A case-control study of readmission to the intensive care unit after cardiac surgery

Perioperative Risk Factors for Intensive Care Unit Readmissions and Mortality After Cardiac Surgery

OBJECTIVE

The aim of this study was to identify perioperative risk factors associated with intensive care unit readmission and in-hospital death after cardiac surgery.

DESIGN

Retrospective analysis using a multivariate regression model to identify independent risk factors for intensive care unit [ICU] readmission and in-hospital mortality.

SETTING

The study was carried out in a single tertiary-care hospital.

PARTICIPANTS

This was an analysis of 2,789 adult patients.

INTERVENTIONS

All patients underwent cardiac surgery and were admitted to the intensive care unit perioperatively at the General Hospital Vienna.

MEASUREMENTS AND MAIN RESULTS

Among the 2,789 patients included in the analysis, 167 (6%) were readmitted to the intensive care unit during the same hospital stay. Preoperative risk factors associated with ICU readmission included end-stage renal failure (odds ratio [OR] 2.80, 95% CI: 1.126-6.964), arrhythmia (OR 1.59, 95% CI: 1.019-2.480), chronic obstructive pulmonary disease (OR 1.51, 95% CI: 1.018-2.237), age >80 (OR 2.55, 95% CI: 1.189-5.466), and European System for Cardiac Operative Risk Evaluation II >8 (OR 1.40, 95% CI: 1.013-1.940). Readmitted patients were more likely to die than nonreadmitted patients (OR 5.3, 95% CI: 3.284-8.558). In-hospital mortality in readmitted patients was 19.2%, whereas that in the nonreadmitted study population was 5.1%.

CONCLUSION

Preoperative risk assessment is crucial for identifying cardiac surgery patients at risk of ICU readmission and in-hospital death. The potentially modifiable risk factors pinpointed by this study call for the optimization of care before surgery and after ICU discharge.

Serum creatinine as a predictor of mortality in patients readmitted to the intensive care unit after cardiac surgery: a retrospective cohort study in China

BACKGROUND

Patients readmitted to the intensive care unit (ICU) after cardiac surgery have a high mortality rate. The relationship between renal function and in-hospital mortality in readmitted patients has not been well demonstrated.

METHODS

We retrospectively evaluated cardiac surgery patients who were readmitted to the ICU at least once. Data on serum creatinine levels before surgery and on the day of ICU readmission were collected. The estimated glomerular filtration rate (eGFR) was calculated according to the creatinine-based Chronic Kidney Disease-Epidemiology Collaboration equation. We used logistic regression models and restricted cubic spline curves with four knots (5%, 35%, 65%, 95%) to investigate the relationship between renal function indicators and mortality.

RESULTS

Of the 184 patients evaluated, 30 patients died during hospitalization, yielding a mortality rate of 16.30%. Cardiac dysfunction (n=84, 45.65%) and respiration disorder (n=51, 27.72%) were the most common reasons for ICU readmission. Creatinine [odds ratio (OR): 1.14, 95% confidence interval (CI): 1.07-1.25] and eGFR (OR: 0.95, 95% CI: 0.93-0.98) were independently associated with in-hospital mortality after adjusting for various confounders. Both creatinine level and eGFR had a linear association with in-hospital mortality (P for non-linearity ˃0.05).

CONCLUSION

Renal function is significantly associated with the in-hospital mortality of patients readmitted to the ICU after cardiac surgery, as evidenced by the independent correlation of both creatinine and eGFR with in-hospital mortality.

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

Objective

To evaluate the frequency, causes, and related predictive factors of intensive care unit (ICU) readmissions after coronary artery bypass grafting (CABG) surgery.

Methods

A 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.

Results

The 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.

Conclusion

ICU 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.

Identification and Estimation of Causal Effects Defined by Shift Interventions

Causal inference quantifies cause effect relationships by means of counterfactual responses had some variable been artificially set to a constant. A more refined notion of manipulation, where a variable is artificially set to a fixed function of its natural value is also of interest in particular domains. Examples include increases in financial aid, changes in drug dosing, and modifying length of stay in a hospital. We define counterfactual responses to manipulations of this type, which we call shift interventions. We show that in the presence of multiple variables being manipulated, two types of shift interventions are possible. Shift interventions on the treated (SITs) are defined with respect to natural values, and are connected to effects of treatment on the treated. Shift interventions as policies (SIPs) are defined recursively with respect to values of responses to prior shift interventions, and are connected to dynamic treatment regimes. We give sound and complete identification algorithms for both types of shift interventions, and derive efficient semi-parametric estimators for the mean response to a shift intervention in a special case motivated by a healthcare problem. Finally, we demonstrate the utility of our method by using an electronic health record dataset to estimate the effect of extending the length of stay in the intensive care unit (ICU) in a hospital by an extra day on patient ICU readmission probability.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Impact of Obesity on Intensive Care Unit Resource Utilization After Cardiac Operations

BACKGROUND

Much has been published about the effect of obesity on adverse outcomes after cardiac operations, yet little is known regarding the effect of obesity on intensive care unit (ICU) resource utilization. This study examined the effect of obesity on ICU resource utilization after cardiac operations.

METHODS

All patients with a body mass index (BMI) of 18.5 kg/m² or higher who underwent a cardiac surgical procedure between 2006 and 2013 were stratified into the following weight categories: normal (BMI 18.5 to 24.99 kg/m²), preobese (BMI 25 to 29.99 kg/m²), obese class I (BMI 30 to 34.99 kg/m²), obese class II (BMI 35 to 39.99 kg/m²), and obese class III (BMI ≥40 kg/m²). Comparisons between weight categories were done, and the risk-adjusted effect of weight category on prolonged ICU stay, prolonged ventilation, and ICU readmission was determined.

RESULTS

Of the 5,365 included patients, 1,948 were obese. Patients with greater obesity experienced longer ICU time, longer ventilation time, and increased ICU readmission. After adjustment, increasing obesity remained independently associated with greater likelihood of prolonged ICU stay (obese class II: odds ratio [OR], 2.4; 95% confidence interval [CI], 1.55 to 3.61; obese class III: OR, 4.1; 95% CI, 2.38 to 7.05), prolonged ventilation (obese class III: OR, 3.4; 95% CI, 1.57 to 7.22), and ICU readmission (obese class II: OR, 3.0; 95% CI, 1.70 to 5.31; obese class III: OR, 2.9; 95% CI, 1.32 to 6.36).

CONCLUSIONS

Increasing obesity was associated with a significant increase in ICU resource utilization after cardiac operations. Further study is needed to determine the mechanisms underlying this association and how the adverse effects of obesity may be mitigated.

Prognostic value of procalcitonin in patients after elective cardiac surgery: a prospective cohort study

Background

Procalcitonin (PCT) is a well-known prognostic marker after elective cardiac surgery. However, the impact of elevated PCT in patients with an initially uneventful postoperative course is still unclear. The aim of this study was to evaluate PCT levels as a prognostic tool for delayed complications after elective cardiac surgery.

Methods

A prospective study was performed in 751 patients with an apparently uneventful postoperative course within the first 24 h after elective cardiac surgery. Serum PCT concentration was taken the morning after surgery. All patients were screened for the occurrence of delayed complications. Delayed complications were defined by in-hospital death, intensive care unit readmission, or prolonged length of hospital stay (>12 days). Odds ratios (OR) [with 95% confidence interval (CI)] were calculated by logistic regression analyses and adjusted for confounders. Predictive capacity of PCT for delayed complications was calculated by ROC analyses. The cutoff value of PCT was derived from the Youden Index calculation.

Results

Among 751 patients with an initially uneventful postoperative course, 117 patients developed delayed complications. Serum PCT levels the first postoperative day were significantly higher in these 117 patients (8.9 ng/ml) compared to the remaining 634 (0.9 ng/ml; p < 0.001). ROC analyses showed that PCT had a high accuracy to predict delayed complications (optimal cutoff value of 2.95 ng/ml, AUC of 0.90, sensitivity 73% and specificity 97%). Patients with PCT levels above 2.95 ng/ml the first postoperative day had a highly increased risk of delayed complications (adjusted OR, 110.2; 95% CI 51.5–235.5; p < 0.001).

Conclusions

A single measurement of PCT seems to be a useful tool to identify patients at risk of delayed complications despite an initially uneventful postoperative course.

Risk Factors and Outcomes Associated With Readmission to the Intensive Care Unit After Cardiac Surgery

Unplanned readmission to the intensive care unit (ICU) is associated with poor prognosis, longer hospital stay, increased costs, and higher mortality rate. In this retrospective study, involving 1368 patients, the risk factors for and outcomes of ICU readmission after cardiac surgery were analyzed. The readmission rate was 5.9%, and the most common reason for readmission was cardiac issues. Preoperative risk factors were comorbid conditions, mechanical ventilation, and admission route. Perioperative risk factors were nonelective surgery, duration of cardiopulmonary bypass, and longer operation time. Postoperative risk factors were prolonged mechanical ventilation time, new-onset arrhythmia, unplanned reoperation, massive blood transfusion, prolonged inotropic infusions, and complications. Other factors were high blood glucose level, hemoglobin level, and score on the Acute Physiology and Chronic Health Evaluation II. In-hospital stay was longer and late mortality was higher in the readmitted group. These data could help clinical practitioners create improved ICU discharge protocols or treatment algorithms to reduce length of stay or to reduce readmissions.

Combination of European System for Cardiac Operative Risk Evaluation (EuroSCORE) and Cardiac Surgery Score (CASUS) to Improve Outcome Prediction in Cardiac Surgery

Background

We hypothesized that the combination of a preoperative and a postoperative scoring system would improve the accuracy of mortality prediction and therefore combined the preoperative ‘additive EuroSCORE‘ (European system for cardiac operative risk evaluation) with the postoperative ‘additive CASUS’ (Cardiac Surgery Score) to form the ‘modified CASUS’.

Material/Methods

We included all consecutive adult patients after cardiac surgery during January 2007 and December 2010 in our prospective study. Our single-centre study was conducted in a German general referral university hospital. The original additive and the ‘modified CASUS’ were tested using calibration and discrimination statistics. We compared the area under the curve (AUC) of the receiver characteristic curves (ROC) by DeLong’s method and calculated overall correct classification (OCC) values.

Results

The mean age among the total of 5207 patients was 67.2±10.9 years. Whilst the ICU mortality was 5.9% we observed a mean length of ICU stay of 4.6±7.0 days. Both models demonstrated excellent discriminatory power (mean AUC of ‘modified CASUS’: ≥0.929; ‘additive CASUS’: ≥0.920), with no significant differences according to DeLong. Neither model showed a significant p-value (<0.05) in calibration. We detected the best OCC during the 2^nd day (modified: 96.5%; original: 96.6%).

Conclusions

Our ‘additive’ and ‘modified’ CASUS are reasonable overall predictors. We could not detect any improvement in the accuracy of mortality prediction in cardiac surgery by combining a preoperative and a postoperative scoring system. A separate calculation of the two individual elements is therefore recommended.

Inclusion of 'ICU-Day' in a Logistic Scoring System Improves Mortality Prediction in Cardiac Surgery

Background

Prolonged intensive care unit (ICU) stay is a predictor of mortality. The length of ICU stay has never been considered as a variable in an additive scoring system. How could this variable be integrated into a scoring system? Does this integration improve mortality prediction?

Material/Methods

The ‘modified CArdiac SUrgery Score’ (CASUS) was generated by implementing the length of stay as a new variable to the ‘additive CASUS’. The ‘logistic CASUS’ already considers this variable. We defined outcome as ICU mortality and statistically compared the three CASUS models. Discrimination, comparison of receiver operating characteristic curves (DeLong’s method), and calibration (observed/expected ratio) were analyzed on days 1–13.

Results

Between 2007 and 2010, we included 5207 cardiac surgery patients in this prospective study. The mean age was 67.2±10.9 years. The mean length of ICU stay was 4.6±7.0 days and ICU mortality was 5.9%. All scores had good discrimination, with a mean area under the curve of 0.883 for the additive and modified, and 0.895 for the ‘logistic CASUS’. DeLong analysis showed superiority in favor of the logistic model as from day 5. The calibration of the logistic model was good. We identified overestimation (days 1–5) and accurate (days 6–9) calibration for the additive and ‘modified CASUS’. The ‘modified CASUS’ remained accurate but the ‘additive CASUS’ tended to underestimate the risk of mortality (days 10–13).

Conclusions

The integration of length of ICU stay as a variable improves mortality prediction significantly. An ‘ICU-day’ variable should be included into a logistic but not an additive model.

Improving clinical handover between intensive care unit and general ward professionals at intensive care unit discharge

Purpose

To systematically review and evaluate the effectiveness of interventions in order to improve the safety and efficiency of patient handover between intensive care unit (ICU) and general ward healthcare professionals at ICU discharge.

Methods

PubMed, CINAHL, PsycINFO, EMBASE, Web of Science, and the Cochrane Library were searched for intervention studies with the aim to improve clinical handover between ICU and general ward healthcare professionals that had been published up to and including June 2013. The methods for article inclusion and data analysis were pre-specified and aligned with recommendations outlined in the PRISMA guideline. Two reviewers independently extracted data (study purpose, setting, population, method of sampling, sample size, intervention characteristics, outcome, and implementation activities) and assessed the quality of the included studies.

Results

From the 6,591 citations initially extracted from the six databases, we included 11 studies in this review. Of these, six (55 %) reported statistically significant effects. Effective interventions included liaison nurses to improve communication and coordination of care and forms to facilitate timely, complete and accurate handover information. Effective interventions resulted in improved continuity of care (e.g., reduced discharge delay) and in reduced adverse events. Inconsistent effects were observed for use of care, namely, reduction of length of stay versus increase of readmissions to higher care. No statistically significant effects were found in the reduction of mortality. The overall methodological quality of the 11 studies reviewed was relatively low, with an average score of 4.5 out of 11 points.

Conclusions

This review shows that liaison nurses and handover forms are promising interventions to improve the quality of patient handover between the ICU and general ward. More robust evidence is needed on the effectiveness of interventions aiming to improve ICU handover and supportive implementation strategies.

Electronic supplementary material

The online version of this article (doi:10.1007/s00134-015-3666-8) contains supplementary material, which is available to authorized users.

Experiences of Slovene ICU physicians with end-of-life decision making: a nation-wide survey

Background

Advances in intensive care medicine have enormously improved ability to successfully treat seriously ill patients. However, intensive treatment and prolongation of life is not always in the patient’s best interest, and many ethical dilemmas arise in end-of-life (EOL) situations. We aimed to assess intensive care unit (ICU) physicians’ experiences with EOL decision making and to compare the responses according to ICU type.

Material/Methods

A cross-sectional survey was performed in all 35 Slovene ICUs, using a questionnaire designed to assess ICU physician experiences with EOL decision making, focusing on limitations of life-sustaining treatments (LST).

Results

We distributed 370 questionnaires (approximating the number of Slovene ICU physicians) and 267 were returned (72% response rate). The great majority of ICU physicians reported using do-not-resuscitate (DNR) orders (97%), withholding LST (94%), and withdrawing antibiotics (86%) or inotropes (95%). Fewer ICU physicians reported withdrawing mechanical ventilation (52%) or extubating patients (27%). Hydration was reported to be only rarely terminated (76% of participants reported never terminating it). In addition, 63% of participants had never encountered advance directives, and 39% reported to “never” or “rarely” participating in decision making with relatives of patients. Nurses were reported to be “never” or “rarely” involved in the EOL decision making process by 84% of participants.

Conclusions

Limitation of LST was regularly used by Slovene ICU physicians. DNR orders and withholding of LST were the most commonly used measures. Hydration was only rarely terminated. In addition, use of advance directives was almost non-existent in practice, and the patients’ relatives and nurses only infrequently participated in the decision making.

Readmission To Intensive Care Unit After Coronary Bypass Operations in the Short Term

OBJECTIVE

Intensive care unit (ICU) readmissions after coronary bypass (CABG) operations occur in a significant number of patients, and the prognosis is poor. We analyzed the risk factors for ICU readmissions after CABG operations.

METHODS

We retrospectively analyzed the prospectively collected data of 679 coronary bypass patients operated in a single institution in order to evaluate the risk factors for readmittance to the ICU with logistic regression analysis. The outcome results of patients readmitted to the ICU (Group R) and others (Group N) were compared.

RESULTS

Thirty-six (5.3%) patients were readmitted to the ICU. Postoperative in-hospital mortality and pulmonary and neurologic morbidity occurred in 43 (6.3%), 135 (19.9%), and 46 (6.8%) patients, respectively. The comparison of groups showed that mortality and morbidity were significantly higher in Group R compared to Group N (mortality 16.7% vs. 5.9, p=0.029; pulmonary morbidity 66.7% vs. 17.3%, p=0.0001; neurologic morbidity 38.9% vs. 5.0%, p=0.0001). Features associated with readmission included presence of left ventricular dysfunction preoperatively[odds ratio (OR)=4.1; 95% confidence interval (CI)=1.4-12.5; p=0.013], advanced NYHA Class (OR=5.3; 95% CI=1.3-21.7; p=0.022), pulmonary complications (OR=7.3; 95% CI=2.1-25.5; p=0.002), and neurologic complications (OR=4.6; 95% CI=1.3-16.7; p=0.021).

CONCLUSION

Patients readmitted to the ICU postoperatively have higher rates of mortality and pulmonary and neurologic morbidity after coronary bypass operations. Left ventricular dysfunction, advanced NYHA class, and postoperative pulmonary and neurologic complications are significant risk factors for readmission to the ICU.

Self-reported physical activity and lung function two months after cardiac surgery--a prospective cohort study

BACKGROUND

Physical activity has well-established positive health-related effects. Sedentary behaviour has been associated with postoperative complications and mortality after cardiac surgery. Patients undergoing cardiac surgery often suffer from impaired lung function postoperatively. The association between physical activity and lung function in cardiac surgery patients has not previously been reported.

METHODS

Patients undergoing cardiac surgery were followed up two months postoperatively. Physical activity was assessed on a four-category scale (sedentary, moderate activity, moderate regular exercise, and regular activity and exercise), modified from the Swedish National Institute of Public Health's national survey. Formal lung function testing was performed preoperatively and two months postoperatively.

RESULTS

The sample included 283 patients (82% male). Two months after surgery, the level of physical activity had increased (p < 0.001) in the whole sample. Patients who remained active or increased their level of physical activity had significantly better recovery of lung function than patients who remained sedentary or had decreased their level of activity postoperatively in terms of vital capacity (94 ± 11% of preoperative value vs. 91 ± 9%; p = 0.03), inspiratory capacity (94 ± 14% vs. 88 ± 19%; p = 0.008), and total lung capacity (96 ± 11% vs. 90 ± 11%; p = 0.01).

CONCLUSIONS

An increased level of physical activity, compared to preoperative level, was reported as early as two months after surgery. Our data shows that there could be a significant association between physical activity and recovery of lung function after cardiac surgery. The relationship between objectively measured physical activity and postoperative pulmonary recovery needs to be further examined to verify these results.

Incidence and predictors of readmission to the cardiac surgery intensive care unit: A retrospective cohort study in Greece

INTRODUCTION:

Readmission in the intensive care unit (ICU) is a significant morbidity index, which has been related to poor patient outcomes

AIM:

To identify the preoperative and intraoperative risk factors for readmission in the cardiac surgery ICU.

METHODS:

We conducted a retrospective cohort study of 595 consecutive patients who were admitted to the cardiac surgery ICU of a tertiary hospital of Athens — Greece during the one-year period (September 2011-September 2012). Data collection was carried out, retrospectively, by the use of a short questionnaire and based on the review of medical and nursing patient records at December 2012.

RESULTS:

The incidence of ICU readmission was 3.7% (22/595). Respiratory disorders were the main reason for readmission (45.4%). Readmitted patients had a significantly higher in-hospital mortality compared to those requiring no readmission (P < 0.001). Multivariate analysis revealed that female gender [for males odds ratio (OR) 0.37, 95% confidence interval (CI) 0.15-0.89], high logistic EuroSCORE (OR 1.02, 95% CI 1.00-1.04), prolonged cardiopulmonary (CPB) duration (OR 1.01, 95% CI 1.00-1.02) and preoperative renal failure (OR 1.02, 95% CI 1.00-1.05) were the independent risk factors for readmission to the cardiac surgery ICU.

CONCLUSIONS:

One intraoperative and three preoperative variables are associated strongly with higher probability for ICU readmission. Shorter CPB duration could contribute to lower ICU readmission incidence. In addition, the early identification of high risk patients for readmission in the cardiac surgery ICU could encourage both the more efficient healthcare planning and resources allocation.