METHODS: We conducted an international, retrospective cohort study using 2019 and 2020 data from 11 national clinical quality registries covering 15 countries. Non-COVID-19 admissions in 2020 were compared with all admissions in 2019, prepandemic. The primary outcome was intensive care unit (ICU) mortality. Secondary outcomes included in-hospital mortality and standardised mortality ratio (SMR). Analyses were stratified by the country income level(s) of each registry.
FINDINGS: Among 1 642 632 non-COVID-19 admissions, there was an increase in ICU mortality between 2019 (9.3%) and 2020 (10.4%), OR=1.15 (95% CI 1.14 to 1.17, p<0.001). Increased mortality was observed in middle-income countries (OR 1.25 95% CI 1.23 to 1.26), while mortality decreased in high-income countries (OR=0.96 95% CI 0.94 to 0.98). Hospital mortality and SMR trends for each registry were consistent with the observed ICU mortality findings. The burden of COVID-19 was highly variable, with COVID-19 ICU patient-days per bed ranging from 0.4 to 81.6 between registries. This alone did not explain the observed non-COVID-19 mortality changes.
INTERPRETATION: Increased ICU mortality occurred among non-COVID-19 patients during the pandemic, driven by increased mortality in middle-income countries, while mortality decreased in high-income countries. The causes for this inequity are likely multi-factorial, but healthcare spending, policy pandemic responses, and ICU strain may play significant roles.
MATERIALS AND METHODS: In this multicenter cross-sectional study, data on mechanical ventilation and clinical outcomes were collected. Predictors of mortality were analyzed by univariate and multivariable logistic regression. A scoring system was generated to predict 28-day mortality.
RESULTS: A total of 1408 patients were enrolled. In 138 patients with acute respiratory distress syndrome (ARDS), 65.9% were on a tidal volume ≤ 8 ml/kg predicted body weight (PBW), and 71.3% were on sufficient PEEP. In 1270 patients without ARDS, 88.8% were on a tidal volume ≤ 10 ml/kg PBW. A plateau pressure
MATERIALS AND METHODS: This cross-sectional study was conducted among 60 registered nurses in the ICU at Taiping Hospital. to assess the nurses' knowledge and attitude level using the Knowledge and Attitude on prevention of PUs questionnaire. A descriptive analysis and Pearson Correlation were used to analyze the data.
RESULT: From a total of 60 nurses 36 (60%) of nurses demonstrated a moderate level of KAP, and 17 (28%) demonstrated a high level of knowledge. They also exhibited neutral attitudes towards PUs prevention 49 (82%). The findings revealed a positive relationship between nurses' KAP toward implementing preventive measures on PUs (p=0.04; r=0.3). The findings show that nurses regularly performed the assessment of the risk factors of PUs for all hospitalized patients when performing PUs care. However, the plan for preventive nursing care was not properly reviewed.
CONCLUSION: This study suggested that appropriate guidelines, education programs, and an environment that makes it possible to provide continuing education should be created for nurses to prevent PUs in the ICU.
METHODS: This was a secondary analysis of the MOSAICS II study, an international prospective observational study on sepsis epidemiology in Asian ICUs. Associations between qSOFA at ICU admission and mortality were separately assessed in LLMIC, UMIC and HIC countries/regions. Modified Poisson regression was used to determine the adjusted relative risk (RR) of qSOFA score on mortality at 28 days with adjustments for confounders identified in the MOSAICS II study.
RESULTS: Among the MOSAICS II study cohort of 4980 patients, 4826 patients from 343 ICUs and 22 countries were included in this secondary analysis. Higher qSOFA was associated with increasing 28-day mortality, but this was only observed in LLMIC (p
METHODS: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV).
RESULTS: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%.
CONCLUSIONS: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.
MATERIALS AND METHODS: A prospective study was conducted at the single centre ICU in Hospital Sultanah Aminah (HSA) Malaysia. External validation of APACHE IV involved a cohort of 916 patients who were admitted in 2009. Model performance was assessed through its calibration and discrimination abilities. A first-level customisation using logistic regression approach was also applied to improve model calibration.
RESULTS: APACHE IV exhibited good discrimination, with an area under receiver operating characteristic (ROC) curve of 0.78. However, the model's overall fit was observed to be poor, as indicated by the Hosmer-Lemeshow goodness-of-fit test (Ĉ = 113, P <0.001). Predicted in-ICU mortality rate (28.1%) was significantly higher than the actual in-ICU mortality rate (18.8%). Model calibration was improved after applying first-level customisation (Ĉ = 6.39, P = 0.78) although discrimination was not affected.
CONCLUSION: APACHE IV is not suitable for application in HSA ICU, without further customisation. The model's lack of fit in the Malaysian study is attributed to differences in the baseline characteristics between HSA ICU and APACHE IV datasets. Other possible factors could be due to differences in clinical practice, quality and services of health care systems between Malaysia and the United States.