Perioperative Factors Associated With Postoperative Delirium in Patients Undergoing Noncardiac Surgery:An Individual Patient Data Meta-Analysis

IMPORTANCE: Postoperative delirium (POD) is a common and serious complication after surgery. Various predisposing factors are associated with POD, but their magnitude and importance using an individual patient data (IPD) meta-analysis have not been assessed.OBJECTIVE: To identify perioperative factors associated with POD and assess their relative prognostic value among adults undergoing noncardiac surgery.DATA SOURCES: MEDLINE, EMBASE, and CINAHL from inception to May 2020.STUDY SELECTION: Studies were included that (1) enrolled adult patients undergoing noncardiac surgery, (2) assessed perioperative risk factors for POD, and (3) measured the incidence of delirium (measured using a validated approach). Data were analyzed in 2020.DATA EXTRACTION AND SYNTHESIS: Individual patient data were pooled from 21 studies and 1-stage meta-analysis was performed using multilevel mixed-effects logistic regression after a multivariable imputation via chained equations model to impute missing data.MAIN OUTCOMES AND MEASURES: The end point of interest was POD diagnosed up to 10 days after a procedure. A wide range of perioperative risk factors was considered as potentially associated with POD.RESULTS: A total of 192 studies met the eligibility criteria, and IPD were acquired from 21 studies that enrolled 8382 patients. Almost 1 in 5 patients developed POD (18%), and an increased risk of POD was associated with American Society of Anesthesiologists (ASA) status 4 (odds ratio [OR], 2.43; 95% CI, 1.42-4.14), older age (OR for 65-85 years, 2.67; 95% CI, 2.16-3.29; OR for &gt;85 years, 6.24; 95% CI, 4.65-8.37), low body mass index (OR for body mass index &lt;18.5, 2.25; 95% CI, 1.64-3.09), history of delirium (OR, 3.9; 95% CI, 2.69-5.66), preoperative cognitive impairment (OR, 3.99; 95% CI, 2.94-5.43), and preoperative C-reactive protein levels (OR for 5-10 mg/dL, 2.35; 95% CI, 1.59-3.50; OR for &gt;10 mg/dL, 3.56; 95% CI, 2.46-5.17). Completing a college degree or higher was associated with a decreased likelihood of developing POD (OR 0.45; 95% CI, 0.28-0.72).CONCLUSIONS AND RELEVANCE: In this systematic review and meta-analysis of individual patient data, several important factors associated with POD were found that may help identify patients at high risk and may have utility in clinical practice to inform patients and caregivers about the expected risk of developing delirium after surgery. Future studies should explore strategies to reduce delirium after surgery.</p

Evaluating the relationship between citation set size, team size and screening methods used in systematic reviews: a cross-sectional study

Background Standard practice for conducting systematic reviews (SRs) is time consuming and involves the study team screening hundreds or thousands of citations. As the volume of medical literature grows, the citation set sizes and corresponding screening efforts increase. While larger team size and alternate screening methods have the potential to reduce workload and decrease SR completion times, it is unknown whether investigators adapt team size or methods in response to citation set sizes. Using a cross-sectional design, we sought to understand how citation set size impacts (1) the total number of authors or individuals contributing to screening and (2) screening methods. Methods MEDLINE was searched in April 2019 for SRs on any health topic. A total of 1880 unique publications were identified and sorted into five citation set size categories (after deduplication):  10,000. A random sample of 259 SRs were selected (~ 50 per category) for data extraction and analysis. Results With the exception of the pairwise t test comparing the under 1000 and over 10,000 categories (median 5 vs. 6, p = 0.049) no statistically significant relationship was evident between author number and citation set size. While visual inspection was suggestive, statistical testing did not consistently identify a relationship between citation set size and number of screeners (title-abstract, full text) or data extractors. However, logistic regression identified investigators were significantly more likely to deviate from gold-standard screening methods (i.e. independent duplicate screening) with larger citation sets. For every doubling of citation size, the odds of using gold-standard screening decreased by 15 and 20% at title-abstract and full text review, respectively. Finally, few SRs reported using crowdsourcing (n = 2) or computer-assisted screening (n = 1). Conclusions Large citation set sizes present a challenge to SR teams, especially when faced with time-sensitive health policy questions. Our study suggests that with increasing citation set size, authors are less likely to adhere to gold-standard screening methods. It is possible that adjunct screening methods, such as crowdsourcing (large team) and computer-assisted technologies, may provide a viable solution for authors to complete their SRs in a timely manner.Medicine, Faculty ofNon UBCPediatrics, Department ofReviewedFacultyResearche

Defining pediatric chronic critical illness: a scoping review

OBJECTIVES: Children with chronic critical illness (CCI) are hypothesized to be a high-risk patient population with persistent multiple organ dysfunction and functional morbidities resulting in recurrent or prolonged critical care; however, it is unclear how CCI should be defined. The aim of this scoping review was to evaluate the existing literature for case definitions of pediatric CCI and case definitions of prolonged PICU admission and to explore the methodologies used to derive these definitions. DATA SOURCES: Four electronic databases (Ovid Medline, Embase, CINAHL, and Web of Science) from inception to March 3, 2021. STUDY SELECTION: We included studies that provided a specific case definition for CCI or prolonged PICU admission. Crowdsourcing was used to screen citations independently and in duplicate. A machine-learning algorithm was developed and validated using 6,284 citations assessed in duplicate by trained crowd reviewers. A hybrid of crowdsourcing and machine-learning methods was used to complete the remaining citation screening. DATA EXTRACTION: We extracted details of case definitions, study demographics, participant characteristics, and outcomes assessed. DATA SYNTHESIS: Sixty-seven studies were included. Twelve studies (18%) provided a definition for CCI that included concepts of PICU length of stay (n = 12), medical complexity or chronic conditions (n = 9), recurrent admissions (n = 9), technology dependence (n = 5), and uncertain prognosis (n = 1). Definitions were commonly referenced from another source (n = 6) or opinion-based (n = 5). The remaining 55 studies (82%) provided a definition for prolonged PICU admission, most frequently greater than or equal to 14 (n = 11) or greater than or equal to 28 days (n = 10). Most of these definitions were derived by investigator opinion (n = 24) or statistical method (n = 18). CONCLUSIONS: Pediatric CCI has been variably defined with regard to the concepts of patient complexity and chronicity of critical illness. A consensus definition is needed to advance this emerging and important area of pediatric critical care research