mechanical ventilation (IMV) has become integral to modern-day critical care. Even though critically ill patients frequently require IMV support, weaning from IMV remains an arduous task, with the reported weaning failure (WF) rates being as high as 50%. Optimizing the timing for weaning may aid in reducing time spent on the ventilator, associated adverse effects, patient discomfort, and medical care costs. Since weaning is a complex process and WF is often multi-factorial, several weaning scores have been developed to predict WF and aid decision-making. These scores are based on the patient's physiological and ventilatory parameters, but each has limitations. This review highlights the current role and limitations of the various clinical prediction scores available to predict WF.
Core Tip: Delay in weaning from invasive mechanical ventilation or weaning failure (WF) may increase patient mortality, morbidity, risk of secondary infections, length of hospital/ICU stay and healthcare costs. Physician’s ability to predict successful weaning has been shown to have low accuracy, with poor positive and negative predictive values. As the pathophysiology of WF is complex and multifactorial, a single parameter may not suffice to predict successful weaning. Hence, several clinical scores, encompassing multiple patients and ventilatory factors have been devised to predict WF. However, none of the current scores is ideal and each have their inherent limitations.