Intensive Care Unit Readmission Research Articles

Effect of Admission Day and Time on Patient Outcome: An Observational Study in Intensive Care Units of a Tertiary Care Hospital in India.

The current study aimed to assess any association between intensive care unit (ICU) and hospital outcomes with ICU admission timings of critically ill patients. Retrospective observational single-center study involving all adult admissions. Each patient admission was categorized in "after-hours" (08:00 p.m.-07:59 a.m.), or "normal-hours" (08:00 a.m.-07:59 p.m.), "Weekday" (Monday-Saturday), or "Weekend" (Sunday), "Same day" (admission directly to ICU) or "other day admission" (admission to ICU after a hospital stay of ≥24 hours). Intensive care unit and hospital mortality, length of stay (LOS), and ICU readmission were assessed for any association with different admission timings. Among 3,029 patients, 54.2% (1,668) were male, with mean age 66.49 (SD ± 15.69) years, mean acute physiology and chronic health evaluation-IV (APACHE-IV) score 55.5 (SD ± 26.3). Around 86.1% of admission occurred during weekdays, 13.9% on weekends, 57.4% normal-hours, 42.6% after-hours, 66.3% same day and 33.7% other day admission. Intensive care unit and hospital mortality were 10.8 and 14.2% respectively. Neither ICU nor hospital mortality were significantly different among patients admitted normal vs after-hours (p = 0.32, 0.23), and weekdays vs weekends (p = 0.09, 0.93), nor was ICU LOS (p = 0.21, 0.74). Intensive care unit and hospital mortality (p = 0.001), DORB (p = 0.001), hospital LOS (p = 0.001), and readmission to ICU (p = 0.001) were significantly higher in the other day admission group compared to same-day admission. In a multivariate regression analysis age, APACHE IV score along with other day admission to ICU did have a significant effect on both ICU and hospital mortality. Intensive care unit and hospital mortality and LOS did not differ significantly with hours or days of ICU admission though they were significantly higher in other day admission groups. Bhattacharyya M, Todi SK. Effect of Admission Day and Time on Patient Outcome: An Observational Study in Intensive Care Units of a Tertiary Care Hospital in India. Indian J Crit Care Med 2024;28(5):436-441.

Complementarity of nutrition screening with Global Leadership Initiative on Malnutrition criteria for diagnosing malnutrition in critically ill patients: A comparison study of Nutritional Risk Screening 2002 and modified Nutrition Risk in the Critically Ill Score.

Critical illness induces hypermetabolism and hypercatabolism, increasing nutrition risk (NR). Early NR identification is crucial for improving outcomes. We assessed four nutrition screening tools (NSTs) complementarity with the Global Leadership Initiative on Malnutrition (GLIM) criteria in critically ill patients. We conducted a comparative study using data from a cohort involving five intensive care units (ICUs), screening patients for NR using NRS-2002 and modified-NUTRIC tools, with three cutoffs (≥3, ≥4, ≥5), and malnutrition diagnosed by GLIM criteria. Our outcomes of interest included ICU and in-hospital mortality, ICU and hospital length of stay (LOS), and ICU readmission. We examined accuracy metrics and complementarity between NSTs and GLIM criteria about clinical outcomes through logistic regression and Cox regression. We established a four-category independent variable: NR(-)/GLIM(-) as the reference, NR(-)/GLIM(+), NR(+)/GLIM(-), and NR(+)/GLIM(+). Of the 377 patients analyzed (median age 64 years [interquartile range: 54-71] and 53.8% male), NR prevalence varied from 87% to 40.6%, whereas 64% presented malnutrition (GLIM criteria). NRS-2002 (score ≥4) showed superior accuracy for GLIM-based malnutrition. Multivariate analysis revealed mNUTRIC(+)/GLIM(+) increased >2 times in the likelihood of ICU and in-hospital mortality, ICU and hospital LOS, and ICU readmission compared with the reference group. No NST exhibited satisfactory complementarity to the GLIM criteria in our study, emphasizing the necessity for comprehensive nutrition assessment for all patients, irrespective of NR status. We recommend using mNUTRIC if the ICU team opts for nutrition screening, as it demonstrated superior prognostic value compared with NRS-2002, and applying GLIM criteria in all patients.

A retrospective chart analysis with 5-year follow-up of early care for geriatric hip fracture patients: why we should continue talking about hip fractures.

Timing of surgery remains a topic of debate for hip fracture treatment in the geriatric patient population. The quality indicator "early surgery" was implemented in 2014 at the Department of Trauma Surgery of the University Hospitals Leuven to enhance timely operative treatment. In this follow-up study, we aim to evaluate the performance of this quality indicator, the clinical outcomes, and room for improvement. The charts of 1190 patients surgically treated for an acute hip fracture were reviewed between June 2017 and May 2022 at the University Hospitals Leuven. Primary endpoints were adherence to early surgery, defined as surgery within the next calendar day, and the evaluation of the reasons for deviating from this protocol. Secondary endpoints were length of stay (LOS); intensive care unit (ICU) admission and length of ICU stay; mortality after 30days, 60days, 90days, and 6months; and 90-day readmission rate. Pearson's Chi-square test and Mann-Whitney U test were used for data analysis. One thousand eighty-four (91.1%) patients received early surgery versus 106 (8.9%) patients who received delayed surgery. The main reasons for surgical delay were the use of anticoagulants (33%), a general health condition not allowing safe surgery and/or existing comorbidities requiring workup prior to surgery (26.4%), and logistical reasons (17.9%). Patient delay and transfer from other hospitals were responsible for respectively 8.5% and 6.6% of delayed surgery. Early surgery resulted in a significantly shorter LOS and ICU stay (12 [8-25] vs. 18 [10-36] and 3 [2-6] vs. 7 [3-13] days, early vs. delayed surgery, respectively). No significant reduction was observed in ICU admission, mortality, and readmission rate. We have been able to maintain the early surgery hip fracture protocol in approximately 90% of the patients. Comorbidities and anticoagulant use were responsible for delayed surgery in the majority of the patients. Correct implementation of the existing protocol on anticoagulant use could lead to a one-third decrease in the number of delayed surgeries. Subsequently, since the LOS and ICU stay in the delayed surgery group were significantly longer, a further increase of early surgery will lower the current economic burden.

Early prediction of long hospital stay for Intensive Care units readmission patients using medication information

ObjectivePredicting Intensive Care Unit (ICU) Length of Stay (LOS) accurately can improve patient wellness, hospital operations, and the health system's financial status. This study focuses on predicting the prolonged ICU LOS (≥3 days) of the 2nd admission, utilizing short historical data (1st admission only) for early-stage prediction, as well as incorporating medication information. Materials and methodsWe selected 18,572 ICU patients’ records from the MIMIC-IV database for this study. We applied five machine learning classifiers: Logistic regression (LR), Random Forest (RF), Support Vector Machine (SVM), AdaBoost (AB) and XGBoost (XGB). We computed both the sum dose and the average dose for the medication and included them in our model. ResultsThe performance of the RF model demonstrates the highest level of accuracy compared to other models, as indicated by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.716 and an Expected Calibration Error (ECE) of 0.023. DiscussionThe calibration improved all five classifiers (LR, RF, SVC, AB, XGB) in terms of ECE. The most important two features for RF are the length of 1st admission and the patient's age when they visited the hospital. The most important medication features are Phytonadione and Metoprolol Succinate XL. Also, both the sum and the average dose for the medication features contributed to the prediction task. ConclusionOur model showed the capability to predict the prolonged ICU LOS of the 2nd admission by utilizing the demographic, diagnosis, and medication information from the 1st admission. This method can potentially support the prevention of patient complications and enhance resource allocation in hospitals.

Successful Implementation of Enhanced Recovery After Surgery (ERAS) in Paediatric Cardiac Surgery in Australia

Fast-track or enhanced recovery after surgery (ERAS) is a care pathway for surgical patients based on a multidisciplinary team approach aimed at optimising recovery without increasing risk with protocols based on scientific evidence, which is monitored continuously to ensure compliance and improvement. These protocols have been shown to reduce the duration of postoperative mechanical ventilation and intensive care unit (ICU) length of stay (LOS) following paediatric cardiac surgery. We present the first structured implementation of ERAS in paediatric cardiac surgery in Australia. All patients enrolled in the ERAS pathway between October 2019 and July 2023 were identified. Demographic and perioperative data were collected retrospectively from hospital records for patients operated before June 2021 and prospectively from June 2021. A control group (non-ERAS) was identified using propensity matching from patients who underwent similar procedures and were not enrolled in the ERAS pathway (prior to October 2019). Patients were matched for age, weight, and comprehensive Aristotle score. Outcomes of interest were duration of postoperative mechanical ventilation, ICU LOS, readmission to the ICU, hospital LOS, cardiac reintervention rate, postoperative complication rate, and number of 30-day readmissions. Of 1,084 patients who underwent cardiac surgery during the study period (October 2019-July 2023), 121 patients (11.2%) followed the ERAS pathway. The median age at the time of surgery was 4.8 years (interquartile range [IQR] 2.8-8.8 years). The most common procedure was the closure of atrial septal defect (n=58, 47.9%). The median cardiopulmonary bypass and cross-clamp times were 40 min (IQR 28-53.5 minutes) and 24.5 min (IQR 13-34 minutes) respectively. The majority were extubated in the operating theatre (n=108, 89.3%). The median ICU and hospital LOS were 4.5 hrs (IQR 4.1-5.6 hours) and 4 days (IQR 4-5 days) respectively. None of the patients required readmission to the ICU within 24 hrs of discharge from the ICU. Three (3) patients (2.5%) required reintervention. When compared with the non-ERAS group, the duration of postoperative mechanical ventilation, ICU and hospital LOS were significantly lower in the ERAS group. There was no significant difference in the ICU readmission rate, reintervention rate, complication rate, and number of 30-day readmissions between both groups. ERAS after paediatric cardiac surgery is feasible and safe in select patients with low preoperative risk. This pathway reduces the duration of postoperative mechanical ventilation, ICU and hospital LOS without increasing risks, enabling the optimisation of resources.

The Rothman Index predicts unplanned readmissions to intensive care associated with increased mortality and hospital length of stay: a propensity-matched cohort study

BackgroundPatients with unplanned readmissions to the intensive care unit (ICU) are at high risk of preventable adverse events. The Rothman Index represents an objective real-time grading system of a patient’s clinical condition and a predictive tool of clinical deterioration over time. This study was designed to test the hypothesis that the Rothman Index represents a sensitive predictor of unanticipated ICU readmissions.MethodsA retrospective propensity-matched cohort study was performed at a tertiary referral academic medical center in the United States from January 1, 2022, to December 31, 2022. Inclusion criteria were adult patients admitted to an ICU and readmitted within seven days of transfer to a lower level of care. The control group consisted of patients who were downgraded from ICU without a subsequent readmission. The primary outcome measure was in-hospital mortality or discharge to hospice for end-of-life care. Secondary outcome measures were overall hospital length of stay, ICU length of stay, and 30-day readmission rates. Propensity matching was used to control for differences between the study cohorts. Regression analyses were performed to determine independent risk factors of an unplanned readmission to ICU.ResultsA total of 5,261 ICU patients met the inclusion criteria, of which 212 patients (4%) had an unanticipated readmission to the ICU within 7 days. The study cohort and control group were stratified by propensity matching into equal group sizes of n = 181. Lower Rothman Index scores (reflecting higher physiologic acuity) at the time of downgrade from the ICU were significantly associated with an unplanned readmission to the ICU (p < 0.0001). Patients readmitted to ICU had a lower mean Rothman Index score (p < 0.0001) and significantly increased rates of mortality (19.3% vs. 2.2%, p < 0.0001) and discharge to hospice (14.4% vs. 6.1%, p = 0.0073) compared to the control group of patients without ICU readmission. The overall length of ICU stay (mean 8.0 vs. 2.2 days, p < 0.0001) and total length of hospital stay (mean 15.8 vs. 7.3 days, p < 0.0001) were significantly increased in patients readmitted to ICU, compared to the control group.ConclusionThe Rothman Index represents a sensitive predictor of unanticipated readmissions to ICU, associated with a significantly increased mortality and overall ICU and hospital length of stay. The Rothman Index should be considered as a real-time objective measure for prediction of a safe downgrade from ICU to a lower level of care.

The association of the Sequential Organ Failure Assessment score at intensive care unit discharge with intensive care unit readmission in the cardiac intensive care unit.

Unplanned intensive care unit (ICU) readmissions contribute to increased morbidity, mortality, and healthcare costs. The severity of patient illness at ICU discharge may predict early ICU readmission. Thus, in this study, we investigated the association of cardiac ICU (CICU) discharge Sequential Organ Failure Assessment (SOFA) score with unplanned CICU readmission in patients admitted to the CICU. We retrospectively reviewed the hospital medical records of 4659 patients who were admitted to the CICU from 2012 to 18. Sequential Organ Failure Assessment scores at CICU admission and discharge were obtained. The predictive performance of organ failure scoring was evaluated by using area under the receiver operating characteristic (AUROC) curves. The primary outcome was unplanned CICU readmission. Of the 3949 patients successfully discharged from the CICU, 184 (4.7%) had an unplanned CICU readmission or they experienced a deteriorated condition but died without being readmitted to the CICU (readmission group). The readmission group had significantly higher rates of organ failure in all organ systems at both CICU admission and discharge than the non-readmission group. The AUROC of the discharge SOFA score for CICU readmission was 0.731, showing good predictive performance. The AUROC of the discharge SOFA score was significantly greater than that of either the initial SOFA score (P = 0.020) or the Acute Physiology and Chronic Health Evaluation II score (P < 0.001). In the multivariable regression analysis, SOFA score, overweight or obese status, history of heart failure, and acute heart failure as reasons for ICU admission were independent predictors of unplanned ICU readmission during the same hospital stay. The discharge SOFA score may identify patients at a higher risk of unplanned CICU readmission, enabling targeted interventions to reduce readmission rates and improve patient outcomes.

Features and outcomes of patients admitted to the ICU for chimeric antigen receptor T cell-related toxicity: a French multicentre cohort

BackgroundChimeric antigen receptor T-cell (CAR-T) therapy is increasingly used in patients with refractory haematological malignancies but can induce severe adverse events. We aimed to describe the clinical features and outcomes of patients admitted to the intensive care unit (ICU) after CAR-T therapy.MethodsThis retrospective observational cohort study included consecutive adults admitted to either of two French ICUs in 2018–2022 within 3 months after CAR-T therapy.ResultsAmong 238 patients given CAR-T therapy, 84 (35.3%) required ICU admission and were included in the study, a median of 5 [0–7] days after CAR-T infusion. Median SOFA and SAPSII scores were 3 [2–6] and 39 [30–48], respectively. Criteria for cytokine release syndrome were met in 80/84 (95.2%) patients, including 18/80 (22.5%) with grade 3–4 toxicity. Immune effector cell-associated neurotoxicity syndrome (ICANS) occurred in 46/84 (54.8%) patients, including 29/46 (63%) with grade 3–4 toxicity. Haemophagocytic lymphohistiocytosis was diagnosed in 15/84 (17.9%) patients. Tocilizumab was used in 73/84 (86.9%) patients, with a median of 2 [1–4] doses. Steroids were given to 55/84 (65.5%) patients, including 21/55 (38.2%) given high-dose pulse therapy. Overall, 23/84 (27.4%) patients had bacterial infections, 3/84 (3.6%) had fungal infections (1 invasive pulmonary aspergillosis and 2 Mucorales), and 2 (2.4%) had cytomegalovirus infection. Vasopressors were required in 23/84 (27.4%), invasive mechanical ventilation in 12/84 (14.3%), and dialysis in 4/84 (4.8%) patients. Four patients died in the ICU (including 2 after ICU readmission, i.e., overall mortality was 4.8% of patients). One year after CAR-T therapy, 41/84 (48.9%) patients were alive and in complete remission, 14/84 (16.7%) were alive and in relapse, and 29/84 (34.5%) had died. These outcomes were similar to those of patients never admitted to the ICU.ConclusionICU admission is common after CAR-T therapy and is usually performed to manage specific toxicities. Our experience is encouraging, with low ICU mortality despite a high rate of grade 3–4 toxicities, and half of patients being alive and in complete remission at one year.

Absence of association between low calf circumference, adjusted or not for adiposity, and ICU mortality in critically ill adults: A secondary analysis of a cohort study.

Despite its correlation with skeletal muscle mass and its predictive value for adverse outcomes in clinical settings, calf circumference is a metric underexplored in intensive care. We aimed to determine whether adjusting low calf circumference for adiposity provides prognostic value superior to its unadjusted measurement for intensive care unit (ICU) mortality and other clinical outcomes in critically ill patients. In a secondary analysis of a cohort study across five ICUs, we assessed critically ill patients within 24 h of ICU admission. We adjusted calf circumference for body mass index (BMI) (25-29.9, 30-39.9, and ≥40) by subtracting 3, 7, or 12 cm from it, respectively. Values ≤34 cm for men and ≤33 cm for women identified low calf circumference. We analyzed 325 patients. In the primary risk-adjusted analysis, the ICU death risk was similar between the low and preserved calf circumference (BMI-adjusted) groups (hazard ratio, 0.90; 95% CI, 0.47-1.73). Low calf circumference (unadjusted) increased the odds of ICU readmission 2.91 times (95% CI, 1.40-6.05). Every 1-cm increase in calf circumference as a continuous variable reduced ICU readmission odds by 12%. Calf circumference showed no significant association with other clinical outcomes. BMI-adjusted calf circumference did not exhibit independent associations with ICU and in-hospital death, nor with ICU and in-hospital length of stay, compared with its unadjusted measurement. However, low calf circumference (unadjusted and BMI-adjusted) was independently associated with ICU readmission, mainly when analyzed as a continuous variable.

Red Blood Cell Transfusion and Pulmonary Complications: The Society of Thoracic Surgeons Adult Cardiac Surgery Database Analysis

BackgroundIntraoperative packed red blood cell (PRBC) transfusion during cardiac surgery is associated with increased postoperative morbidity and mortality; however, data on the association between PRBC transfusion and postoperative pulmonary complications (PPCs) are somewhat conflicting. Using The Society of Thoracic Surgeons Adult Cardiac Surgery Database, we sought to determine whether intraoperative PRBC transfusion was associated with PPCs as well as with longer intensive care unit (ICU) stay after isolated coronary artery bypass grafting (CABG) surgery. MethodsA registry-based cohort study was performed on 751,893 patients with isolated CABG between January 1, 2015, to December 31, 2019. Using propensity score–weighted regression analysis, we analyzed the effect of intraoperative PRBC on the incidence of PPCs (hospital-acquired pneumonia [HAP], mechanical ventilation for >24 hours, or reintubation), ICU length of stay, and ICU readmission. ResultsTransfusion of 1, 2, 3, and ≥4 units of PRBCs was associated with increased odds for HAP (odds ratios [ORs], 1.24 [95% CI, 1.21-1.26], 1.28 [95% CI, 1.26-1.32], 1.36 [95% CI, 1.33-1.39], 1.31 [95% CI, 1.28-1.34]), reintubation (ORs, 1.23 [95% CI, 1.21-1.25], 1.38 [95% CI, 1.35-1.40], 1.57 [95% CI, 1.55-1.60], 1.70 [95% CI, 1.67-1.73]), prolonged ventilation (ORs, 1.34 [95% CI, 1.33-1.36], 1.56 [95% CI, 1.53-1.58], 1.97 [95% CI, 1.94-2.00], 2.27 [95% CI, 2.24-2.30]), initial ICU length of stay (mean difference in hours, 6.79 [95% CI, 6.00-7.58], 9.55 [95% CI, 8.71-10.38], 17.26 [95% CI, 16.38-18.15], 22.14 [95% CI, 21.22-23.06]), readmission to ICU (ORs, 1.14 [95% CI, 1.12-1.64], 1.15 [95% CI, 1.12-1.17], 1.15 [95% CI, 1.13-1.18], 1.32 [95% CI, 1.29-1.35]), and additional ICU length of stay (mean difference in hours, 0.55 [95% CI, 0.18-0.92], 0.38 [95% CI, 0.00-0.77], 1.02 [95% CI, 0.61-1.43], 1.83 [95% CI, 1.40-2.26]), respectively. ConclusionsIntraoperative PRBC transfusion was associated with increased incidence of PPCs, prolonged ICU stay, and ICU readmissions after isolated CABG surgery.

Assessment of Nursing Workload and Adverse Events Reporting among Critical Care Nurses in the United Arab Emirates

Background: Nursing is a demanding job, and excessive workloads have been demonstrated to negatively impact patient care. This study aimed to determine the associations between nursing workload on the days of intensive care unit (ICU) admission and discharge and adverse events among patients (i.e. ICU readmission and medication errors). Methods: This study used a retrospective cohort design. We reviewed medical records for 270 patients admitted to the ICU from three hospitals in the United Arab Emirates between February and April 2023. Collected data included patients’ demographics, diagnosis, acuity score on ICU admission/discharge days, Nursing Activities Score (NAS) on ICU admission/discharge days and adverse events reported (i.e. occurrence of medication errors and re-admission to ICU after discharge). Results: The nursing workload on ICU admission and discharge days was high (NAS=72.61 and NAS=52.61, respectively). There were significant associations between ICU readmission and nursing workload at ICU admission and discharge. Moreover, there was a significant relationship between the occurrence of medication errors and nursing workload on the day of ICU admission, with more medication errors occurring in patients with higher NAS scores. Conclusion: The complexity of nursing activities and the severity of patients’ conditions directly impact the nursing workload and patient outcomes. A practical strategy to reduce the nursing workload may be calculating the NAS to clarify the actual time spent by nurses to provide the required care based on the patient’s condition. Adoption of new technologies to enhance medication safety and minimise errors may be another strategy to reduce the impact of the high nursing workload in ICU settings.

Intensive care risk and long-term outcomes in pediatric allogeneic hematopoietic cell transplant recipients

AbstractAllogeneic hematopoietic cell transplantation (HCT) can be complicated by life-threatening organ toxicity and infection necessitating intensive care. Epidemiologic data have been limited by single-center studies, poor database granularity, and a lack of long-term survivors. To identify contemporary trends in intensive care unit (ICU) use and long-term outcomes, we merged data from the Center for International Blood and Marrow Transplant Research and the Virtual Pediatric Systems databases. We identified 6995 pediatric patients with HCT aged ≤21 years who underwent first allogeneic HCT between 2008 and 2014 across 69 centers in the United States or Canada and followed patients until the year 2020. ICU admission was required for 1067 patients (8.3% by day +100, 12.8% by 1 year, and 15.3% by 5 years after HCT), and was linked to demographic background, pretransplant organ toxicity, allograft type and HLA-match, and the development of graft-versus-host disease or malignancy relapse. Survival to ICU discharge was 85.7%, but more than half of ICU survivors required ICU readmission, leading to 52.5% and 42.6% survival at 1- and 5-years post-ICU transfer, respectively. ICU survival was worse among patients with malignant disease, poor pretransplant organ function, and alloreactivity risk factors. Among 1-year HCT survivors, those who required ICU in the first year had 10% lower survival at 5 years and developed new dialysis-dependent renal failure at a greater rate (P<.001). Thus, although ICU management is common and survival to ICU discharge is high, ongoing complications necessitate recurrent ICU admission and lead to a poor 1-year outcome in select patients who are at high risk.

High versus standard blood pressure target in hypertensive high-risk patients undergoing elective major abdominal surgery: a study protocol for the HISTAP randomized clinical trial

BackgroundThe intraoperative period is often characterized by hemodynamic instability, and intraoperative hypotension is a common complication. The optimal mean arterial pressure (MAP) target in hypertensive patients is still not clear. We hereby describe the protocol and detailed statistical analysis plan for the high versus standard blood pressure target in hypertensive high-risk patients undergoing elective major abdominal surgery: the HISTAP randomized clinical trial. The HISTAP trial aims at addressing whether the use of a higher intraoperative MAP target in high-risk hypertensive surgical patients scheduled for elective abdominal surgery would improve postoperative outcomes, as compared to the standard and recommended perioperative MAP, by using a composite outcome including a 30-day mortality from surgical intervention and at least one major organ dysfunction or new onset of sepsis and septic shock occurring 7 days after surgery.MethodsThe HISTAP trial is an investigator-initiated, pragmatic, parallel-grouped, randomized, stratified, analyst-blinded trial with adequate allocation sequence generation, and allocation concealment. We will allocate 636 patients to a MAP target ≥ 80 mmHg (treatment group) or to a MAP target ≥65 mmHg (control group). The primary outcome is a composite outcome including a 30-day mortality from the operation and major organ complications. Secondary outcomes are mortality at 30 days, intensive care unit (ICU) length of stay, ICU readmission, Sequential Organ Failure Assessment (SOFA) scores recorded up to postoperative day 7, overall intraoperative fluid balance, vasopressors use, and the need for reoperation. An unadjusted χ2 test will be used for the primary outcome analysis. A Cox proportional hazards model will be used to adjust the association between the primary outcome and baseline covariates.ConclusionsThe HISTAP trial results will provide important evidence to guide clinicians’ choice regarding the intraoperative MAP target in high-risk hypertensive patients scheduled for elective abdominal surgery.

Hazardous alcohol consumption and perioperative complications in a cardiac surgery patient. A retrospective study.

We investigated the prevalence and effects of hazardous alcohol consumption on perioperative complications in cardiac surgery patients. Preoperative hazardous alcohol consumption has been associated with an increased risk of postoperative complications in noncardiac patient populations. We retrospectively collected data from the Finnish Intensive Care Consortium database and electronic patient records on all cardiac surgery patients treated in the intensive care units (ICUs) of Helsinki University Hospital (n = 919) during 2017. Data on preoperative alcohol consumption were routinely collected using the alcohol use disorder identification test consumption (AUDIT-C) questionnaire. We analyzed perioperative data and outcomes for any associations with hazardous alcohol consumption. Outcome measures were length of stay in the ICU, re-admissions to ICU, bleeding and infectious complications, and incidence of postoperative arrhythmias. AUDIT-C scores were available for 758 (82.5%) patients, of whom 107 (14.1%) fulfilled the criteria for hazardous alcohol consumption (AUDIT-C score of 5/12 or higher for women and 6/12 or higher for men). Patients with hazardous alcohol consumption were younger, median age 59 (IQR 52.0-67.0) vs. 69.0 (IQR 63.0-74.0), p < .001, and more often men 93.5% vs. 71.9%, p < .001 than other patients and had an increased risk for ICU re-admissions [adjusted OR (aOR) 4.37 (95% CI, 1.60-11.95)] and severe postoperative infections aOR 3.26 (95% CI, 1.42-7.54). Cardiac surgery patients with a history of hazardous alcohol consumption are younger than other patients and are predominantly men. Hazardous alcohol consumption is associated with an increased risk of severe postoperative infections and ICU re-admissions.

Increased Neonatal Mortality and Increasing Rate of Cerebral Venous Sinus Thrombosis in Hospitalized Children: A Pediatric Health Information System Database Study

Introduction: Pediatric Cerebral Venous Sinus Thrombosis (CVST) poses risks of neurological sequelae and mortality, necessitating timely diagnosis and appropriate antithrombotic therapy. Limited sample sizes in previous studies have led to inconsistent treatment recommendations. To better understand pediatric CVST, we used the Pediatric Health Information System (PHIS) database to compare clinical features, treatment practices, and outcomes in neonates versus older children, and in different time periods, to analyze the influence of various parameters on healthcare outcomes. Methods: Deidentified, retrospective data of pediatric CVST was extracted from the large multi-center PHIS administrative database from January 1, 2011, to October 1, 2022. Diagnostic, imaging, procedure, and pharmaceutical billing codes were used to identify demographic information, clinical characteristics, management, and outcome. Multivariance analysis was performed on study parameters in neonates vs. older children (Table 1) and early (2011-2015) vs. late (2016-2022) study era (Table 2). Results: 6080 hospitalizations with CVST diagnosis (0.1% of all hospitalizations) were identified (61% male; median age 5 years; range 0-17 years). Median hospital stay was 8 days (IQR 4, 22), with 52% (N=3147) admitted to the intensive care unit (ICU). Overall mortality of all children was 4.2%. Neonates constituted 17.3% of the hospitalizations (N=1,054). Clinical features in neonates were less-often reported vs. older children more often had headache, hypertension, vomiting, papilledema and hemiparesis (p&amp;lt;0.001). Congenital heart disease/sepsis were common associated diagnoses in neonates vs. sinusitis/mastoiditis in older children (p&amp;lt;0.001). Neonates had a longer hospital stay (median 24 (IQR 11, 55), vs. 8 days (IQR 4, 17); p &amp;lt;0.001), but lower ICU admission (33.4% vs. 55.6%; p&amp;lt;0.001) and readmission rate (0% vs. 1.0%; p=0.002) when compared to older children. CT without contrast was used less often (33.4% vs. 55.1%; p &amp;lt; 0.001), and head ultrasound more often (76.3% vs. 8.0%; p &amp;lt; 0.001) for neonates vs. older children. Enoxaparin and unfractionated heparin (UFH) remained the primary treatments for CVST, with UFH utilized more often in neonates (71.6% vs. 59.2%; p&amp;lt;0.001). Direct oral anticoagulants (DOACs) were predominantly used in older children in limited numbers. Coma and hydrocephalus as complications were lower (0.7% vs. 5.6%, p&amp;lt;0.001 and 6.2% vs. 9.4%, p=0.001), and intracranial bleeding was (19.1% vs.7.0%, p&amp;lt;0.001) in neonates vs. older children. Neonates had increased mortality rate compared to older children (9.7% vs. 3.1%; p&amp;lt;0.001). The number of CVST admissions increased in the late (2016-2022) compared to the early study era (2011-2015) (0.11% vs. 0.08% of all admissions, p&amp;lt;0.001). Patient demographics, duration of hospital stay, ICU admission rates, clinical features, and imaging modalities remained similar in both groups. The use of bivalirudin, and DOACs was present in the late vs. none in the early era (p&amp;lt;0.001 except Dabigatran). Coma in the late (p&amp;lt;0.001) and brain infarct in the early study era (p&amp;lt;0.001) were more common complications. Both readmission rate (p=0.006) and hospital stay (p=0.006) were slightly higher in the late era. No statistically significant differences were found in mortality rate between the two eras (p= 0.226). Conclusion: Pediatric CVST is a serious disorder, with an overall mortality rate of 4.2% in our study. Neonates had distinct clinical features, associated diagnoses, and complications compared to older children. Predominantly UFH and rarely DOACs were administered in neonates. Neonates experienced longer hospital stay, and statistically significant higher mortality rate when compared to older children, consistent with prior studies. Newer anticoagulants were utilized increasingly in the late vs. early study era. Though readmission rate and hospital stay increased in the late era (not statistically significant), this did not translate into increased mortality. Increasing rate of hospitalizations in late compared to early study era is likely due to increasing medical complexity/technological advances in diagnosis/management of pediatric CVST. Future multi-center, prospective studies are needed to better address the increased neonatal mortality and improve overall care of pediatric CVST which is increasingly prevalent as seen in our study.

Prognostic factors for critically ill surgical patients with unplanned intensive care unit readmission: Developing a novel predictive scoring model for predicting readmission

BackgroundUnplanned readmission to the surgical intensive care unit has been demonstrated to worsen patient outcomes. Our objective was to identify risk factors and outcomes associated with unplanned surgical intensive care unit readmission and to develop a predictive scoring model to identify patients at high risk of readmission. MethodsWe retrospectively analyzed patients admitted to the surgical intensive care unit (2020–2021) and categorized them as either with or without unplanned readmission. ResultsOf 1,112 patients in the derivation cohort, 76 (6.8%) experienced unplanned surgical intensive care unit readmission, with sepsis being the leading cause of readmission (35.5%). Patients who were readmitted had significantly higher in-hospital mortality rates than those who were not. Multivariate analysis identified congestive heart failure, high Sequential Organ Failure Assessment–Hepatic score, use of carbapenem during surgical intensive care unit stay, as well as factors before surgical intensive care unit discharge such as inadequate glycemic control, positive fluid balance, low partial pressure of oxygen in arterial blood/fraction of inspired oxygen ratio, and receipt of total parenteral nutrition as independent predictors for unplanned readmission. The scoring model developed using these predictors exhibited good discrimination between readmitted and non-readmitted patients, with an area under the curve of 0.74. The observed rates of unplanned readmission for scores of <4 points and ≥4 points were 4% and 20.2% (P < .001), respectively. The model also demonstrated good performance in the validation cohort, with an area under the curve of 0.74 and 19% observed unplanned readmission rate for scores ≥4 points. ConclusionBesides congestive heart failure, clinicians should meticulously re-evaluate critical variables such as the Sequential Organ Failure Assessment–Hepatic score, partial pressure of oxygen in arterial blood/fraction of inspired oxygen ratio, glycemic control, and fluid status before releasing the patient from the surgical intensive care unit. It is crucial to determine the reasons for using carbapenems during surgical intensive care unit stay and the causes for the inability to discontinue total parenteral nutrition before discharging the patient from the surgical intensive care unit.

Utilisation of artificial intelligence to predict early readmission to the cardiac intensive care unit in critically ill patients

Abstract Background The need for cardiac intensive care unit (ICU) beds remains high in order to treat patients with severe cardiovascular diseases. Therefore, safe and timely discharge policies from the cardiac ICU to normal wards are crucial to meet the continuously increasing demand for cardiac ICU beds. ICU readmission after ICU discharge has been shown to increase mortality, hospital length of stay and costs. Artificial intelligence may provide a timely and accurate discharge decision support system for intensivists based on comprehensive, multi-dimensional ICU data. Purpose This is the first study to develop and validate a neuronal network, called Feedforward Neural Network (FNN), to safely discharge patients from the cardiac ICU and predict ICU readmission within 72 hours. Methods Adult patients who were admitted to the cardiac ICU due to a primary cardio-pulmonary admission diagnosis (such as acute myocardial infarction, cardiogenic shock or cardiac arrest) at a German tertiary care center between 2003 and 2021 were included. The dataset was split into a training and test dataset. The FNN was trained with 127 variables, including patient demographics, co-morbidities, medical diagnoses, disease acuity levels, laboratory values, vital parameters, ICU procedures and administered ICU medications. FNN was compared to the predictability of a classic logistic regression model and the Stability and Workload Index for Transfer (SWIFT) score, which is a clinical score to predict ICU readmission. Results 2,498 adult patients in the cardiac ICU met the inclusion criteria, out of which the FNN was trained in 1,998 (80.0%) patients and tested in 500 (20.0%) patients. The FNN had a 97.9% sensitivity, 86.9% specificity, 99.4% precision and 97.4% accuracy. FNN showed a better predictability of early ICU readmission than the logistic regression model and the SWIFT score: areas under the receiver operating characteristic (AUC ROC) curves were 90.78% vs. 71.34% vs. 71.13% (P &amp;lt;0.001) (Figure), respectively. Conclusions ICU transfer to the normal ward is considered to be a high-risk event and the vast amount of daily clinical, physiologic, laboratory and monitoring data may overwhelm critical care providers in making well informed decisions on patient discharge readiness. Artificial intelligence might be used as a sensitive, specific and accurate decision support system to help with patient discharge management and reduce ICU readmission rates.

Outcomes and Direct Cost of Isolated Nonemergent CABG in Patients With Low Ejection Fraction.

Preoperative left ventricular ejection fraction (LVEF) is one of the main predictors of outcomes in cardiac surgery. We present current era outcomes and associated direct cost in nonemergent isolated coronary artery bypass surgery (CABG) patients with LVEF <20% over the past 6 years and compare it with higher EF subgroups. Six-year data from 2016 to 2022 at hospitals sharing Society of Thoracic Surgeons and financial data with Biome Analytics were analyzed based on 3 EF subgroups (EF ≤20%, EF 21% to 35%, and EF >35%). Outcomes and costs were assessed. Overall 30-day mortality of 12,649 patients was 1.9%. The EF ≤20% (n = 248), EF 21% to 35% (n = 1,408), and EF >35 (n = 10,993) cohorts had mortality of 6.9%, 3.7%, and 1.6%, respectively. The EF ≤20% subgroup had higher use of cardiopulmonary bypass, blood products, and mechanical support. In addition, the EF ≤20% subgroup had higher complication rates in almost all measured categories. Also, the EF ≤20% cohort had significantly higher length of stay, intensive care unit (ICU) hours, ICU and hospital readmissions, and lowest discharge to home rate. The strongest factors associated with mortality were postoperative cardiac arrest, renal failure requiring dialysis, extracorporeal membrane oxygenation, sepsis, prolonged ventilation, and gastrointestinal event. The overall median direct cost of care was $37,387.79 ($27,605.18, $51,720.96), with a median direct cost of care in the EF ≤20%, EF 21% to 35%, and EF >35% subgroups of $52,500.17 ($34,103.52, $80,806.79), $44,108.32 ($31,597.58, $63,788.03), and $36,521.80 ($27,168.91, $50,019.31), respectively. In nonemergent isolated CABG surgery, low EF continues to have higher surgical risks and higher direct cost of care despite advances in cardiovascular care.

Diversifying cardiac intensive care unit models: Successful example of an operating surgeon-led unit

ObjectiveThe intensivist-led cardiovascular intensive care unit model is the standard of care in cardiac surgery. This study examines whether a cardiovascular intensive care unit model that uses operating cardiac surgeons, cardiothoracic surgery residents, and advanced practice providers is associated with comparable outcomes. MethodsThis is a single-institution review of the first 400 cardiac surgery patients admitted to an operating surgeon-led cardiovascular intensive care unit from 2020 to 2022. Inclusion criteria are elective status and operations managed by both cardiovascular intensive care unit models (aortic operations, valve operations, coronary operations, septal myectomy). Patients from the surgeon-led cardiovascular intensive care unit were exact matched by operation type and 1:1 propensity score matched with controls from the traditional cardiovascular intensive care unit using a logistic regression model that included age, sex, preoperative mortality risk, incision type, and use of cardiopulmonary bypass and circulatory arrest. Primary outcome was total postoperative length of stay. Secondary outcomes included postoperative intensive care unit length of stay, 30-day mortality, 30-day Society of Thoracic Surgeons–defined morbidity (permanent stroke, renal failure, cardiac reoperation, prolonged intubation, deep sternal infection), packed red cell transfusions, and vasopressor use. Outcomes between the 2 groups were compared using chi-square, Fisher exact test, or 2-sample t test as appropriate. ResultsA total of 400 patients from the surgeon-led cardiovascular intensive care unit (mean age 61.2 ± 12.8 years, 131 female patients [33%], 346 patients [86.5%] with European System for Cardiac Operative Risk Evaluation II <2%) and their matched controls were included. The most common operations across both units were coronary artery bypass grafting (n = 318, 39.8%) and mitral valve repair or replacement (n = 238, 29.8%). Approximately half of the operations were performed via sternotomy (n = 462, 57.8%). There were 3 (0.2%) in-hospital deaths, and 47 patients (5.9%) had a 30-day complication. The total length of stay was significantly shorter for the surgeon-led cardiovascular intensive care unit patients (6.3 vs 7.0 days, P = .028), and intensive care unit length of stay trended in the same direction (2.5 vs 2.9 days, P = .16). Intensive care unit readmission rates, 30-day mortality, and 30-day morbidity were not significantly different between cardiovascular intensive care unit models. The surgeon-led cardiovascular intensive care unit was associated with fewer postoperative red blood cell transfusions in the cardiovascular intensive care unit (P = .002) and decreased vasopressor use (P = .001). ConclusionsIn its first 2 years, the surgeon-led cardiovascular intensive care unit demonstrated comparable outcomes to the traditional cardiovascular intensive care unit with significant improvements in total length of stay, postoperative transfusions in the cardiovascular intensive care unit, and vasopressor use. This early success exemplifies how an operating surgeon-led cardiovascular intensive care unit can provide similar outcomes to the standard-of-care model for patients undergoing elective cardiac surgery.

Biological age as a predictor of unplanned intensive care readmission during the same hospitalization

BackgroundBiological age is increasingly being recognized as an important predictor of health but its utility in acute care setting remains uncertain. ObjectiveWe assessed whether biological age on intensive care unit (ICU) admission can predict unplanned ICU readmission during the same hospitalization. MethodsThe Levine PhenoAge model based on biomarkers of DNA methylation was used to determine each patient's biological age. The difference between PhenoAge and chronological age was indexed to the local context by regressing PhenoAge on chronological age using linear regression. A positive residual implied one's biological age was older than the corresponding chronological age compared to other patients — defined as PhenoAgeAccel. ResultsOf the 2950 patients included, 153 (5.2%) had unplanned ICU readmission. Chronological age, Acute Physiology and Chronic Health Evaluation II score, the use of mechanical ventilation, vasopressor, or renal replacement therapy were not significantly different between those with and without readmission. PhenoAgeAccel was, however, more common among those who had unplanned ICU readmission (52% vs 43%, p =0.031). Quantitatively, the degree of phenotypical age above chronological age exhibited a ‘dose-related’ relationship with the risk of readmission (odds ratio 1.12, 95% confidence interval 1.01-1.24; p=0.040) after adjusting for chronological age, comorbidities, and severity of acute illness in the index (first) ICU admission. ConclusionBiological age was predictive of unplanned ICU readmission during the same hospitalization.