Higher Risk Of In-hospital Mortality Research Articles

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy.

Background: Patients with acute heart failure (AHF) who require continuous renal replacement therapy (CRRT) have a high risk of in-hospital mortality. It is clinically important to screen high-risk patients using a model or scoring system. This study aimed to develop and validate a simple-to-use nomogram consisting of independent prognostic variables for the prediction of in-hospital mortality in patients with AHF undergoing CRRT.Methods: We collected clinical data for 121 patients with a diagnosis of AHF who underwent CRRT in an AHF unit between September 2011 and August 2020 and from 105 patients in the medical information mart for intensive care III (MIMIC-III) database. The nomogram model was created using a visual processing logistic regression model and verified using the standard method.Results: Patient age, days after admission, lactic acid level, blood glucose concentration, and diastolic blood pressure were the significant prognostic factors in the logistic regression analyses and were included in our model (named D-GLAD) as predictors. The resulting model containing the above-mentioned five factors had good discrimination ability in both the training group (C-index, 0.829) and the validation group (C-index, 0.740). The calibration and clinical effectiveness showed the nomogram to be accurate for the prediction of in-hospital mortality in both the training and validation cohort when compared with other models. The in-hospital mortality rates in the low-risk, moderate-risk, and high-risk groups were 14.46, 40.74, and 71.91%, respectively.Conclusion: The nomogram allowed the optimal prediction of in-hospital mortality in adults with AHF undergoing CRRT. Using this simple-to-use model, the in-hospital mortality risk can be determined for an individual patient and could be useful for the early identification of high-risk patients. An online version of the D-GLAD model can be accessed at https://ahfcrrt-d-glad.shinyapps.io/DynNomapp/.Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT0751838.

Incidence, risk factors, and feto-maternal outcomes of inappropriate birth weight for gestational age among singleton live births in Qatar: A population-based study.

Abnormal fetal growth can be associated with factors during pregnancy and at postpartum. In this study, we aimed to assess the incidence, risk factors, and feto-maternal outcomes associated with small-for-gestational age (SGA) and large-for-gestational age (LGA) infants. We performed a population-based retrospective study on 14,641 singleton live births registered in the PEARL-Peristat Study between April 2017 and March 2018 in Qatar. We estimated the incidence and examined the risk factors and outcomes using univariate and multivariate analysis. SGA and LGA incidence rates were 6.0% and 15.6%, respectively. In-hospital mortality among SGA and LGA infants was 2.5% and 0.3%, respectively, while for NICU admission or death in labor room and operation theatre was 28.9% and 14.9% respectively. Preterm babies were more likely to be born SGA (aRR, 2.31; 95% CI, 1.45-3.57) but male infants (aRR, 0.57; 95% CI, 0.4-0.81), those born to parous (aRR 0.66; 95% CI, 0.45-0.93), or overweight (aRR, 0.64; 95% CI, 0.42-0.97) mothers were less likely to be born SGA. On the other hand, males (aRR, 1.82; 95% CI, 1.49-2.19), infants born to parous mothers (aRR 2.16; 95% CI, 1.63-2.82), or to mothers with gestational diabetes mellitus (aRR 1.36; 95% CI, 1.11-1.66), or pre-gestational diabetes mellitus (aRR 2.58; 95% CI, 1.8-3.47) were significantly more likely to be LGA. SGA infants were at high risk of in-hospital mortality (aRR, 226.56; 95% CI, 3.47-318.22), neonatal intensive care unit admission or death in labor room or operation theatre (aRR, 2.14 (1.36-3.22). Monitoring should be coordinated to alleviate the risks of inappropriate fetal growth and the associated adverse consequences.

Smoking Status and Factors associated with COVID-19 In-Hospital Mortality among US Veterans.

IntroductionThe role of smoking in risk of death among patients with COVID-19 remains unclear. We examined the association between in-hospital mortality from COVID-19 and smoking status and other factors in the United States Veterans Health Administration (VHA).MethodsThis is an observational, retrospective cohort study using the VHA COVID-19 shared data resources for February 1 to September 11, 2020. Veterans admitted to the hospital who tested positive for SARS-CoV-2 and hospitalized by VHA were grouped into Never (as reference, NS), Former (FS), and Current smokers (CS). The main outcome was in-hospital mortality. Control factors were the most important variables (among all available) determined through a cascade of machine learning. We reported adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) from logistic regression models, imputing missing smoking status in our primary analysis.ResultsOut of 8 667 996 VHA enrollees, 505 143 were tested for SARS-CoV-2 (NS = 191 143; FS = 240 336; CS = 117 706; Unknown = 45 533). The aOR of in-hospital mortality was 1.16 (95%CI 1.01, 1.32) for FS vs. NS and 0.97 (95%CI 0.78, 1.22; p > .05) for CS vs. NS with imputed smoking status. Among other factors, famotidine and nonsteroidal anti-inflammatory drugs (NSAID) use before hospitalization were associated with lower risk while diabetes with complications, kidney disease, obesity, and advanced age were associated with higher risk of in-hospital mortality.ConclusionsIn patients admitted to the hospital with SARS-CoV-2 infection, our data demonstrate that FS are at higher risk of in-hospital mortality than NS. However, this pattern was not seen among CS highlighting the need for more granular analysis with high-quality smoking status data to further clarify our understanding of smoking risk and COVID-19-related mortality. Presence of comorbidities and advanced age were also associated with increased risk of in-hospital mortality.ImplicationsVeterans who were former smokers were at higher risk of in-hospital mortality compared to never smokers. Current smokers and never smokers were at similar risk of in-hospital mortality. The use of famotidine and nonsteroidal anti-inflammatory drugs (NSAIDs) before hospitalization were associated with lower risk while uncontrolled diabetes mellitus, advanced age, kidney disease, and obesity were associated with higher risk of in-hospital mortality.

Outcomes of Thoracic Endovascular Aortic Repair in Octogenarians.

The aim of this study is to compare outcomes between octogenarians and non-octogenarians undergoing thoracic endovascular aortic repair (TEVAR). Using the National Inpatient Sample database, we identified octogenarians (≥80years) and non-octogenarians (<80years) who had undergone thoracic endovascular aortic repair between 2012 and 2017. We compared patients' demographic, socioeconomic, comorbidity data between the two groups as well as the procedure indications and perioperative outcomes. A multivariable logistic regression analysis was conducted to evaluate the impact of advanced age (≥80years) on the in-hospital mortality rates in patients who underwent TEVAR. This analysis was also performed for a separate cohort which included only patients who underwent TEVAR for ruptured thoracic aortic aneurysm. A total of 4108 patients were included in our study; 3432 (83.5%) patients were <80years (37.9% female; median age, 64years; 34.3% non-white) and 676 (16.5%) patients were ≥80 years (50.7% female; median age, 83 years; 20.4% non-white). Non-ruptured thoracic aortic aneurysm was the most common indication for TEVAR in older patients (61.4%), whereas type B aortic dissection was the most common indication in younger patients (36.4%). In-hospital complications were comparable between the two groups except for respiratory complications that were higher in the younger patients (21.2% vs. 15.2%; P <.001). The multivariable analysis demonstrated that advanced age had no association with increased in-hospital mortality rates (adjusted odds ratio [aOR], 1.41; 95% confidence interval [CI], .97-2.05), However, in ruptured thoracic aortic aneurysm cohort, octogenarians had higher in-hospital mortality rates (aOR, 1.86; 95% CI, 1.04-3.32). Octogenarians have acceptable rates of perioperative morbidity and mortality compared to the younger group and should be considered for TEVAR. Octogenarians are at higher risk for in-hospital mortality in the setting of ruptured thoracic aortic aneurysm, supporting the appropriateness of elective TEVAR in selected Octogenarians.

Characteristics and outcome of critically ill patients with coronavirus disease-2019 (COVID-19) pneumonia admitted to a tertiary care center in the United Arab Emirates during the first wave of the SARS-CoV-2 pandemic. A retrospective analysis.

BackgroundThe aim of this study was to describe the clinical characteristics and outcome of patients with coronavirus disease-2019 (COVID-19) pneumonia admitted to an intensive care unit (ICU) of a tertiary care center in the United Arab Emirates (UAE) and to identify early risk factors for in-hospital mortality in these patients.MethodsA total of 371 adult patients (>18 years) admitted to the ICU of Al Ain Hospital between March 16 and July 19, 2020 with SARS-CoV-2 infection confirmed using real-time reverse transcription polymerase chain reaction (rt-PCR) on nasopharyngeal swabs were included.ResultsThe mean patient age was 53 years (standard deviation = 13). Patients were mostly male (n = 314 [84.6%]) and of South Asian origin (n = 231 [62.3%]). Invasive mechanical ventilation was required in 182 (49.1%) patients for a median of 11 days (25–75% interquartile range: 6–17). During the ICU stay, renal replacement therapy was required in 87 (23.5%) and vasopressor therapy in 190 (51.2%) patients. ICU and hospital lengths of stay were 9 (IQ: 5–17) and 18 (IQ: 13–29) days, respectively and ICU and hospital mortality rates were both 20.2%. In a multivariable analysis with in-hospital mortality as the dependent variable, greater Acute Physiology and Chronic Health Evaluation II score on ICU admission, diarrhea prior to hospital admission, greater, admission from hospital ward, and higher lactate dehydrogenase levels and neutrophil:lymphocyte ratio on admission to the ICU were independently associated with higher risk of in-hospital mortality.ConclusionIn this cohort of patients admitted to the ICU of a tertiary hospital in the UAE, COVID-19 pneumonia was associated with high morbidity and mortality rates. Identifying patients at high risk of death may help detect future therapeutic targets.

Comparing the adverse outcomes of left atrial appendage occlusion in patients with diabetes

Abstract Introduction In patients with atrial fibrillation, it is estimated that greater than 90 percent of left atrial thrombi are located in the left atrial appendage. Multiple percutaneously implanted devices have been approved worldwide for left atrial appendage occlusion (LAAO) to reduce stroke risk in patients not suitable for long-term oral anticoagulation. Device implantation has been associated with a high success rate and low risk for peri-procedural complications. However, as the prevalence of diabetes continues to rise, there is a considerable need to establish peri-procedural risk in these patients. Purpose This study aimed to evaluate and compare the in-hospital outcomes of LAAO in patients with and without diabetes. Methods We performed a retrospective cross-sectional analysis using the 2018 National Inpatient Sample. All patients aged 18 years and older with atrial fibrillation and LAAO-related hospitalizations were included in this study. To mitigate selection bias and control for patient and institutional imbalances, propensity scoring method was used to select matched sample between patients with diabetes and patients without diabetes. The scoring was based on a multivariate logistic regression model accounting for age, gender, race, hospital type, hospital region, hospital teaching status, median household income, and medical comorbidities. Using an 8-to-1-digit match, we paired each admission in the diabetes group with one admission without diabetes. Results We identified a total of 3572 patients admitted for LAAO; 1298 of these patients had comorbid diabetes. Diabetics did not have a higher risk of in-hospital mortality with LAAO (0.2% vs 0.3%, p=0.620). The risk for 17 out of the 18 identified peri-procedural complications was similar in patients with and without diabetes. However, diabetes was associated with an increased risk of acute kidney injury (Adjusted OR 1.75; 95% CI 1.05–2.93, p=0.03). Interestingly, 0 endocarditis events were captured in both groups, indicating that this complication is only seen in long-term follow-up and had a peri-procedural risk of 0%. Conclusion As the use of implantable LAAO devices increases worldwide, clinicians should be cognizant of the increased risk for peri-procedural acute kidney injury in diabetics. Patients with diabetes often have diabetes-induced chronic kidney disease with susceptibility to acute injury. Therefore, volume status should be closely monitored in the peri-procedural period to mitigate further damage to the kidneys in these patients. Funding Acknowledgement Type of funding sources: None. Characteristics of the matched cohortOutcomes in the matched cohort

Levels of hypersensitive troponin T in the emergency department as a predictive factor of mortality for hospitalized COVID-19 patients

Abstract Background Coronavirus disease 2019 (COVI-19) has resulted in considerable morbidity ans mortality worldwide since December 2019. Cardiac complications are a common condition among patients with COVID-19. The association between elevated hypersensitivity troponin T in COVID-19 disease and risk of mortality remains unclear but data suggest it could be associated with higher risk of in-hospital mortality. Purpose The present study examine the potential association between the level of hypersensitive troponin T (Hs TnT) in emergency department (ED) and mortality among patients hospitalized with COVID-19. Methods Consecutive patients admitted in two hospitals from ED with confirmed PCR COVID-19 were included in this retrospective study. The data were collected from October 1, 2020 to December 31, 2020. The demographic characteristics (age and sex), clinical data (symptoms, comorbidities, laboratory findings, treatments, complications, and outcomes), and results of cardiac examinations (cardiac biomarkers and electrocardiogram) were collected in an electronic database. There data were analyzed and the mortality at 1 month was compared for patients with normal or elevated Hs TnT (&amp;gt;14 ng/L). Results The study population included 413 hospitalized patients with a confirmed PCR COVID-19. The median age was 82. The comorbidities like cardiovascular diseases, cerebrovascular diseases, pulmonary diseases and renal insufficiency are associated with a significant higher mortality (P&amp;lt;0.05). Clinicals findings like tachypnea (respiratory rate &amp;gt;20/minute) or hypotension (&amp;lt;90 mmHg systolic blood pressure) also result an increased mortality (P&amp;lt;0.05). In this cohort, 90 patients had an analysis of Hs TnT in the ED. The mortality at 1 month was higher in patients with elevated Hs TnT (&amp;gt;14 ng/L) compared to the patients with normal levels of Hs TnT and the correlation was significant (P&amp;lt;0.05). The relative risk of fatal outcome is 3.86 when the troponin level is &amp;gt;14ng/L. Conclusion Elevated Hs TnT levels in the emergency department appear to be a predictive factor of mortality at one month for patients with COVID-19 infection requiring admission. Funding Acknowledgement Type of funding sources: None.

PREDICTION OF PHYSIOLOGICAL DETERIORATION AND MORTALITY IN MECHANICALLY VENTILATED PATIENTS ADMITTED TO THE ICU

TOPIC: Critical Care TYPE: Original Investigations PURPOSE: Recent studies have shown that the severity of lung damage in experimental models of ventilator-induced lung injury depend on the mechanical power (MP) of the ventilator, which describes the energy delivered by the ventilator to the respiratory system per unit time. This study aims to build machine learning models that leverage knowledge of ICU data and ventilator settings to predict physiological deterioration and mortality in mechanically ventilated patients. METHODS: Patient data from the Phillips eICU Database were used to build predictive models. Inclusion criteria include age ≥18 years, ICU stay duration ≥48 hours, ventilation duration ≥48 hours, and volume- or pressure-controlled mechanical ventilation. Physiological deterioration was defined as any increase between daily Sequential Organ Failure Assessment (SOFA) scores within the first 7 days of ventilation. Daily maximum MP values were calculated using previously validated equations. Predictive features such as ventilator settings, lab values, medications, vitals, comorbidity indices, patient demographics, and hospital stay information were extracted for each patient stay. Classification models including logistic regression, random forest, and support-vector machines were evaluated for predicting mortality and physiological deterioration using area under the receiver operating characteristic curve (AUC) with six-fold cross-validation. RESULTS: A total of 1338 patients met inclusion criteria for this study. After data processing and imputation, features from 789 patients were curated as inputs to predictive models. These preliminary models showed predictive power for overall physiological deterioration with an AUC of 0.74 ± 0.03. For organ-specific deterioration, these models exhibited comparable or higher performance in predicting renal deterioration (AUC: 0.74 ± 0.08) and pulmonary deterioration (AUC: 0.79 ± 0.03; p<0.05). Prediction of in-hospital mortality resulted in an AUC of 0.78 ± 0.05. CONCLUSIONS: Based on our preliminary data, these predictive models have the potential to be used in real-time to enable early detection and intervention for patients at high risk of physiological deterioration or in-hospital mortality. Implementation of additional time-series physiological data is expected to further improve the performance of these models. CLINICAL IMPLICATIONS: This study explores the effectiveness of multiple statistical learning models in predicting physiological deterioration and mortality in mechanically ventilated ICU patients. Our results have the potential to inform clinicians about the risk of downstream complications associated with a patient's ICU stay and can therefore aid in the prevention of end-organ dysfunction associated with mechanical ventilation. With models that have predictive capacity days before the onset of physiological deterioration, clinicians and other health care providers in the ICU will be able to provide more personalized care for mechanically ventilated patients. We foresee that these predictive models will not only minimize the risk of or prevent mechanical ventilation-associated adverse outcomes but will also be useful in risk-stratifying mechanically ventilated patients based on patient-specific and ventilator-derived data. DISCLOSURES: No relevant relationships by Timothy Bedard, source=Web Response No relevant relationships by Yunru Chen, source=Web Response No relevant relationships by Andy Ding, source=Web Response No relevant relationships by Joseph Greenstein, source=Web Response No relevant relationships by Madi Kusmanov, source=Web Response No relevant relationships by Pedro Mendez-Tellez, source=Web Response No relevant relationships by Morgan Sanchez, source=Web Response No relevant relationships by Shreyash Sonthalia, source=Web Response No relevant relationships by Raimond Winslow, source=Web Response

Association between Thymosin beta-4, acute kidney injury, and mortality in patients with sepsis: An observational cohort study

BackgroundSepsis is a systemic inflammatory response syndrome, associated with high risk of acute kidney injury (AKI) and in-hospital mortality. Thymosin beta-4 (Tβ4) is an actin-sequestering protein that can prevent inflammation in several tissues. Thus, we studied the role of Tβ4 in sepsis. MethodsThe Tβ4 concentrations were prospectively measured in 191 patients within 6 h of the intensive care units (ICU) admission with diagnosis of sepsis. The cohort was divided into Tβ4 concentration tertiles: 1.19–7.11 ng/ml (n = 64), 7.12–11.01 ng/ml (n = 64), and 11.02–28.10 ng/ml (n = 63). ResultsOf 191 patients, 92 patients developed AKI, 24 of whom received continuous renal replacement therapy (CRRT), 29 patients died within 7 days, and 53 patients died within 28 days. Lower Tβ4 stages were correlated with poor prognosis, including AKI(odds ratio [OR], 2.102 per stage lower; 95% confidence interval [CI], 1.448 to 3.050; P < 0.001), CRRT(OR, 2.346 per stage lower; 95% CI, 1.287 to 4.276; P = 0.005), 7-day mortality(OR, 1.755 per stage lower; 95% CI, 1.050 to 2.935; P = 0.032), and 28-day mortality(OR, 1.821 per stage lower; 95% CI, 1.209 to 2.743; P = 0.004). Kaplan-Meier analysis also demonstrated that patients with lower Tβ4 stages had a high risk of AKI and death. In addition, the area under the curve (AUC) of Tβ4 for predicting AKI, CRRT, 7-day mortality, and 28-day mortality were, respectively, 0.702 (95% CI 0.628–0.776), 0.717 (95% CI 0.592–0.842), 0.694 (95% CI 0.579–0.808), and 0.682 (95% CI 0.598–0.767). ConclusionsLower Tβ4 stages are associated with higher odds of poor prognosis in ICU patients with sepsis.

Development and Validation of a Novel Nomogram for Preoperative Prediction of In-Hospital Mortality After Coronary Artery Bypass Grafting Surgery in Heart Failure With Reduced Ejection Fraction.

Background and Aims: Patients with heart failure with reduced ejection fraction (HFrEF) are among the most challenging patients undergoing coronary artery bypass grafting surgery (CABG). Several surgical risk scores are commonly used to predict the risk in patients undergoing CABG. However, these risk scores do not specifically target HFrEF patients. We aim to develop and validate a new nomogram score to predict the risk of in-hospital mortality among HFrEF patients after CABG.Methods: The study retrospectively enrolled 489 patients who had HFrEF and underwent CABG. The outcome was postoperative in-hospital death. About 70% (n = 342) of the patients were randomly constituted a training cohort and the rest (n = 147) made a validation cohort. A multivariable logistic regression model was derived from the training cohort and presented as a nomogram to predict postoperative mortality in patients with HFrEF. The model performance was assessed in terms of discrimination and calibration. Besides, we compared the model with EuroSCORE-2 in terms of discrimination and calibration.Results: Postoperative death occurred in 26 (7.6%) out of 342 patients in the training cohort, and in 10 (6.8%) out of 147 patients in the validation cohort. Eight preoperative factors were associated with postoperative death, including age, critical state, recent myocardial infarction, stroke, left ventricular ejection fraction (LVEF) ≤35%, LV dilatation, increased serum creatinine, and combined surgery. The nomogram achieved good discrimination with C-indexes of 0.889 (95%CI, 0.839–0.938) and 0.899 (95%CI, 0.835–0.963) in predicting the risk of mortality after CABG in the training and validation cohorts, respectively, and showed well-fitted calibration curves in the patients whose predicted mortality probabilities were below 40%. Compared with EuroSCORE-2, the nomogram had significantly higher C-indexes in the training cohort (0.889 vs. 0.762, p = 0.005) as well as the validation cohort (0.899 vs. 0.816, p = 0.039). Besides, the nomogram had better calibration and reclassification than EuroSCORE-2 both in the training and validation cohort. The EuroSCORE-2 underestimated postoperative mortality risk, especially in high-risk patients.Conclusions: The nomogram provides an optimal preoperative estimation of mortality risk after CABG in patients with HFrEF and has the potential to facilitate identifying HFrEF patients at high risk of in-hospital mortality.

The clinical impact of paroxysmal arrhythmias on the hospital outcomes of patients admitted with cirrhosis: propensity score matched analysis of 2011–2017 US hospitals

ABSTRACT Background We evaluate the effects of paroxysmal arrhythmia on the hospital outcomes of patients admitted with cirrhosis. Research design and methods 2011–2017 National Inpatient Sample was used to isolate patients with decompensated/compensated cirrhosis, stratified by paroxysmal arrhythmia (supraventricular: PSVT and ventricular: PVT). The cohorts were matched using propensity-score matching and compared to mortality, length of stay, cost, and cardiac complications (cardioversion, cardiogenic shock, cardiac arrest, and ventricular fibrillation). Results In compensated cirrhosis, 2,453 had PSVT with matched controls; 5,274 had PVT with matched controls. Those with PSVT had higher mortality (aOR 1.55 95%CI 1.23–1.95) and higher rates of cardioversion and cardiogenic shock; likewise, those with PVT had higher mortality (aOR 2.41 95%CI 2.09–2.78) and higher rates of all complications. In decompensated cirrhosis, 1,598 had PSVT with matched controls; 4,178 had PVT with matched controls. Those with PSVT had higher mortality (aOR 1.57 95%CI 1.28–1.93) and higher rates of cardioversion, cardiogenic shock, cardiac arrest; those with PVT had higher mortality (aOR 2.25 95%CI 1.98–2.56) and higher rates of all complications. Conclusion The findings from this study show that in either decompensated or compensated cohort, those with paroxysmal arrhythmias are at a higher risk of in-hospital mortality and adverse cardiac outcomes.

The myocardial and neuronal infectivity of SARS-CoV-2 and detrimental outcomes.

The epidemiological outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), alias COVID-19, began in Wuhan, Hubei, China, in late December and eventually turned into a pandemic that has led to over 3.71 million deaths and over 173 million infected cases worldwide. In addition to respiratory manifestations, COVID-19 patients with neurological and myocardial dysfunctions exhibit a higher risk of in-hospital mortality. The immune function tends to be affected by cardiovascular risk factors and is thus indirectly related to the prognosis of COVID-19 patients. Many neurological symptoms and manifestations have been reported in COVID-19 patients; however, detailed descriptions on the prevalence and characteristic features of these symptoms are restricted due to insufficient data. It is thus advisable for clinicians to be vigilant for both cardiovascular and neurological manifestations to detect them at an early stage to avoid inappropriate management of COVID-19 and to address the manifestations adequately. Patients with severe COVID-19 are notably more susceptible to developing cardiovascular and neurological complications than non-severe COVID-19 patients. This review focuses on the consequential outcomes of COVID-19 on cardiovascular and neuronal functions, including other influencing factors.

In-hospital Outcomes of Infective Endocarditis from 1978 to 2015: Analysis Through Machine-Learning Techniques

BackgroundEarly identification of patients with infective endocarditis (IE) at higher risk for in-hospital mortality is essential to guide management and improve prognosis. MethodsA retrospective analysis was conducted of a cohort of patients followed up from 1978 to 2015, classified according to the modified Duke criteria. Clinical parameters, echocardiographic data, and blood cultures were assessed. Techniques of machine learning, such as the classification tree, were used to explain the association between clinical characteristics and in-hospital mortality. Additionally, the log-linear model and graphical random forests (GRaFo) representation were used to assess the degree of dependence among in-hospital outcomes of IE. ResultsThis study analyzed 653 patients: 449 (69.0%) with definite IE; 204 (31.0%) with possible IE; mean age, 41.3 ± 19.2 years; 420 (64%) men. Mode of IE acquisition: community-acquired (67.6%), nosocomial (17.0%), undetermined (15.4%). Complications occurred in 547 patients (83.7%), the most frequent being heart failure (47.0%), neurologic complications (30.7%), and dialysis-dependent renal failure (6.5%). In-hospital mortality was 36.0%. The classification tree analysis identified subgroups with higher in-hospital mortality: patients with community-acquired IE and peripheral stigmata on admission; and patients with nosocomial IE. The log-linear model showed that surgical treatment was related to higher in-hospital mortality in patients with neurologic complications. ConclusionsThe use of a machine-learning model allowed identification of subgroups of patients at higher risk for in-hospital mortality. Peripheral stigmata, nosocomial IE, absence of vegetation, and surgery in the presence of neurologic complications are predictors of fatal outcomes in machine learning–based analysis.

Effects of seasonal and climate variations on in-hospital mortality and length of stay in patients with type A aortic dissection

ObjectiveTo investigate the effects of seasonal and climatic changes on postoperative in-hospital mortality and length of stay (LOS) in patients with type A acute aortic dissection (AAD).MethodsPatients undergoing implantation of the modified triple-branched stent graft to replace the descending aorta in addition to aortic root reconstruction for type A AAD in our hospital from January 2016 to December 2019 were included. Relevant data were retrospectively collected and analyzed.ResultsA total of 404 patients were included in our analyses. The multivariate unconditional logistic regression analysis showed that patients admitted in autumn (OR 4.027, 95% CI 1.023–17.301, P = 0.039) or with coronary heart disease (OR 8.938, 95% CI 1.991–29.560, P = 0.049) were independently associated with an increased risk of postoperative in-hospital mortality. Furthermore, patients admitted in autumn (OR 5.956, 95% CI 2.719–7.921, P = 0.041) or with hypertension (OR 3.486, 95% CI 1.192–5.106, P = 0.035) were independently associated with an increased risk of longer LOS.ConclusionPatients admitted in autumn or with coronary heart disease are at higher risk of in-hospital mortality following surgery for type A AAD. Also, patients admitted in autumn or with hypertension have a longer hospital LOS. In the autumn of the temperature transition, we may need to strengthen the management of medical quality after surgery for type A AAD.

Comparison of Outcomes in Patients With COVID-19 and Thrombosis Versus Those Without Thrombosis

The occurrence of venous thromboembolisms in patients with COVID-19 has been established. We sought to evaluate the clinical impact of thrombosis in patients with COVID-19 over the span of the pandemic to date. We analyzed patients with COVID-19 with a diagnosis of thrombosis who presented to the MedStar Health system (11 hospitals in Washington, District of Columbia, and Maryland) during the pandemic (March 1, 2020, to March 31, 2021). We compared the clinical course and outcomes based on the presence or absence of thrombosis and then, specifically, the presence of cardiac thrombosis. The cohort included 11,537 patients who were admitted for COVID-19. Of these patients, 1,248 had noncardiac thrombotic events and 1,009 had cardiac thrombosis (myocardial infarction) during their hospital admission. Of the noncardiac thrombotic events, 562 (45.0%) were pulmonary embolisms, 480 (38.5%) were deep venous thromboembolisms, and 347 (27.8%) were strokes. In the thrombosis arm, the mean age of the cohort was 64.5 ± 15.3 years, 53.3% were men, and the majority were African-American (64.9%). Patients with thrombosis tended to be older with more co-morbidities. The in-hospital mortality rate was significantly higher (16.0%) in patients with COVID-19 with concomitant non-cardiac thrombosis than in those without thrombosis (7.9%, p <0.001) but lower than in patients with COVID-19 with cardiac thrombosis (24.7%, p <0.001). In conclusion, patients with COVID-19 with thrombosis, especially cardiac thrombosis, are at higher risk for in-hospital mortality. However, this prognosis is not as grim as for patients with COVID-19 and cardiac thrombosis. Efforts should be focused on early recognition, evaluation, and intensifying antithrombotic management for these patients.

In-Hospital Mortality Risk Factor Analysis in Multivessel Percutaneous Coronary Intervention Inpatient Recipients in the United States.

ObjectivesThe primary goal of our study is to evaluate the mortality rate in inpatient recipients of multivessel percutaneous coronary intervention (MVPCI) and to evaluate the demographic risk factors and medical complications that increase the risk of in-hospital mortality.MethodsWe conducted a cross-sectional study using the Nationwide Inpatient Sample (NIS, 2016) and included 127,145 inpatients who received MVPCI as a primary procedure in United States' hospitals. We used a multivariable logistic regression model adjusted for demographic confounders to measure the odds ratio (OR) of association of medical complications and in-hospital mortality risk in MVPCI recipients.ResultsThe in-hospital mortality rate was 2% in MVPCI recipients and was seen majorly in older-age adults (>64 years, 74%) and males (61%). Even though the prevalence of mortality among females was comparatively low, yet in the regression model, they were at a higher risk for in-hospital mortality than males (OR 1.2; 95% CI 1.13-1.37). While comparing ethnicities, in-hospital mortality was prevalent in whites (79%) followed by blacks (9%) and Hispanics (7.5%). Patients who developed cardiogenic shock were at higher odds of in-hospital mortality (OR 9.2; 95% CI 8.27-10.24) followed by respiratory failure (OR 5.9; 95% CI 5.39-6.64) and ventricular fibrillation (OR 3.5; 95% CI 3.18-3.92).ConclusionAccelerated use of MVPCI made it important to study in-hospital mortality risk factors allowing us to devise strategies to improve the utilization and improve the quality of life of these at-risk patients. Despite its effectiveness and comparatively lower mortality profile, aggressive usage of MVPCI is restricted due to the periprocedural complications and morbidity profile of the patients.

Retrospective evaluation of the prognostic utility of quick sequential organ failure assessment scores in dogs with surgically treated sepsis (2011-2018): 204 cases.

To assess the prognostic utility of admission quick Sequential Organ Failure Assessment (qSOFA) scores for in-hospital mortality in a population of dogs with surgically treated sepsis. Retrospective cohort study of dogs from January 2011 to January 2018. University teaching hospital. One thousand three hundred nine cases were identified with a clinical diagnosis of sepsis requiring surgical source control. Two hundred and four dogs with surgically treated sepsis met inclusion criteria, defined as: meeting 2 or more systemic inflammatory response syndrome (SIRS) criteria with a documented source of infection. One hundred and forty-three cases of septic peritonitis, 26 cases of septic soft tissue infection, 20 cases of pyometra, and 15 cases of pyothorax were evaluated. None. Overall in-hospital mortality was 63 of 204 (30.9%). Patients with a qSOFA≥2 were more likely to die or be euthanized (odds ratio [OR] 7.1, 95% confidence interval [CI] 2.9-16.4; P<0.0001). Survivor and nonsurvivor qSOFA scores were significantly different in all categories. Dogs with septic peritonitis and a qSOFA≥2 had an increased risk of postoperative complications (OR 3.9; 95% CI 1.3-11.1; P=0.02). qSOFA scores were correlated with length of hospitalization in survivors of all-cause surgical sepsis (r=0.28, P=0.0007), septic peritonitis (r=0.33, P=0.001), and septic soft tissue infection (r=0.59, P=0.004). This was the first study to retrospectively evaluate the prognostic utility of qSOFA scores in dogs surgically treated for sepsis. Dogs diagnosed with septic peritonitis and other causes of surgically treated sepsis with a qSOFA≥2 may have a higher risk of in-hospital mortality, although future prospective studies are necessary.

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.

Prevalence, Clinical Features, and In-hospital Outcome of Fatty Liver Disease in Acute Aortic Dissection: A Single-Center Retrospective Study.

Background and Aims: Fatty liver disease (FLD) has emerged as a major public issue in China. We aim to investigate prevalence, clinical features, and in-hospital outcome of FLD in acute aortic dissection (AAD) patients.Methods: Data of 379 AAD patients from 2017 to 2019 at Renmin hospital of Wuhan University was retrospectively collected and divided according to age and FLD absence. Propensity score matching was used for minimal confounding. We compared their physical environmental parameter of onset, clinical features, and in-hospital outcome.Results: The mean age was 52.0 ± 11.5 years in type A and 55.1 ± 11.4 in type B. 25.0% of type A and 19.2% of type B AAD patients had FLD. Logistic regression indicated a negative association between FLD and age, both in type A [unadjusted odds ratio (OR) 0.958 (per 1 year), 95% confidence interval (CI) 0.930–0.988, p = 0.0064] and type B [unadjusted OR 0.943 (per 1 year), 95% CI 0.910–0.978, p = 0.0013]. After matching, type A with FLD had onset with a lower air quality index (AQI) of 68.5 [interquartile range (IQR) 46.0–90.0] and a lower Pm 2.5 concentration of 36.0 μg/m3 (IQR 23.0–56.0) compared with non-FLD group. In Kaplan-Meier estimation, FLD was associated with higher risk of in-hospital mortality in type B AAD (p = 0.0297).Conclusion: The prevalence of FLD in AAD decrease with age, both in type A and type B AAD. Type A AAD patients with FLD had onset with better air quality parameters compared with non-FLD group. FLD was associated with higher risk of in-hospital mortality in type B AAD.

The potential value of the neutrophil to lymphocyte ratio for early differential diagnosis and prognosis assessment in patients with aortic dissection

ObjectivesThe aim of the study was to assess the diagnostic performance and clinical utility of the neutrophil to lymphocyte ratio (NLR) in patients with suspected aortic dissection (AD) and investigate its role in predicting in-hospital mortality in AD. MethodsNLR values were calculated and compared in 467 consecutive patients with initially suspected AD. A receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC) was used to evaluate the discriminative accuracy and predictive capability of the NLR for AD. Clinical utility was determined by decision curve analysis (DCA). The association between NLR and in-hospital mortality was investigated by logistic regression analyses in patients diagnosed with AD. ResultsThe NLR was significantly elevated in patients with AD, and the optimal cut-off point for the NLR to distinguish AD from other acute chest pain diseases was 5.67 [AUC (95% CI): 0.877 (0.844–0.905)]. We recommended an NLR of 2.43 as the appropriate cut-off point with 96.9% sensitivity and a negative likelihood ratio (LR) of 0.09 to satisfy clinical requirements for diagnosis. DCA showed that the use of NLR had a positive net benefit. The deceased patients with AD had a higher NLR than the discharged patients. Moreover, the NLR was an independent predictor of in-hospital mortality for AD [adjusted odds ratio (OR): 1.084 (1.029–1.142)], and patients with higher NLR values tended to have a higher risk of in-hospital mortality. The optimal cut-off point for the NLR to predict in-hospital mortality was 9.20 [AUC (95% CI): 0.695 (0.619–0.765)]. ConclusionsAs an easily available and inexpensive parameter, the NLR could serve as a valuable clinical biomarker for early differential diagnosis and prognosis assessment of AD.