Abstract
Rev Bras Ter Intensiva. 2020;32(2):301-307
DOI 10.5935/0103-507X.20200047
To evaluate the hypothesis that the Modified Early Warning Score (MEWS) at the time of intensive care unit discharge is associated with readmission and to identify the MEWS that most reliably predicts intensive care unit readmission within 48 hours of discharge.
This was a retrospective observational study of the MEWSs of discharged patients from the intensive care unit. We compared the demographics, severity scores, critical illness characteristics, and MEWSs of readmitted and non-readmitted patients, identified factors associated with readmission in a logistic regression model, constructed a Receiver Operating Characteristic (ROC) curve of the MEWS in predicting the probability of readmission, and presented the optimum criterion with the highest sensitivity and specificity.
The readmission rate was 2.6%, and the MEWS was a significant predictor of readmission, along with intensive care unit length of stay > 10 days and tracheostomy. The ROC curve of the MEWS in predicting the readmission probability had an AUC of 0.82, and a MEWS > 6 carried a sensitivity of 0.78 (95%CI 0.66 - 0.9) and specificity of 0.9 (95%CI 0.87 - 0.93).
The MEWS is associated with intensive care unit readmission, and a score > 6 has excellent accuracy as a prognostic predictor.
Abstract
Rev Bras Ter Intensiva. 2016;28(1):33-39
DOI 10.5935/0103-507X.20160011
The purpose of our study was to determine the admission factors associated with intensive care unit readmission among oncohematological patients.
Retrospective cohort study using an intensive care unit database from a tertiary oncological center. The participants included 1,872 critically ill oncohematological patients who were admitted to the intensive care unit from January 2012 to December 2014 and who were subsequently discharged alive. We used univariate and multivariate analysis to identify the admission risk factors associated with later intensive care unit readmission.
One hundred seventy-two patients (9.2% of 1,872 oncohematological patients discharged alive from the intensive care unit) were readmitted after intensive care unit discharge. The readmitted patients were sicker compared with the non-readmitted group and had higher hospital mortality (32.6% versus 3.7%, respectively; p < 0.001). In the multivariate analysis, the independent risk factors for intensive care unit readmission were male sex (OR: 1.5, 95% CI: 1.07 - 2.12; p = 0.019), emergency surgery as the admission reason (OR: 2.91, 95%CI: 1.53 - 5.54; p = 0.001), longer hospital length of stay before intensive care unit transfer (OR: 1.02, 95%CI: 1.007 - 1.035; p = 0.003), and mechanical ventilation (OR: 2.31, 95%CI: 1.57 - 3.40; p < 0.001).
In this cohort of oncohematological patients, we identified some risk factors associated with intensive care unit readmission, most of which are not amenable to interventions. The identification of risk factors at intensive care unit discharge might be a promising approach.
Abstract
Rev Bras Ter Intensiva. 2015;27(1):51-56
DOI 10.5935/0103-507X.20150009
To assess the causes and factors associated with the death of patients between intensive care unit discharge and hospital discharge.
The present is a pilot, retrospective, observational cohort study. The records of all patients admitted to two units of a public/private university hospital from February 1, 2013 to April 30, 2013 were assessed. Demographic and clinical data, risk scores and outcomes were obtained from the Epimed monitoring system and confirmed in the electronic record system of the hospital. The relative risk and respective confidence intervals were calculated.
A total of 581 patients were evaluated. The mortality rate in the intensive care unit was 20.8% and in the hospital was 24.9%. Septic shock was the cause of death in 58.3% of patients who died after being discharged from the intensive care unit. Of the patients from the public health system, 73 (77.6%) died in the intensive care unit and 21 (22.4%) died in the hospital after being discharged from the unit. Of the patients from the Supplementary Health System, 48 (94.1%) died in the intensive care unit and 3 (5.9%) died in the hospital after being discharged from the unit (relative risk, 3.87%; 95% confidence interval, 1.21 - 12.36; p < 0.05). The post-discharge mortality rate was significantly higher in patients with intensive care unit hospitalization time longer than 6 days.
The main cause of death of patients who were discharged from the intensive care unit and died in the ward before hospital discharge was septic shock. Coverage by the public healthcare system and longer hospitalization time in the intensive care unit were factors associated with death after discharge from the intensive care unit.
Abstract
Rev Bras Ter Intensiva. 2014;26(2):130-136
DOI 10.5935/0103-507X.20140019
To assess the performance of central venous oxygen saturation, lactate, base deficit, and C-reactive protein levels and SOFA and SWIFT scores on the day of discharge from the intensive care unit as predictors of patient readmission to the intensive care unit.
This prospective and observational study collected data from 1,360 patients who were admitted consecutively to a clinical-surgical intensive care unit from August 2011 to August 2012. The clinical characteristics and laboratory data of readmitted and non-readmitted patients after discharge from the intensive care unit were compared. Using a multivariate analysis, the risk factors independently associated with readmission were identified.
The C-reactive protein, central venous oxygen saturation, base deficit, and lactate levels and the SWIFT and SOFA scores did not correlate with the readmission of critically ill patients. Increased age and contact isolation because of multidrug-resistant organisms were identified as risk factors that were independently associated with readmission in this study group.
Inflammatory and perfusion parameters were not associated with patient readmission. Increased age and contact isolation because of multidrug-resistant organisms were identified as predictors of readmission to the intensive care unit.
Abstract
Rev Bras Ter Intensiva. 2013;25(1):32-38
DOI 10.1590/S0103-507X2013000100007
OBJECTIVES: Identify patients at risk for intensive care unit readmission, the reasons for and rates of readmission, and mortality after their stay in the intensive care unit; describe the sensitivity and specificity of the Stability and Workload Index for Transfer scale as a criterion for discharge from the intensive care unit. METHODS: Adult, critical patients from intensive care units from two public hospitals in Porto Alegre, Brazil, comprised the sample. The patients' clinical and demographic characteristics were collected within 24 hours of admission. They were monitored until their final outcome on the intensive care unit (death or discharge) to apply the Stability and Workload Index for Transfer. The deaths during the first intensive care unit admission were disregarded, and we continued monitoring the other patients using the hospitals' electronic systems to identify the discharges, deaths, and readmissions. RESULTS: Readmission rates were 13.7% in intensive care unit 1 (medical-surgical, ICU1) and 9.3% in intensive care unit 2 (trauma and neurosurgery, ICU2). The death rate following discharge was 12.5% from ICU1 and 4.2% from ICU2. There was a statistically significant difference in Stability and Workload Index for Transfer (p<0.05) regarding the ICU1 patients' outcome, which was not found in the ICU2 patients. In ICU1, 46.5% (N=20) of patients were readmitted very early (within 48 hours of discharge). Mortality was high among those readmitted: 69.7% in ICU1 and 48.5% in ICU2. CONCLUSIONS: The Stability and Workload Index for Transfer scale showed greater efficacy in identifying patients more prone to readmission and death following discharge from a medical-surgical intensive care unit. The patients' intensive care unit readmission during the same hospitalization resulted in increased morbidity, mortality, length of stay, and total costs.
Abstract
Rev Bras Ter Intensiva. 2009;21(4):353-358
DOI 10.1590/S0103-507X2009000400004
OBJECTIVE: To predict readmission in intensive care unit analyzing the first 24 hours data after intensive care unit admission. METHODS: The first intensive care unit admission of patients was analyzed from January to May 2009 in a mixed unit. Readmission to the unit was considered those during the same hospital stay or within 3 months after intensive care unit discharge. Deaths during the first admission were excluded. Demographic data, use of mechanical ventilation, and report of stay longer than 3 days were submitted to uni and multivariate analysis for readmission. RESULTS: Five hundred seventy-seven patients were included (33 excluded deaths). The readmission group had 59 patients, while 518 patients were not readmitted. The lead time between the index admission and readmission was 9 (3-28) days (18 were readmitted in less than 3 days), and 10 died. Patients readmitted at least once to the intensive care unit had the differences below in comparison to the control group: older age: 75 (67-81) versus 67 (56-78) years, P<0.01; admission for respiratory insufficiency or sepsis: 33 versus 13%, P<0.01; medical admission: 49 versus 32%, P<0.05; higher SAPS II score: 27 (21-35) versus 23 (18-29) points, P<0.01; Charlson index: 2 (1-2) versus 1 (0-2) points, P<0.01; first ICU stay longer than 3 days: 35 versus 23%, P<0.01. After logistic regression, higher age, Charlson index and admission for respiratory and sepsis were independently associated to readmissions in intensive care unit. CONCLUSION: Age, comorbidities and respiratory- and/or sepsis-related admission are associated with increased readmission risk in the studied sample.
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