Risk Of Intensive Care Unit Readmission Research Articles

Role of Charlson comorbidity index in predicting intensive care unit readmission in patients with aortic aneurysm.

The purpose of this study was to investigate the value of the Charlson comorbidity index (CCI) in predicting intensive care unit (ICU) readmission in aortic aneurysm (AA) patients. Patient information came from the Medical Information Mart for Intensive Care- IV (MIMIC-IV) database. The relationship between CCI and ICU readmission was analyzed by restricted cubic spline, generalized linear regression, trend analysis, and hierarchical analysis. The clinical value of CCI in predicting ICU readmission was analyzed by receiver operating characteristic curve, decision curve analysis, XGBoost regression, and random forest regression. A total of 523 patients with AA were enrolled in the study. Patients with AA who were readmitted to the ICU had higher width of red blood cell distribution width (RDW) and higher CCI. CCI had better performance and clinical net benefit for predicting ICU readmission than RDW. An independent nonlinear relationship was found between CCI and ICU readmission. The trend analysis suggested that the risk of ICU readmission increased with higher CCI scores. The hierarchical analysis showed that their association was mainly found in surgery requirement populations regardless of AA types. Further, CCI was found to have better clinical value in predicting ICU readmission of thoracic aortic aneurysm (TAA) patients undergoing surgery. Age, renal disease, chronic lung disease, and dementia were important components of CCI in predicting ICU readmission of TAA patients undergoing surgery. CCI was independently associated with the ICU readmission of AA patients in a positive relationship and had more favorable prediction performance in TAA patients who underwent surgery.

Epidemiology and outcome of medical emergency team calls within 48 hours of intensive care unit discharge.

Some patients experience early (within 48 h) clinical deterioration and medical emergency team (MET) review following intensive care unit (ICU) discharge. Few studies have explored early MET review, despite it being a recognised quality and safety indicator. To evaluate the (i) proportion of patients discharged from ICU receiving MET review and timing of reviews; (ii) characteristics of patients who received early MET review and (iii) predictors of early MET review and associations with clinical outcomes. This is a retrospective observational study of ICU discharges over 2 years in a tertiary hospital and involves descriptive and inferential statistics, including logistic regression analysis. Of 3712 patients, 312 (8.4%) had an early MET review. Patients with cardiothoracic, cardiovascular, gastrointestinal and general surgical diagnoses, higher illness severity or who received invasive ventilation had a higher risk of early MET review. On multivariable analysis, early MET review was associated with an increased risk of ICU re-admission (odds ratio (OR) 6.76, 95% confidence interval (CI) 5.01-9.13, P < 0.001), in-hospital mortality (OR 3.62, 95% CI 2.19-5.99, P < 0.001) and discharge to a nursing home (OR 2.49, 95% CI 1.25-4.97, P = 0.01). Length of stay was longer in patients requiring early post-ICU MET review compared to those who did not (median 16 days vs. 10 days, P < 0.001). One in 12 patients received post-ICU early MET review. This was more likely in patients who were invasively ventilated, had higher illness severity and had certain admission diagnoses. Such patients were at risk for worse outcomes. There is a need to identify reversible factors contributing to such increased risk.

PREDICTING INTENSIVE CARE UNIT READMISSION AMONG PATIENTS AFTER LIVER TRANSPLANTATION USING MACHINE LEARNING

Intensive care unit (ICU) readmission of patients following liver transplantation (LT) is associated with poor outcomes. However, its risk factors remain unclarified. Nowadays, machine learning methods are widely used in many aspects of medical health. This study aims to develop a reliable prognostic model for ICU readmission for post-LT patients using machine learning methods. In this paper, a single center cohort ([Formula: see text]) was studied, of which 5.9% ([Formula: see text]) were readmitted to the ICU during hospitalization for LT. A retrospective review of baseline and perioperative factors possibly related to ICU readmission was performed. Three feature selection techniques were used to detect the best features influencing ICU readmission. Moreover, seven machine learning classifiers were proposed and compared to detect the risk of ICU readmission. Alanine transaminase (ALT) at hospital admission, intraoperative fresh frozen plasma (FFP) and red blood cell (RBC) transfusion, and N-Terminal pro-brain natriuretic peptide (NT-proBNP) after LT were found to be essential features for ICU readmission risk prediction. And the stacking model produced the best performance, identifying patients that were readmitted to the ICU after LT at an accuracy of 97.50%, precision of 96.34%, recall of 96.32%, and F1-score of 96.32%. RBC transfusion is the most crucial feature of the stacking classification model, which produced the best performance with overall accuracy, precision, recall, and F1-score of 88.49%, 88.66%, 76.01%, and 81.84%, respectively.

Epidemiology and Outcomes of Patients Readmitted to the Intensive Care Unit After Cardiac Intensive Care Unit Admission

Readmission to the intensive care unit (ICU) during the index hospitalization is associated with poor outcomes in medical or surgical ICU survivors. Little is known about critically ill patients with acute cardiovascular conditions cared for in a cardiac intensive care unit (CICU). We sought to describe the incidence, risk factors, and outcomes of all ICU readmissions in patients who survived to CICU discharge. We retrospectively reviewed Mayo Clinic patients from 2007 to 2015 who survived the index CICU admission and identified patients with a second ICU stay during their index hospitalization; these patients were categorized as ICU transfers (patients who went directly from the CICU to another ICU) or ICU readmissions (patients initially transferred from the CICU to the ward, and then back to an ICU). Among 9,434 CICU survivors (mean age 67 years), 138 patients (1.5%) had a second ICU stay during the index hospitalization: 60 ICU transfers (0.6%) and 78 ICU readmissions (0.8%). The most common indications for ICU readmission were respiratory failure and procedure/surgery. On multivariable modeling, respiratory failure, severe acute kidney injury, and Charlson Comorbidity Index at the time of discharge from the index ICU stay were associated with ICU readmission. Death during the first ICU readmission (n=78) occurred in 7.7% of patients. In-hospital mortality was higher for patients with a second ICU stay. In conclusion, few CICU survivors have a second ICU stay during their index hospitalization; these patients are at a higher risk of in-hospital and 1-year mortality. Respiratory failure, severe acute kidney injury, and higher co-morbidity burden identify CICU survivors at elevated risk of ICU readmission.

Risk factors for readmission to ICU and analysis of intra-hospital mortality

IntroductionCritical patients, despite initial recovery in the intensive care unit (ICU), may require readmission to the ICU or even die in the same hospital episode. The objectives are to determine the incidence and to identify risk factors for ICU readmission, and to determine hospital mortality. MethodsObservational cohort study of all patients admitted consecutively for more than 24 h to the ICU of the University Hospital of Getafe between April 1, 2018 and September 30, 2018 and discharged alive from their first ICU admission. ResultsOf the 164 patients alive at ICU discharge, 14 (8.5%) were readmitted to ICU (2.4% at ≤48 h). The adjusted risk of ICU readmission was higher in patients with disabling neurological deficits prior to ICU admission [odds ratio (OR) 7.96, 95% confidence interval (CI) 1.55–40.92] or who received vasoactive drugs (OR 5.07, 95% CI 1.41–18.29) during their ICU stay. Readmitted patients had higher hospital mortality (4 of 14 [29%] versus 5 of 150 [3%], P < 0.001) and longer hospital stay (74.5 [37.5−99.75] days versus 16 [9−34] days, median [interquartile range], P = 0.001). ConclusionsPatients with disabling neurological deficits prior to hospital admission or who received vasoactive drugs during their ICU stay have a higher risk of readmission to the ICU, which increases hospital stay and mortality.

Risk factors for intensive care unit readmission after lung transplantation: a retrospective cohort study.

Background Lung transplantation (LT) is an accepted therapeutic modality for end-stage lung disease patients. Intensive care unit (ICU) readmission is a risk factor for mortality after LT, for which consistent risk factors have not been elucidated. Thus, we investigated the risk factors for ICU readmission during index hospitalization after LT, particularly regarding the posttransplant condition of LT patients.Methods In this retrospective study, we investigated all adult patients undergoing LT between October 2012 and August 2017 at our institution. We collected perioperative data from electronic medical records such as demographics, comorbidities, laboratory findings, ICU readmission, and in-hospital mortality.Results We analyzed data for 130 patients. Thirty-two patients (24.6%) were readmitted to the ICU 47 times during index hospitalization. At the initial ICU discharge, the Sequential Organ Failure Assessment (SOFA) score (odds ratio [OR], 1.464; 95% confidence interval [CI], 1.083−1.978; P=0.013) and pH (OR, 0.884; 95% CI, 0.813−0.962; P=0.004; when the pH value increases by 0.01) were related to ICU readmission using multivariable regression analysis and were still significant after adjusting for confounding factors. Thirteen patients (10%) died during the hospitalization period, and the number of ICU readmissions was a significant risk factor for in-hospital mortality. The most common causes of ICU readmission and in-hospital mortality were infection-related.Conclusions The SOFA score and pH were associated with increased risk of ICU readmission. Early postoperative management of these factors and thorough posttransplantation infection control can reduce ICU readmission and improve the prognosis of LT patients.

Factores de riesgo de reingreso en UCI y análisis de la mortalidad intrahospitalaria

IntroductionCritical patients, despite initial recovery in the intensive care unit (ICU), may require readmission to the ICU or even die in the same hospital episode. The objectives are to determine the incidence and to identify risk factors for ICU readmission, and to determine hospital mortality. MethodsObservational cohort study of all patients admitted consecutively for more than 24hours to the ICU of the University Hospital of Getafe between April 1, 2018 and September 30, 2018 and discharged alive from their first ICU admission. ResultsOf the 164 patients alive at ICU discharge, 14 (8.5%) were readmitted to ICU (2.4% at≤48hours). The adjusted risk of ICU readmission was higher in patients with disabling neurological deficits prior to ICU admission [odds ratio (OR) 7.96, 95% confidence interval (CI) 1.55-40.92] or who received vasoactive drugs (OR 5.07, 95% CI 1.41-18.29) during their ICU stay. Readmitted patients had higher hospital mortality (4 of 14 [29%] versus 5 of 150 [3%], P<.001) and longer hospital stay (74.5 [37.5-99.75] days versus 16 [9-34] days, median [interquartile range], P=.001). ConclusionsPatients with disabling neurological deficits prior to hospital admission or who received vasoactive drugs during their ICU stay have a higher risk of readmission to the ICU, which increases hospital stay and mortality.

A Tool to Predict Readmission to the Intensive Care Unit in Surgical Critical Care Patients-The RISC Score.

Readmission to the Intensive Care Unit (ICU) is associated with a high risk of in-hospital mortality and higher health care costs. Previously published tools to predict ICU readmission in surgical ICU patients have important limitations that restrict their clinical implementation. We sought to develop a clinically intuitive score that can be implemented to predict readmission to the ICU after surgery or trauma. We designed the score to emphasize modifiable predictors. In this retrospective cohort study, we included surgical patients requiring critical care between June 2015 and January 2019 at Beth Israel Deaconess Medical Center, Harvard Medical School, MA, USA. We used logistic regression to fit a prognostic model for ICU readmission from a priori defined, widely available candidate predictors. The score performance was compared with existing prediction instruments. Of 7,126 patients, 168 (2.4%) were readmitted to the ICU during the same hospitalization. The final score included 8 variables addressing demographical factors, surgical factors, physiological parameters, ICU treatment and the acuity of illness. The maximum score achievable was 13 points. Potentially modifiable predictors included the inability to ambulate at ICU discharge, substantial positive fluid balance (>5 liters), severe anemia (hemoglobin <7 mg/dl), hyperglycemia (>180 mg/dl), and long ICU length of stay (>5 days). The score yielded an area under the receiver operating characteristic curve of 0.78 (95% CI 0.74-0.82) and significantly outperformed previously published scores. The performance of the underlying model was confirmed by leave-one-out cross-validation. The RISC-score is a clinically intuitive prediction instrument that helps identify surgical ICU patients at high risk for ICU readmission. The simplicity of the score facilitates its clinical implementation across surgical divisions.

Analysis of Readmissions to The Intensive Care Unit After Coronary Artery Bypass Surgery: Ten Years' Experience.

ObjectiveTo evaluate the frequency, causes, and related predictive factors of intensive care unit (ICU) readmissions after coronary artery bypass grafting (CABG) surgery.MethodsA total of 4112 consecutive patients who underwent on-pump CABG between January 2007 and January 2017 were retrospectively evaluated. The patients were divided into two groups as patients with and without ICU readmission. Demographic and perioperative characteristics were compared between the two groups.ResultsThe ICU readmission rate was 3.5%. The most common reasons for ICU readmissions were respiratory (29%) and cardiac (23.4%) complications. The 90-day mortality risk was significantly higher in the readmitted patients than the non-readmitted patients (22.1% and 1.6%, respectively; P<0.001; OR=17.6; 95% CI=11.19-28.41). Severe left ventricular dysfunction, chronic obstructive pulmonary disease, end-stage renal disease, emergency CABG, EuroSCORE II > 5%, cross-clamp time > 35 minutes, postoperative respiratory complications, neurological complications, and cardiac complications showed a strong association with ICU readmissions.ConclusionICU readmission after CABG is associated with an increased mortality rate. Evaluation, not only of patients’ comorbidities, but also of intraoperative conditions and postoperative complications, is important to identify patients at risk for ICU readmission.

Intensive Care Unit Readmission After Left Ventricular Assist Device Implantation: Causes, Associated Factors, and Association With Patient Mortality.

Previous studies on readmissions after left ventricular assist device (LVAD) implantation have focused on hospital readmissions after dismissal from the index hospitalization. Because few data exist, the purpose of this study was to examine intensive care unit (ICU) readmissions in patients during their initial hospitalization for LVAD implantation to determine reasons for, factors associated with, and incidence of mortality after ICU readmission. A retrospective analysis was performed from February 2007 to March 2015 of patients at our institution receiving first-time LVAD implantation. After LVAD implantation, patients dismissed from the ICU who then required ICU readmission before hospital dismissal were compared to those not requiring ICU readmission before hospital dismissal with respect to preoperative, intraoperative, and postoperative factors. Among 287 LVAD patients, 266 survived their initial ICU admission, of which 49 (18.4%) required ICU readmission. The most common reasons for readmission were bleeding and respiratory failure. Factors found to be univariably associated with ICU readmission were preoperative hemoglobin, preoperative aspartate aminotransferase, preoperative atrial fibrillation, preoperative dialysis, longer cardiopulmonary bypass times, and higher intraoperative allogeneic blood transfusion requirements. Multivariable analysis revealed ICU readmission to be independently associated with preoperative dialysis (odds ratio, 12.86; 95% confidence interval, 3.16-52.28; P < .001). Overall mortality at 1 year was 22.6%. Survival after hospital dismissal was worse for patients who required ICU readmission during the index hospitalization (adjusted hazard ratio, 2.35; 95% confidence interval, 1.15-4.81; P = .019). ICU readmission after LVAD implantation occurred relatively frequently and was significantly associated with 1-year mortality after hospital dismissal. These data can perhaps be used to identify subsets of LVAD patients at risk for ICU readmission and may lead to implementation of practice changes to mitigate ICU readmissions. Future larger and prospective studies are warranted.

The effect of early cardiopulmonary rehabilitation on the outcomes of intensive care unit survivors.

This study aims to compare the impact of early and late post-discharge cardiopulmonary rehabilitation on the outcomes of intensive care unit (ICU) survivors.The retrospective, cohort study used a sub-database of the Taiwan National Health Insurance Research Database (NHIRD) that contained information of all patients had ICU admission between 2000 and 2012. Early group was defined if patients had received cardiopulmonary rehabilitation within 30 days after ICU discharge, and late group was define as if patients had received cardiopulmonary rehabilitation between 30 days and 1 year after ICU discharge. The end points were mortality and re-admission during the 3-year follow-up.Among 2136 patients received cardiopulmonary rehabilitation after ICU discharge, 994 was classified early group and other 1142 patients were classified as late group. Overall, early group had a lower mortality rate (6.64% vs. 10.86%, P = .0006), and a lower ICU readmission rate (47.8% vs. 57.97%, P < 0.0001) than late group after 3-year follow-up. Kaplan-Meier analysis showed that early group had significantly lower mortality (P = .0009) and readmission rate (P < .0001) than late group. In multivariate analysis, the risk of ICU readmission was found to be independently associated with late group (hazard ratio, [HR], 1.28; 95% confidence intervals, [CI], 1.13–1.47).Early post-discharge cardiopulmonary rehabilitation among ICU survivors has the long-term survival benefit and significantly decreases the readmission rate.

Revised Acute Physiology and Chronic Health Evaluation score as a predictor of neurosurgery intensive care unit readmission: A case-controlled study

Purpose Patients with neurologic system problems are among the most common patients readmitted to the intensive care unit (ICU). Readmission predictors for neurologic ICU patients have not been established. Previous research suggests that the Revised Acute Physiology and Chronic Health Evaluation (APACHE II) score is one indication of the critical status of ICU-admitted patients; however, the ability of the discharge APACHE II to predict readmission to the ICU requires further study. The purpose of this study was to investigate the ability of the APACHE II scoring system to predict ICU readmission of neurosurgical and ICU patients. Materials and Methods A retrospective case-controlled comparison study and a review of patient records for all patients admitted to 8 ICUs from January 2003 to June 2005 (N = 753) were conducted. Readmitted neurosurgery ICU patients were matched with 58 randomly selected nonreadmitted patients. Results Nine variables were significantly different between the readmission and case-controlled group. The APACHE II discharge score was the only significant predictor and was able to predict 18.6% of neurologic ICU readmissions. The risk of ICU readmission increased when the APACHE II score at the time of discharge exceeded 8.5 points. Conclusions The risk of ICU readmission of neurologic ICU patients can be predicted by determining APACHE II score upon ICU discharge.