Dataset Information

Improved night shift schedule related to the mortality of critically ill patients with Corona Virus Disease 2019.

ABSTRACT: PURPOSE:To determine the relationship between the improved night shift schedule and the mortality of critically ill patients with Corona Virus Disease 2019 (COVID-19). METHODS:According to the time of the implementation of the new night shift schedule, we divided all patients into two groups: initial period group and recent period group. The clinical electronic medical records, nursing records, laboratory findings, and radiological examinations for all patients with laboratory confirmed Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection were reviewed. Cox proportional hazard ratio (HR) models were used to determine the risk factors associated with in hospital death. RESULTS:A total of 75 patients were included in this study. Initial period group includes 45 patients and recent period group includes 30 patients. The difference in mortality between the two groups was significant, 77.8% and 36.7%, respectively. Leukocytosis at admission and admitted to hospital before the new night shift schedule were associated with increased odds of death. CONCLUSIONS:Shift arrangement of medical staff are associated with the mortality of critically ill patients with COVID-19. The new night shift schedule might improve the continuity of treatment, thereby improving the overall quality of medical work and reducing the mortality of critically ill patients.

SUBMITTER: Zhang S

PROVIDER: S-EPMC7429562 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Improved night shift schedule related to the mortality of critically ill patients with Corona Virus Disease 2019.

Zhang Sun S Xu Yuanda Y Wu Kang K Wang Tao T Su Xiaofen X Han Qian Q Xi Yin Y Zhu Shitao S Gao Yong Y Wang Hongbo H Hu Yu Y Liu Chunli C Zhong Nanshan N Ran Pixin P Zhang Nuofu N

Sleep medicine 20200817

<h4>Purpose</h4>To determine the relationship between the improved night shift schedule and the mortality of critically ill patients with Corona Virus Disease 2019 (COVID-19).<h4>Methods</h4>According to the time of the implementation of the new night shift schedule, we divided all patients into two groups: initial period group and recent period group. The clinical electronic medical records, nursing records, laboratory findings, and radiological examinations for all patients with laboratory con ...[more]

PMID: 32950880

Similar Datasets

Project description:ObjectivesCoronavirus disease 2019 is caused by severe acute respiratory syndrome-coronavirus-2 infection to which there is no community immunity. Patients admitted to ICUs have high mortality, with only supportive therapies available. Our aim was to profile plasma inflammatory analytes to help understand the host response to coronavirus disease 2019.DesignDaily blood inflammation profiling with immunoassays.SettingTertiary care ICU and academic laboratory.SubjectsAll patients admitted to the ICU suspected of being infected with severe acute respiratory syndrome-coronavirus-2, using standardized hospital screening methodologies, had daily blood samples collected until either testing was confirmed negative on ICU day 3 (coronavirus disease 2019 negative), or until ICU day 7 if the patient was positive (coronavirus disease 2019 positive).InterventionsNone.Measurements and main resultsAge- and sex-matched healthy controls and ICU patients that were either coronavirus disease 2019 positive or coronavirus disease 2019 negative were enrolled. Cohorts were well-balanced with the exception that coronavirus disease 2019 positive patients were more likely than coronavirus disease 2019 negative patients to suffer bilateral pneumonia. Mortality rate for coronavirus disease 2019 positive ICU patients was 40%. We measured 57 inflammatory analytes and then analyzed with both conventional statistics and machine learning. Twenty inflammatory analytes were different between coronavirus disease 2019 positive patients and healthy controls (p < 0.01). Compared with coronavirus disease 2019 negative patients, coronavirus disease 2019 positive patients had 17 elevated inflammatory analytes on one or more of their ICU days 1-3 (p < 0.01), with feature classification identifying the top six analytes between cohorts as tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2. While tumor necrosis factor, granzyme B, heat shock protein 70, and interleukin-18 were elevated for all seven ICU days, interferon-gamma-inducible protein 10 transiently elevated on ICU days 2 and 3 and elastase 2 increased over ICU days 2-7. Inflammation profiling predicted coronavirus disease 2019 status with 98% accuracy, whereas elevated heat shock protein 70 was strongly associated with mortality.ConclusionsWhile many inflammatory analytes were elevated in coronavirus disease 2019 positive ICU patients, relative to healthy controls, the top six analytes distinguishing coronavirus disease 2019 positive ICU patients from coronavirus disease 2019 negative ICU patients were tumor necrosis factor, granzyme B, heat shock protein 70, interleukin-18, interferon-gamma-inducible protein 10, and elastase 2.

Project description:OBJECTIVES:Increasing time to mechanical ventilation and high-flow nasal cannula use may be associated with mortality in coronavirus disease 2019. We examined the impact of time to intubation and use of high-flow nasal cannula on clinical outcomes in patients with coronavirus disease 2019. DESIGN:Retrospective cohort study. SETTING:Six coronavirus disease 2019-specific ICUs across four university-affiliated hospitals in Atlanta, Georgia. PATIENTS:Adults with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection who received high-flow nasal cannula or mechanical ventilation. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:Among 231 patients admitted to the ICU, 109 (47.2%) were treated with high-flow nasal cannula and 97 (42.0%) were intubated without preceding high-flow nasal cannula use. Of those managed with high-flow nasal cannula, 78 (71.6%) ultimately received mechanical ventilation. In total, 175 patients received mechanical ventilation; 44.6% were female, 66.3% were Black, and the median age was 66 years (interquartile range, 56-75 yr). Seventy-six patients (43.4%) were intubated within 8 hours of ICU admission, 57 (32.6%) between 8 and 24 hours of admission, and 42 (24.0%) greater than or equal to 24 hours after admission. Patients intubated within 8 hours were more likely to have diabetes, chronic comorbidities, and higher admission Sequential Organ Failure Assessment scores. Mortality did not differ by time to intubation (? 8 hr: 38.2%; 8-24 hr: 31.6%; ? 24 hr: 38.1%; p = 0.7), and there was no association between time to intubation and mortality in adjusted analysis. Similarly, there was no difference in initial static compliance, duration of mechanical ventilation, or ICU length of stay by timing of intubation. High-flow nasal cannula use prior to intubation was not associated with mortality. CONCLUSIONS:In this cohort of critically ill patients with coronavirus disease 2019, neither time from ICU admission to intubation nor high-flow nasal cannula use were associated with increased mortality. This study provides evidence that coronavirus disease 2019 respiratory failure can be managed similarly to hypoxic respiratory failure of other etiologies.

Project description:OBJECTIVES:To identify characteristics that predict 30-day mortality among patients critically ill with coronavirus disease 2019 in England, Wales, and Northern Ireland. DESIGN:Observational cohort study. SETTING:A total of 258 adult critical care units. PATIENTS:A total of 10,362 patients with confirmed coronavirus disease 2019 with a start of critical care between March 1, 2020, and June 22, 2020, of whom 9,990 were eligible (excluding patients with a duration of critical care less than 24 hr or missing core variables). MEASUREMENTS AND MAIN RESULTS:The main outcome measure was time to death within 30 days of the start of critical care. Of 9,990 eligible patients (median age 60 yr, 70% male), 6,027 died within 30 days of the start of critical care. As of July 22, 2020, 189 patients were still receiving critical care and a further 446 were still in acute hospital. Data were missing for between 0.1% and 7.2% of patients across prognostic factors. We imputed missing data ten-fold, using fully conditional specification and continuous variables were modeled using restricted cubic splines. Associations between the candidate prognostic factors and time to death within 30 days of the start of critical care were determined after adjustment for multiple variables with Cox proportional hazards modeling. Significant associations were identified for age, ethnicity, deprivation, body mass index, prior dependency, immunocompromise, lowest systolic blood pressure, highest heart rate, highest respiratory rate, PaO2/FIO2 ratio (and interaction with mechanical ventilation), highest blood lactate concentration, highest serum urea, and lowest platelet count over the first 24 hours of critical care. Nonsignificant associations were found for sex, sedation, highest temperature, and lowest hemoglobin concentration. CONCLUSIONS:We identified patient characteristics that predict an increased likelihood of death within 30 days of the start of critical care for patients with coronavirus disease 2019. These findings may support development of a prediction model for benchmarking critical care providers.

Project description:BackgroundThere are large uncertainties with regard to the outcome of patients with coronavirus disease 2019 (COVID-19) and mechanical ventilation (MV). High mortality (50-97%) was proposed by some groups, leading to considerable uncertainties with regard to outcomes of critically ill patients with COVID-19.ObjectivesThe aim was to investigate the characteristics and outcomes of critically ill patients with COVID-19 requiring intensive care unit (ICU) admission and MV.MethodsA multicentre retrospective observational cohort study at 15 hospitals in Hamburg, Germany, was performed. Critically ill adult patients with COVID-19 who completed their ICU stay between February and June 2020 were included. Patient demographics, severity of illness, and ICU course were retrospectively evaluated.ResultsA total of 223 critically ill patients with COVID-19 were included. The majority, 73% (n = 163), were men; the median age was 69 (interquartile range = 58-77.5) years, with 68% (n = 151) patients having at least one chronic medical condition. Their Sequential Organ Failure Assessment score was a median of 5 (3-9) points on admission. Overall, 167 (75%) patients needed MV. Noninvasive ventilation and high-flow nasal cannula were used in 31 (14%) and 26 (12%) patients, respectively. Subsequent MV, due to noninvasive ventilation/high-flow nasal cannula therapy failure, was necessary in 46 (81%) patients. Renal replacement therapy was initiated in 33% (n = 72) of patients, and owing to severe respiratory failure, extracorporeal membrane oxygenation was necessary in 9% (n = 20) of patients. Experimental antiviral therapy was used in 9% (n = 21) of patients. Complications during the ICU stay were as follows: septic shock (40%, n = 90), heart failure (8%, n = 17), and pulmonary embolism (6%, n = 14). The length of ICU stay was a median of 13 days (5-24), and the duration of MV was 15 days (8-25). The ICU mortality was 35% (n = 78) and 44% (n = 74) among mechanically ventilated patients.ConclusionIn this multicentre observational study of 223 critically ill patients with COVID-19, the survival to ICU discharge was 65%, and it was 56% among patients requiring MV. Patients showed high rate of septic complications during their ICU stay.

Project description:Objective: The aims of this systematic review and meta-analysis were to summarize the current existing evidence on the outcome of critically ill patients with COVID-19 as well as to evaluate the effectiveness of clinical interventions. Data Sources: We searched MEDLINE, the Cochrane library, Web of Science, the China Biology Medicine disc, China National Knowledge Infrastructure, and Wanfang Data from their inception to May 15, 2021. The search strings consisted of various search terms related to the concepts of mortality of critically ill patients and clinical interventions. Study Selection: After eliminating duplicates, two reviewers independently screened all titles and abstracts first, and then the full texts of potentially relevant articles were reviewed to identify cohort studies and case series that focus on the mortality of critically ill patients and clinical interventions. Main Outcomes and Measures: The primary outcome was the mortality of critically ill patients with COVID-19. The secondary outcomes included all sorts of supportive care. Results: There were 27 cohort studies and six case series involving 42,219 participants that met our inclusion criteria. All-cause mortality in the intensive care unit (ICU) was 35% and mortality in hospital was 32% in critically ill patients with COVID-19 for the year 2020, with very high between-study heterogeneity (I 2 = 97%; p < 0.01). In a subgroup analysis, the mortality during ICU hospitalization in China was 39%, in Asia-except for China-it was 48%, in Europe it was 34%, in America it was 15%, and in the Middle East it was 39%. Non-surviving patients who had an older age [-8.10, 95% CI (-9.31 to -6.90)], a higher APACHE II score [-4.90, 95% CI (-6.54 to -3.27)], a higher SOFA score [-2.27, 95% CI (-2.95 to -1.59)], and a lower PaO2/FiO2 ratio [34.77, 95% CI (14.68 to 54.85)] than those who survived. Among clinical interventions, invasive mechanical ventilation [risk ratio (RR) 0.49, 95% CI (0.39-0.61)], kidney replacement therapy [RR 0.34, 95% CI (0.26-0.43)], and vasopressor [RR 0.54, 95% CI (0.34-0.88)] were used more in surviving patients. Conclusions: Mortality was high in critically ill patients with COVID-19 based on low-quality evidence and regional difference that existed. The early identification of critical characteristics and the use of support care help to indicate the outcome of critically ill patients.

Project description:BackgroundSevere acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection causes direct lung damage, overwhelming endothelial activation, and inflammatory reaction, leading to acute respiratory failure and multi-organ dysfunction. Ongoing clinical trials are evaluating targeted therapies to hinder this exaggerated inflammatory response. Critically ill coronavirus disease 2019 (COVID-19) patients have shown heterogeneous severity trajectories, suggesting that response to therapies is likely to vary across patients.Research questionAre critically ill COVID-19 patients biologically and immunologically dissociable based on profiling of currently evaluated therapeutic targets?Study design and methodsWe did a single-center, prospective study in an ICU department in France. Ninety-six critically ill adult patients admitted with a documented SARS-CoV-2 infection were enrolled. We conducted principal components analysis and hierarchical clustering on a vast array of immunologic variables measured on the day of ICU admission.ResultsWe found that patients were distributed in three clusters bearing distinct immunologic features and associated with different ICU outcomes. Cluster 1 had a "humoral immunodeficiency" phenotype with predominant B-lymphocyte defect, relative hypogammaglobulinemia, and moderate inflammation. Cluster 2 had a "hyperinflammatory" phenotype, with high cytokine levels (IL-6, IL-1β, IL-8, tumor necrosis factor-alpha [TNF⍺]) associated with CD4+ and CD8+ T-lymphocyte defects. Cluster 3 had a "complement-dependent" phenotype with terminal complement activation markers (elevated C3 and sC5b-9).InterpretationPatients with severe COVID-19 exhibiting cytokine release marks, complement activation, or B-lymphocyte defects are distinct from each other. Such immunologic variability argues in favor of targeting different mediators in different groups of patients and could serve as a basis for patient identification and clinical trial eligibility.

Project description:Hospitals are increasingly adopting 24-hour intensivist physician staffing as a strategy to improve intensive care unit (ICU) outcomes. However, the degree to which nighttime intensivists are associated with improvements in the quality of ICU care is unknown.We conducted a retrospective cohort study involving ICUs that participated in the Acute Physiology and Chronic Health Evaluation (APACHE) clinical information system from 2009 through 2010, linking a survey of ICU staffing practices with patient-level outcomes data from adult ICU admissions. Multivariate models were used to assess the relationship between nighttime intensivist staffing and in-hospital mortality among ICU patients, with adjustment for daytime intensivist staffing, severity of illness, and case mix. We conducted a confirmatory analysis in a second, population-based cohort of hospitals in Pennsylvania from which less detailed data were available.The analysis with the use of the APACHE database included 65,752 patients admitted to 49 ICUs in 25 hospitals. In ICUs with low-intensity daytime staffing, nighttime intensivist staffing was associated with a reduction in risk-adjusted in-hospital mortality (adjusted odds ratio for death, 0.62; P=0.04). Among ICUs with high-intensity daytime staffing, nighttime intensivist staffing conferred no benefit with respect to risk-adjusted in-hospital mortality (odds ratio, 1.08; P=0.78). In the verification cohort, there was a similar relationship among daytime staffing, nighttime staffing, and in-hospital mortality. The interaction between nighttime staffing and daytime staffing was not significant (P=0.18), yet the direction of the findings were similar to those in the APACHE cohort.The addition of nighttime intensivist staffing to a low-intensity daytime staffing model was associated with reduced mortality. However, a reduction in mortality was not seen in ICUs with high-intensity daytime staffing. (Funded by the National Heart, Lung, and Blood Institute.).

Dataset Information

Improved night shift schedule related to the mortality of critically ill patients with Corona Virus Disease 2019.

Publications

Improved night shift schedule related to the mortality of critically ill patients with Corona Virus Disease 2019.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets