Identifying factors predicting outcomes after major trauma in older patients: Prognostic systematic review and meta-analysis.

INTRODUCTION: Trauma is the most common cause of morbidity and mortality in older people and it is important to determine the predictors of outcomes after major trauma in older people. METHODS: MEDLINE, Embase, Web of Science and manual search of relevant papers since 1987 to February 2023 was searched. Random effects meta-analyses were performed. The primary outcome of interest was mortality and secondary outcomes were medical complications, length of stay, discharge destination, readmission, and intensive care requirement. RESULTS: Amongst 6064 studies in the search strategy, 136 studies qualified inclusion criteria. 43 factors, ranging from demographics, patient-factors, admission measurements and injury factors, were identified as potential predictors. Mortality was the commonest outcome investigated and increasing age was associated with increased risk of in-hospital mortality (OR 1.05, 95%CI1.03-1.07) along with male gender (OR1.40, 95%CI1.24-1.59). Comorbidities of heart disease (OR 2.59, 95%CI1.41-4.77), renal disease (OR2.52, 95%CI1.79-3.56), respiratory disease (OR1.40. 95%CI 1.09-1.81), diabetes (OR1.35, 95%CI1.03-1.77) and neurological disease (OR 1.42, 95%CI 0.93-2.18) were also associated with increased in-hospital mortality risk. Each point increase in the Glasgow Coma Scale lowered the risk of in-hospital mortality (OR 0.85, 95%CI 0.76-0.95) while each point increase in Injury Severity Score increased the risk of in-hospital mortality (OR 1.07, 95%CI1.04-1.09). There were limited studies and substantial variability in secondary outcome predictors, however, medical comorbidities, frailty, premorbid living condition appeared predictive for those outcomes. CONCLUSIONS: This review was able to identify potential predictors for older trauma patients. The identification of these factors allows for future development of risk stratification tools for clinicians. LEVEL OF EVIDENCE: Level II, Prognostic Systematic Review and Meta-Analysis.

Introduction to the novel model of preoperative Multi - Domain Risk Stratification (pMDRS).

Preoperative risk stratification is an important step in surgical procedures. The current scoring systems do not predict accurate overall surgical outcomes in complex comorbid patients. The novel model of preoperative multi-domain risk stratification is described in this article, which categorises patients in to three risk groups, aiming to modify the risk for optimal surgical outcomes.

Clinical systematic reviews - a brief overview.

OBJECTIVE: Systematic reviews answer research questions through a defined methodology. It is a complex task and multiple articles need to be referred to acquire wide range of required knowledge to conduct a systematic review. The aim of this article is to bring the process into a single paper. METHOD: The statistical concepts and sequence of steps to conduct a systematic review or a meta-analysis are examined by authors. RESULTS: The process of conducting a clinical systematic review is described in seven manageable steps in this article. Each step is explained with examples to understand the method evidently. CONCLUSION: A complex process of conducting a systematic review is presented simply in a single article.

Patient Controlled Analgesia and its effect on postoperative outcomes in an older cohort of patients undergoing orthopaedic procedures: A retrospective observational study.

BACKGROUND: Patient Controlled Analgesia is a popular technique used to manage postoperative pain. The suitability of Patient Controlled Analgesia in older patients after surgical procedures and its effect on postoperative outcomes are not clear. METHOD: The records of 305 older patients undergoing orthopaedic surgeries in a single tertiary centre were reviewed. Postoperative outcomes were compared between those given Patient Controlled Analgesia and those who were not, using multinomial logistic regression adjusted by propensity scores. RESULTS: Physical function on day 3 after surgery is worse, and risk of requiring personal assistance is higher if the patient had Patient Controlled Analgesia (p = 0.01). Length of stay in patients using patient-controlled analgesia was longer than patients not using patient-controlled analgesia (p = 0.002), and patients given Patient Controlled Analgesia had higher odds of needing support on discharge (p = 0.01). Surprisingly, pain control is poor in the Patient Controlled Analgesia group (p = 0.009). CONCLUSION: In this review, Patient Controlled Analgesia use was common (40% of our sample), and postoperative outcomes such as physical function on day 3, length of stay and discharge destination were unfavourable in patients who had Patient Controlled Analgesia.

Prognostication accuracy of final destination in poststroke patients requiring transitional care.

OBJECTIVES: Transitional care program in Australia targets older patients in hospitals requiring ongoing slow-stream restorative care prior to discharge. Poststroke patients often require extended care and are transferred to these facilities. Transitional care providers require a predicted discharge destination. The aim of this study was to assess the accuracy of this prediction. METHODOLOGY: This study included all patients transferred to transitional care from a stroke rehabilitation unit over eight years. Information regarding the predicted final discharge destination was collected from medical records, and the actual discharge destination was obtained from the transitional care registry. RESULTS: Final destination prediction was equivalent between medical and multidisciplinary teams (κ = 0.87). However, only 60% of the predictions were accurate. Subgroup analysis, as measured by the Modified Barthel Index, suggested that functional gain was a better predictor of final destination. Other characteristics, such as age, sex and type of stroke, did not demonstrate good correlation with the final destination. CONCLUSION: Functional improvement, that is the Modified Barthel Index, is the best predictor of final destination after transitional care.