Assessing the Impact of Emergency Transfers in Pediatric Cardiology.

PSY112 - Healthcare Resource Use (HRU) Associated with Severe Adverse Events (AES) Of Interest in Adults With Relapsed or Refractory (R/R) B-Precursor Acute Lymphoblastic Leukemia (All) In Eu-4 Countries

BackgroundAcute kidney injury (AKI) is defined as oliguria or rise in serum creatinine but oliguria alone as a diagnostic criterion may over-diagnose AKI.ObjectivesGiven the association between fluid overload and AKI, we aimed to determine if positive fluid balance can complement the known parameters in assessing outcomes of AKI.DesignProspective observational study.SettingTeaching hospital in Vancouver, Canada.Patients111 consecutive patients undergoing elective cardiac surgery from January to April 2012.MeasurementsOutcomes of cardiac surgery intensive care unit (CSICU) and hospital length of stay (LOS) in relation to fluid balance, urine output and serum creatinine.MethodsAll fluid input and output was recorded for 72 hours post-operatively. Positive fluid balance was defined as >6.5 cc/kg. Daily serum creatinine and hourly urine output were recorded and patients were defined as having AKI according to the AKIN criteria.ResultsOf the patients who were oliguric, those with fluid overload trended towards longer LOS than those without fluid overload [CSICU LOS: 62 and 39 hours (unadjusted p-value 0.02, adjusted p-value 0.58); hospital LOS: 13 and 9 days (unadjusted p-value: 0.05, adjusted p-value: 0.16)]. Patients with oliguria who were fluid overloaded had similar LOS to patients with overt AKI (change in serum creatinine ≥ 26.5 µmol/L), [CSICU LOS: 62 and 69 hours (adjusted p value: 0.32) and hospital LOS: 13 and 14 days (adjusted p value: 0.19)]. Patients with oliguria regardless of fluid balance had longer CSICU LOS (adjusted p value: 0.001) and patients who were fluid overloaded in the absence of AKI had longer hospital LOS (adjusted p value: 0.02).LimitationsSingle centre, small sample, LOS as outcome.ConclusionsOliguria and positive fluid balance is associated with a trend towards longer LOS as compared to oliguria alone. Fluid balance may therefore be a useful marker of AKI, in addition to urine output and serum creatinine.

Although patients readmitted to intensive care units (ICUs) typically have poor outcomes, ICU readmission rates have not been studied as a measure of hospital performance. To determine variation in ICU readmission rates across hospitals and associations of readmission rates with other ICU-based measures of hospital performance. Observational cohort study. One hundred three thousand nine hundred eighty four consecutive ICU patients who were admitted to twenty eight hospitals who were then transferred to a hospital ward in those 28 hospitals. Predicted risk of in-hospital death and ICU length of stay (LOS) were determined by a validated method based on age, ICU admission source, diagnosis, comorbidity, and physiologic abnormalities. Severity-adjusted mortality rates, LOS, and readmission rates were determined for each hospital. One or more ICU readmissions occurred in 5.8% patients who were initially classified as postoperative and in 6.4% patients who were initially classified as nonoperative. In-hospital mortality rate was 24.7% in patients who were readmitted as compared with 4.0% in other patients (P < 0.001). After adjusting for predicted risk of death, the odds of death remained 7.5 times higher (OR 7.5, 95% CI, 6.8-8.3). Readmitted patients also had longer (P < 0.001) ICU LOS (5.2 vs. 3.7 days) and hospital LOS (29.3 vs. 11.7 days). Severity-adjusted readmission rates varied across hospitals from 4.2% to 7.6%. Readmission rates were not correlated with severity-adjusted hospital mortality, ICU LOS, or hospital LOS. ICU patients who were subsequently readmitted have a higher risk of death and longer LOS after adjusting for severity of illness. However, readmission rates were not associated with severity-adjusted mortality or LOS. Those data indicate that ICU readmission may capture other aspects of hospital performance and may be complementary to these measures.

The nature of the volume-outcome relationship in cases with severe traumatic brain injury (TBI) remains unclear, with considerable interhospital variation in patient outcomes. The objective of this study was to understand the state of the volume-outcome relationship at different levels of trauma centers in the United States. The authors queried the National Trauma Data Bank for the years 2007-2014 for patients with severe TBI. Case volumes for each level of trauma center organized into quintiles (Q1-Q5) served as the primary predictor. Analyzed outcomes included in-hospital mortality, total hospital length of stay (LOS), and intensive care unit (ICU) stay. Multivariable regression models were performed for in-hospital mortality, overall complications, and total hospital and ICU LOSs to adjust for possible confounders. The analysis was stratified by level designation of the trauma center. Statistical significance was established at p < 0.001 to avoid a type I error due to a large sample size. A total of 122,445 patients were included. Adjusted analysis did not demonstrate a significant relationship between increasing hospital volume of severe TBI cases and in-hospital mortality, complications, and nonhome hospital discharge disposition among level I-IV trauma centers. However, among level II trauma centers, hospital LOS was longer for the highest volume quintile (adjusted mean difference [MD] for Q5: 2.83 days, 95% CI 1.40-4.26 days, p < 0.001, reference = Q1). For level III and IV trauma centers, both hospital LOS and ICU LOS were longer for the highest volume quintile (adjusted MD for Q5: LOS 4.6 days, 95% CI 2.3-7.0 days, p < 0.001; ICU LOS 3.2 days, 95% CI 1.6-4.8 days, p < 0.001). Higher volumes of severe TBI cases at a lower level of trauma center may be associated with a longer LOS. These results may assist policymakers with target interventions for resource allocation and point to the need for careful prehospital decision-making in patients with severe TBI.

50 Short Term Use of Neuromuscular Blocking Agents in Post Rapid Sequence Intubation Patients Are Not Harmful, and May Be Beneficial

Standardized diagnostic criteria for malnutrition were developed by the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition (AND/ASPEN) in 2012. The criteria as a whole has had little validation, and the effect of underlying condition on the impact of malnutrition has not been well studied. We measured the association between severe malnutrition and hospital length of stay (LOS), intensive care unit (ICU) LOS, and mortality among critically ill inpatients. We analyzed hospital records from 5606 patients whose admission included an ICU stay. Associations between severe malnutrition and LOS and mortality were examined by multivariable linear and logistic regression. Thirteen percent were diagnosed with severe malnutrition. These had significantly longer hospital LOS (18 [interquartile range 10-35] days vs 8 [5-14] days), total ICU LOS (7 [3-15] days vs 3 [1-6] days) and in-hospital mortality (odds ratio [OR] 2.78, 95% confidence interval [CI] 2.33-3.31), compared with those without severe malnutrition. After adjusting for demographics, we found significant interactions between severe malnutrition and ICU location. Patients with malnutrition in the cardiothoracic surgery ICU experienced the largest increases in hospital LOS (21.10 days, 95% CI 18.58-23.61), ICU LOS (12.14 days, 95% CI 10.41-13.87), and in-hospital mortality (OR 8.78, 95% CI 5.11-15.07). Critically ill patients diagnosed with severe malnutrition based on the AND/ASPEN diagnostic characteristics experienced longer hospital and ICU LOS and increased mortality. The magnitude of effect of malnutrition was modified by ICU location, underscoring the need to identify the major comorbidities associated with malnutrition.

In an attempt to improve patient care, a perioperative complex spine surgery management protocol was developed through collaboration between spine surgeons and neuroanesthesiologists. The aim of this study was to investigate whether implementation of the protocol in 2015 decreased total hospital and intensive care unit (ICU) length of stay (LOS) and complication rates after elective complex spine surgery. A retrospective cohort study was conducted by review of the medical charts of patients who underwent elective complex spine surgery at an academic medical center between 2012 and 2017. Patients were divided into 2 groups based on the date of their spine surgery in relation to implementation of the spine surgery protocol; before-protocol (January 2012 to March 2015) and protocol (April 2015 to March 2017) groups. Outcomes in the 2 groups were compared, focusing on hospital and ICU LOS, and complication rates. A total of 201 patients were included in the study; 107 and 94 in the before-protocol and protocol groups, respectively. Mean (SD) hospital LOS was 14.8±10.8 days in the before-protocol group compared with 10±10.7 days in the protocol group (P<0.001). The spine surgery protocol was the primary factor decreasing hospital LOS; incidence rate ratio 0.78 (P<0.001). Similarly, mean ICU LOS was lower in the protocol compared with before-protocol group (4.2±6.3 vs. 6.3±7.3 d, respectively; P=0.011). There were no significant differences in the rate of postoperative complications between the 2 groups (P=0.231). Implementation of a spine protocol reduced ICU and total hospital LOS stay in high-risk spine surgery patients.

Introduction Communication is a key competency – the effective exchange of information is essential to a physician’s role. Currently, our centre does not have a communication tool to help guide point of care discussions between healthcare providers and during family meetings. Prognostic relationship of the BAUX score and ABSI index should be determined. An objective communication tool that shows predicted mortality, length of stay (LOS), and number of operations, specifically in our hospital using BAUX index and ABSI score will allow patients and healthcare providers to better understand prognosis, course in hospital, and develop appropriate expectations for outcomes in our centre. Methods In this cross-sectional study, all burn patients admitted to our Centre from 2012 to June 2022 were retrospectively recruited. Our burn registry was used to extract complete data of patient information including age, gender, %TBSA, burn depth, presence of inhalational injury, need for ventilator support, intensive care unit (ICU) admission days, hospital LOS, BAUX score, rBAUX score, and ABSI index. Patients were divided into three cohorts: all patients without an inhalation injury, a subgroup of smokers with and without an inhalation injury, and all patients with an inhalation injury. For each cohort, a mean LOS in hospital and/or ICU, number of burn operations, and mortality rate per incremental BAUX score and ABSI index was computed. Results A total of 839 patients were included, 725 without and 114 (13.6%) with an inhalation injury. A subgroup of patients (n=286) smokers with and without inhalational injury were separately analyzed. With severity of burn and presence of inhalational injury, both BAUX score and ABSI index show an incremental increase in LOS in hospital, number of operations, and increased mortality. Smokers with rBAUX ≥110 had the longest LOS in hospital, 78.4 hospital days and 35 ICU days. Interestingly, all patients with ABSI 6-7 had the longest LOS/%TBSA and those patients who additionally had an inhalational injury had the highest LOS/%TBSA (5.1 days/%TBSA). Increase in BAUX and ABSI did not correlate with increase in LOS/%TBSA. For BAUX ≥ 90 and ABSI ≥ 8, number of operations and mortality exponentially increased. Conclusions Patients with BAUX ≥ 90 and ABSI ≥ 8 should be counselled on a complex course in hospital. Higher BAUX and ABSI correlate with increased mean LOS and number of operations but not LOS/%TBSA. Using our Centre’s burn registry, we can predict course in hospital and provide this to patients, family, and healthcare providers before tertiary centre transfer and admission. Applicability of Research to Practice An objective communication model showing the burn centre’s mean LOS, LOS/%TBSA, number of operations, and risk of mortality, can help guide physician-patient and physician-healthcare provider communication. This tool will provide realistic burn recovery expectations at admission, family meetings, and when discussing consent.

BackgroundThere are limited published data on the epidemiology of skin and soft tissue infections (SSTIs) requiring intensive care unit (ICU) admission. This study intended to describe the annual prevalence, characteristics, and outcomes of critically ill adult patients admitted to the ICU for an SSTI. MethodsThis was a registry-based retrospective cohort study, using data submitted to the Australian and New Zealand Intensive Care Society Adult Patient Database for all admissions with SSTI between 2006 and 2017. The inclusion criteria were as follows: primary diagnosis of SSTI and age ≥16 years. The exclusion criteria were as follows: ICU readmissions (during the same hospital admission) and transfers from ICUs from other hospitals. The primary outcome was in-hospital mortality, and the secondary outcomes were ICU mortality and length of stay (LOS) in the ICU and hospital with independent predictors of outcomes. ResultsAdmissions due to SSTI accounted for 10 962 (0.7%) of 1 470 197 ICU admissions between 2006 and 2017. Comorbidities were present in 25.2% of the study sample. The in-hospital mortality was 9% (991/10 962), and SSTI necessitating ICU admission accounted for 0.07% of in-hospital mortality of all ICU admissions between 2006 and 2017. Annual prevalence of ICU admissions for SSTI increased from 0.4% to 0.9% during the study period, but in-hospital mortality decreased from 16.1% to 6.8%. The median ICU LOS was 2.1 days (interquartile range = 3.4), and the median hospital LOS was 12.1 days (interquartile range = 20.6). ICU LOS remained stable between 2006 and 2017 (2.0–2.1 days), whereas hospital LOS decreased from 15.7 to 11.2 days. Predictors for in-hospital mortality included Australian and New Zealand Risk of Death scores [odds ratio (OR): 1.07; confidence interval (CI) (1.05, 1.09); p < 0.001], any comorbidity except diabetes [OR: 2.00; CI (1.05, 3.79); p = 0.035], and admission through an emergency response call [OR: 2.07; CI (1.03, 4.16); p = 0.041]. ConclusionsSSTIs are uncommon as primary ICU admission diagnosis. Although the annual prevalence of ICU admissions for SSTI has increased, in-hospital mortality and hospital LOS have decreased over the last decade.

To determine the effects of dexmedetomidine versus propofol on extubation time, intensive care unit (ICU) length of stay, total hospital length of stay and in-hospital mortality rates in cardiac surgery patients. Recovery from cardiovascular surgery involves weaning from mechanical ventilation. Mechanical ventilation decreases the work of breathing for patients by inhaling oxygen and exhaling carbon dioxide via a ventilator or breathing machine. Prolonged mechanical ventilation is associated with complications, such as pneumonia and lung injury, and increases the risk of morbidity and mortality. Major risk factors that contribute to lung injury are due to high tidal volumes and barotrauma. Cardiac surgery patients remain on the ventilator postoperatively due to the high dose opioid-based anesthesia and the initial vulnerable hemodynamic state. An important component of postoperative management following cardiac surgery is the use of sedation to reduce the stress response, facilitate assisted ventilation, and provide anxiolysis. Propofol and dexmedetomidine are two common sedative agents with differing pharmacological profiles used to provide comfort and minimize hemodynamic disturbances during this recovery phase. Choice of drug may have an impact on length of mechanical ventilation, length of stay and mortality. Participants included were ≥18 years, of any gender or ethnicity, undergoing valvular surgery, coronary artery bypass graft (CABG) surgery, or valvular surgery and CABG. Studies were excluded if participants received both dexmedetomidine and propofol concurrently as a primary sedative. Interventions were propofol compared to dexmedetomidine as continuous infusions for sedation after cardiac surgery. All variations of dosages and duration of both sedative agents were included. Outcomes of interest were: total time (hours) of mechanical ventilation after cardiac surgery, specifically from end of surgery to extubation; total length of stay (LOS) in the ICU (hours) following cardiac surgery, specifically from ICU admission to transfer to medical ward; total hospital LOS (hours) following cardiac surgery, from date of admission to date of discharge; and in-hospital mortality rates, from date of admission to date of discharge. Randomized controlled trials (RCTs), controlled trials, and prospective and retrospective cohort studies were considered for inclusion. A search was conducted in MEDLINE via PubMed, Embase, Trip Database, ProQuest Nursing and Allied Health Source Database, Web of Science, ProQuest Dissertations and Theses Global, and MedNar to locate both published and unpublished studies between January 1, 1999 and November 23, 2017. Two reviewers assessed the methodological quality using standardized critical appraisal instruments from the Joanna Briggs Institute System for the Unified Management, Assessment and Review of Information (JBI SUMARI). Quantitative data were extracted using the standardized data extraction tool from JBI SUMARI. Data were pooled using Comprehensive Meta-Analysis Software Version 3 (Biostat, NJ, USA). Mean differences (95% confidence interval [CI]) and effect size estimates were calculated for continuous outcomes. Meta-analysis using a random-effects model was performed for length of mechanical ventilation, ICU LOS, and hospital LOS. Results have been presented in narrative form when findings could not be pooled using meta-analysis. Standard GRADE (Grading of Recommendations, Assessment, Development, and Evaluation) evidence assessment of outcomes has been reported. A total of four studies were included in the review. Meta-analysis of three cohort studies revealed dexmedetomidine to be superior to propofol with an average reduction of 4.18 hours (95% CI -6.69 to -1.67, p = 0.001) on the extubation times, an average 9.89 hour (95% CI -18.6 to -1.19, p = 0.03) reduction in ICU LOS, and an average 37.9 hour (95% CI, -60.41 to -15.46, p = 0.00) reduction in overall hospital LOS. A RCT was excluded from pooling for meta-analysis, but its results were congruent with meta-analysis results. There was lack of sufficient data to perform meta-analysis on in-hospital mortality rates. In postoperative cardiac surgery patients, dexmedetomidine is associated with a shorter time to extubation, shorter ICU LOS, and shorter hospital LOS in postoperative cardiac surgery patients compared to propofol. The quality of evidence for these findings however is low and no recommendations can be made to change current practice. There was insufficient evidence to determine significant differences in-hospital mortality rates. Sedation protocols still need to be formulated.There are significant gaps in the literature. Areas of further research include additional well-designed and appropriately powered RCTs with wide inclusion criteria to reflect this surgical population; quantitative, transparent, and standardized sedation, weaning, and extubation protocols; precise and standardized methods and measurements for interventions and outcomes, and short- and long-term morbidity and mortality follow-up.

Late recognition of in-hospital deterioration is a source of preventable harm. Emergency transfers (ET), when hospitalized patients require intensive care unit (ICU) interventions within 1 h of ICU transfer, are a proximal measure of late recognition associated with increased mortality and length of stay (LOS). To apply diagnostic process improvement frameworks to identify missed opportunities for improvement in diagnosis (MOID) in ETs and evaluate their association with outcomes. A single-center retrospective cohort study of ETs, January 2015 to June 2019. ET criteria include intubation, vasopressor initiation, or 60 mL/kg fluid resuscitation 1 h before to 1 h after ICU transfer. The primary exposure was the presence of MOID, determined using SaferDx. Cases were screened by an ICU and non-ICU physician. Final determinations were made by an interdisciplinary group. Diagnostic process improvement opportunities were identified. Primary outcomes were in-hospital mortality and posttransfer LOS, analyzed by multivariable regression adjusting for age, service, deterioration category, and pretransfer LOS. MOID was identified in 37 of 129 ETs (29%, 95% confidence interval [CI] 21%-37%). Cases with MOID differed in originating service, but not demographically. Recognizing the urgency of an identified condition was the most common diagnostic process opportunity. ET cases with MOID had higher odds of mortality (odds ratio 5.5; 95%CI 1.5-20.6; p = .01) and longer posttransfer LOS (rate ratio 1.7; 95%CI 1.1-2.6; p = .02). MOID are common in ETs and are associated with increased mortality risk and posttransfer LOS. Diagnostic improvement strategies should be leveraged to support earlier recognition of clinical deterioration.

Trends in Acute Myocardial Infarction in Young Patients and Differences by Sex and Race, 2001 to 2010

Area deprivation index and social vulnerability index in Milwaukee County: Impact on hospital outcomes after traumatic injuries

PurposeTo assess the occurrence of hyperlactatemia among patients admitted to the intensive care unit (ICU) with diabetic ketoacidosis (DKA), and effect on in-hospital mortality. Materials and methodsA retrospective, multicentre, cohort study of adult patients admitted to ICU with a primary diagnosis of DKA in Australia and New Zealand, utilising a pre-existing dataset. The primary exposure variable was lactate, dichotomised into normolactatemia (lactate <2.0 mmol/L) and hyperlactatemia (lactate ≥ 2.0 mmol/L) groups. The primary outcome was in-hospital mortality. Secondary outcomes included ICU and hospital length of stay (LOS), requirement for ventilation, renal replacement therapy (RRT) and inotropes. ResultsThe final dataset included 9061 patients. Hyperlactatemia was associated with in-hospital mortality (Odds Ratio [OR] 1.785 (95% CI 1.122–2.841, p = 0.014), hospital LOS (Geometric mean ratio [GMR] 1.063, 95% CI 1.025–1.103, p = 0.001), ICU LOS (GMR 1.057, 95% CI 1.026–1.09. p < 0.001), RRT (OR 2.198, 95% CI 1.449–3.334, p < 0.001) and inotropes (OR 1.578, 95% CI 1.311–1.899, p < 0.001). These associations persisted in Type 2 but not Type 1 diabetics. ConclusionsHyperlactatemia in patients admitted to ICU with DKA is associated with higher mortality, longer hospital and ICU LOS, and higher rates of mechanical ventilation, RRT and inotropes.

DOES THE CLINICAL FRAILTY SCALE PREDICT ADVERSE OUTCOMES?