Factors related to cardiac rupture after acute myocardial infarction.

Background: Cardiac rupture (CR) after acute myocardial infarction (AMI) is a fatal mechanical complication. The early identification of factors related to CR in high-risk cases may reduce mortality. The purpose of our study was to discover relevant risk factors for CR after AMI and in-hospital mortality from CR. Methods: In this study, we enrolled 1,699 AMI cases from October 2013 to May 2020. A total of 51 cases were diagnosed with CR. Clinical diagnostic information was recorded and analyzed retrospectively. We randomly matched these cases with AMI patients without CR in a 1:4 ratio. Univariate and multivariate logistic regression and stratifying analysis were used to identify risk factors for CR. Univariate and multivariate Cox regression hazard analysis and stratifying analysis were used to assess predictors of in-hospital mortality from CR. Results: The incidence of CR after AMI was 3.0% and in-hospital mortality was approximately 57%. Multivariate logistic regression analysis identified that white blood cell count, neutrophil percentage, anterior myocardial infarction, a Killip class of >II, and albumin level were independently associated with CR (p < 0.05). Stratifying analysis showed that age, systolic blood pressure, and bicarbonate were independent risk factors for female CR (p < 0.05) but not male CR. Triglyceride and cardiac troponin I were independent risk factors for male CR (p < 0.05) but not female CR. Anterior myocardial infarction, a Killip class of >II, and neutrophil percentage were independent risk factors for male and female CR (p < 0.05). Multivariate Cox regression analysis showed that the time from symptom to CR and the site of CR were independent predictors for in-hospital mortality from CR (p < 0.05). Stratification analysis indicated that risk factors did not differ based on gender, but platelet counts were predictors for in-hospital mortality in female and male CR. Conclusion: Low albumin, a high white blood cell count, neutrophil percentage, anterior myocardial infarction, and a Killip class of >II were independent and significant predictors for CR. However, risk factors are different in male and female CR. The time from symptom to CR, the site of CR, and platelet counts were independent predictors for in-hospital mortality from CR. These may be helpful in the early and accurate identification of high-risk patients with CR and the assessment of prognosis. In addition, gender differences should be considered.

Association between Poor Outcomes and Risk of Refeeding Syndrome among Patients Urgently Admitted to the High Dependency Unit: A Single-Center Cohort Study in Japan.

Background/Objectives: Refeeding syndrome (RFS) is recognized as a potentially fatal metabolic disturbance, particularly concerning for non-critically ill patients who do not receive frequent electrolyte assessments. Assessing the risk of developing RFS and implementing preventive strategies is essential in these cases. We investigated the proportion of risk and its association with prognosis in a high-dependency unit (HDU). Method: This observational study was conducted in a tertiary care hospital's HDU in Japan. We consecutively enrolled all patients who had been admitted urgently to the HDU and hospitalized for three days or more. We evaluated the National Institute for Health and Clinical Excellence (NICE) RFS risk factors at admission and classified patients into four groups based on the modified NICE criteria. The primary outcome was 30-day in-hospital mortality. The secondary outcome was a composite of 30-day in-hospital mortality and transfer to the intensive care unit, or discharge to locations other than home. Using logistic regression, we assessed the association between the four risk groups and outcomes, using the no-risk group as a reference. Results: A total of 955 patients were analyzed, of which 33.1%, 26.7%, 37.8%, and 2.4% were classified into the no-risk, low-risk, high-risk, and very high-risk groups, respectively. The 30-day in-hospital mortality was 4.4%, 5.5%, 5.0%, and 21.7%, respectively (Log-rank trend test: p = 0.047). In multivariable logistic regression, adjusting for sepsis, comorbidities, and age, only the very high-risk group was associated with 30-day in-hospital mortality (odds ratio: 5.54, 95% confidence interval: 1.73-17.79) A similar association was observed for the secondary outcomes. Conclusions: For patients admitted urgently to the HDU, there may be an opportunity to improve outcomes for very high-risk patients through preventive strategies.

Inflammation scores based on C-reactive protein and albumin predict mortality in hospitalized older patients independent of the admission diagnosis.

Systemic inflammation significantly increases the risk of short- and long-term mortality in geriatric hospitalized patients. To predict mortality in older patients with various age-related diseases and infections, including COVID-19, inflammatory biomarkers such as the C-reactive protein (CRP) to albumin ratio (CAR), and related scores and indexes, i.e. Glasgow Prognostic Score (GPS), modified GPS (mGPS), and high sensitivity (hs)-mGPS, have been increasingly utilized. Despite their easy affordability and widespread availability, these biomarkers are predominantly assessed for clinical purposes rather than predictive applications, leading to their underutilization in hospitalized older patients. In this study, we investigated the association of CAR, GPS, mGPS, and hs-mGPS with short-term mortality in 3,206 geriatric hospitalized patients admitted for acute conditions, irrespective of admission diagnosis. We observed that unit increases of CAR, and the highest classes of GPS, mGPS, and hs-mGPS were significantly associated with a two- to threefold increased risk of death, even adjusting the risk for different confounding variables. Interestingly, a hs-mGPS of 2 showed the highest effect size. Furthermore, gender analysis indicated a stronger association between all CRP-albumin based parameters and mortality in men, underscoring the gender-specific relevance of inflammation-based circulating parameters in mortality prediction. In conclusion, scores based on serum CRP and albumin levels offer additional guidance for the stratification of in-hospital mortality risk in older patients by providing additional information on the degree of systemic inflammation.

Older hospitalised patients with a chief complaint of weakness and nonspecific presentations are not at risk of adverse health outcomes.

RATIONALE AND OBJECTIVE: Older adults in the Emergency Department (ED) often present with nonspecific complaints (NSC) that might be associated with adverse health outcomes due to underestimating the seriousness of the illness by health care workers. METHODS: We selected a random sample of patients aged 65 or older who complained of weakness and were hospitalised in internal medicine departments in 2019-2021. We divided the patients into those with and without specific reasons for hospitalisation after the ED evaluation. Outcome variables included changes in medical care based on CT head scans and blood tests, and whether a delay in diagnosis led to a longer stay, in-hospital mortality, or readmission within 30 days. RESULTS: Patients were aged 82 ± 8 years and 43.6% (233/536)were female. 46.8% (260/556) of the patients had a specific reason for hospitalisation after the ED evaluation including four patients presenting with confusion, without neurological findings but with acute ischaemia found on the brain CT. Patients without a specific presentation had fewer blood tests done due to a significantly shorter hospital stay (median (1st-3rd quartiles: 3 (2-4) vs. 4 (3-6) days, p < 0.001), a lower mortality rate, 0.3% (n = 1) compared to 4.2% (n = 11), p = 0.002), and fewer readmissions 13.5%(n = 40) compared to 20.4% (n = 53). The deaths and readmissions in both groups were not due to a delay in diagnosis. CONCLUSIONS: Elderly patients with a chief complaint of weakness with and without a specific reason for hospitalisation were not at an increased risk for inappropriate treatment or a missed diagnosis.

Machine learning models for mortality prediction in critically ill patients with acute pancreatitis-associated acute kidney injury.

Background: The occurrence of acute kidney injury (AKI) was associated with an increased mortality rate among acute pancreatitis (AP) patients, indicating the importance of accurately predicting the mortality rate of critically ill patients with acute pancreatitis-associated acute kidney injury (AP-AKI) at an early stage. This study aimed to develop and validate machine learning-based predictive models for in-hospital mortality rate in critically ill patients with AP-AKI by comparing their performance with the traditional logistic regression (LR) model. Methods: This study used data from three clinical databases. The predictors were identified by the Recursive Feature Elimination algorithm. The LR and two machine learning models-random forest (RF) and eXtreme Gradient Boosting (XGBoost)-were developed using 10-fold cross-validation to predict in-hospital mortality rate in AP-AKI patients. Results: A total of 1089 patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD) were included in the training set and 176 patients from Xiangya Hospital were included in the external validation set. The in-hospital mortality rates of the training and external validation sets were 13.77% and 54.55%, respectively. Compared with the area under the curve (AUC) values of the LR model and the RF model, the AUC value of the XGBoost model {0.941 [95% confidence interval (CI) 0.931-0.952]} was significantly higher (both P < .001) and the XGBoost model had the smallest Brier score of 0.039 in the training set. In the external validation set, the performance of the XGBoost model was acceptable, with an AUC value of 0.724 (95% CI 0.648-0.800). However, it did not differ significantly from the LR and RF models. Conclusions: The XGBoost model was superior to the LR and RF models in terms of both the discrimination and calibration in the training set. Whether the findings can be generalized needs to be further validated.

An update of the severe trauma scoring system using the Korean National Emergency Department Information System (NEDIS) database.

BACKGROUND: Various scoring systems are utilized to assess severe trauma patients, with one of the most commonly used tools being the International Classification of Diseases Injury Severity Score (ICISS) criteria derived from the Survival Risk Ratio (SRR) calculated using diagnostic codes. This study aimed to redefine the severe trauma scoring system in Korea based on the SRR for diagnostic codes, and subsequently evaluate its performance in predicting survival outcomes for trauma patients. METHODS: This study included trauma patients who visited Level 1 and 2 emergency departments (EDs) between January 2016 and December 2019, utilizing the Korean National Emergency Department Information System (NEDIS) database. The primary outcome of this study was in-hospital mortality. The new SRR-2020 value was calculated for each of the 865 trauma diagnosis codes (Korean Standard Classification of Diseases [KCD-7] codes, 4-digit format), and the patient-specific ICISS-2020 value was derived by multiplying the corresponding SRR-2020 value based on patient diagnosis. We compared the predictive performance for in-hospital mortality between severe trauma patients with an ICISS <0.9 based on the newly developed ICISS-2020 version and those defined by the previously used ICISS-2015 version. RESULTS: A total of 3,841,122 patients were enrolled, with an in-hospital mortality rate of 0.5 %. Severe trauma patients with ICISS-2020 < 0.9 accounted for 5.3 % (204,897 cases) that was lower than ICISS-2015 < 0.9 accounting for 15.3 % (587,801 cases). Among the 20,619 in-hospital mortality cases, 81.4 % had ICISS-2020 < 0.9, and 88.6 % had ICISS-2015 < 0.9. When comparing predictive performance for in-hospital mortality between the two ICISS versions, ICISS-2020 showed higher accuracy (0.95), specificity (0.95), positive predictive value (PPV) (0.08), positive likelihood ratio (LR+) (16.53), and area under the receiver operating characteristic curve (AUROC) (0.96) than ICISS-2015 for accuracy (0.85), sensitivity (0.88), specificity (0.85), PPV (0.03), LR+ (5.94), and AUROC (0.94). However, regarding sensitivity, ICISS-2020 < 0.9 showed a lower value of 0.81 compared to ICISS-2015 < 0.9, which was 0.88. The negative predictive value (NPV) was 1.00 for both versions. CONCLUSIONS: The newly developed ICISS-2020, utilizing a nationwide emergency patient database, demonstrated relatively good performance (accuracy, specificity, PPV, LR+, and AUROC) in predicting survival outcomes for patients with trauma.

Hypoalbuminemia is a predictor of mortality in patients with cardiogenic shock requiring veno-arterial extracorporeal membrane oxygenation.

INTRODUCTION: Hypoalbuminemia is predictive of mortality in critically ill patients, especially those with cardiac etiologies of illness. The objective of this study was to determine the association of albumin level pre-cannulation for veno-arterial (V-A) extracorporeal membrane oxygenation (ECMO) and important clinical hospital outcomes. METHODS: This was a retrospective, observational cohort study of albumin levels in patients with cardiogenic shock requiring V-A ECMO between December 2015 and August 2021 in a single, high-volume ECMO center. The primary outcome was in-hospital mortality. RESULTS: Of 434 patients assessed, 318 were included. The overall mean pre-ECMO albumin was 3 ± 0.8 g/dL and mean albumin at 72 hours post-cannulation was 2.7 ± 0.5 g/dL. For patients with pre-ECMO albumin ≤3 g/dL vs. >3 g/dL, in-hospital mortality was 44.9% vs. 27.5%, respectively (p = .002). In multivariable logistic regression analysis, higher albumin (per 1 g/dL increase) at time of V-A ECMO initiation was associated with decreased odds of in-hospital mortality (OR, 0.68; 95% CI, 0.48-0.96; p = .03). Patients with a pre-ECMO albumin ≤3 g/dL required significantly more platelet transfusions and had higher incidence of gastrointestinal bleeding during V-A ECMO support (both p < .05). CONCLUSIONS: Hypoalbuminemia at time of cannulation is significantly associated with in-hospital mortality and ECMO-related complications including platelet transfusion and gastrointestinal bleeding. Albumin levels at the time of consideration of V-A ECMO may serve as a key prognostic indicator and may assist in effective decision-making regarding this invasive and costly resource.

Development and validation of the PHM-CPA model to predict in-hospital mortality for cirrhotic patients with acute kidney injury.

BACKGROUND: The presence of acute kidney injury (AKI) significantly increases in-hospital mortality risk for cirrhotic patients. Early prognosis prediction for these patients is crucial. We aimed to develop and validate a machine learning model for in-hospital mortality prediction for cirrhotic patients with AKI. METHODS: Data from cirrhotic patients with AKI hospitalized at the First Affiliated Hospital of Zhejiang University between January 1, 2013, and December 31, 2020 were used to train and validate an extreme Gradient Boosting model to predict in-hospital mortality risk. The Boruta algorithm was used for variable selection. The optimal model was selected and named as PHM-CPA (Prediction of in-Hospital Mortality for Cirrhotic Patients with AKI). The PHM-CPA model was then externally validated in patients from eICU Collaborative Research Database (eICU-CRD) and Medical Information Mart for Intensive Care III dataset (MIMIC). The predictive performance of PHM-CPA model was compared with that of logistic regression (LR) model and 25 previously reported models. RESULTS: A total of 519 cirrhotic patients with AKI were enrolled in model training cohort, of whom 118 (23%) died during hospitalization. Fifteen variables from common laboratory tests were selected to develop the PHM-CPA model. The PHM-CPA model achieved an AUROC of 0.816 (95% CI, 0.763-0.861) in the internal validation cohort and 0.787 (95% CI, 0.745-0.830) in the external validation cohort. The PHM-CPA model consistently outperformed the LR model and 25 previously reported models. CONCLUSION: We developed and validated the PHM-CPA model, comprising readily available clinical variables, which demonstrated superior performance and calibration in predicting in-hospital mortality for cirrhotic patients with AKI.

Effect of disability, homelessness, and neighborhood marginalization on risk-adjustment for hospital performance measurement.

Background It is not known how disability, homelessness, or neighborhood marginalization influence risk-adjusted hospital performance measurement in a universal health care system. Methods We evaluated the effect of including these equity-related factors in risk-adjustment models for in-hospital mortality, and 7- and 30-day readmission in 28 hospitals in Ontario, Canada. We compared risk-adjustment with commonly-used clinical factors to models that also included homelessness, disability, and neighborhood indices of marginalization. We evaluated models in historical data using internal-external cross-validation. We calculated risk-standardized outcome rates for each hospital in a recent reporting period using mixed-effects logistic regression. Results The cohort included 544,805 admissions. Adjustment for disability, homelessness, and neighborhood marginalization had little impact on discrimination or calibration of risk-adjustment models. However, it influenced comparative hospital performance on risk-standardized 30-day readmission rates, resulting in 5 hospitals being reclassified between below-average, average, and above-average groups. No hospitals were reclassified for mortality and 7-day readmission. Conclusion In a system with universally insured hospital services, adjustment for disability, homelessness, and neighborhood marginalization influenced estimates of hospital performance for 30-day readmission but not 7-day readmission or in-hospital mortality. These findings can inform researchers and policymakers as they thoughtfully consider when to adjust for these factors in hospital performance measurement.

The clinical applications of ensemble machine learning based on the Bagging strategy for in-hospital mortality of coronary artery bypass grafting surgery.

Background: Machine learning (ML) has excelled after being introduced into the medical field. Ensemble ML models were able to integrate the advantages of several different ML models. This study compares the ensemble ML model's and EuroSCORE II's performance predicting in-hospital mortality in patients undergoing coronary artery bypass grafting surgery. Methods: The study included 4,764 patients from three heart centers between January 2007 and December 2021. Of these, 3812 patients were assigned to the modeling group, and 952 patients were assigned to the internal test group. Patients from other two heart center (1733 and 415 cases, respectively) constituted the external test group. The modeling set data are trained using each of the three ML strategies (XGBoost, CatBoost, and LightGBM), and the new model (XCL model) is constructed by integrating these three models through an ensemble ML strategy. Performance of different models in the three test groups comparative assessments were performed by calibration, discriminant, decision curve analysis, net reclassification index (NRI), integrated discriminant improvement (IDI), and Bland-Altman analysis. Results: In terms of discrimination, the XCL model performed the best with an impressive AUC value of 0.9145 in the internal validation group. The XCL model continued to perform best in both external test groups. The NRI and IDI suggested that the ML model showed positive improvements in all three test groups compared to EuroSCORE II. Conclusions: ML models, particularly the XCL model, outperformed EuroSCORE II in predicting in-hospital mortality for CABG patients, with better discrimination, calibration, and clinical utility.

Is there an obesity paradox in cardiovascular outcomes for patients undergoing Transcatheter Edge-to-Edge Repair? A pilot meta-analysis.

Background: The impact of body mass index (BMI) on Transcatheter Edge-to-Edge Repair (TEER) outcomes remains uncertain, with studies showing conflicting results. Some suggest an 'obesity paradox' exists, favoring better outcomes for obese patients and worse outcomes for underweight patients, while others report no significant impact of BMI. Methodology: We systematically searched major databases for studies on baseline BMI and post-procedural outcomes in TEER patients. Patients were grouped by BMI: underweight (<18.5 kg/m2), normal (18.5-24.9 kg/m2), overweight (25-29.9 kg/m2), and obese (≥30 kg/m2). Data were pooled using a random-effects model, with risk ratios (RRs) and their 95 % confidence intervals (CIs) as effect measures. Statistical significance was set at p < 0.05. Results: Our study, analyzing five observational studies with 7580 obese and 74,717 non-obese patients, found no significant difference in in-hospital mortality between the groups (RR: 0.85; p = 0.427). Subgroup analysis indicated a higher mortality risk for underweight patients compared to overweight (RR: 1.48; p = 0.006) and obese patients (RR: 1.40; p = 0.036), though the difference between underweight and normal-weight patients was not significant (RR: 1.18; p = 0.216). The risks of myocardial infarction (RR: 1.10; p = 0.592) and stroke (RR: 0.43; p = 0.166) were also similar between obese and non-obese patients. Conclusions: In conclusion, our analysis found no significant difference in in-hospital mortality, myocardial infarction or stroke risk between obese and non-obese patients undergoing TEER. However, underweight patients may have a higher risk of in-hospital mortality compared to overweight and obese individuals, highlighting the potential impact of BMI on outcomes in TEER patients.

Characteristics and outcomes of patients with cancer hospitalized with new onset acute heart failure.

AIMS: Limited evidence exists regarding the outcomes of cancer patients hospitalized with new onset acute heart failure (AHF). We assessed the in-hospital mortality and 1 year outcomes of cancer patients admitted for new onset AHF, taking into account both past and active cancer status as well as cancer site. METHODS: We examined administrative data of adult patients hospitalized with a first episode of AHF from 2003 to 2018 in Lombardy, Italy. Patients were categorized based on their cancer history. The primary endpoint was in-hospital mortality with secondary endpoints including 1 year all-cause mortality and 1 year re-hospitalization for AHF. RESULTS: Among 283 144 patients AHF hospitalizations, 55 145 (19%) involved patients with a history of cancer (60% past cancer, 40% active cancer). Both in-hospital and 1 year mortality rates were higher among cancer patients compared with those without (9.3% vs. 6.4% and 34.9% vs. 22.3%, respectively; P < 0.0001). After adjustment, cancer patients exhibited increased risk of in-hospital mortality [odds ratio (OR) 1.40; 99% confidence interval (CI) 1.34-1.46] and 1 year mortality (HR 1.35; 99% CI 1.32-1.39), particularly among those with lung cancer. Patients with active and past cancer had a similar in-hospital mortality risk (OR 0.99; 99% CI 0.91-1.07) while 1 year mortality risk was higher among those with active cancer (HR 1.26; 99% CI 1.21-1.31). CONCLUSIONS: Cancer is a prevalent comorbidity in patients hospitalized with new onset AHF, and it is associated with a poorer prognosis. Mortality risk appears to vary based on cancer status and type.

Identification of novel sub-phenotypes of severe ARDS requiring ECMO using latent class analysis.

BACKGROUND: Sub-phenotyping of acute respiratory distress syndrome (ARDS) could be useful for evaluating the severity of ARDS or predicting its responsiveness to given therapeutic strategies, but no studies have yet investigated the heterogeneity of patients with severe ARDS requiring veno-venous extracorporeal membrane oxygenation (V-V ECMO). METHODS: We conducted this retrospective multicenter observational study in adult patients with severe ARDS treated by V-V ECMO. We performed latent class analysis (LCA) for identifying sub-phenotypes of severe ARDS based on the radiological and clinical findings at the start of ECMO support. Multivariate Cox regression analysis was conducted to investigate the differences in mortality and association between the PEEP setting of ≥ 10 cmH2O and mortality by the sub-phenotypes. RESULTS: We identified three sub-phenotypes from analysis of the data of a total of 544 patients with severe ARDS treated by V-V ECMO, as follows: Dry type (n = 185; 34%); Wet type (n = 169; 31%); and Fibrotic type (n = 190; 35%). The 90-days in-hospital mortality risk was higher in the patients with the Fibrotic type than in those with the Dry type (adjusted hazard ratio [95% confidence interval] 1.75 [1.10-2.79], p = 0.019) or the Wet type (1.50 [1.02-2.23], p = 0.042). The PEEP setting of ≥ 10 cmH2O during the first 3 days of ECMO decreased the 90-days in-hospital mortality risk only in patients with the Wet type, and not in those with the Dry or Fibrotic type. A significant interaction effect was observed between the Wet type and the PEEP setting of ≥ 10 cmH2O in relation to the 90-day in-hospital mortality (pinteraction = 0.036). CONCLUSIONS: The three sub-phenotypes showed different mortality rates and different relationships between higher PEEP settings in the early phase of V-V ECMO and patient outcomes. Our data suggest that we may need to change our management approach to patients with severe ARDS during V-V ECMO according to their clinical sub-phenotype.

The prognostic impact of maximal aortic diameter on acute type B aortic dissection progression in a Chinese population.

Currently, evidence concerning the link between maximal aortic diameter and in-hospital mortality in cases of acute type B aortic dissection (ATBAD) is insufficient. Thus, this study aimed to explore the relationship between the maximal aortic diameter at the time of admission and the early prognosis of patients diagnosed with ATBAD. A total of 678 patients with ATBAD were included between January 2016 and December 2018, during which their clinical data was gathered. The independent variable analyzed was the maximal diameter of the aorta, while the dependent variable was mortality during hospitalization. Factors considered in this analysis included the patients' age, gender, body mass index (BMI), medical history of hypertension, stroke, diabetes, atherosclerosis, smoking habits, chronic kidney insufficiency, time until presentation, systolic and diastolic blood pressures, ejection fraction, presence of aortic regurgitation, symptoms, involvement of abdominal vessels, laboratory findings, and treatment approaches. Of these patients collected, the mean age was 56.03 ± 12.22 years, and approximately 82.45% of them were male. After analysis, it was found that the maximal aortic diameter of patients with ATBAD was positively correlated with in-hospital mortality (OR = 1.06, 95% CI 1.03 to 1.10). Surprisingly, a J curve relationship was detected between maximal aortic diameter (point 31 mm) and in-hospital death for patients with ATBAD. The effect sizes and confidence intervals of the right (maximal aortic diameter > 31 mm) and left (maximal aortic diameter ≤ 31 mm) aspects of the inflection point were 1.06 (1.02-1.11) and 1.03 (0.83-1.28), respectively. In addition, the stratified analysis showed a stable relationship between maximal aortic diameter and in-hospital mortality, while there was no significant difference in the interaction between different subgroups. In patients with ATBAD, a J-curve relationship was identified between the maximal aortic diameter and in-hospital mortality. Specifically, when the maximal aortic diameter exceeds 31 mm, a positive correlation with in-hospital death was observed.

Impact of PM2.5 exposure on mortality and tumor recurrence in resectable non-small cell lung carcinoma.

This study aimed to explore the impact of PM 2.5 exposure on survival, post-operative outcomes, and tumor recurrence in resectable non-small cell lung cancer (NSCLC) patients. The study cohort comprised 587 patients at Chiang Mai University Hospital between January 1, 2010, and December 31, 2017. Patients were categorized based on their residents' average PM 2.5 concentration into two groups: exposed (PM 2.5 ≥ 25 µg/m3 annual mean) and unexposed (PM 2.5 < 25 µg/m3 annual mean). The exposed group had 278 patients, while the unexposed group had 309 patients. Baseline differences in gender and surgical approach were observed between the groups. Multivariable regression analysis revealed that patients in the exposed group had a higher risk of death (HR 1.44, 95% CI, 1.08-1.89, p = 0.012). However, no significant associations were found between PM 2.5 and post-operative pulmonary complications (RR 1.12, 95% CI, 0.60-2.11, p = 0.718), in-hospital mortality (RR 1.98, 95% CI, 0.40-9.77, p = 0.401), and tumor recurrence (HR 1.12, 95% CI, 0.82-1.51, p = 0.483). In conclusion, a PM 2.5 concentration ≥ 25 µg/m3 annual mean was associated with decreased overall survival and a potential increase in in-hospital mortality among resectable NSCLC patients. Larger studies with extended follow-up periods are required to validate these findings.

Demographic-based disparities in outcomes for adults with central line-associated bloodstream infections in the United States: a National Inpatient Sample database study (2016-2020).

Introduction: Central line-associated bloodstream infections (CLABSI) are prevalent and preventable hospital-acquired infections associated with high morbidity and costs. Disparities based on race, ethnicity, and hospital factors remain underexplored. This study compares cost, length of stay, and mortality for adults with CLABSI by race-ethnicity, hospital location-teaching status, and geographic region in the United States using data from the National Inpatient Sample (NIS) database from 2016 to 2020. Methods: The hospitalization cohort included adults diagnosed with CLABSI, excluding those with primary CLABSI diagnoses, cancer, immunosuppressed states, or neonatal conditions. Primary outcomes were in-hospital mortality, length of stay, and hospital costs, adjusted to mid-year 2020 US dollars. Independent variables included race-ethnicity, hospital location-teaching status, and geographic region. All analyses accounted for NIS sampling design. Results: From 2016 to 2020, there were approximately 19,835 CLABSI hospitalizations. The overall in-hospital mortality rate was 9.1%, with a median hospital stay of 16.9 days and median cost of $44,810. Hispanic patients experienced significantly higher mortality, longer length of stay, and higher costs compared to non-Hispanic Black and White patients. Urban teaching hospitals had longer stays and higher costs than rural and urban non-teaching hospitals. Regionally, the Northeast and West had higher costs and longer stays than the Midwest and South, but mortality rates did not differ significantly. Conclusion: This study highlights significant disparities in CLABSI outcomes based on demographic factors. Addressing these disparities is crucial for improving CLABSI management and healthcare equity. Further research should explore the underlying causes of these differences to inform targeted interventions.

Characteristics and In-Hospital Outcomes of Patients With Myocardial Infarction With Non-Obstructive Coronary Arteries　- Insights From the Real-World JAMIR Database.

BACKGROUND: Few studies have investigated the clinical characteristics and in-hospital outcomes of patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) using real-world databases in the coronary intervention era. METHODS AND RESULTS: We conducted a retrospective analysis of 22,236 patients (mean [±SD] age 68±13 years, 23.4% female) enrolled in the Japan Acute Myocardial Infarction Registry (JAMIR) between 2011 and 2016. Based on urgent coronary angiography findings, 286 (1.3%) patients were diagnosed as MINOCA, and the remaining 21,950 (98.7%) as MI with obstructive coronary artery disease (MI-CAD). MINOCA patients were characterized by younger age, fewer coronary risk factors, lower rate of ST-elevation myocardial infarction, lower Killip classification, and lower peak creatinine phosphokinase levels than MI-CAD patients. In-hospital all-cause mortality did not differ between the MINOCA and MI-CAD groups (5.2% vs. 5.7%, respectively; P=0.82). Comparing cause-specific mortality, non-cardiac mortality was higher in the MINOCA than MI-CAD group (4.2% vs. 1.6%; P<0.01). Importantly, non-cardiac death was more prevalent among elderly (≥65 years) than younger (<65 years) patients in the MI-CAD group, whereas this trend was not observed in the MINOCA group. CONCLUSIONS: Analysis of the real-world JAMIR database revealed a relatively high prevalence of non-cardiac death among MINOCA patients, underscoring the need for comprehensive management to improve disease prognosis, particularly in younger patients.

Association between liver fibrosis and the in-hospital mortality in patients with sepsis-induced coagulopathy.

BACKGROUND: The impact of liver fibrosis on the clinical outcomes of patients with sepsis-induced coagulopathy (SIC) is not well understood. This study aimed to evaluate the association between liver fibrosis scores and in-hospital mortality in SIC patients. METHODS: In this retrospective observational cohort study, data were collected from patients diagnosed with sepsis and admitted to the ICU at the First Affiliated Hospital of Wenzhou Medical University between January 2017 and December 2023. Liver fibrosis was evaluated using three scores: Fibrosis-4 (Fib-4), Aspartate Aminotransferase-to-Platelet Ratio Index (APRI), and Nonalcoholic Fatty Liver Disease Fibrosis Score (NFS). Patients were divided into tertiles according to their liver fibrosis scores, and the primary outcome was in-hospital mortality. Multivariable logistic regression and restricted cubic spline regression analyses were used to assess associations, complemented by sensitivity analyses through subgroup evaluations. RESULTS: The cohort included 948 patients diagnosed with SIC with an in-hospital mortality of 26.16%. Multivariate logistic regression analysis revealed a significant association between higher liver fibrosis scores and increased in-hospital mortality. Specifically, patients in the highest tertile of Fib-4, APRI, and NFS scores had significantly higher odds of mortality (FIB-4: OR 3.62, 95% CI 1.03-12.69; APRI: OR 2.16, 95% CI 0.88-5.30; NFS: OR 6.80, 95% CI 2.11-21.93) compared to those in the lowest tertile. The restricted cubic spline regression model showed a linear increase in the risk of in-hospital mortality with increasing liver fibrosis score. Sensitivity analysis confirmed the consistency and stability of the results across the different subgroups. CONCLUSION: Our study suggests that elevated liver fibrosis scores, particularly Fib-4 and NFS, are associated with higher in-hospital mortality in SIC patients. Further research, especially larger prospective studies, are needed to validate these findings.

Association between toxicity-index of diquat and in-hospital mortality in patients with acute diquat poisoning: a retrospective cohort study.

BACKGROUND: This study investigates the impact of diquat toxicity levels on in-hospital mortality rates among patients with acute diquat poisoning. It aims to clarify the relationship between diquat toxicity scores and the likelihood of death during hospitalization. METHODS: A retrospective cohort study was conducted on 98 individuals with acute diquat poisoning. Data on post-ingestion time, initial diquat plasma concentration, and clinical outcomes were systematically collected for all participants. The toxicity-index of diquat was calculated based on post-ingestion time and initial diquat plasma concentration. Logistic regression analysis was utilized to assess the association between the toxicity-index of diquat and in-hospital mortality rates, adjusting for potential confounding variables such as age, comorbidities, and treatment interventions. RESULTS: The study found that the overall prevalence of in-hospital mortality was 34.7%, with 58.2% in males. The multivariable-adjusted regression coefficient for in-hospital mortality associated with the toxicity-index was 1.09, with a 95% confidence interval (CI) of 1.01-1.17. Subsequent exploratory subgroup analysis indicated that there were no significant interactions (all p values for interaction were >0.05). CONCLUSIONS: The study found that higher diquat toxicity-index values correlate with increased in-hospital mortality in acute diquat poisoning cases, indicating that the toxicity-index could be a useful biomarker for assessing mortality risk.

The toxicity-index of diquat plays a pivotal role in the identification, management, and prognostic prediction of acute diquat poisoning; however, its specific predictive value warrants further investigation.The toxicity-index of diquat serves as a more precise biomarker for differentiating between low-risk and high-risk categories.In comparison to low-risk patients with acute diquat poisoning, the toxicity-index of diquat in high-risk patients were significantly elevated.

[18F]FDG PET/CT Imaging Is Associated with Lower In-Hospital Mortality in Patients with Pyogenic Spondylodiscitis-A Registry-Based Analysis of 29,362 Cases.

BACKGROUND: While MRI is the primary diagnostic tool for the diagnosis of spondylodiscitis, the role of [18F]-fluorodeoxyglucose ([18F]FDG) PET/CT is gaining prominence. This study aimed to determine the frequency of [18F]FDG PET/CT usage and its impact on the in-hospital mortality rate in patients with spondylodiscitis, particularly in the geriatric population. METHODS: We conducted a Germany-wide cross-sectional study from 2019 to 2021 using an open-access, Germany-wide database, analyzing cases with ICD-10 codes M46.2-, M46.3-, and M46.4- ('Osteomyelitis of vertebrae', 'Infection of intervertebral disc (pyogenic)', and 'Discitis unspecified'). Diagnostic modalities were compared for their association with in-hospital mortality, with a focus on [18F]FDG PET/CT. RESULTS: In total, 29,362 hospital admissions from 2019 to 2021 were analyzed. Of these, 60.1% were male and 39.9% were female, and 71.8% of the patients were aged 65 years and above. The overall in-hospital mortality rate was 6.5% for the entire cohort and 8.2% for the geriatric subgroup (p < 0.001). Contrast-enhanced (ce) MRI (48.1%) and native CT (39.4%) of the spine were the most frequently conducted diagnostic modalities. [18F]FDG PET/CT was performed in 2.7% of cases. CeCT was associated with increased in-hospital mortality (OR = 2.03, 95% CI: 1.90-2.17, p < 0.001). Cases with documented [18F]FDG PET/CT showed a lower frequency of in-hospital deaths (OR = 0.58, 95% CI: 0.18-0.50; p = 0.002). This finding was more pronounced in patients aged 65 and above (OR = 0.42, 95% CI: 0.27-0.65, p = 0.001). CONCLUSIONS: Despite its infrequent use, [18F]FDG PET/CT was associated with a lower in-hospital mortality rate in patients with spondylodiscitis, particularly in the geriatric cohort. This study is limited by only considering data on hospitalized patients and relying on the assumption of error-free coding. Further research is needed to optimize diagnostic approaches for spondylodiscitis.