Probability Of In-hospital Mortality Research Articles

Association of Obesity With Clinical Outcomes in Neurocritically Ill Patients

Background: To evaluate whether the obesity paradox exists in neurocritically ill patients.Methods: This was a retrospective, observational study of patient admitted to the neurosurgical intensive care unit (ICU) from January 2013 to December 2019. The subjects were classified into two groups: the non-obese group (body mass index [BMI] < 25 kg/m2) and the overweighted or obese group (BMI ≥ 25 kg/m2). The primary endpoint was in-hospital mortality. Results: A total of 527 patients were included in this study. The mean BMI was 23.7 ± 3.6 kg/m2. Of all neurosurgical patients, 157 patients were overweighted or obese. There were no significant differences in in-hospital mortality, 28-day mortality, and ICU mortality between the two groups (all p > 0.05). BMI on ICU admission was similar between survivors and non-survivors at discharge (p = 0.596). In the multivariable analysis, Acute Physiology and Chronic Health Evaluation (APACHE) II score on ICU admission, invasive intracranial pressure (ICP) monitoring, and use of more than one hyperosmolar agent were identified to be significantly associated with in-hospital mortality. However, BMI on ICU admission, and serum albumin level were not associated with in-hospital mortality. The obesity demonstrated a borderline significance relationship with the probability of in-hospital mortality (p=0.073). Conclusions: In this study, BMI on ICU admission, and serum albumin level demonstrated a lack of significant association with in-hospital mortality. Clinical factors including APHCHE II score, ICP monitoring, and hyperosmolar therapy were identified to be associated with prognosis in neurocritically ill patients. Eventually, the impact of the obesity paradox on these patients remains unclear.

EGS plus: Predicting futility in LVAD patients with emergency surgical disease

BackgroundWhile emergent, non-cardiac surgery can be safely performed in LVAD patients, the inherent perioperative challenges of these rare procedures and the perception that these patients may be poor surgical candidates can contribute to reluctance to perform necessary emergency general surgery (EGS) procedures. We, therefore, sought to identify predictors of inpatient mortality to assist perioperative decision-making. MethodsThe Nationwide Inpatient Sample (2010-2015Q3) was used to identify patients with previously placed LVADs with a subsequent EGS admission diagnosis. Multivariable logistic regression analysis was performed to identify independent predictors of 30-day mortality, and a risk-adjusted probability of death was calculated for significant patient subgroups across age. Additional demographic variables were included in the regression due to clinical relevance. ResultsThere were 1805 (weighted) LVAD-EGS patients with an overall mortality rate of 11%. Independent predictors of mortality were intestinal ischemia and sepsis present on admission. Patients older than 70 with sepsis had an 80% probability of in-hospital mortality (10.6 OR, 1.70–65.5 95% CI) while those over 70 presenting with intestinal ischemia had a 38% probability of death (3.6 OR, 1.50–8.78 95% CI). Mortality risk for younger patients with sepsis was still approximately 50%. ConclusionOlder LVAD patients presenting with either sepsis or intestinal ischemia have a substantial mortality risk while younger patients have a modest risk. These results can be used to guide treatment discussions when emergency surgery is being considered in LVAD patients.

Impact of the COVID-19 Pandemic on the Use and Outcomes of Cardiac Procedures in COPD Patients.

(1) Background: The aim of this study was to assess the effects of the COVID-19 pandemic on the use and outcomes of cardiac procedures among people with chronic obstructive pulmonary disease (COPD) in Spain. (2) Methods: We used national hospital discharge data to select patients admitted to hospital with a diagnosis of COPD from 1 January 2019 to 31 December 2020. (3) Results: The number of COPD patients hospitalized in 2019 who underwent a cardiac procedure was 4483, 16.2% higher than in 2020 (n = 3757). The length of hospital stay was significantly lower in 2020 than in 2019 (9.37 vs. 10.13 days; p = 0.004), and crude in-hospital mortality (IHM) was significantly higher (5.32% vs. 4.33%; p = 0.035). Multivariable logistic regression models to assess the differences in IHM from 2019 to 2020 showed Odds Ratio (OR) values over 1, suggesting a higher risk of dying in 2020 compared to in 2019. However, the ORs were only statistically significant for “any cardiac procedure” (1.18, 95% CI 1.03–1.47). The Charlson comorbidity index increased IHM for each of the procedures analyzed. The probability of IHM was higher for women and older patients who underwent coronary artery bypass graft or open valve replacement procedures. Suffering a COVID-19 infection was associated with significantly higher mortality after cardiac procedures. (4) Conclusions: The COVID-19 pandemic limited the access to healthcare for patients with COPD.

External validation of 5A score model for predicting in-hospital mortality among the accidental hypothermia patients: JAAM-Hypothermia study 2018–2019 secondary analysis

BackgroundThe 5A score including five components “Age, Activities of daily living, Arrest, Acidemia and Albumin” was developed as an easy-to-use screening tool for predicting in-hospital mortality among patients with accidental hypothermia. However, the external validity of the 5A score has not yet been evaluated. We aimed to perform an external validation of the 5A score model.MethodThis secondary analysis of the multicenter, prospective cohort Japanese Association for Acute Medicine-Hypothermia Study (2018–2019), which was conducted at 87 and 89 institutions throughout Japan, collected data from December 2018 to February 2019 and from December 2019 to February 2020. Adult accidental hypothermia patients whose body temperature was 35 °C or less were included in this analysis. The probability of in-hospital mortality was calculated using a logistic regression model of the 5A score. The albumin was not recorded in this database; thus, it was imputed by estimation. Predictions were compared with actual observations to evaluate the calibration of the model. Furthermore, decision-curve analysis was used to evaluate the clinical usefulness.ResultsOf the 1363 patients registered in the database, data of 1139 accidental hypothermia patients were included for analysis. The median [interquartile range] age was 79 [68–87] years, and there were 625 men (54.9%) in the study cohort. The predicted probability and actual observation by risk groups produced the following results: low 7% (5.4–8.6), mild 19.1% (17.4–20.8), moderate 33.2% (29.9–36.5), and high 61.9% (55.9–67.9) predicted risks, and the low 12.4% (60/483), mild 17.7% (59/334), moderate 32.6% (63/193), and high 69% (89/129) observed mortality. These results indicated that the model was well calibrated. Decision-curve analysis visually indicated the clinical utility of the 5A score model.ConclusionThis study indicated that the 5A score model using estimated albumin value has external validity in a completely different dataset from that used for the 5A model development. The 5A score is potentially helpful to predict the mortality risk and may be one of the valuable information for discussing the treatment strategy with patients and their family members.

Corticosteroid Therapy in COVID-19 Associated With In-hospital Mortality in Geriatric Patients: A Propensity Matched Cohort Study.

BackgroundFew data are available on the prognosis of older patients who received corticosteroids for COVID-19. We aimed to compare the in-hospital mortality of geriatric patients hospitalized for COVID-19 who received corticosteroids or not.MethodsWe conducted a multicentric retrospective cohort study in 15 acute COVID-19 geriatric wards in the Paris area from March to April 2020 and November 2020 to May 2021. We included all consecutive patients aged 70 years and older who were hospitalized with confirmed COVID-19 in these wards. Propensity score and multivariate analyses were used.ResultsOf the 1 579 patients included (535 received corticosteroids), the median age was 86 (interquartile range 81–91) years, 56% of patients were female, the median Charlson Comorbidity Index (CCI) was 2.6 (interquartile range 1–4), and 64% of patients were frail (Clinical Frailty Score 5–9). The propensity score analysis paired 984 patients (492 with and without corticosteroids). The in-hospital mortality was 32.3% in the matched cohort. On multivariate analysis, the probability of in-hospital mortality was increased with corticosteroid use (odds ratio [OR] = 2.61 [95% confidence interval (CI) 1.63–4.20]). Other factors associated with in-hospital mortality were age (OR = 1.04 [1.01–1.07], CCI (OR = 1.18 [1.07–1.29], activities of daily living (OR = 0.85 [0.75–0.95], oxygen saturation < 90% on room air (OR = 2.15 [1.45–3.17], C-reactive protein level (OR = 2.06 [1.69–2.51], and lowest lymphocyte count (OR = 0.49 [0.38–0.63]). Among the 535 patients who received corticosteroids, 68.3% had at least one corticosteroid side effect, including delirium (32.9%), secondary infections (32.7%), and decompensated diabetes (14.4%).ConclusionsIn this multicentric matched-cohort study of geriatric patients hospitalized for COVID-19, the use of corticosteroids was significantly associated with in-hospital mortality.

Investigation Into the Effect of COVID-19 Infection on Length of Hospital Stay and Mortality in Patients With Rheumatoid Arthritis.

BackgroundSARS-CoV-2 (COVID-19) is a positive-stranded ribonucleic acid (RNA) virus of the coronavirus family, which has resulted in one of the most serious pandemics, with more than 14 million cases confirmed globally. Rheumatoid arthritis (RA) is estimated to be prevalent in 0.5-1% of the U.S. population. So far, there has been little evidence of COVID-19 infection and its propensity to result in increased mortality or length of hospital stay in patients with RA. To contribute to this body of literature, this study will assess the degree to which COVID-19 is associated with increased mortality and length of hospital stay in patients with RA while also taking into account these patients' comorbidities.MethodsOur retrospective study included 14,180 patients (age >18, median 58, range 18-90) who tested positive for COVID-19 or were assumed to have COVID-19 infection from January 1st, 2020, through July 31st, 2020. Patients were grouped based on the diagnosis of RA and COVID-19 infection versus those without RA. Patients who were diagnosed with systemic lupus erythematosus (SLE), chronic obstructive pulmonary disease, and hypertension were excluded. Covariates included age, body mass index (BMI), race, sex, maximum C-reactive protein value, maximum D-dimer value, and comorbid diabetes mellitus. Outcome measures were length of hospital stay (LOS), in-hospital mortality, intensive care unit (ICU) admission, ICU LOS, mechanical ventilation, time on mechanical ventilation, and discharge to hospice. The logistic regression model was used to estimate the probability of in-hospital mortality, ICU admission, placement on mechanical ventilation, discharge to hospice, and in-hospital mortality related to home anti-inflammatory use when comparing patients with RA and COVID-19 infection to COVID-19 infected patients without RA.ResultsOf the total 14,180 patients (males 57.1%, females 42.9%), 159 patients (1.1%), had a diagnosis of RA. There was no significant association between RA and hospital LOS, ICU admission, ICU LOS, LOS on mechanical ventilation, or discharge to hospice among those infected with COVID-19. Yet, RA was associated with higher mortality (OR: 1.65; 95% CI: 1.07-2.53; p=0.02) and placement on mechanical ventilation (OR: 1.82; 95% CI: 1.22-2.71; p<0.01) amidst patients infected with COVID-19.ConclusionThis study suggests that patients with RA and COVID-19 have a significantly increased likelihood of in-hospital mortality and placement on mechanical ventilation. While challenging to realize in a pandemic situation, large studies nationwide are necessary to improve our understanding of COVID-19 infection in patients diagnosed with RA.

Prediction of in-hospital mortality by using get with the guideline-heart failure (GWTG-HF) risk scores in patients hospitalized with heart failure

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): University Grants Commission Bangladesh Background Prognostic stratification using readily available clinical data can assist clinical decision making in heart failure. Get with the Guideline- Heart Failure (GWTG-HF) score approved by American Heart Association (AHA) can be used to inform hospitals about the expected in-hospital mortality of their patients. Purpose This study aims to predict in-hospital mortality of patients with heart failure using GWTG-HF score in order to give evidence based therapy to high risk patients. Methods We have included patients who were hospitalized with a diagnosis of heart failure from February 2020 to 15 January 2021. A total of 2038 patients were admitted during this period of which 144 patients were diagnosed with heart failure (7%). The GWTG-HF risk score uses 7 clinical factors collected at admission. These are older age, low systolic blood pressure, elevated heart rate, low serum sodium, elevated BUN, presence of COPD, and ethnicity. The probability of in-hospital mortality is estimated for an individual patient by summing points assigned to the value of each predictor for a total point score within a range of 0-100. These scores were calculated for 144 heart failure patients involved in this study. Results Death occurred in 29 heart failure patients (20.13%). Mean age was 59 ±13 years. Male/female ratio was 3.65. All patients were ethnically Bangladeshi Asian. 60% of patients had left ventricular ejection fraction (LVEF) &amp;lt;40%. Overall LVEF was median (IQR) 36% (30-45). Those who died were more likely to have a prior heart failure diagnosis and an LVEF &amp;lt;40%. The observed mortality was 0% for the GWTG-HF score 0-33, 14.14% for 34-50, 42% for 51-57, 40% for 58-61 and 50% with a score of 62-65. The observed mortality of our patients were much higher than expected GWTG-HF score (20% vs 2.8%). The probable reasons for increased mortality in our study could be 1) The number of patients having LVEF &amp;lt;40% is much higher (60%), 2) surgically uncorrected/absence of intervention for underlying valvular disease/advance heart failure/ischaemic cardiomyopathy, 3) different treatment regimens and non-compliance of patients regarding long-term medication. Additionally, those who died had higher serum creatinine and BUN and lower serum sodium and haemoglobin levels at admission. Further multi-centre study involving large population is needed to clarify higher death rate in heart failure patients in our population. Conclusion The GWTG-HF risk score can identify patients at high risk of in-hospital death to aid clinical decision making. The risk score could be used to inform hospitals about the expected mortality rates of patients with heart failure admitted to their hospital. Although GWTG-HF risk score is validated in different populations, the mortality rate in this study is greater than expected mortality due to aforementioned reasons. Abstract Figure. GWTG-HF Risk Score (Reference 1) Abstract Figure. Predicted and Observed Mortality Rates

A Preliminary Scoring Model to Predict In-hospital Mortality Risk for Geriatric Patients with Delirium

BACKGROUND: Elderly patients are at an increased risk of death, particularly those with altered mental status. AIM: We aimed to develop a scoring model from simple clinical data and routine laboratory testing to aid in predicting in-hospital mortality risk for geriatric patients with delirium. METHODS: A total of 73 hospitalized geriatric patients with delirium were included in the study. A multivariate regression analysis employed to obtain independent risk factors to predict in-hospital mortality. All patients were followed until dead or discharged from hospital. The formula of (B/SE)/lowest B/SE was used to calculate the scores for each variable with strong discrimination power to be included in scoring system. RESULTS: A total of 25 (34.2%) of patients were death when being hospitalized. The mean age of the patients was 73.27 ± 7.8. From a total of 20 probable variables, three variables were then included in constructing the scoring model; no caregiver (p &lt; 0.012), abnormal diastolic blood pressure (p &lt; 0.05), and abnormal serum SGOT levels (p &lt; 0.03). Each variable was scored as 1, following the use of formula. Total score ranges from 0 to maximum of 3. The cutoff score of ≥ 2 provided the best accuracy with sensitivity of 40% and specificity of 89.6% (p &lt; 0.001). The probability of in-hospital mortality was 8.8%, 32.6%, 70.8%, and 92.4% for the total score of 0, 1, 2, and 3, respectively. CONCLUSION: This novel scoring system with simple examination may aid to identify geriatric patients with delirium which possess higher risk for in-hospital mortality.

Electrocardiogram-based mortality prediction in patients with COVID-19 using machine learning

Funding AcknowledgementsType of funding sources: Public hospital(s). Main funding source(s): The Netherlands Organisation for Health Research and Development (ZonMw) University of Amsterdam Research Priority Area Medical IntegromicsOnBehalfCAPACITY-COVID19 RegistryBackgroundThe electrocardiogram (ECG) is an easy to assess, widely available and inexpensive tool that is frequently used during the work-up of hospitalized COVID-19 patients. So far, no study has been conducted to evaluate if ECG-based machine learning models are able to predict all-cause in-hospital mortality in COVID-19 patients.PurposeWith this study, we aim to evaluate the value of using the ECG to predict in-hospital all-cause mortality of COVID-19 patients by analyzing the ECG at hospital admission, comparing a logistic regression based approach and a DNN based approach. Secondly, we aim to identify specific ECG features associated with mortality in patients diagnosed with COVID-19. Methods and resultsWe studied 882 patients admitted with COVID-19 across seven hospitals in the Netherlands. Raw-format 12-lead ECGs recorded after admission (<72 hours) were collected, manually assessed, and annotated using pre-defined ECG features. Using data from five out of seven centers (n = 634), two mortality prediction models were developed: (a) a logistic regression model using manually annotated ECG features, and (b) a pre-trained deep neural network (DNN) using the raw ECG waveforms. Data from two other centers (n = 248) were used for external validation. Performance of both prediction models was similar, with a mean area under the receiver operating curve of 0.69 [95%CI 0.55–0.82] for the logistic regression model and 0.71 [95%CI 0.59–0.81] for the DNN in the external validation cohort. After adjustment for age and sex, ventricular rate (OR 1.13 [95% CI 1.01–1.27] per 10 ms increase), right bundle branch block (3.26 [95% CI 1.15–9.50]), ST-depression (2.78 [95% CI 1.03–7.70]) and low QRS voltages (3.09 [95% CI 1.02-9.38]) remained as significant predictors for mortality.ConclusionThis study shows that ECG-based prediction models at admission may be a valuable addition to the initial risk stratification in admitted COVID-19 patients. The DNN model showed similar performance to the logistic regression that needs time-consuming manual annotation. Several ECG features associated with mortality were identified.Figure 1: Overview of methods, using and example case: (left) logistic regression and (right) deep learning. This specific case had a high probability of in-hospital mortality (above the threshold of 30%). Follow-up of this case showed that the patient had died during admission. Figure. Overview of ML methods used

Optimal Blood Pressure at Vasopressor Weaning in Intensive Care Units — What Are Targets of Blood Pressure Management?

Objective: Vasopressors are one of the main treatments for severe hypotension or shock, which commonly occurs in intensive care unit (ICU) patients. However, only a few studies have been conducted on the appropriate targets for vasopressor weaning. This study aims to explore the effect of blood pressure at vasopressor weaning on the probability of in-hospital mortality. Design: Single-center retrospective observational study. Setting: ICU from Beth Israel Deaconess Medical Center between 2008 and 2019.PatientsICU patients who received vasopressor treatment were selected. Patients younger than 18 years old, died before vasopressor weaning or without blood pressure measurement at weaning were excluded. Finally, 8,298 patients were included. Result: General additive model (GAM) result showed that blood pressures at weaning had “U-shape” non-linear relationship with in-hospital mortality probability. The optimal values ​​of WSBP, WDBP, and WMAP are approximately 120, 65, and 80 mmHg, respectively. Compared with the lower blood pressure cohort, the sensitivity analysis results showed that when WSBP, WDBP, and WMAP are within 120-160, 50-65, >80 mmHg, the hospital mortality risk were lowest with HR(95%CI)= 0.37(0.32,0.43), 0.45(0.39,0.52) and 0.32(0.28,0.38), respectively. The results of the subgroup analysis explicated that the blood pressure booster weaning had an interaction with congestive heart failure, cerebrovascular disease, chronic pulmonary disease, diabetes, and renal disease. GAM results revealed that there were differences in the optimal weaning blood pressure of patients with different diagnoses. Conclusion: Higher vasopressor weaning blood pressure(WSBP>95, WDBP>50, WMAP>65 mmHg) can significantly improve survival, and the best target WSBP, WDBP, WMAP is 120-160, 50-65, and >80 mmHg. When treating patients with different diagnoses, the optimal blood pressure may shift, requiring comprehensive analysis in treatment strategy decision-making. Funding Statement: None to declare. Declaration of Interests: None to declare. Ethics Approval Statement: The study was an analysis of a third-party anonymized publicly available database with pre-existing institutional review board (IRB) approval.

Development and Validation of a Dynamic 48-Hour In-Hospital Mortality Risk Stratification for COVID-19 in a UK Teaching Hospital: A Retrospective Cohort Study

Background: While numerous point-of-admission disease severity models for COVID-19 have been proposed, disease stratification that accounts for changes in a patient’s condition while in hospital is urgently needed to facilitate patient management and resource allocation.Methods: We developed a prognostic model for 48-hour in-hospital mortality using 473 consecutive patients with COVID-19 presenting to a UK hospital between March 1 and September 12, 2020; and temporally validated using data on 405 patients presenting between September 13, 2020 and January 3, 2021.The primary outcome was all-cause in-hospital mortality. We additionally considered the competing risks of discharge from hospital and transfer to a tertiary Intensive Care Unit for extracorporeal membrane oxygenation. We adopted a landmarking approach to dynamic prediction that accounts for competing risks and informative missingness, and selected predictors using penalised regression. The model estimates, at any point during a hospital visit, the probability of in-hospital mortality during the next 48 hours.Results: Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, SpO2/FiO2 ratio, white cell count, presence of acidosis (pH Interpretation: Our model uniquely incorporates both static risk factors (e.g. age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient’s clinical condition. External validation outside the study hospital will be required before adoption.Funding: NIHR Cambridge Biomedical Research Centre, UKRI Medical Research CouncilDeclaration of Interest: None to declare. Ethical Approval: The study was approved by a UK Health Research Authority ethics committee (20/WM/0125). Patient consent was waived because the de-identified data presented here were collected during routine clinical practice; there was no requirement for informed consent.

Clinical Characteristics and Outcomes of 821 Older Patients With SARS-Cov-2 Infection Admitted to Acute Care Geriatric Wards.

BackgroundThere is limited information describing the characteristics and outcomes of hospitalized older patients with confirmed coronavirus disease 2019 (COVID-19).MethodWe conducted a multicentric retrospective cohort study in 13 acute COVID-19 geriatric wards, from March 13 to April 15, 2020, in Paris area. All consecutive patients aged 70 years and older, with confirmed COVID-19, were enrolled.ResultsOf the 821 patients included in the study, the mean (SD) age was 86 (7) years; 58% were female; 85% had ≥2 comorbidities; 29% lived in an institution; and the median [interquartile range] Activities of Daily Living scale (ADL) score was 4 [2–6]. The most common symptoms at COVID-19 onset were asthenia (63%), fever (55%), dyspnea (45%), dry cough (45%), and delirium (25%). The in-hospital mortality was 31% (95% confidence interval [CI] 27–33). On multivariate analysis, at COVID-19 onset, the probability of in-hospital mortality was increased with male gender (odds ratio [OR] 1.85; 95% CI 1.30–2.63), ADL score <4 (OR 1.84; 95% CI 1.25–2.70), asthenia (OR 1.59; 95% CI 1.08–2.32), quick Sequential Organ Failure Assessment score ≥2 (OR 2.63; 95% CI 1.64–4.22), and specific COVID-19 anomalies on chest computerized tomography (OR 2.60; 95% CI 1.07–6.46).ConclusionsThis study provides new information about older patients with COVID-19 who are hospitalized. A quick bedside evaluation at admission of sex, functional status, systolic arterial pressure, consciousness, respiratory rate, and asthenia can identify older patients at risk of unfavorable outcomes.

Invasive pulmonary aspergillosis in cirrhotic patients: analysis of a 10-year clinical experience

BackgroundCirrhosis is not recognised as one of the main risk factors of invasive pulmonary aspergillosis (IPA), although its prevalence is increasing. The aim of our study was to identify factors for IPA in such patients with a positive Aspergillus sp. culture in respiratory samples and to evaluate its impact on outcome.MethodsWe conducted a monocentric retrospective study between January 2005 and December 2015. All cirrhotic patients hospitalised in our liver ICU with a positive Aspergillus sp. respiratory sample were included. These patients were case-matched with cirrhotic patients without positive Aspergillus respiratory sample. Finally, the patients were classified as having putative aspergillosis or colonisation according to the criteria described previously.ResultsIn total, 986 cirrhotic patients were admitted to ICU during the study period. Among these, sixty patients had a positive Aspergillus sp. respiratory sample. Chronic obstructive pulmonary disease (COPD) comorbidity and organ supports were significantly associated with Aspergillus colonisation. Seventeen patients (28%) were diagnosed as proven or putative IPA and 43 were considered as colonised by Aspergillus sp. The median delay between ICU admission and an IPA diagnosis was 2 [2–24] days. Only COPD was predictive of the presence of IPA (OR 6.44; 95% CI 1.43–28.92; p = 0.0151) in patients with a positive Aspergillus sp. culture. The probability of in-hospital mortality was 71% in the IPA group versus 19% in the colonisation group (p = 0.0001).ConclusionPatients with cirrhosis can be at risk of IPA, especially with COPD. Antifungal agents should be given as soon as possible mainly in cirrhotic patients with COPD.

Vasoactive-inotropic score as a predictor of in-hospital mortality in out-of-hospital cardiac arrest

Background. The Vasoactive-Inotropic Score (VIS) is an objective clinical tool used to quantify the need for cardiovas-cular support in children and adolescents after surgery and to predict prognosis of pediatric septic shock. Considering the post-cardiac arrest syndrome (PCAS) is a sepsis-like syndrome, we aimed to inves-tigate the correlation between VIS and in-hospital mortality in out-of-hospital car-diac arrest (OHCA) patients who achieved a sustained return of spontaneous circula-tion (ROSC) and admitted to the intensive care unit (ICU).Methods. A retrospective chart review of 504 OHCA patients who were admitted to the emergency room with OHCA from Jan 2015 to Dec 2016 was done. VIS was calculated with the recorded administra-tion rate of the drugs on electronic medi-cal record at the same time during the first 24 hours in ICU. The highest value of VIS in 24 hours (24hr-peak VIS) was used for investigating the correlation between VIS and in-hospital mortality.Results. Among 504 OHCA patients, 166 patients were admitted to the intensive care unit and 116 patients died during hospital stay. The probability of in-hospital mortality was significantly higher when 24hr-peak VIS was higher than 33.3 [Odds ratio (OR) = 3.18, 95% CI = 1.22 – 8.29, p value = 0.018]. Conclusion. 24hr-Peak VIS could be a good scoring system for predicting in-hospital mortality in OHCA patients who admit-ted to ICU. The AUC was 0.762 (95% CI = 0.690 to 0.825) and the optimal cut-off values were 33.3 (sensitivity 0.764, speci-ficity 0.610).

Burden of cytomegalovirus disease in allogeneic hematopoietic cell transplant recipients: a national, matched cohort study in an inpatient setting

Purpose of the studyNo studies have compared the risk of mortality or graft-versus-host disease, in an inpatient setting in France, in allogeneic hematopoietic cell transplant recipients who develop cytomegalovirus disease with those who do not. This study assessed the impact of cytomegalovirus disease on clinical outcomes and healthcare resource utilization in allogeneic hematopoietic cell transplant recipients using the French Programme de Médicalisation des Systèmes d'Information database. Patients and methodsRecipients who had undergone allogeneic hematopoietic cell transplant in French hospitals between 2008 and 2011 were included in this retrospective, matched cohort study. Those with cytomegalovirus disease were each matched with two allogeneic hematopoietic cell transplant recipients without cytomegalovirus disease according to demographic and clinical characteristics. Probabilities of in-hospital mortality, graft rejection and/or graft-versus-host disease, and healthcare resource utilization were compared up to 12 months after cytomegalovirus disease diagnosis. ResultsOverall, 4884 transplant recipients were enrolled, of which 194 had cytomegalovirus disease. Of these, 165 recipients with cytomegalovirus disease were matched to 330 without cytomegalovirus disease (1:2 ratio). The development of cytomegalovirus disease was associated with a significantly higher risk of in-hospital mortality (relative risk = 1.7, p = 0.0005) and higher cumulative number of inpatient days (p < 0.0001), but was not associated with a significantly higher risk of graft rejection and/or graft-versus-host disease or healthcare costs. ConclusionsDue to the increased risk of in-hospital mortality and higher cumulative number of inpatient days in allogeneic hematopoietic cell transplant recipients with cytomegalovirus disease versus those without, new strategies to prevent and manage cytomegalovirus disease are warranted.

Argininemia and plasma arginine bioavailability - predictive factors of mortality in the severe trauma patients?

BackgroundArginine is an amino acid determinant in the metabolic, immune and reparative responses to severe trauma. The present study aims to determine argininemia and plasma arginine bioavailability (PAB) in critical trauma patients and to analyze its correlation with prognosis.MethodsA prospective study of 23 critical trauma patients was undertaken. Aminoacidemias were determined, by ion exchange chromatography, at admission and in the first and third days and compared with those of 11 healthy individuals. PAB was calculated. Severity indexes and outcome parameters were recorded.ResultsValues of argininemia, citrullinemia and ornithinemia at the admission were significantly lower than those of the controls (arginine: 41.2 ± 20.6 versus 56.1 ± 11.9 μmol/L, P = 0.034). Hipoargininemia (<60 μmol/L) prevalence was 82.6 %. Mean PAB was 62.4 ± 25.6 %. Argininemia < 26 μmol/L constituted a significant predictive factor of in-hospital mortality [n = 4 (17.4 %); 75 versus 15.8 %, P = 0.04; odds ratio = 4.7; accuracy = 87 %] and lower actuarial survival (63.5 ± 43.9 versus 256.1 ± 33.3 days, P = 0.031). PAB <42 % [n = 6 (26.1 %)] was associated with higher lactacidemia levels (P = 0.033), higher in-hospital mortality (66.7 versus 11.8 %, P = 0.021; odds ratio = 5.7, accuracy = 82.6 %) and lower actuarial survival (87.2 ± 37.5 versus 261.4 ± 34.7 days, n.s.). Probability of in-hospital mortality was inversely and significantly related with PAB [61.8 ± 8.8 % (95 % CI 50.8–72.7) when PAB <41 % and 2.8 ± 1.9 % (95 % CI 1.9–8.3) when PAB > 81 %, P = 0.0001]. Charlson’s index ≥1, APACHE II ≥19.5, SOFA ≥7.5, and glutaminemia < 320 μmol/L were also predictive factors of actuarial survival.ConclusionsThose results confirm the high prevalence of arginine depletion in severe trauma patients and the relevance of argininemia and PAB as predictive factors of mortality in this context.

External validation of the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) multivariable prediction rule.

To validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) multivariable prediction rule using admission claims data. Retrospective claims database analysis. This analysis was performed using Humana admission claims data from January 2007 to March 2014. We included adult patients admitted for their first PE during this period (International Classification of Diseases, ninth edition, Clinical Modification code of 415.1x in in the primary position or secondary position when accompanied by a primary code for a PE complication). The IMPACT rule, consisting of age plus 11 comorbidities, was used to estimate patients' probability of in-hospital mortality and classify risk. Low risk was defined as in-hospital mortality ≤ 1.5%. IMPACT was evaluated by evaluating prognostic test characteristic values and 95% confidence intervals (CIs). A total of 23,858 patients admitted for PE were included, and 3.3% died in-hospital. The IMPACT prediction rule classified 2371 (9.9%) as low-risk; with a sensitivity of 97.6%, 95% CI: 96.1-98.5, specificity of 10.2%, 95% CI: 9.8-10.6, negative and positive predictive values of 99.2% (95% CI: 98.7-99.5) and 3.5% (95% CI: 3.3-3.8) and c-statistic of 0.70, 95% CI: 0.0.68-0.72, for in-hospital mortality. IMPACT classified 42.7% of patients < 65 years old as low-risk; with a sensitivity, specificity and c-statistic of 85.0%, 95% CI: 77.4-90.5, 43.3%, 95% CI: 42.0-44.7 and 0.74, 95% CI: 0.69-0.78, respectively. The IMPACT prediction rule was valid when implemented in a database consisting largely of Medicare claims. Following further external validation and direct comparison to commonly used clinical prediction rules, IMPACT may become a valuable tool for payers and hospitals wishing to retrospectively assess whether their PE patients are being kept hospitalized for the optimal period of time.

Abstract 18891: Racial Differences in End-of-life Care Associated With Heart Failure Hospitalizations in the United States: A Population-based Analysis From 2011-2012

Background and objectives: Racial disparities in healthcare delivery constitute a major public health problem in the US. There are few studies evaluating the effect of race on utilization of end-of-life (EOL) procedures in HF hospitalizations in the US. Hypothesis: Utilization of EOL procedures differs significantly between racial-ethnic groups independent of socioeconomic status (SES) or probability of in-hospital death. Methods: We used the 2011-2012 Nationwide/National Inpatient Sample to identify primary HF hospitalizations. EOL procedures of interest were intubation, tracheostomy and prolonged mechanical ventilation, hemodialysis, cardiopulmonary resuscitation, gastrostomy, enteral or parenteral nutrition. Relevant ICD-9 codes were used. We used residential ZIP code as a proxy for SES. Multivariate logistic models were used to evaluate racial differences in EOL care while adjusting for SES and probability of in-hospital mortality. Results: 375,740 hospitalizations representing 1.8 million hospitalizations nationwide were included in the study. Mean age was 72.6 (SD 14.6) years and 50.1% were women. Overall 7.81% were intubated, 0.69% underwent tracheostomy, and 6.55% underwent hemodialysis, 0.55% underwent CPR, 0.22% had a gastrostomy and 0.45% received enteral or parenteral nutrition. Blacks, Hispanics, Asians or Pacific Islanders and Other races were more likely to receive EOL procedures compared to Whites after adjusting for SES and probability of in-hospital death. (Fig) Use of any EOL procedure was associated with higher age and sex adjusted odds of in-hospital mortality (OR 6.54, 6.09 - 7.04; p&lt;0.001) and average charges ($76,917 vs. 35,841, p&lt;0.001). Conclusions: Racial-ethnic minorities hospitalized for HF are significantly more likely to receive aggressive EOL care compared to Whites. The reasons for racial differences in utilization of EOL care in HF should be investigated in future studies.

Validation of the multivariable In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule within an all-payer inpatient administrative claims database

ObjectiveTo validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule, in a database consisting only of inpatient claims.DesignRetrospective claims database analysis.SettingThe 2012 Healthcare Cost and Utilization...

41 UNDERSTANDING THE COMPARATIVE EFFECTIVENESS OF LAPAROSCOPIC RADICAL NEPHRECTOMY FOR PATIENTS WITH KIDNEY CANCER

INTRODUCTION AND OBJECTIVES: Although laparoscopic radical nephrectomy (LRN) is now a preferred treatment for many patients with kidney cancer, there is limited population-based data evaluating its comparative effectiveness relative to open radical nephrectomy (ORN). In this context, we compared recent trends in hospital-based outcomes among a nationally-representative sample of Medicare beneficiaries undergoing LRN vs. ORN. METHODS: Using linked SEER-Medicare data, we identified a population-based sample of patients treated with LRN or ORN for non-urothelial, non-metastatic kidney cancer from 2000 through 2005. For each patient, we measured an array of demographic (e.g., age), clinical (e.g., Charlson comorbidity index), and cancer-specific (e.g., tumor size and stage) characteristics. Next, we defined the following outcomes: ICU admission; prolonged length of stay (LOS); readmission within 30 days; and in-hospital mortality. We then fit multivariable logistic regression models to estimate the association between type of surgery and each clinical outcome, adjusting for measurable patient characteristics and year of surgery. RESULTS: Among our analytic sample, 2,108 (26%) and 5,895 (74%) patients underwent treatment with LRN and ORN, respectively. Patients treated with LRN were more likely to be White, female, of higher socioeconomic position, and to have a tumor size 4 cm (all p-values 0.05). After adjusting for demographic, clinical and tumor characteristics, the probability of ICU admission and prolonged LOS was 42.4% and 46.6% lower, respectively, for patients undergoing LRN vs. ORN (Figure, p 0.001). Conversely, although still uncommon, the adjusted probability of in-hospital mortality was 52% (p 0.041) higher for patients treated with a laparoscopic vs. open approach (Figure). CONCLUSIONS: In this population-based sample, patients treated with LRN had a lower likelihood of ICU admission and prolonged LOS, findings that support the convalescence benefits of laparoscopy. That in-hospital mortality was higher among patients treated with LRN suggests a potentially unanticipated consequence of this minimally-invasive technique and highlights the need for long-term monitoring following diffusion of new surgical technologies. Source of Funding: Edwin Beer Research Fellowship