Evaluating the Modified Aldrete Score for Pediatric Recovery and Discharge Readiness: A Systematic Review of Evidence
Keywords:
Modified Aldrete Score, paediatric anaesthesia, PACU, Fast-Track CriteriaAbstract
Background: Safe recovery following anaesthesia in children is critical due to unique physiological and developmental vulnerabilities. The Modified Aldrete Score (MAS), originally developed for adults, is widely used to determine readiness for discharge from the post-anaesthesia care unit (PACU). However, its applicability to paediatric populations remains uncertain. Aim: This systematic review aimed to evaluate the effectiveness of MAS in assessing recovery and predicting outcomes in paediatric PACU patients, compared with alternative discharge criteria. Methods: A systematic search of PubMed, Medline, Cochrane Library, and Google Scholar was conducted for studies published between 2009 and 2024. Eligible studies included randomized controlled trials, observational studies, and reviews reporting on MAS use in paediatric populations. Data were extracted on study characteristics, comparators, and outcomes including PACU length of stay, discharge readiness, postoperative complications, and hospital stay. Methodological quality was assessed using the Cochrane Risk of Bias Tool, Newcastle-Ottawa Scale, and AMSTAR-2. Results: Eighteen studies met the inclusion criteria. Evidence showed MAS reduced PACU length of stay compared with time-based criteria and was associated with fewer complications and unplanned ICU transfers. Compared with the Fast-Track Criteria (FTC) and Modified Post-Anaesthetic Discharge Scoring System (MPADSS), MAS was more efficient but less comprehensive, as it excludes pain, nausea, and behavioural recovery markers. Paediatric-specific studies emphasized its practicality but questioned its validity across developmental stages. Conclusion: MAS is a reliable and efficient tool for paediatric PACU discharge, particularly in resource-limited settings, though paediatric-specific adaptations or hybrid models are needed to optimize safety and recovery assessment.