Risk Of 30-day Mortality Research Articles

Prognostic significance of fibrinogen levels in sepsis-associated acute kidney injury: unveiling a nonlinear relationship and clinical implications.

Fibrinogen plays a pivotal role in the inflammatory cascade and is intricately linked to the pathogenesis of sepsis. Nevertheless, its significance as a prognostic marker for sepsis-associated acute kidney injury (SA-AKI) remains uncertain. This study aimed to investigate the association between fibrinogen levels and 28-day mortality with sepsis-associated acute kidney injury. The fibrinogen levels of patients admitted to the intensive care unit of Beth Israel Deaconess Medical Center between 2008 and 2019 were retrospectively assessed, and those diagnosed with SA-AKI were divided into low, middle and high fibrinogen level groups according to tertiles. Multivariate Cox proportional hazards model was used to assess the 28-day mortality risk of the SA-AKI patients. A total of 3,479 patients with SA-AKI were included in the study. Fibrinogen demonstrated an independent association with 28-day mortality, yielding a hazard ratio (HR) of 0.961 (95% confidence interval [CI]: 0.923-0.999, P = 0.0471). Notably, a non-linear relationship between fibrinogen levels and 28-day mortality was observed, with the threshold observed at approximately 1.6 g/l. The effect sizes and corresponding CIs below and above this threshold were 0.509 (0.367, 0.707) and 1.011 (0.961, 1.064), respectively. Specifically, the risk of mortality among SA-AKI patients decreased by 49.1% for every 1 g/l increment in fibrinogen, provided that fibrinogen levels were less than 1.6 g/l. In patients with SA-AKI, a non-linear relationship was identified between fibrinogen levels and 28-day mortality. Particularly, when their fibrinogen levels were less than 1.6 g/l, a concomitant decrease in 28-day mortality was observed as fibrinogen levels increased.

Construction and validation of a clinical prediction model for sepsis using peripheral perfusion index to predict in-hospital and 28-day mortality risk.

Sepsis is a clinical syndrome caused by infection, leading to organ dysfunction due to a dysregulated host response. In recent years, its high mortality rate has made it a significant cause of death and disability worldwide. The pathophysiological process of sepsis is related to the body's dysregulated response to infection, with microcirculatory changes serving as early warning signals that guide clinical treatment. The Peripheral Perfusion Index (PI), as an indicator of peripheral microcirculation, can effectively evaluate patient prognosis. This study aims to develop two new prediction models using PI and other common clinical indicators to assess the mortality risk of sepsis patients during hospitalization and within 28 days post-ICU admission. This retrospective study analyzed data from sepsis patients treated in the Intensive Care Unit of Peking Union Medical College Hospital between December 2019 and June 2023, ultimately including 645 patients. LASSO regression and logistic regression analyses were used to select predictive factors from 35 clinical indicators, and two clinical prediction models were constructed to predict in-hospital mortality and 28-day mortality. The models' performance was then evaluated using ROC curve, calibration curve, and decision curve analyses. The two prediction models performed excellently in distinguishing patient mortality risk. The AUC for the in-hospital mortality prediction model was 0.82 in the training set and 0.73 in the validation set; for the 28-day mortality prediction model, the AUC was 0.79 in the training set and 0.73 in the validation set. The calibration curves closely aligned with the ideal line, indicating consistency between predicted and actual outcomes. Decision curve analysis also demonstrated high net benefits for the clinical utility of both models. The study shows that these two prediction models not only perform excellently statistically but also hold high practical value in clinical applications. The models can help physicians accurately assess the mortality risk of sepsis patients, providing a scientific basis for personalized treatment.

Association between prognostic nutritional index and mortality risk in patients with community-acquired pneumonia: a retrospective study

BackgroundThe prognostic nutritional index (PNI), reflecting the body’s immune-nutritional status, has been established as a correlate of prognosis across various diseases. However, its significance in community-acquired pneumonia (CAP) remains unclear. This study investigated the relationship between PNI and clinical outcomes in CAP patients.MethodsIn this retrospective cohort study, we aimed to evaluate the prognostic value of the PNI in adults with CAP admitted to the ICU. Participants were selected from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database and categorized into quartiles (Q1–Q4) according to their PNI values. We employed Kaplan-Meier survival analysis, multivariate Cox regression, and restricted cubic spline (RCS) models to explore the association between PNI and the clinical outcomes of these CAP patients.ResultsIn this study, we included 1,608 patients with CAP. The observed 30-day and 90-day mortality rates stood at 30.85% and 39.99%, respectively. Patients with higher PNI levels exhibited a reduced risk of both 30-day and 90-day mortality. Following adjustment for confounders, PNI showed a significant negative association with 30-day mortality [HR, 0.93 (0.91–0.94), P < 0.001] and 90-day mortality [HR, 0.94 (0.92–0.95), P < 0.001]. RCS analysis revealed a consistent trend of declining all-cause mortality risk corresponding to increasing PNI values. PNI demonstrated predictive value for 30-day and 90-day mortality in CAP patients, with AUCs of 0.71 and 0.68, respectively. Combining PNI with CURB-65 enhanced the predictive value of CURB-65.ConclusionOur investigation identified a significant negative association between the PNI and the risk of mortality in patients with CAP. Additionally, the PNI demonstrated superior predictive value for mortality risk in CAP patients when compared to the CURB-65 scoring system.

Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The purpose was to develop a machine learning (ML) model for predicting the 30-day all-cause mortality risk in SAP patients and to explain the most important predictors. This research utilized six ML methods, including logistic regression (LR), k-nearest neighbors(KNN), support vector machines (SVM), naive Bayes (NB), random forests(RF), and extreme gradient boosting(XGBoost), to construct six predictive models for SAP. An extensive evaluation was conducted to determine the most effective model and then the Shapley Additive exPlanations (SHAP) method was applied to visualize key variables. Utilizing the optimized model, stratified predictions were made for patients with SAP. Further, the study employed multivariable Cox regression analysis and Kaplan-Meier survival curves, along with subgroup analysis, to explore the relationship between the machine learning-based score and 30-day mortality. Through LASSO regression and recursive feature elimination (RFE), 25 optimal feature variables are selected. The XGBoost model performed best, with an area under the curve (AUC) of 0.881, a sensitivity of 0.5714, a specificity of 0.9651 and an F1 score of 0.64. The first six most important feature variables were the use of vasopressor, high Charlson comorbidity index, low blood oxygen saturation, history of malignant tumor, hyperglycemia and high APSIII score. Based on the optimal threshold of 0.62, patients were divided into high and low-risk groups, and the 30-day survival rate in the high-risk group decreased significantly. COX regression analysis further confirmed the positive correlation between high-risk scores and 30-day mortality. In the subgroup analysis, the model showed good risk stratification ability in patients with different gender, renal replacement therapy and with or without a history of malignant tumor, but it was not effective in predicting peripheral vascular disease. the XGBoost model effectively predicts the severity of SAP, serving as a valuable tool for clinicians to identify SAP early.

The impact of serum potassium ion variability on 28-day mortality in ICU patients.

Potassium ion disorders are prevalent among patients in Intensive Care Units (ICUs), yet there is a notable deficiency in established protocols and supplemental plans for potassium management. This retrospective study conducted at a single center aims to explore the relationship between potassium levels, their variability, and the 28-day mortality rate in ICU patients. This study analyzed data from patients admitted to the ICU of the First Affiliated Hospital of Guangxi Medical University between October 2022 and October 2023. We assessed serum potassium variability using the coefficient of variation and categorized it into four quartile groups (Q1, Q2, Q3, Q4). Additionally, patients were classified into six groups based on serum potassium concentrations. The associations between these categories and the 28-day mortality rate were evaluated using binary logistic regression, adjusting for potential confounders. A total of 506 patients and 12,099 potassium measurements were analyzed. The group with the lowest potassium variability (Q1) exhibited the lowest mortality rate at 21% (P<0.01). It is noteworthy that within 28 days in the intensive care unit (ICU), the coefficient of variation (CV) of potassium levels significantly increased among deceased patients compared to surviving patients (P < 0.01). Significant variability in potassium levels is associated with an increased risk of 28-day mortality among ICU patients, underscoring the need for stringent monitoring and management of potassium levels in this population.

A Comparative Analysis of Age, BMI, Age/BMI Ratio, Nottingham Hip Fracture Score, and American Society of Anesthesiologists (ASA) Grade as Predictors of 30-Day Mortality After Neck of Femur Fractures: A Retrospective Cohort Study.

Background and objective Hip fracture is a condition associated with high mortality rates, necessitating the use of risk assessment tools to optimise patient care. This study aimed to introduce and describe a novel score using Age/BMIas an improved predictor of 30-day mortality Methods A retrospective cohort study was conducted at a high-volume neck of the femur centre. Data from 574 patients treated over one year were collected and analysed. Multivariate logistic regression analysis was used to determine variables that significantly increased the risk of 30-day mortality. Results A total of 574 patients were identified: 388 females and 186 males.The overall mortality of the patient cohort at the time of data collection was21.78% (n=125). The 30-day mortality was found to be5.75% (n=33) while the one-year mortality rate was 21.08% (n=121). The key risk factors for mortality in neck of femur fractures, highlighted in the literature review, were compared against the binomial outcome variable of 30-day mortality. Categorical data analysis was first completed to highlight key trends. A regression analysis thendemonstrated the significance of each factor. Age (p=0.75207), BMI (p=0.97674), and Age/BMI (p=0.92205) showed no statistical significance. The Nottingham Hip Fracture Score (NHFS) was marginally significant (p=0.05749). The American Society of Anesthesiologists (ASA) grade was shown to be statistically significant, emergingas the strongest predictor of 30-day mortality(p=0.00953). Conclusions Our findings showthat current guidelines utilising ASA and NHFS are excellent predictors of 30-day mortality in hip fracture patients. The proposed Age/BMI score did not demonstrate efficacy in this cohort. Further research is warranted to explore alternative predictors and enhance risk assessment in this population.

Association of cumulative methylprednisolone dosages with mortality risk from pneumonia in connective tissue disease patients

Corticosteroid is essential in the treatment regimen for connective tissue disease (CTD); however, its long-term use poses significant risks, including pulmonary infections. The relationship between cumulative corticosteroid doses and adverse pneumonia outcomes requires further investigation. This study aimed to explore the association between cumulative methylprednisolone dosages (CMD) and pneumonia mortality risks among CTD patients. We conducted a retrospective analysis of data from CTD patients treated with intravenous or oral corticosteroids across six academic hospitals over approximately five years in China. We evaluated follow-up outcomes at 30 and 90 days after the onset of pneumonia. Piecewise linear regression, Cox regression analysis, and survival analysis were employed to investigate the relationship between CMD and 30-day and 90-day mortality risks. Among 335 CTD patients with pneumonia, the mean CMD was 12 g. The 30-day and 90-day mortality rates were 25.07% and 29.55%, respectively. After adjusting for potential confounders, smooth curve fitting analysis revealed a specific nonlinear relationship between CMD and 30-day and 90-day mortality risks. Cox regression analysis indicated that the lowest pneumonia mortality risk occurred when CMD ranged from 11 to 24 g (30-day adjusted hazard ratio (aHR) 0.33, 95% CI 0.14–0.77; 90-day aHR 0.37, 95% CI 0.17–0.81). Patients in the 11–24 g CMD group demonstrated significantly lower cumulative hazard and death rates compared to both the low CMD (< 11 g) and high CMD (> 24 g) groups (P < 0.05). Furthermore, interaction testing suggested that CMD’s negative impact on pneumonia mortality risks was more pronounced in community-acquired pneumonia (CAP) compared to hospital-acquired pneumonia (P for interaction < 0.05). CMD shows a distinct nonlinear relationship with 30-day and 90-day pneumonia mortality risks, with potentially lower risks observed within the 11–24 g CMD range. Moreover, the varying impact of CMD on CAP mortality risk warrants further consideration in clinical management strategies.

Temporal trends (2003–2018) of in-hospital and 30-day mortality in patients hospitalized with acute heart failure

BackgroundLimited temporal data on in-hospital mortality trends of patients hospitalized with acute heart failure (AHF) have been reported. We evaluated whether, in AHF hospitalized patients, the rate of in-hospital and 30-day mortality, and 30-day re-hospitalization for AHF have changed in the past 15 years. Methods and resultsWe examined administrative data from the Lombardy region, Italy and analysed data of all adults hospitalized for AHF from 2003 to 2018. Patients were stratified according to the hospitalization period: 2003–2006; 2007–2010; 2011–2014; 2015–2018. Primary endpoint was the comparison of in-hospital mortality rates among periods. Secondary endpoints were 30-day mortality rates and temporal trends of re-hospitalization for AHF. During this period, 414,164 hospitalizations with a primary diagnosis of AHF were identified, involving 286,028 patients aged 18 and older. In-hospital and 30-day mortality in the entire cohort showed a progressive increase over time (from 6.7 % to 8.5 % and from 12.4 % to 14.5 %, respectively). Thirty-day re-hospitalization for AHF was 2 %, showing a progressive decrease over the years. However, patient’ age and complexity increased in the most recently hospitalized patients. After adjusting for major confounders, in-hospital and 30-day mortality risks were similar moving from one study period to the next (relative risk for trend 1.00 [95 % CI 0.99–1.01] and 1.00 [95 % CI 0.98–1.01], respectively), while that of 30-day AHF re-hospitalization decreased progressively (hazard ratio for trend 0.86 [95 % CI 0.84–0.88]). ConclusionsIn our study, the increasing age and complexity of patients largely accounted for the continued rise in early mortality observed in patients hospitalized with AHF.

Severe Vitamin D Deficiency is Associated with Mortality Risk in Critically Ill Patients with Acute Kidney Injury.

Deficiency in vitamin D is associated with adverse outcomes in several health conditions. However, the specific impact of vitamin D levels on mortality in acute kidney injury (AKI) patients remains inadequately explored. This study aims to investigate the association between serum vitamin D concentrations and mortality risk in critically ill patients diagnosed with AKI. We hypothesize that severe vitamin D deficiency is associated with an increased risk of 90-day all-cause mortality in these patients. This study retrospectively enrolled 259 adult AKI patients admitted to the intensive care unit (ICU) at The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People's Hospital) between July 2021 and June 2023. Based on 25-hydroxyvitamin D (25-OHD) levels, they were categorized into 4 groups: severe deficiency (<10 ng/mL), deficiency (10-20 ng/mL), insufficiency (20-30 ng/mL), and sufficiency (>30 ng/mL). Multivariate survival analysis using Cox's regression model was used to analyze the impact of vitamin D concentrations on the 90-day all-cause mortality risk after controlling for potential confounders. The 90-day all-cause mortality rate was the highest in patients with severe deficiency (50.8%), followed by those with deficiency (35.0%), insufficiency (23.9%), and sufficiency (12.2%). Multivariate Cox regression showed that compared with sufficiency, severe deficiency (HR=3.34, 95% CI: 1.14-9.77; P=0.03) was independently associated with a higher risk of 90-day all-cause mortality, but deficiency and insufficiency were not significantly associated with 90-day all-cause mortality risk. Severe vitamin D deficiency (<10 ng/mL) significantly increases the risk of mortality in AKI patients, underlining the need for monitoring and potentially supplementing vitamin D in this population.

Establishment of a nomogram prediction model for 28-day mortality of septic shock patients based on routine laboratory data mining

To construct a nomogram prediction model for 28-day mortality in septic shock patients based on routine laboratory data mining and verify its predictive value. The clinical data of patients with septic shock admitted to Anhui Medical University Affiliated Fuyang Hospital from January 2018 to November 2023 were retrospectively analyzed. The patients were randomly divided into training set and validation set according to the ratio of 8 : 2. The patient's gender, age, body mass index, underlying disease, smoking history, alcohol history, infection site, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), respiratory rate, heart rate, mean arterial pressure, blood lactate, procalcitonin, C-reactive protein, white blood cell count, platelet count, serum alanine aminotransferase, aspartate aminotransferase, urea nitrogen, serum creatinine, fibrinogen, D-dimer, albumin on the first day of admission to the intensive care unit (ICU), duration of mechanical ventilation, and length of ICU stay were collected. The patients were divided into survival and death groups based on their 28-day prognosis. The factors influencing 28-day mortality were analyzed, and routine laboratory data were used to develop a nomogram model for predicting the risk of 28-day mortality in septic shock patients. The model was validated and assessed using the Bootstrap method, calibration curve, and receiver operator characteristic curve (ROC curve). Finally, 128 patients with septic shock were enrolled, and 32 (31.07%) death within 28-day of 103 patients in the training set, 8 (32.00%) death within 28-day of 25 patients in the validation set. Logistic regression analysis showed that APACHE II score [odds ratio (OR) = 5.254, 95% confidence interval (95%CI) was 2.161-12.769], SOFA score (OR = 4.909, 95%CI was 2.020-11.930), blood lactate (OR = 4.419, 95%CI was 1.818-10.741), procalcitonin (OR = 4.358, 95%CI was 1.793-10.591) were significant factors influencing 28-day mortality in septic shock patients (all P < 0.01). Taking the above influencing factors as predictors, a nomogram model was established, with a total score of 89-374, corresponding to a mortality risk of 0.07-0.89. The results of nomogram model validation showed that the C-index was 0.801 (95%CI was 0.759-0.832), and the correction curve for predicting 28-day mortality in patients with septic shock was close to the ideal curve, Hosmer-Lemeshow test showed that χ 2 = 0.263, P = 0.512. The results of the ROC curve of the training set showed that the nomogram model had a sensitivity of 78.13% (95%CI was 59.57%-90.06%), a specificity of 80.28% (95%CI was 68.80%-88.43%) and area under the curve (AUC) of 0.854 (95%CI was 0.776-0.937) in predicting 28-day mortality in patients with septic shock. The results of the validation set ROC curve showed that the nomogram model had a sensitivity of 75.00% (95%CI was 35.58%-95.55%), a specificity of 88.23% (95%CI was 62.25%-97.94%) and AUC of 0.871 (95%CI was 0.793-0.946) in predicting 28-day mortality in patients with septic shock. A nomogram prediction model constructed based on routine laboratory data mining can effectively predict 28-day mortality in septic shock patients, and its prediction performance is good.

The Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score Predicts the Prognosis of Adults with Status Epilepticus: A Retrospective Study.

The hemoglobin, albumin, lymphocyte, and platelet (HALP) score has been indicated to be a novel indicator that reflects systemic inflammation and is associated with the functional outcome in various neurological diseases. Since inflammation is closely involved in the pathogenesis of status epilepticus (SE), this study aimed to explore the predictive value of HALP for the prognosis of SE patients. In the retrospective study, we investigated and validated the predictive value of HALP for the prognosis of adult SE patients. We collected patient's clinical characteristics and laboratory test data. Information of 30-day mortality after SE onset was obtained, and modified Rankin scale (mRS) scores were used to evaluate the clinical outcomes. Multivariable logistic regression models were applied to explore the association between HALP and SE prognosis. Receiver operating characteristic (ROC) curve analysis was performed to determine the optimal cutoff of HALP to predict 30-day mortality in SE patients. We first analyzed the discovery cohort of 116 patients with SE. We observed that 19.0% (22/116) of the patients died within 30 days after SE onset, and 26.3% (20/76) had poor outcomes during the 6-month follow-up. Multivariate logistic regression analysis indicated that lower HALP on admission was an independent predictor of 30-day mortality (odds ratio: 0.980; 95% confidence interval, 0.962-0.999; P = 0.044). In ROC analysis, a HALP of 20.32 was identified as the optimal cutoff value to predict 30-day mortality in SE patients. Furthermore, multivariate logistic regression analysis showed that HALP < 20.32 was related to an increased risk of poor SE outcomes (odds ratio: 27.051; 95% confidence interval, 3.589-203.909; P = 0.001), which was validated in the external cohort. Lower HALP is independently associated with an increased risk of 30-day mortality and poor functional outcomes in patients with SE. Our findings suggest that HALP may be a promising biomarker for predicting SE prognosis.

Предикторы госпитальной летальности при экстренном хирургическом лечении острейшего расслоения аорты типа А по Стенфорду в условиях искусственного кровообращения: ретроспективное когортное исследование

INTRODUCTION: Acute Stanford type A aortic dissection is one of the most severe cardiovascular diseases with high in-hospital mortality. OBJECTIVE: To establish predictors of in-hospital mortality in the treatment of patients with acute Stanford type A aortic dissection under conditions of artificial circulation and to determine their threshold values. MATERIALS AND METHODS: Study design: retrospective, cohort, single-center. Inclusion criteria: surgical intervention with cardiopulmonary bypass, confirmed diagnosis of acute Stanford type A aortic dissection, age &gt; 18 years. The study included 51 patients: 42 men and 9 women aged from 35 to 77 years, median 59 years [47; 65]. All patients (n = 51) were treated in 2022 and were divided into 2 groups depending on the outcome: group 1 (n = 27) included those who died in the intensive care unit within 30 days, group 2 (n = 24) included survived and discharged patients. The endpoint of trial was 30-day in-hospital mortality. RESULTS: Postoperative Sequential Organ Failure Assessment (SOFA) score &gt; 7, Acute Physiology And Chronic Health Evaluation (APACHE) II score &gt; 19, and Vasoactive-inotropic score (VIS) &gt; 10, cardiopulmonary bypass time &gt; 177 minutes, and total hypothermic circulatory arrest time &gt; 30 minutes were associated with an increased risk of 30-day in-hospital mortality. CONCLUSIONS: Statistically significant predictors of hospital mortality in the treatment of patients with acute Stanford type A aortic dissection under cardiopulmonary bypass are the SOFA index, the APACHE II index and the VIS index after the end of surgery, as well as the time of cardiopulmonary bypass and the time of total hypothermic circulatory arrest.

Initial blood pressure and adverse cardiac events following acute ischaemic stroke: An individual patient data pooled analysis from the VISTA database.

Adverse cardiac events following ischaemic stroke (stroke-heart syndrome, SHS) pose a clinical challenge. We investigated the association between initial blood pressure at stroke presentation and the risk of SHS. We utilised data from the Virtual International Stroke Trials Archive (VISTA). We defined SHS as the incidence of cardiac complications within 30 days post-ischaemic stroke. These presentations included acute coronary syndrome encompassing myocardial injury, heart failure/left ventricular dysfunction, atrial fibrillation/flutter, other arrhythmia/electrocardiogram abnormalities, and cardiorespiratory arrest. Using Cox proportional hazards models, we assessed the risk trajectories for developing SHS and its presentations associated with initial blood pressure. We also explored the risk trajectories for 90-day mortality related to initial blood pressure. From 16,095 patients with acute ischaemic stroke, 14,965 (mean age 69 ± 12 years; 55% male) were analysed. Of these, 1774 (11.8%) developed SHS. The risk of SHS and initial blood pressure showed a U-shaped relationship. The lowest blood pressures (⩽130 mmHg systolic and ⩽55 mmHg diastolic) were associated with the highest risks (adjusted hazard ratio [95%confidence interval]: 1.40 [1.21-1.63]; p < 0.001, 1.71 [1.39-2.10]; p < 0.001, respectively, compared to referential blood pressure range).Cardiorespiratory arrest posed the greatest risk at higher blood pressure levels (2.34 [1.16-4.73]; p = 0.017 for systolic blood pressure >190 mmHg), whereas other presentations exhibited the highest risk at lower pressures. The 90-day mortality risk also followed a U-shaped distribution, with greater risks observed at high blood pressure thresholds. There is a U-shaped relationship between initial blood pressure at ischaemic stroke presentation and the risk of subsequent SHS.

Association of Benzodiazepine Prescription With Short-Term Prognosis in Elderly Patients Attended in Emergency Department: Results From the EDEN PROJECT.

Benzodiazepine prescription is a growing phenomenon among the elderly population. However, information related to the frequency of these drugs among the elderly population attending in emergency departments (ED) and its impact over prognosis is scarce. The aim of this study is to assess the prevalence of benzodiazepine prescription and to analyze its association with short-term prognosis in elderly patients attended in ED. A retrospective analysis of the EDEN (Emergency Department Elderly in Need) cohort was conducted. This registry included all elderly patients attending in 52 Spanish EDs for any condition, between April 1st and 7th in 2019. Socio-demographic data, comorbidities, and medication were recorded by consulting the patient's electronic health records. The assessed outcomes consisted on new ED visit, hospitalization, and mortality at 30 days after the first ED visit, associated with the use of benzodiazepines at baseline in comparison with no prescription of benzodiazepines. Crude and adjusted logistic regression analyses including patient's comorbidities were performed. Two sensitivity analyses were performed considering concomitant prescription of other central nervous system depressants as well as direct discharge from the ED. 25 557 patients were evaluated (mean age 78 [IQR: 71-84]). 7865 (30.8%) patients were taken benzodiazepines at admission. After adjustment for comorbidities and other central nervous system drugs, benzodiazepine prescription was associated with ED revisit [OR: 1.10 (95%CI: 1.03-1.18)]. Similar results were found in the sensitivity analysis, eliminating patients with central nervous depressors [OR: 1.11 (1.03-1.25)] and patients discharged to home [OR: 1.13 (1.04-1.23)]. No association was found between the use of these drugs and new hospitalizations [OR: 0.90 (0.77-1.05)] or mortality 30 days after discharge [OR: 1.01 (0.88-1.18)]. The results held for all three outcomes in the sensitivity analyses. The use of benzodiazepines is a frequent phenomenon among the elderly population attended in the ED, being associated with an increased risk of new visits to the emergency room, but not with an increased risk of 30-day hospitalization or mortality.

Association of postoperative opioid type with mortality and readmission rates: multicentre retrospective cohort study.

Opioid treatment in postoperative pain management is crucial, but the impact of administration practices on outcomes is unclear. The hypothesis was that prescription trends remained stable over recent years, and that no difference in mortality and readmission risks is associated with prescription strategies. Electronic health records of surgical episodes in the Capital and Zealand Regions of Denmark from 2017 to 2021 were analysed. All opioids administered during postoperative admission were converted to oral morphine equivalents (OMEQs) and an average daily dose per patient was calculated. The opioid administered in the highest OMEQ dosages is considered the primary opioid strategy for the surgical case. Administration trends were analysed through linear regression, and Cox regression was used to calculate hazard ratios to assess dominant opioid strategies' association with 90-day mortality and readmission rates while controlling for confounders. A total of 183 317 patients met the inclusion criteria. Prescription trends remained steady during the study period. Multivariable analysis revealed increased readmission risk (HR 1.18, P < 0.001) of tramadol and tapentadol compared to morphine. They exhibited decreased 90-day mortality risk (HR 0.63, P < 0.001). Oxycodone had similar readmission risk (HR 1.009, P = 0.24) but lower 90-day mortality risk (HR 0.68, P < 0.001). Postoperative in-hospital opioid administration remained stable from 2017 to 2021. Tramadol/tapentadol had a higher risk of readmission but lower mortality risk. Oxycodone had comparable readmission but reduced mortality risk. This study provides a framework for future clinical trials assessing this potential impact of opioids in a targeted manner.

30-day mortality and mortality-related risk factors in the Polish cohort undergoing catheter ablation of the accessory pathway between 2010 and 2020.

30-day mortality and mortality-related risk factors in the Polish cohort undergoing catheter ablation of the accessory pathway between 2010 and 2020.

Percutaneous mechanical circulatory support versus intraaortic balloon counterpulsation in patients with acute myocardial infarction complicated by cardiogenic shock

Abstract Background Acute myocardial infarction complicated by cardiogenic shock (AMI-CS) is a disease process associated with significantly poor clinical prognosis, placing patients at increased risk for morbidity and mortality. Currently, the optimal choice for temporary mechanical circulatory support remains unclear, with studies evaluating use of percutaneous ventricular assist devices (pVAD) yielding conflicting results. Purpose The goal of this meta-analysis is to evaluate the efficacy of pVAD compared to intra-aortic balloon counterpulsation (IABP) in patients presenting with AMI-CS. Methods A database search was performed for studies reporting on the association of pVAD compared to IABP with clinical outcomes in patients with AMI-CS. The primary endpoint of interest was 30-day all-cause mortality. Secondary endpoints included cardiovascular (CV) mortality, and recurrence of AMI. The databases searched included Pubmed, Web of Science, and Embase. The search was not restricted by time or publication status. Registry studies were excluded from this analysis. Subgroup analysis was performed separating randomized controlled trials from retrospective cohort studies. Results A total of 8 studies with 651 participants (322 treated with pVAD, 329 treated with IABP) met inclusion criteria. Mean age was 65 years old, 73.9% were men, mean left ventricular ejection fraction was 28%, mean follow-up was 9.8 months (ranging 1-66 months). Treatment of AMI-CS patients with pVAD was not associated with lower risk of 30-day all-cause mortality compared to IABP (OR 0.90, 95% CI 0.63-1.27; p=0.55). Heterogeneity was low for the RCT subgroup and moderate for the cohort study subgroup (I2=0%; I2=48%). Use of pVAD in patients with AMI-CS was associated with a non-statistically significant trend toward lower CV mortality compared to IABP (OR 0.53, 95% CI 0.29-0.99; p=0.05). The heterogeneity was low (I2=0%). Use of pVAD was not associated with significantly lower risk of recurrent AMI (OR 0.62, 95% CI 0.22-1.74; p=0.37). Heterogeneity was low for this analysis (I2=0%). Test for subgroup differences was not statistically significant for any of the above analyses. Conclusion In patients presenting with AMI-CS, use of pVAD compared to IABP is not associated with lower risk of all-cause mortality or recurrent AMI. However given the apparent trend toward lower risk of CV mortality in patients treated with pVAD, additional high-quality prospective studies are required.Figure 1

Utility of venoarterial extracorporeal membrane oxygenation in patients with acute myocardial infarction complicated by cardiogenic shock

Abstract Background Acute myocardial infarction complicated by cardiogenic shock (AMI-CS) continues to portend poor clinical prognosis and remains a major cause of morbidity and mortality. Although venoarterial (VA) extracorporeal membrane oxygenation (ECMO) is frequently used in the treatment of AMI-CS, studies evaluating its benefit compared to percutaneous ventricular assist devices (pVAD) or standard medical therapy in this patient population have yielded conflicting results. Purpose The goal of this meta-analysis is to evaluate the use of ECMO compared to either pVAD or medical therapy with or without intra-aortic balloon counterpulsation (IABP) in patients presenting with AMI-CS. Methods A database search was performed for studies reporting on the association of ECMO compared to pVAD or medical therapy with or without IABP with clinical outcomes in patients with AMI-CS. The endpoints of interest were 30-day all-cause mortality and long term all-cause mortality. The databases searched included Pubmed, Web of Science, and Embase. The search was not restricted by time or publication status. Registry studies were excluded from this analysis. Results A total of 8 studies with 937 participants (447 treated with ECMO, 243 treated with pVAD, 247 treated with medical therapy with or without IABP) met inclusion criteria. Mean age was 63 years old, 80.5% were men, mean left ventricular ejection fraction was 26%, mean follow-up was 6.3 months (ranging 1-12 months). Treatment of AMI-CS patients with ECMO was not associated with lower risk of 30-day all-cause mortality compared to pVAD or standard medical therapy with or without IABP placement (OR 1.29, 95% CI 0.87-1.90; p=0.21; OR 0.58, 95% CI 0.25-1.35; p=0.13). Heterogenetic was low to moderate for each subgroup. Test for subgroup differences did not demonstrate statistically significant differences in the results for pVAD and for standard medical therapy with or without IABP (p=0.10, I2=64.1%). Compared to pVAD, ECMO was not associated lower risk of long-term mortality (OR 1.27, 95% CI 0.85-1.90; p=0.24). The heterogeneity for this analysis was low (I2=0%). Conclusion In patients presenting with AMI-CS, use of VA-ECMO is not associated with lower risk of mortality compared to pVAD or standard medical therapy with or without IABP placement. The risks and benefits of ECMO should be carefully considered compared to other forms of temporary mechanical circulatory support.Figure 1

Impact of a blood return system on mechanical thrombectomy in treatment of acute pulmonary embolism: a retrospective cohort study comparing 30-day mortality and need for blood transfusion

Abstract Background Mechanical thrombectomy (MT) has become an increasingly popular approach in treatment of pulmonary embolism (PE). Blood loss from aspiration is common during this procedure and can potentially limit clot extraction. A blood return system designed to be used during MT was introduced in January 2022; however, there is limited data demonstrating if its use has impacted mortality or need for blood transfusion in patients treated with MT. Purpose The aim of this study is to assess if there is a difference in outcomes amongst patients with acute PE that underwent MT with a blood return system vs. those that underwent MT without one. We hypothesize that MT with a blood return system will reduce mortality and need for post-procedure blood transfusions. Methods A large retrospective, multicentre database was used to identify patients diagnosed with PE that underwent MT. Patients were subsequently divided into two groups: 1) After and including January 2022, which was after the implementation of a blood return system vs. 2) Before January 2022, which was prior to the implementation of a blood return system. Student’s t-test was performed to compare baseline characteristics between the two cohorts. Propensity matching was performed based on relevant comorbidities and severity of PE estimated by PESI score parameters. Kaplan Meier curves were calculated to compare 30-day post-procedure mortality and need for blood transfusion. Results Patients that underwent MT after implementation of a blood return system (n= 2511) and before implementation of a blood return system (n= 2755) were propensity matched yielding 1915 patients per cohort. MT after implementation of a blood return system was associated with a decreased 30-day mortality compared to MT before implementation (6.99% vs 11.77% HR=0.602; 95% CI [0.486, 0.746], log-rank p&amp;lt;0.0001). Additionally, MT after implementation of a blood return system was associated with a decreased need for blood transfusion (7.52% vs 10.38%; HR=0.717; 95% CI [0.572, 0.898], log-rank p=0.0034). Conclusion MT after implementation of a blood return system was associated with a decreased risk of 30-day mortality and a lower likelihood of requiring blood transfusion when compared to MT prior to implementation of a blood return system.

Explainable machine learning and multi-modal data for predicting readmission in patients with heart failure

Abstract Background Cardiovascular diseases (CVDs) are among the leading causes of mortality and morbidity globally, with an estimated 1 million hospital admissions for CVD in England in 2019/20, leading to 5.5 million bed days. In addition, patients with CVDs have a notably high rate of hospital readmission, with approximately one in four patients experiencing heart failure (HF) being readmitted within one month of discharge. We explored whether machine learning models trained on electrocardiogram (ECG) and patient electronic health records (EHRs) can support decision-making and risk management and ultimately improve health outcomes for HF patients. Purpose The project aims to develop a machine learning model to predict health outcomes for HF patients. To test the hypothesis, we trained and tested an explainable machine learning model to predict the risk of mortality and hospital readmission rate for HF patients. Methods We used EHR data and tabulated ECG records to train an XGBoost model to predict the risk of 30-day mortality and 30-day hospital readmission for HF patients. EHR data from a cohort of 2,868 patients with their ECG records were used for model development. We extracted a total of 78 features from the ECG data, such as heart rate variability (HRV), P-wave durations, and QT intervals. These ECG features were combined with coded and free-text EHR data (e.g., demographic information, diagnosis, medication history, and lab results) and used as tabular inputs to the XGBoost model. Of the 2,868 patients, an internal set of 574 patients stratified by age, sex, and health outcomes (30-day mortality and 30-day hospital readmission) were held out for testing. Results Among 2,868 HF patients with 10-year follow-up, 1065 patients were reported for mortality or hospital readmission within 30 days of discharge. When the machine learning model was trained on ECG data in addition to EHR data, the model was able to predict patient mortality and hospital readmission rate in the test set with an area under the curve (AUC) of 0.91 and 0.70, respectively. For mortality prediction, the model achieved a sensitivity and specificity of 0.81 and 0.82, respectively, when employing an operating point with minimum difference between the sensitivity and specificity. When the threshold was adjusted to favor sensitivity at 0.91, the model specificity decreased to 0.74. The machine learning model also identified high sensitive troponin levels, QT dispersion, and lactate dehydrogenase levels as features of high importance for predicting the outcomes for HF patients. Conclusions Our developed machine learning model was able to predict mortality and readmission risks in HF patients using multi-modal data. Upon further validation, the machine learning model has the potential to be tested for supporting clinical decision-making and risk management for HF patients.ROC CurveFeature Importance