Unit Readmission Research Articles

Risk Factors of Readmission to Pediatric Intensive Care Unit Within 1 Year: A Case-Control Study.

BackgroundResearch on pediatric intensive care unit (PICU) readmission is lacking in China. This study was conducted to describe the risk factors associated with PICU readmission within 1 year after PICU discharge.MethodsThis retrospective case-control study included patients aged from 1 month to 16 years who were discharged between January 2018 and May 2020. The case group included readmitted patients with two or more PICU admissions within 1 year during the study period. The control group included survivors with only one PICU admission during the same study period, and the controls were matched on age and sex. Demographic and clinical variables were collected from the electronic administrative database. Risk factors were analyzed by univariate and multivariate analyses.ResultsFrom January 2018 to May 2020, 2,529 patients were discharged from the PICU, and 103 (4.07%) were readmitted within 1 year. In the univariate analysis, PICU readmission within 1 year was associated with lower weight, the presence of chronic conditions, a higher StrongKids score on admission, length of PICU stay of more than 2 weeks, the presence of dysfunction at discharge, sedation medications use, vasopressor use, and invasive mechanical ventilation in the first PICU stay. Patients had a higher StrongKids score as a surrogate for increased risk of malnutrition. In the multivariate analysis, the factors most significantly associated with PICU readmission within 1 year were the presence of chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks in the first PICU stay. In the subgroup analysis, compared with the control group, the factors most significantly associated with readmission within 48 h of discharge were the presence of chronic conditions, a higher StrongKids score on admission, and vasopressor use during the first PICU stay. The mortality rate was 8.74% (9/103) in patients with PICU readmission. The overall PICU mortality rate was 7.39% (201/2,721) during the study period.ConclusionsPatients with chronic conditions, a higher StrongKids score on admission, and length of PICU stay of more than 2 weeks were at much higher risk for PICU readmission within 1 year. Patients with vasopressor use during the first PICU hospitalization were more likely to be readmitted within 48 h of discharge.

Prediction of unplanned 30-day readmission for ICU patients with heart failure

BackgroundIntensive Care Unit (ICU) readmissions in patients with heart failure (HF) result in a significant risk of death and financial burden for patients and healthcare systems. Prediction of at-risk patients for readmission allows for targeted interventions that reduce morbidity and mortality.Methods and resultsWe presented a process mining/deep learning approach for the prediction of unplanned 30-day readmission of ICU patients with HF. A patient’s health records can be understood as a sequence of observations called event logs; used to discover a process model. Time information was extracted using the DREAM (Decay Replay Mining) algorithm. Demographic information and severity scores upon admission were then combined with the time information and fed to a neural network (NN) model to further enhance the prediction efficiency. Additionally, several machine learning (ML) algorithms were developed to be used as the baseline models for the comparison of the results.ResultsBy using the Medical Information Mart for Intensive Care III (MIMIC-III) dataset of 3411 ICU patients with HF, our proposed model yielded an area under the receiver operating characteristics (AUROC) of 0.930, 95% confidence interval of [0.898–0.960], the precision of 0.886, sensitivity of 0.805, accuracy of 0.841, and F-score of 0.800 which were far better than the results of the best baseline model and the existing literature.ConclusionsThe proposed approach was capable of modeling the time-related variables and incorporating the medical history of patients from prior hospital visits for prediction. Thus, our approach significantly improved the outcome prediction compared to that of other ML-based models and health calculators.

130 SEVERITY OF ANASTOMOTIC LEAKAGE AFTER DIFFERENT TYPES OF ESOPHAGECTOMY: A NATIONWIDE COHORT STUDY

Abstract Orringer, McKeown and Ivor Lewis esophagectomy are the most commonly performed procedures for esophageal and gastro-esophageal junction cancer. Anastomotic leakage remains a major problem after all types of esophagectomy and it is currently unknown whether anastomotic leakage severity is different between the types of esophagectomy. The aim of this study was to investigate the relationship between surgical techniques and the severity of anastomotic leakage in patients after Orringer esophagectomy, McKeown esophagectomy or Ivor Lewis esophagectomy. Methods All esophageal and gastro-esophageal junction cancer patients with anastomotic leakage after Orringer, McKeown or Ivor Lewis esophagectomy between 2011 and 2019 were selected from the Dutch Upper Gastrointestinal Cancer Audit (DUCA). The primary outcome parameter was a composite endpoint of reoperation, intensive care unit (ICU) readmission and 30-day/in-hospital mortality. Secondary outcome parameters included postoperative complications, re-intervention rate, ICU and hospital length of stay. Results Data from 1034 patients with anastomotic leakage after Orringer (n = 287), McKeown (n = 397) and Ivor Lewis esophagectomy (n = 346) were evaluated. The primary endpoint occurred in 36.3% of patients with anastomotic leakage after Orringer esophagectomy, in 55.4% of patients with anastomotic leakage after McKeown esophagectomy and in 61.2% of patients with anastomotic leakage after Ivor Lewis esophagectomy (p < 0.001). When adjusting for potential confounding variables, the sequelae of anastomotic leakage after Orringer and McKeown esophagectomy remained less severe compared to anastomotic leakage after Ivor Lewis esophagectomy (OR 0.28, 95% CI 0.20–0.41, p < 0.001 and OR 0.71, 95% CI 0.52–0.97, p = 0.031, respectively). Conclusion Consequences of anastomotic leakage are most severe after Ivor Lewis esophagectomy, moderately severe after McKeown esophagectomy and least severe after Orringer esophagectomy. This study demonstrated that not only the incidence, but also the severity of anastomotic leakage should be considered in current clinical practice and in studies that compare leakage rates between different surgical techniques of esophagectomy.

For adults with a range of internal medicine diseases and conditions, how does admission to a short-stay unit impact mortality, re-admission, and serious adverse events?

For adults with a range of internal medicine diseases and conditions, how does admission to a short-stay unit impact mortality, re-admission, and serious adverse events?

Comorbidities and Readmissions in Survivors of Acute Hypercapnic Respiratory Failure.

Chronic obstructive pulmonary disease (COPD) is defined by chronic airflow obstruction, but is presently considered as a complex, heterogeneous, and multicomponent disease in which comorbidities and extrapulmonary manifestations make important contributions to disease expression. COPD-related hospital readmission. In particular frequent intensive care unit (ICU) readmissions for exacerbations represent a major challenge and place a high burden on patient outcomes and health-related quality of life, as well as on the healthcare system.In this narrative review, we first address major and often undiagnosed comorbidities associated with COPD that could have an impact on hospital readmission after an index ICU admission for acute hypercapnic respiratory failure. Some guidance for treatment is discussed. Second, we present predictors of hospital and ICU readmission and discuss various strategies to reduce such events.There is a strong rationale to detect and treat major comorbidities early after index ICU admission for acute hypercapnic respiratory failure. It still remains unclear, however, if a comprehensive and holistic approach to comorbidities in frail patients surviving hypercapnic respiratory failure can efficiently reduce the readmission rate.

Risk Factors for Unplanned Admission to the Pediatric Intensive Care Unit in Pediatric Trauma Patients

Background and Hypothesis: A number of risk factors for unplanned pediatric intensive care unit (PICU) admission and readmission have been identified. However, little is known of the risk factors associated with unplanned admission to the PICU in pediatric trauma populations. We hypothesize specific risk factors can be identified which may be associated with unplanned admission to the PICU following traumatic injury.
 Methods: For this national retrospective study, we queried the 2016 National Trauma Data Bank for patients younger than 18 years experiencing a traumatic injury requiring hospital admission from the Emergency Department (ED). We excluded patients who had experienced burn injuries. Statistically significant (p<.05) risk factors for unplanned PICU admission were identified in bivariate analysis and used to build a multiple logistic regression model.
 Results: Patients experiencing unplanned admission to the PICU had lower ED Glasgow Coma Scale (11.83 vs. 14.31; p<0.001), higher Injury Severity Scores (ISS) (17.96 vs. 7.32; p<0.001), and were older (age 11.35 vs. 9.60; p<0.001). Initial ED disposition to the PICU was significantly associated with unplanned admission to the PICU (p<0.001). Initial ED disposition to the OR was significantly associated with unplanned admission to the PICU (p=.018). After multiple logistic regression, ISS (p<0.001), initial ED disposition to the PICU (p=0.002), initial ED disposition to the OR (p=0.005), and older age (p=0.005) remained statistically significant risk factors for unplanned admission to the PICU.
 Conclusion: ISS and ED disposition to the PICU, OR disposition to the PICU and age are significant risk factors for unplanned admission to the PICU in pediatric trauma. These findings will assist in identifying patients at risk for unplanned admission to the PICU, thereby reducing the adverse effects of unplanned PICU admission and ultimately improving the quality of care for pediatric trauma populations.

Identifying the relationship between unstable vital signs and intensive care unit (ICU) readmissions: an analysis of 10-year of hospital ICU readmissions

Advanced healthcare information systems capture extensive electronic healthcare records (EHR) to provide accurate healthcare delivery and make informed clinical and management decisions. EHR also include records of Intensive Care Unit (ICU) admissions, discharges, readmissions and more. This study aims to investigate trends and patterns from electronically recorded vital signs and identify the relationship between vital signs and ICU readmissions. After appropriate ethics approvals and permissions, we obtained access to the MIMIC-III dataset. A total of 150 patient data has been selected from the MIMIC-III dataset to evaluate the vital signs patterns, which included heart rate, respiratory rate, temperature for patients admitted twice in the ICU. Statistical analysis was conducted to identify the key patterns associated with the vital signs of the selected patient samples. The study findings indicate that the mean value of heart rate and respiratory rate was within the normal range for all incidents. However, there was a small difference between the readmission-day of the vital signs compared with the previous admission recordings. The finding also suggests that hospital length of stay (LOS) for patients was high for the second admission compared to the first admission. We identified a key relationship between the vital signs and ICU readmissions, it is evident that discharges with unstable vitals are directly linked to readmissions. Additionally, it is also observed that the LOS varies depending on the stability of the vital signs. In future, a larger sample with more variables are required, such as modifiable (medications, procedures, room temperature, discharge time) and non-modifiable (age, ethnicity, family history) which could explain the significance of longer LOS and its impact on patient-condition, readmission and mortality rate.

Propensity analysis of outcome in coronary artery bypass graft surgery patients >75 years old

We looked at the complications and hospital resources of an elderly population undergoing first-time isolated coronary artery bypass graft surgery (CABG) in comparison to a younger counterpart for a propensity matched cohort. A retrospective analysis of prospectively collected data was conducted on 2804 CABG patients. Two age groups, >75 years and ≤75 years, were generated. Potential differences in demographic, baseline, preoperative, and intraoperative characteristics were investigated. A propensity score based on these differences was calculated and used to create a matched set of patients. Major postoperative complications were recorded, and data on indicators of resource utilization were collected. In all, 311 (11.1%) patients were identified as >75 years of age. The observed complication rate was significantly higher in overall, pulmonary, cardiac, renal, gastrointestinal (GI), neurological, infective, and mortality categories (P < 0.0001). Observed hospital resource utilization was significant in the elderly group in terms of initial stay in the intensive care unit (ICU) and ICU readmission (P < 0.05) and in all preoperative, postoperative, cardiac surgery, and total hospital stays (P < 0.001). However, after propensity matching to 311 patients ≤75 years, the overall postoperative complication rate maintained its significance (P < 0.0001), in addition to atrial fibrillation and neurological, renal, and GI complications (P < 0.05). Elderly patients required longer duration of ventilation postoperatively and longer postoperative stay, cardiac surgery stay, and total hospital stay; and they maintained a higher surgical mortality rate (6.1% vs. 2.6%) (P < 0.05). Elderly patients undergoing CABG had significantly higher rates of postoperative complications. Their prolonged hospital stay and consequently higher resources utilization need to be adequately highlighted to heath care officials and appropriately addressed.

Mandatory checklists at discharge may have the potential to prevent readmissions

To the Editor:Recently in Critical Care Medicine, Chrusch et al (1) showed that intensive care unit (ICU) readmission or unexpected death after ICU discharge were not only dependent on age, particular diagnoses, Acute Physiology and Chronic Health Evaluation II score, and ICU length of stay but also