Unplanned Intensive Care Unit Readmission Research Articles

Factors associated with unplanned intensive care unit readmission among trauma patients in Republic of Korea.

In trauma patients, unplanned intensive care unit (ICU) readmission (UIR) is associated with poor clinical outcomes. In this study, we aimed to analyze associated factors for UIR in trauma patients. This retrospective study was conducted on trauma patients admitted to the ICU at a trauma center from January 2016 to December 2022. Clinical information at admission, the first ICU hospitalization, first discharge from the ICU, and reasons for readmission were collected. Patients who were successfully discharge from the ICU were compared to UIR patients. Logistic regression was performed to determine the factors with a significant impact on ICU readmission. Here, 5,529 patients were admitted to the ICU over 7 years, and 212 patients (3.8%) experienced UIR. Among patients who experienced UIR, 9 (4.2%) died. In the UIR patients, hospital stay (20 days [interquartile range, 13-35] vs. 45 days [28-67], P<0.001), total ICU stay (5 days [3- 11] vs. 17 days [9-35], P<0.001), and complications during the first ICU hospitalization were significantly higher. The most common reason for UIR was respiratory problem (53.8%). In multivariable analysis, cervical spine operation during the first ICU hospitalization (odds ratio, 6.56; 95% CI, 3.62-11.91; P<0.001), renal replacement therapy (RRT; 3.52, 2.06-5.99, P<0.001), and massive blood transfusion protocol (MTP; 1.74, 1.08-2.81, P=0.023) were most highly related with UIR. Because UIR patients had poor outcomes, trauma patients who underwent cervical spine operation, RRT, or MTP require monitoring in the general ward, especially for respiratory problems.

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.

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.

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.

Incurring detriments of unplanned readmission to the intensive care unit following surgery for brain metastasis

ObjectPostoperative intensive care unit (ICU) monitoring is a common regime after neurosurgical resection of brain metastasis (BM). In comparison, unplanned secondary readmission to the ICU after initial postoperative treatment course occurs in response to adverse events and might significantly impact patient prognosis. In the present study, we analyzed the potential prognostic implications of unplanned readmission to the ICU and aimed at identifying preoperatively collectable risk factors for the development of such adverse events.MethodsBetween 2013 and 2018, 353 patients with BM had undergone BM resection at the authors’ institution. Secondary ICU admission was defined as any unplanned admission to the ICU during the initial hospital stay. A multivariable logistic regression analysis was performed to identify preoperatively identifiable risk factors for unplanned ICU readmission.ResultsA total of 19 patients (5%) were readmitted to the ICU. Median overall survival (mOS) of patients with unplanned ICU readmission was 2 months (mo) compared to 13 mo for patients without secondary ICU admission (p<0.0001). Multivariable analysis identified “multiple BM” (p=0.02) and “preoperative CRP levels > 10 mg/dl” (p=0.01) as significant and independent predictors of secondary ICU admission.ConclusionsUnplanned ICU readmission following surgical therapy for BM is significantly related to poor OS. Furthermore, the present study identifies routinely collectable risk factors indicating patients that are at a high risk for unplanned ICU readmission after BM surgery.

Social vulnerability is associated with increased postoperative morbidity following esophagectomy

ObjectivesThe effect of a patient’s Social Vulnerability Index (SVI) on complication rates after esophagectomy remains unstudied. The purpose of this study was to determine how social vulnerability influences morbidity following esophagectomy. MethodsThis was a retrospective review of a prospectively collected esophagectomy database at one academic institution, 2016 to 2022. Patients were grouped into low-SVI (<75%ile) and high-SVI (>75%ile) cohorts. The primary outcome was overall postoperative complication rate; secondary outcomes were rates of individual complications. Perioperative patient variables and postoperative complication rates were compared between the 2 groups. Multivariable logistic regression was used to control for covariates. ResultsOf 149 patients identified who underwent esophagectomy, 27 (18.1%) were in the high-SVI group. Patients with high SVI were more likely to be of Hispanic ethnicity (18.5% vs 4.9%, P = .029), but there were no other differences in perioperative characteristics between groups. Patients with high SVI were significantly more likely to develop a postoperative complication (66.7% vs 36.9%, P = .005) and had greater rates of postoperative pneumonia (25.9% vs 6.6%, P = .007), jejunal feeding-tube complications (14.8% vs 3.3%, P = .036), and unplanned intensive care unit readmission (29.6% vs 12.3%, P = .037). In addition, patients with high SVI had a longer postoperative hospital length of stay (13 vs 10 days, P = .017). There were no differences in mortality rates. These findings persisted on multivariable analysis. ConclusionsPatients with high SVI have greater rates of postoperative morbidity following esophagectomy. The effect of SVI on esophagectomy outcomes warrants further investigation and may prove useful in identifying populations that benefit from interventions to mitigate these complications.

Status and Risk Factors in Patients Requiring Unplanned Intensive Care Unit Readmission Within 48 Hours: A Retrospective Propensity-Matched Study in China.

This study investigated the current status and related risk factors of 48-hour unplanned return to the intensive care unit (ICU) to reduce the return rate and improve the quality of critical care management. Data were collected from 2365 patients discharged from the comprehensive ICU. Multivariate and 1:1 propensity score matching analyses were performed. Forty patients (1.69%) had unplanned readmission to the ICU within 48 hours after transfer. The primary reason for return was respiratory failure (16 patients, 40%). Furthermore, respiratory failure (odds ratio [OR] = 5.994, p = 0.02) and the number of organ failures (OR = 5.679, p = 0.006) were independent risk factors for unplanned ICU readmission. Receiver operating characteristic curves were drawn for the predictive value of the number of organ injuries during a patient's unplanned transfer to the ICU (area under the curve [AUC] = 0.744, sensitivity = 60%, specificity = 77.5%). The reason for patient transfer and the number of organ injuries during the process were independent risk factors for patients who were critically ill. The number of organs damaged had a predictive value on whether the patient would return to the ICU within 48 hours.

Unplanned intensive care unit readmission after surgical treatment in patients with newly diagnosed glioblastoma — forfeiture of surgically achieved advantages?

Postoperative intensive care unit (ICU) monitoring is an established option to ensure patient safety after resection of newly diagnosed glioblastoma. In contrast, secondary unplanned ICU readmission following complicating events during the initial postoperative course might be associated with severe morbidity and impair initially intended surgical benefit. In the present study, we assessed the prognostic impact of secondary ICU readmission and aimed to identify preoperatively ascertainable risk factors for the development of such adverse events in patients treated surgically for newly diagnosed glioblastoma. Between 2013 and 2018, 240 patients were surgically treated for newly diagnosed glioblastoma at the authors’ neuro-oncological center. Secondary ICU readmission was defined as any unplanned admission to the ICU during initial hospital stay. A multivariable logistic regression analysis was performed to identify preoperatively measurable risk factors for unplanned ICU readmission. Nineteen of 240 glioblastoma patients (8%) were readmitted to the ICU. Median overall survival of patients with unplanned ICU readmission was 9 months compared to 17 months for patients without secondary ICU readmission (p=0.008). Multivariable analysis identified “preoperative administration of dexamethasone > 7 days” (p=0.002) as a significant and independent predictor of secondary unplanned ICU admission. Secondary ICU readmission following surgery for newly diagnosed glioblastoma is significantly associated with poor survival and thus may negate surgically achieved prerequisites for further treatment. This underlines the indispensability of precise patient selection as well as the importance of further scientific debate on these highly relevant aspects for patient safety.

Nursing Activities Score at Discharge from the Intensive Care Unit Is Associated with Unplanned Readmission to the Intensive Care Unit.

This study evaluated the accuracy of predicting unplanned the intensive care unit (ICU) readmission using the Nursing Activities Score (NAS) at ICU discharge based on nursing workloads, and compared it to the accuracy of the prediction made using the Stability and Workload Index for Transfer (SWIFT) score. Patients admitted to the ICU of Sapporo Medical University Hospital between April 2014 and December 2017 were included, and unplanned ICU readmissions were retrospectively evaluated using the SWIFT score and the NAS. Patient characteristics, such as age, sex, the Charlson Comorbidity Index, and sequential organ failure assessment score at ICU admission, were used as covariates, and logistic regression analysis was performed to calculate the odds ratios for the SWIFT score and NAS. Among 599 patients, 58 (9.7%) were unexpectedly readmitted to the ICU. The area under the receiver operating characteristic curve of NAS (0.78) was higher than that of the SWIFT score (0.68), and cutoff values were 21 for the SWIFT and 53 for the NAS. Multivariate analysis showed that the NAS was an independent predictor of unplanned ICU readmission. The NAS was superior to the SWIFT in predicting unplanned ICU readmission. NAS may be an adjunctive tool to predict unplanned ICU readmission.

Sepsis in a Combined Medical and Surgical High Dependency/Intensive Care Unit in Singapore: A Cohort Study and Survival Analysis.

BackgroundSepsis is a common indication for intensive care unit (ICU) admission and is associated with significant mortality and morbidity. The aim of our study was to first assess the incidence, severity, short-term and long-term mortality of sepsis in a combined medical and surgical high dependency/ ICU in Singapore, and to identify factors associated with increasing short-term and long-term mortality.MethodsAll admissions from July 1 to December 31, 2017 were retrospectively screened and clinical data were collected. Patients were followed up until 3 years post ICU admission.ResultsOf a total 1526 admissions, 281 had infection at ICU admission, and 254 (16.6%) fulfilled sepsis-3 criteria for sepsis. A total of 141 (9.2%) had septic shock. The 30-day, 1-year, 2-year and 3-year mortality of sepsis patients were 19.3%, 25.2%, 30.3% and 32.3%, respectively. Lung was the most common site of infection. Compared with 30-day sepsis survivors, non-survivors were older (median age 70 vs 63, P <0.001), had higher percentage of lung infection (65.3% vs 36.1%, P <0.05), higher admission Sequential Organ Failure Assessment (SOFA) score (median 9 vs 5, P <0.001), and longer ICU stay (median days: 4 vs 3, P = 0.037). In stepwise Cox regression analysis, lung infection was an independent risk factor for both increasing 30-day and 3-year mortality. Immunocompromised host, increasing age and SOFA score were associated with higher 30-day mortality. Diabetes, admission quick Sequential Organ Failure Assessment (qSOFA) score >1 and unplanned ICU re-admission were associated with increasing 3-year mortality in 30-day survivors.ConclusionOur retrospective cohort single center study first reported sepsis admission incidence of 16.6% in a combined medical and surgical high dependency/ICU in Singapore, with significant short-term and long-term mortality. Lung infection was an independent risk factor for both 30-day and 3-year mortality.

The Impact of Critical Care Transition Programs (CCTPs) on Relocation Stress in Patients and Patient Families in the Intensive Care Unit

The intensive care unit (ICU) is designed to care for patients with high disease severity who require critical care and close monitoring. Patients in the ICU may be transferred to the general ward for further treatment following recovery from the acute phase. Transferring from the ICU to the general ward after acute phase recovery is a stressful event that may stress both the patient and their family, potentially resulting in relocation stress syndrome (RSS). RSS has been found to be closely related to unplanned ICU readmissions, prolonged hospitalization, and adverse events, affecting recovery to health and family peace of mind. Furthermore, RSS may result in ineffective disease coping, feelings of uncertainty, and poor treatment response, leading to prolonged hospitalization, reduced trust in medical staff, and decreased happiness and quality of life. In recent years, the nursing profession has attached increasing importance to holistic health care. This has encouraged critical care teams to map out customized relocation plans for patients who are about to be transferred from the ICU that use standardized evaluation tools for transfers and elicit the situation and needs from patients or their family. Through the setting of care goals, shared decision making, and cross-unit support, enhanced communications among the medical team facilitate transition preparation and improve the quality and effect of intensive care.

Identifying the limitations of cardiopulmonary exercise testing prior to esophagectomy using a pooled analysis of patient-level data.

Preoperative cardiopulmonary exercise testing (CPET) provides an objective assessment of aerobic fitness in patients undergoing surgery. While peak oxygen uptake during exercise (VO2peak) and anaerobic threshold have demonstrated a moderate correlation with the development of complications following esophagectomy, no clinically useful threshold values have been defined. By pooling patient level data from existing studies, we aimed to define optimal thresholds for preoperative CPET parameters to predict patients at high risk of postoperative complications. Studies reporting on the relationship between preoperative CPET variables and post-esophagectomy complications were determined from a comprehensive literature search. Patient-level data were obtained from six contributing centers for pooled-analyses. Outcomes of interest included cardiopulmonary and non-cardiopulmonary complications, unplanned intensive care unit readmission, and 90-day and 12-month all-cause mortality. Receiver operating characteristic curves and logistic regression models estimated the predictive value of CPET parameters for each individual outcome of interest. This analysis comprised of 621 patients who underwent CPET prior to esophagectomy during the period from January 2004 to March 2017. For both anaerobic threshold and VO2peak, none of the receiver operating characteristic curves achieved an area under the curve value > 0.66 for the outcomes of interest. The discriminatory ability of CPET for determining high-risk patients was found to be poor in patients undergoing an esophagectomy. CPET may only carry an adjunct role to clinical decision-making.

Readmission into intensive care unit in patients with aneurysmal subarachnoid hemorrhage.

ObjectiveAneurysmal subarachnoid hemorrhage (aSAH) is a devastating cerebrovascular event; patients are routinely admitted to the intensive care unit (ICU) for initial management. Because complications may be delayed, unplanned ICU readmissions can occur. Therefore, in this study we evaluate the rate of and factors associated with readmission after aSAH and identify if readmission is associated with poor clinical outcomes.MethodsWe retrospectively reviewed the medical records of all patients receiving surgical or endovascular treatment for aSAH and admitted to the ICU between January 2008 and December 2019. We categorized patients by readmission and analyzed their clinical parameters.ResultsOf the 345 patients who transferred to ward-level care after an initial ICU stay (Group 2), 27 (7.3%) were readmitted to the ICU (Group 1). History of hypertension (HTN), initial Glasgow Coma Scale (GCS) score, modified Fisher grade, and vasospasm therapy during first ICU stay were significantly different between the groups. The most common reason for readmission was delayed cerebral ischemia (DCI; 70.3%; OR 5.545; 95% CI 1.25−24.52; p=0.024). Comorbid HTN (OR 5.311; 95% CI 1.75−16.12; p=0.03) and vasospasm therapy during first ICU stay (OR 7.234; 95% CI 2.41−21.7; p＜0.01) also were associated with readmission. Readmitted patients had longer hospital stay and lower GCS scores at discharge (p＜0.01).ConclusionsDCI was the most common cause of ICU readmission in patients with aSAH. Readmission may indicate clinical deterioration, and patients who are at a high risk for DCI should be monitored to prevent readmission.

Predictors of Early and Late Unplanned Intensive Care Unit Readmission: A Retrospective Cohort Study

AbstractPurposeIntensive care unit (ICU) readmission is considered one of the major quality indicators of critical care. Reducing ICU readmission can improve patients’ outcomes and optimize health resources, but there are limited data on the predictors of unplanned ICU readmission. This study aimed to identify the risk factors associated with unplanned ICU readmission within 48 hr (early) and after 48 hr (late) from ICU discharge.DesignRetrospective cohort study.MethodsData were collected from patients’ electronic medical records in a 24‐bed medical ICU at a tertiary academic medical center in Busan, South Korea. Among all the patients admitted to the medical ICU (n= 1,033) between January 2015 and December 2017, 739 eligible patients were analyzed. A multivariable multinomial logistic regression model was conducted to identify predictors of ICU readmission.FindingsOut of the 739 patients analyzed, 66 (8.9%) were readmitted to the medical ICU: 13 (1.8%) as early readmission and 53 (7.1%) as late readmission. Two significant predictors were identified for early readmission: ICU admission from the ward (odds ratio [OR] = 4.14; 95% confidence interval [CI] 1.25, 13.67) and mechanical ventilation support &gt;14 days (OR= 13.25; 95% CI 1.78, 98.89). For late ICU admission, there were four risk factors: ICU admission from the ward (OR= 2.69; 95% CI 1.44, 5.05), tracheostomy placement (OR= 3.58; 95% CI 1.49, 8.59), mechanical ventilation support &gt;14 days (OR= 4.77; 95% CI 1.67, 13.63), and continuous renal replacement therapy (OR= 4.57; 95% CI 2.42, 8.63).ConclusionsTo prevent unplanned ICU readmission in patients at high risk, it is necessary to investigate further the role of clinical judgment and communication within the ICU clinical team and institutional‐level support regarding ICU readmission events.Clinical RelevanceBoth ICU nurses and nurses in post‐ICU settings should be aware of the potential risk factors associated with early and late ICU readmission. Predictors and readmission strategies may be different for early and late readmissions. Prospective multicenter studies are needed to examine how these factors influence post‐ICU outcomes.

Lactate level and unplanned readmission to the surgical intensive care unit: a retrospective cohort study.

This study aimed to investigate the association between lactate levels during intensive care unit (ICU) stay and unplanned ICU readmission rates within 48 and 120 h in surgical patients. This single-center retrospective cohort study evaluated adult patients who were discharged from the ICU between January 2012 and December 2018. The association between lactate levels (initial lactate at ICU admission, peak level during ICU stay, and last level before ICU discharge) and unplanned ICU readmission was investigated using uni- and multivariable logistic regression analyses. The cohort included 3,707 patients. The unplanned ICU readmission rate within 48 and 120 h was 2.1% (n=78 patients) and 4.5% (n=166 patients), respectively. In the multivariable model, 1 mg dL-1 increase in the peak lactate level during ICU stay was associated with 1.1-fold increase in unplanned ICU readmission within 48 h (odds ratio: 1.10; 95% confidence interval: 1.02 to 1.2; P=0.016). In contrast, both initial and last lactate levels during ICU stay were not significantly associated. A similar trend was observed for unplanned ICU readmission within 120 h. On receiver operating characteristic analysis, the areas under the curve (AUC) of the initial, last, and peak lactate levels were 0.61, 0.53, and 0.63, respectively. The peak lactate level during ICU admission is independently associated with unplanned ICU readmission within both, 48 and 120 h among surgical ICU patients. However, the lactate level has relatively poor predictive capability for unplanned ICU readmissions, and a new model is needed to predict unplanned ICU readmissions among surgical patients.

Impact of Glasgow Coma Scale scores on unplanned intensive care unit readmissions among surgical patients.

Physiological instability at discharge from intensive care units (ICU) is known to increase readmission rates among critically ill patients. However, associations between consciousness levels at discharge and readmission rates remain unclear. This study aimed to investigate the association between the Glasgow Coma Scale (GCS) score at discharge and unplanned ICU readmissions in surgical patients. This retrospective cohort study in a single tertiary academic hospital analyzed the electronic health records of adults aged 18 years or older, who were discharged from the ICU between January 2012 and December 2018. The primary endpoint was unplanned readmission within 48 hours after discharge. Multivariable logistic regression analysis was performed. Among 9,512 patients, unplanned readmissions occurred in 161 (1.7%). At discharge, GCS and verbal response scores of ≤13 (vs. ≥14) were associated with 2.28-fold higher unplanned readmissions within 48 hours [odds ratio (OR): 2.35, 95% confidence interval (CI): 1.51-3.65, P<0.001]. Sensitivity analysis showed that verbal response scores of ≤4 (vs. 5) at ICU discharge were associated with 2.21-fold higher unplanned readmissions within 48 hours (OR: 2.21, 95% CI: 1.49-3.29, P<0.001), whereas eye or motor responses at time of ICU discharge were not significantly associated with unplanned readmissions (P>0.05). In this surgical ICU population cohort, GCS scores at ICU discharge were significantly associated with unplanned readmissions within 48 hours. This association was stronger with GCS scores of ≤13 and with verbal response scores of ≤4 at time of discharge. These findings suggest that surgical ICU patients with GCS scores of ≤13 or verbal response scores of ≤4 should be monitored carefully for discharge in order to avoid unplanned ICU readmissions.

Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory.

BackgroundUnplanned readmission of a hospitalized patient is an indicator of patients’ exposure to risk and an avoidable waste of medical resources. In addition to hospital readmission, intensive care unit (ICU) readmission brings further financial risk, along with morbidity and mortality risks. Identification of high-risk patients who are likely to be readmitted can provide significant benefits for both patients and medical providers. The emergence of machine learning solutions to detect hidden patterns in complex, multi-dimensional datasets provides unparalleled opportunities for developing an efficient discharge decision-making support system for physicians and ICU specialists.Methods and findingsWe used supervised machine learning approaches for ICU readmission prediction. We used machine learning methods on comprehensive, longitudinal clinical data from the MIMIC-III to predict the ICU readmission of patients within 30 days of their discharge. We incorporate multiple types of features including chart events, demographic, and ICD-9 embeddings. We have utilized recent machine learning techniques such as Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM), by this we have been able to incorporate the multivariate features of EHRs and capture sudden fluctuations in chart event features (e.g. glucose and heart rate). We show that our LSTM-based solution can better capture high volatility and unstable status in ICU patients, an important factor in ICU readmission. Our machine learning models identify ICU readmissions at a higher sensitivity rate of 0.742 (95% CI, 0.718–0.766) and an improved Area Under the Curve of 0.791 (95% CI, 0.782–0.800) compared with traditional methods. We perform in-depth deep learning performance analysis, as well as the analysis of each feature contribution to the predictive model.ConclusionOur manuscript highlights the ability of machine learning models to improve our ICU decision-making accuracy and is a real-world example of precision medicine in hospitals. These data-driven solutions hold the potential for substantial clinical impact by augmenting clinical decision-making for physicians and ICU specialists. We anticipate that machine learning models will improve patient counseling, hospital administration, allocation of healthcare resources and ultimately individualized clinical care.

Betwixt and between: a surgical post-acute treatment unit (SPA) for the optimal care of elderly patients with isolated hip fractures.

A performance improved project identified elderly trauma patients to have a disproportionate incidence of complications. The purpose of this study was to assess the efficacy of a small specialty care unit to decrease complications in patients who no longer warrant care in an intensive care unit (ICU). A surgical post-acute treatment unit (SPA) was developed with focused attention to cognition, nutrition, respiration, and mobilization needs of patients who no longer had physiologic need for an intensive care unit environment, but were still in need of increased attention at the bedside. While ICU and hospital lengths of stay were unchanged, patients placed in the SPA experienced less complications and required less unplanned ICU re-admissions. Geriatric patients, especially the elderly, are not simply old adults. They have unique needs as a consequence of the aging process, which can be encompassed by four pillars of intercession: cognition, nutrition, respiration, and mobilization. By adapting a physical environment supported by bedside attention to address the interwoven needs of geriatric and elderly patients who no longer care in an ICU, complications and unplanned return admissions to the ICU can be decreased. III.

The outcomes and prognostic factors of the patients with unplanned intensive care unit readmissions: Erratum.

The outcomes and prognostic factors of the patients with unplanned intensive care unit readmissions: Erratum.

The outcomes and prognostic factors of the patients with unplanned intensive care unit readmissions.

This retrospective cohort study investigated the outcomes of patients with unplanned intensive care unit (ICU) readmission.All of the patients readmitted to ICU within 48 hours between 2010 and 2016 were enrolled.A total of 99 patients early readmitted to ICU were identified and their mean age of the patients was 68.8 ± 14.8 years. Respiratory failure was the most common cause of ICU readmission (n = 48, 48.5%), followed by acute myocardial ischemia or worsening heart failure (n = 25, 25.3%), sepsis (n = 22, 22.2%), gastrointestinal disease (n = 16, 16.2%), and neurologic disease (n = 11, 11.1%). The median length of stay in the ICU and hospital was 7 (IQR, 4–11.5) and 32 (IQR, 15.5–48.5) days, respectively. A total of 34 patients died during the hospital stay and the rate of in-hospital mortality was 34.3%. Patients with higher APACHE II scores (adjusted odds ratio [OR], 1.17; 95% CI, 1.02–1.33), underlying malignancy (adjusted OR, 4.70; 95% CI, 1.19–18.57), and cardiovascular organ dysfunction (adjusted OR, 5.14; 95% CI, 1.24–21.38) were more likely to die.The mortality rate of ICU readmission patients was high, especially for those with higher APACHE II score, underlying malignancy and cardiovascular organ dysfunction.