Predictor Of Mortality In Patients Research Articles

Global longitudinal strain as a predictor of mortality in patients with cardiogenic shock

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Aarhus University Dagmar Marshalls Fond. Background The assessment of left ventricular (LV) function through transthoracic echocardiography (TTE) is essential for guiding diagnosis and treatment in cases of cardiogenic shock (CS). Myocardial global longitudinal strain (GLS) provides an objective and reproducible measure of systolic function, independently predicting outcomes in acute heart failure, regardless of left ventricular ejection fraction (LVEF). However, whether assessment of GLS can predict mortality in patients with CS remains unknown. Purpose In this study, we aimed to evaluate the prognostic significance of GLS in patients with CS. Methods Data from cardiac intensive care unit (CICU) patients admitted between 2007 and 2018 with CS who received vasoactive agents and/or mechanical circulatory support were analysed. GLS (as absolute values) and biplane LVEF were measured via TTE performed within 24 hours of CICU admission. Patients with CS were categorised based on the GLS quartile: mild (GLS >9.7%), moderate (7.0% < GLS <9.6%), severe (5.0% < GLS < 6.9%), and very severe (GLS ≤ 4.9%). CICU and in-hospital mortality were compared across GLS categories, and the relationship between GLS and mortality was assessed using multivariable logistic regression. Results The study included 626 patients with a median age of 68.6 years, a median LVEF of 31% (IQR 24 to 40%), and a median GLS of 7.0% (IQR 5.0 to 9.7%). In-hospital mortality was 29.1%. As GLS deteriorated, there was an increasing need for vasopressors (P<0.001). Patients with progressively lower GLS exhibited significantly higher CICU and in-hospital mortality across the GLS quartiles (Figure A; P<0.001). Patients in the severe (adjusted OR 2.67; p<0.001) and very severe category (adjusted OR 3.54; P<0.001) had significantly increased risk of in-hospital death compared with mild category. In multivariable analysis, every 1% decrease in GLS corresponded to a 14% higher risk of in-hospital mortality (P<0.001). Finally, GLS outperformed LVEF for discrimination of in-hospital mortality (P=0.002), and when both measurements were included in the same multivariable model, only GLS remained significant. When patients were divided according to whether they had GLS and/or LVEF below the median value, patients with low GLS had higher mortality irrespective of the LVEF (Figure B). Conclusion In patients with CS, GLS assessment surpasses LVEF in its prognostic value and improves risk stratification. Routine evaluation of GLS should be considered for patients with CS.Figure AFigure B

Urinary non-albumin protein-creatinine ratio is an independent predictor of mortality in patients with type 2 diabetes: a retrospective cohort study

Albuminuria is a well-known predictor of chronic kidney disease in patients with type 2 diabetes mellitus (DM). However, proteinuria is associated with chronic complications in patients without albuminuria. In this retrospective cohort study, we explored whether non-albumin proteinuria is associated with all-cause mortality and compared the effects of non-albumin proteinuria on all-cause mortality between patients with and without albuminuria. We retrospectively collected data from patients with type 2 DM for whom we had obtained measurements of both urinary albumin-to-creatinine ratio (UACR) and urinary protein-to-creatinine ratio (UPCR) from the same spot urine specimen. Urinary non-albumin protein-creatinine ratio (UNAPCR) was defined as UPCR–UACR. Of the 1809 enrolled subjects, 695 (38.4%) patients died over a median follow-up of 6.4 years. The cohort was separated into four subgroups according to UACR (30 mg/g) and UNAPCR (120 mg/g) to examine whether these indices are associated with all-cause mortality. Compared with the low UACR and low UNAPCR subgroup as the reference group, multivariable Cox regression analyses indicated no significant difference in mortality in the high UACR and low UNAPCR subgroup (hazard ratio [HR] 1.189, 95% confidence interval [CI] 0.889–1.589, P = 0.243), but mortality risks were significantly higher in the low UACR and high UNAPCR subgroup (HR 2.204, 95% CI 1.448–3.356, P < 0.001) and in the high UACR with high UNAPCR subgroup (HR 1.796, 95% CI 1.451–2.221, P < 0.001). In the multivariable Cox regression model with inclusion of both UACR and UNAPCR, UNAPCR ≥ 120 mg/g was significantly associated with an increased mortality risk (HR 1.655, 95% CI 1.324–2.070, P < 0.001), but UACR ≥ 30 mg/g was not significantly associated with mortality risk (HR 1.046, 95% CI 0.820–1.334, P = 0.717). In conclusion, UNAPCR is an independent predictor of all-cause mortality in patients with type 2 DM.

Outcomes and predictors of mortality in patients with KPC-Kp infections treated with meropenem vaborbactam: an observational multicenter study

Abstract Background Meropenem-vaborbactam is a recent and promising option for the treatment of KPC-producing Klebsiella pneumoniae (KPC-Kp) infections, including those resistant to ceftazidime-avibactam. Methods We conducted a retrospective analysis of observational data from 19 Italian hospitals on use and outcomes of patients treated with meropenem-vaborbactam for at least ≥24 h for KPC-Kp infections. Crude and propensity-weighted multiple Cox regression models were performed to ascertain risk factors independently associated with 30-day mortality. Results The cohort included 342 adults with bloodstream infections (n = 172) and non-bacteremic infections (n = 170), of which 107 were lower respiratory tract infections, 30 complicated urinary tract infections, and 33 infections involving other sites. Most infections (62.3%) were managed with meropenem-vaborbactam monotherapy, or in combination with at least 1 other active drug (usually fosfomycin, tigecycline, or gentamicin) (37.7%). The 30-day mortality rate was 31.6% (108/342). In multiple Cox regression model, 30-day mortality was independently associated with septic shock at infection onset, Charlson comorbidity index ≥ 3, dialysis, concomitant COVID-19, and INCREMENT score ≥ 8. Administration of meropenem-vaborbactam within 48 hours from infection onset was a negative predictor of mortality. All predictors, except administration of meropenem-vaborbactam within 48 hours remained significant when the multiple Cox regression model was repeated after adjustment for the propensity score for receipt of combination therapy. Conclusions Despite the limits of a retrospective study, the data derived from this multicenter cohort provides additional evidence on the efficacy of meropenem-vaborbactam in treating severe KPC-Kp infections, even when utilized as monotherapy.

Machine Learning for Short-Term Mortality in Acute Decompensation of Liver Cirrhosis: Better than MELD Score

Prediction of short-term mortality in patients with acute decompensation of liver cirrhosis could be improved. We aimed to develop and validate two machine learning (ML) models for predicting 28-day and 90-day mortality in patients hospitalized with acute decompensated liver cirrhosis. We trained two artificial neural network (ANN)-based ML models using a training sample of 165 out of 290 (56.9%) patients, and then tested their predictive performance against Model of End-stage Liver Disease-Sodium (MELD-Na) and MELD 3.0 scores using a different validation sample of 125 out of 290 (43.1%) patients. The area under the ROC curve (AUC) for predicting 28-day mortality for the ML model was 0.811 (95%CI: 0.714- 0.907; p &lt; 0.001), while the AUC for the MELD-Na score was 0.577 (95%CI: 0.435–0.720; p = 0.226) and for MELD 3.0 was 0.600 (95%CI: 0.462–0.739; p = 0.117). The area under the ROC curve (AUC) for predicting 90-day mortality for the ML model was 0.839 (95%CI: 0.776- 0.884; p &lt; 0.001), while the AUC for the MELD-Na score was 0.682 (95%CI: 0.575–0.790; p = 0.002) and for MELD 3.0 was 0.703 (95%CI: 0.590–0.816; p &lt; 0.001). Our study demonstrates that ML-based models for predicting short-term mortality in patients with acute decompensation of liver cirrhosis perform significantly better than MELD-Na and MELD 3.0 scores in a validation cohort.

Clinical characteristics and the prognostic impact of acute kidney injury in critically ill patients with invasive pulmonary Aspergillosis in the intensive care unit: A retrospective, single-center study

Introduction: The incidence and impact of acute kidney injury (AKI) in patients with invasive pulmonary aspergillosis (IPA) admitted to the intensive care unit (ICU) are unknown. Methods: This retrospective study included 140 patients who were diagnosed IPA and admitted to the medical ICU of China–Japan Friendship Hospital in Beijing, China. AKI was defined according to the kidney disease improving global outcomes guidelines. Data on demographic characteristics, comorbidities, laboratory tests, treatments, and prognosis at ICU admission were collected. Results: The rate of AKI was 71.4% (n = 100), and approximately 30% of the patients had preadmission acute kidney dysfunction. Of the 100 patients with AKI, 19, 8, and 73 patients had stage I, II, and III AKI, respectively, and 64 (87.6%) patients required continuous renal replacement therapy. Overall ICU mortality rate was 52.1%. Irreversible AKI was a strong independent risk factor for ICU mortality (odds ratio 13.36, 95% confidence interval 4.52–39.48, p &amp;lt; 0.001), followed by chronic lung disease, use of intermittent positive-pressure ventilation, and long-term corticosteroid treatment within 1 year prior to ICU admission. Higher cardiac troponin I levels at admission and worse volume control during the first 7 days of ICU stay were potential predictive factors of irreversible kidney dysfunction. Patients with irreversible AKI and those who died during the ICU stay had greater volume overload during the first 14 days of ICU stay. Patients who survived received earlier renal replacement therapy support after ICU admission compared to those who died (median, 2 vs. 5 days; p = 0.026). Conclusion: Compared to the patients with IPA in the absence of AKI, those with AKI presented with more volume overload, worse disease burden, and required stronger respiratory support, while experiencing worse prognosis. Irreversible AKI was a strong predictor of mortality in patients with critical IPA. Better volume control and earlier CRRT initiation should be considered key points in AKI management and prognostic improvement.

Point-of-Care Serum Proenkephalin as an Early Predictor of Mortality in Patients Presenting to the Emergency Department with Septic Shock

Background: The aim of the present study is to investigate the prognostic utility of point-of-care (POC)-measured proenkephalin (PENK), a novel biomarker, in terms of predicting in-hospital mortality in patients presenting to the emergency department (ED) with septic shock. Methods: Bedside PENK was measured in consecutive patients presenting to the ED with septic shock according to the Sepsis-3 clinical criteria. The association of PENK with inflammatory and routine biomarkers, and its role as a predictor of in-hospital mortality, was examined. Results: Sixty-one patients with septic shock [53% females, median age 83 years (IQR 71–88)] were evaluated. Median (IQR) values of creatinine, plasma lactate, soluble urokinase plasminogen activator receptor (SuPAR), procalcitonin and PENK were 1.7 (1.0–2.9) mg/dL, 3.6 (2.1–6.8) mmol/L, 13.1 (10.0–21.4) ng/mL, 2.06 (0.84–3.49) ng/mL, and 205 (129–425) pmol/L, respectively. LogPENK significantly correlated with LogLactate (rho = 0.369, p = 0.004), LogCreatinine (rho = 0.537, p &lt; 0.001), LogProcalcitonin (rho = 0.557, p &lt; 0.001), and LogSuPAR (rho = 0.327, p = 0.011). During hospitalization, 39/61 (64%) patients died. In a multivariable logistic regression model, logPENK was an independent predictor of in-hospital mortality (OR 11.9, 95% CI: 1.7–84.6, p = 0.013). Conclusion: POC PENK levels measured upon presentation to the ED strongly correlated with metabolic, renal and inflammatory biomarkers, and may serve as a predictor of in-hospital mortality in patients with septic shock.

Sarcopenia evaluated by EASL/AASLD computed tomography-based criteria predicts mortality in patients with cirrhosis: a systematic review and meta-analysis

Sarcopenia evaluated by EASL/AASLD computed tomography-based criteria predicts mortality in patients with cirrhosis: a systematic review and meta-analysis

OR10-3 | Gender Disparities and Predictors of In-Patient Mortality with Takotsubo Cardiomyopathy – Insights from National Inpatient Sample

OR10-3 | Gender Disparities and Predictors of In-Patient Mortality with Takotsubo Cardiomyopathy – Insights from National Inpatient Sample

Postoperative complications and predictors of mortality in patients with COVID-19

Postoperative complications and predictors of mortality in patients with COVID-19

Validation of a short form of the practice environment scale of the nursing work index: The PES-5.

The Practice Environment Scale of the Nursing Work Index (PES-NWI) has been utilized for two decades globally to measure nurse work environments. Its 31 items in five domains present a substantial respondent burden, threatening survey response rates. The purpose of this study was to derive and validate a short form: the PES-5. We conducted a cross-sectional, secondary analysis of survey data from nurses in 760 hospitals in six U.S. states in 2016 or 2019. One representative item per subscale was selected by highest item-to-subscale R2 from the original PES-NWI publication. Five psychometric properties of the PES-5 were evaluated. The reproduced structure of the full form was confirmed in the 2016 data by the highest R2 for the selected items. The unidimensional structure of the PES-5 was confirmed through confirmatory factor analysis. The correlation between the composite values of the 28-item and 5-item versions was 0.94. The Cronbach's alpha reliability of the PES-5 was >0.80. The intraclass correlation coefficient (ICC 1, k), which evaluates the stability of aggregated values when data are clustered, i.e., nurses are nested within hospitals, was >0.80 in both datasets, demonstrating satisfactory aggregate properties. Construct validity was supported by the selected items being ranked highly in their respective subscales by an expert panel. Criterion validity was supported by an analysis of variance of the PES-5 mean value across responses to a single-item work environment measure. Similar patterns of relationships with other key variables were identified by statistically significant odds ratios in regression models predicting patient mortality from the PES-5. The classification accuracy of the PES-5 was high, with 88% of hospitals classified identically by both versions. The PES-5 shows promise for measurement of nurses' work environments while maximizing response rate by reducing participant burden.

Lactate level is an independent predictor of mortality in patients with hematologic malignancy receiving urgent chemotherapy in intensive care unit

BackgroundIntensive care unit (ICU) survival of cancer patients has improved. Urgent chemotherapy has become feasible in critically ill patients with specific organ dysfunction due to hematological malignancies. ObjectiveThe aim of the study was to assess ICU mortality rates and the factors associated with mortality in patients with hematologic malignancies receiving urgent chemotherapy in the ICU. MethodsWe retrospectively included all patients admitted to the ICU who received chemotherapy due to hematologic malignancy in 2012–2022. ResultsOf the 129 patients undergoing chemotherapy in the ICU, 50 (38.7 %) died during the ICU follow-up. The following conditions were significantly more common among nonsurvivors: presence of infection at the time of ICU admission (p < 0.001), the requirement for mechanical ventilation during ICU stay (p < 0.001), the need for noninvasive mechanical ventilation during ICU stay (p = 0.014), vasopressor support (p < 0.001), and sepsis (p < 0.001). Logistic regression analysis revealed that among laboratory parameters on ICU admission, lactate (p = 0.008), albumin (p = 0.022), C-reactive protein (p = 0.046), baseline sequential organ failure assessment (SOFA) score (p < 0.001), newly developed heart failure (p = 0.006), and the requirement for vasopressor agents during ICU stay (p < 0.001) significantly influenced the risk of mortality in the univariate analysis. The multivariate analysis revealed lactate levels (p = 0.047) on ICU admission as an independent predictor of mortality. ConclusionThe development of heart failure and lactate levels on admission were the main predictors of mortality. Additionally, higher SOFA scores revealed that illness severity was closely associated with mortality. Future studies should focus on strategies to further reduce these risks and achieve the best outcomes for these patients.

Echocardiographic parameters as adjuncts to Pulmonary Embolism Severity Index (PESI) in prediction of 30-day mortality in patients with acute pulmonary embolism.

Echocardiographic parameters as adjuncts to Pulmonary Embolism Severity Index (PESI) in prediction of 30-day mortality in patients with acute pulmonary embolism.

The Accuracy of Monocyte Lymphocyte Ratio as a Predictor of Mortality in Patients Undergoing Regular Haemodialysis at H Adam Malik General Hospital Medan

The Accuracy of Monocyte Lymphocyte Ratio as a Predictor of Mortality in Patients Undergoing Regular Haemodialysis at H Adam Malik General Hospital Medan

Nationwide hospitalizations of patients with down syndrome and congenital heart disease over a 15-year period.

A younger age at first admission is a predictor for mortality in patients with Down syndrome and congenital heart disease. If patients undergo more than one admission, the risk of further readmissions increases. There is a pivotal role for heart disease in influencing the hospitalization rate and subsequent mortality. • Down syndrome individuals often face an increased risk of congenital heart diseases. • Congenital heart diseases contribute significantly to morbidity and mortality in Down syndrome patients. • This study analyzes nationwide data covering a 15-year period of pediatric and adult patients in Italy with Down syndrome and congenital heart disease. • It identifies a younger age at first admission as a predictor for mortality in these patients, emphasizing the criticality of early intervention. • Demonstrates a correlation between multiple admissions, particularly those related to cardiac issues, and an increased risk of further readmissions, providing insights into the ongoing healthcare needs of these individuals.

The Use of Thrombectomy during Primary Percutaneous Coronary Intervention: Resurrecting an Old Concept in Contemporary Practice.

Optimal myocardial reperfusion during primary percutaneous coronary intervention (pPCI) is increasingly recognized to be beyond restoring epicardial coronary flow. Both invasive and non-invasive tools have highlighted the limitation of using this metric, and more efforts are focused towards achieving optimal reperfusion at the level of the microcirculation. Recent data highlighted the close relationship between thrombus burden and impaired microcirculation in patients presenting with ST-segment elevation myocardial infarction (STEMI). Moreover, distal embolization was an independent predictor of mortality in patients with STEMI. Likewise, the development of no-reflow phenomenon has been directly linked with worse clinical outcomes. Adjunctive thrombus aspiration during pPCI is intuitively intended to remove atherothrombotic material to mitigate the risk of distal embolization and the no-reflow phenomenon (NRP). However, prior trials on the use of thrombectomy during pPCI did not support its routine use, with comparable clinical endpoints to patients who underwent PCI alone. This article aims to review the existing literature highlighting the limitation on the use of thrombectomy and provide future insights into trials investigating the role of thrombectomy in contemporary pPCI.

Outcomes of bailout use of continuous positive airway pressure in patients with severe COVID-19 respiratory failure

During the first wave of the Coronavirus-19 (COVID-19) pandemic, due to an overflow of patients in the ICU, continuous positive airway pressure (CPAP) was used as a last resort to mechanical ventilation. The purpose of this study is to evaluate prognostic factors in COVID-19 severe respiratory failure patients treated with helmet CPAP. We reviewed the medical records of COVID-19 respiratory failure patients treated with H-CPAP at the Emergency Department from February 23rd to March 14th, 2020. A total of 202 (40%) patients admitted for respiratory failure due to COVID-19 pneumonia were considered. 129 (64%) patients received H-CPAP, while 73 (36%) required endotracheal intubation and invasive mechanical ventilation despite initial H-CPAP. 99 patients (49%) died. The mortality rate in the IMV group was 37%, compared to 56% in the group that received only H-CPAP (p= 0.004). The age and comorbidities of patients in the two groups differed significantly (p &lt; 0.001). Age and PaO2/FiO2 were identified as the only independent risk factors for death. Identifying these independent predictors of mortality in patients with acute respiratory insufficiency may help clinicians optimize treatment escalation.

Investigating Machine Learning Models in Acute Myocardial Infarction to Predict Mortality

Abstract:&#x0D; Background&#x0D; Pakistan and the rest of the world suffer from a high rate of acute myocardial infarctions (AMIs). In this study, we employed a machine learning model to predict mortality in patients with AMI patients. By analyzing various variables, they assessed the impact of these factors on the predictive models, highlighting the potential of machine learning in improving mortality prediction and informing clinical decision-making in AMI cases.&#x0D; Method&#x0D; This study conducted three experiments using a Kaggle dataset to predict mortality in Acute Myocardial Infarction (AMI) patients with machine learning. Relevant input features were selected, and three models (SVM, DT, KNN) classified mortality status. Model performance was rigorously evaluated with metrics like Accuracy, AUC, Precision, Recall, and F1-score. Data preprocessing, including handling missing values and normalization, preceded model training.&#x0D; Results&#x0D; Among the evaluated models, the Support Vector Machine (SVM) exhibited the highest accuracy of approximately 87.66% and demonstrated robust discrimination capabilities, with an AUC score of 0.796. Precision, recall, and F1-scores indicated a balanced trade-off between correctly identifying negative outcomes and effectively capturing positive cases.&#x0D; Conclusion&#x0D; The SVM model emerged as the most promising classifier, showcasing strong potential for predicting patient mortality in the context of AMI. However, further refinements and optimizations may be necessary to enhance model performance, ensuring its clinical relevance and utility in real-world medical scenarios.

Decompensated liver cirrhosis: assessment of complications and mortality in hospitalised patients

Background. Liver cirrhosis is a severe, progressively fatal disease if untreated. Hospitalised patients face high mortality rates, and current methods for assessing prognosis vary widely. The research aims to investigate complications and predictors of mortality in patients admitted for decompensated cirrhosis to a tertiary care centre in Tirana, Albania. Materials and methods. The retrospective study included 212 patients aged (58.67 ± 10.09) years: 174 (82.1 %) men, 38 (17.9 %) women. The Child-Turcotte-Pugh, MELD, MELD-Na, MELD 3.0, iMELD, MESO, and UKELD scales were used to assess the severity of the condition and risk stratification of patients. The number of patients with a fatal outcome was 43 (20.3 %). Results. Among participants with different etiological factors of liver cirrhosis, the mortality rate did not differ significantly (p = 0.873). The presence of hepatic encepha­lopathy (0.43; p = 0.001), acute-on-chronic liver failure (r = 0.47; p = 0.001) and hepatorenal syndrome (r = 0.49; p = 0.001), and, to a lesser extent, ascites (r = 0.18; p = 0.006) and spontaneous bacterial peritonitis (r = 0.23; p = 0.041) was a marker of unfavourable prognosis of hospitalisation. Also, the risk of death increased in the presence of leukaemia (hazard ratio = 4.21 (1.65; 10.74); p = 0.003). Conclusions. The MELD 3.0 and MELD-Na scores, calculated based on laboratory values obtained within 48–72 hours of hospitalisation, were found to be the prognostically significant (p &lt; 0.05)

Impact of age over 70 years in the new allocation system on the outcomes of heart transplantation in the US.

United Network for Organ Sharing (UNOS) allocation criteria changed in 2018 to accommodate the increased prevalence of patients on a ventricular assist device as a bridge to heart transplant and prioritize sicker people in anticipation of a heart graft. We aimed to assess the impact of patient age in the new allocation policy on mortality following heart transplantation. Secondary outcomes included the effect of age ≥70 on post-transplant events, including stroke, dialysis, pacemaker, and rejection requiring treatment. The UNOS Registry was queried to identify patients who underwent heart transplants alone in the US between 2000 and 2021. Patients were divided into groups according to their age (over 70 and under 70 years old). Patients aged over 70 were more likely to require dialysis during follow-up, but less likely to experience rejection requiring treatment, compared with patients aged <70. Age ≥70 in the new allocation system was a significant predictor of 1-year mortality (adjusted HR: 1.41; 95% CI: 1.05-1.91; p=.024), but its effect on 5-year mortality was not significant after adjusting for potential confounders (adjusted HR: 1.27; 95% CI:.97-1.66; p=.077). Undergoing transplantation under the new allocation policy vs the old allocation policy was not a significant predictor of mortality in patients over 70 years old. Age ≥70 is a significant predictor of 1-year mortality following heart transplantation, but not at 5 and 10 years; however, the new allocation does not seem to have changed the outcomes for this group of patients.

Establishment of a model to predict mortality after decompression craniotomy for traumatic brain injury.

The mortality rate of patients with traumatic brain injury (TBI) is still high even while undergoing decompressive craniectomy (DC), and the expensive treatment costs bring huge economic burden to the families of patients. The aim of this study was to identify preoperative indicators that influence patient outcomes and to develop a risk model for predicting patient mortality by a retrospective analysis of TBI patients undergoing DC. A total of 288 TBI patients treated with DC, admitted to the First Affiliated Hospital of Shantou University Medical School from August 2015 to April 2021, were used for univariate and multivariate logistic regression analysis to determine the risk factors for death after DC in TBI patients. We also built a risk model for the identified risk factors and conducted internal verification and model evaluation. Univariate and multivariate logistic regression analysis identified four risk factors: Glasgow Coma Scale, age, activated partial thrombin time, and mean CT value of the superior sagittal sinus. These risk factors can be obtained before DC. In addition, we also developed a 3-month mortality risk model and conducted a bootstrap 1000 resampling internal validation, with C-indices of 0.852 and 0.845, respectively. We developed a risk model that has clinical significance for the early identification of patients who will still die after DC. Interestingly, we also identified a new early risk factor for TBI patients after DC, that is, preoperative mean CT value of the superior sagittal sinus (p<.05).