IntroductionDelirium is a frequent form of acute brain dysfunction in critically ill patients, and several detection tools for it have been developed for use in the Intensive Care Unit (ICU). The objective of this study is to evaluate the current evidence on the accuracy of the Confusion Assessment Method for Intensive Care Unit (CAM-ICU) and the Intensive Care Delirium Screening Checklist (ICDSC) for the diagnosis of delirium in critically ill patients.MethodsA systematic review was conducted to identify articles on the evaluation of the CAM-ICU and the ICDSC in ICU patients. A MEDLINE, SciELO, CINAHL and EMBASE databases search was performed for articles published in the English language, involving adult populations and comparing these diagnostic tools with the gold standard, the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria. Results were summarized by meta-analysis. The QUADAS scale was used to assess the quality of the studies.ResultsNine studies evaluating the CAM-ICU (including 969 patients) and four evaluating the ICDSC (n = 361 patients) were included in the final analysis. The pooled sensitivity of the CAM-ICU was 80.0% (95% confidence interval (CI): 77.1 to 82.6%), and the pooled specificity was 95.9% (95% CI: 94.8 to 96.8%). The diagnostic odds ratio was 103.2 (95% CI: 39.6 to 268.8). The pooled area under the summary receiver operating characteristic curve (AUC) was 0.97. The pooled sensitivity of the ICDSC was 74% (95% CI: 65.3 to 81.5%), and the pooled specificity was 81.9% (95% CI: 76.7 to 86.4%). The diagnostic odds ratio was 21.5 (95% CI: 8.51 to 54.4). The AUC was 0.89.ConclusionsThe CAM-ICU is an excellent diagnostic tool in critically ill ICU patients, whereas the ICDSC has moderate sensitivity and good specificity. The available data suggest that both CAM-ICU and the ICDSC can be used as a screening tool for the diagnosis of delirium in critically ill patients.

Background : COVID-19 pandemic caused increased workload and stress for health professionals involved in the care of such patients. We aimed to describe the health-related quality of life, and burnout in frontline physicians diagnosed with anxiety during the COVID-19 pandemic. Methods : This was a cross-sectional study conducted during the first-wave phase of COVID-19, from September to October 2020. Questionnaires were sent electronically to 450 physicians from State of Bahia, assessing symptoms of anxiety, health-related quality of life (HRQOL) and burnout syndrome. For the categorical variables, the Pearson's chi-square test was used and difference between means was compare using the Mann-Whitney test. was Groups with and without anxiety symptoms were compared using prevalence ratios (PR). Pearson's correlation measured the correlation between WHOQOL-BREF and MBI (Maslach Burnout Inventory) domains. The Fisher r-to-z transformation was used to assess the significance of the difference between two correlation coefficients. The significance level was <0.05. Results : Out of the 450 physicians, 223 (49,6%) completely answered the questionnaire and 38 (17%) showed symptoms of anxiety. Physicians with anxiety had higher scores in emotional exhaustion (EE) (38.31 ± 8.59 vs 25.31±0.87; p=0.0001) and depersonalization (DP) (9.0 ± 5.6 vs 5.9 ± 5.3; p=0.001) domains, and lower scores in personal accomplishment (PA) (32.1 ± 8.2 vs 36.3 ± 7.6; p=0.004), than those without anxiety. All correlations between WHOQOL-BREF domains and MBI in physicians without anxiety were significant (p = 0.01). Conclusion : Physicians with anxiety showed more emotional exhaustion, less personal accomplishment, and lower quality of life. All domains of WHOQOL BREF were correlated with all MBI domains among physicians without anxiety. Differences in correlation according to anxiety were remarkable in psychological HOQOL BREF domain and emotional exhaustion and depersonalization MBI domains. The effect of anxiety leading to poorer levels of perceived health needs to be further investigated.

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