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Patients with immune thrombocytopenia (ITP) admitted for non-ST elevation myocardial infarction (NSTEMI) present a unique therapeutic challenge due to the increased risk of bleeding with antiplatelet and anticoagulation therapies. There is limited evidence studying hospital mortality and complications in this population. The study included a patient cohort from the 2018-2021 National Inpatient Sample database. Propensity score matched NSTEMI patients with and without ITP using a 1:1 matching ratio. Outcomes analyzed were in-hospital mortality, rates of diagnostic angiogram, percutaneous coronary intervention (PCI), acute kidney injury (AKI), congestive heart failure (CHF), cardiogenic shock, cardiac arrest, mechanical ventilation, tracheal intubation, ventricular tachycardia (VT), ventricular fibrillation (VF), major bleeding, need for blood and platelet transfusion, length of stay (LOS), and total hospitalization charges. A total of 1,699,020 patients met inclusion criteria (660,490 females [39%], predominantly Caucasian 1,198,415 (70.5%); mean [SD] age 67, [3.1], including 2,615 (0.1%) patients with ITP. Following the propensity matching, 1,020 NSTEMI patients with and without ITP were matched. ITP patients had higher rates of inpatient mortality (aOR 1.98, 95% CI 1.11-3.50, p 0.02), cardiogenic shock, AKI, mechanical ventilation, tracheal intubation, red blood cells and platelet transfusions, longer LOS, and higher total hospitalization charges. The rates of diagnostic angiogram, PCI, CHF, VT, VF, and major bleeding were not different between the two groups. Patients with ITP demonstrated higher odds of in-hospital mortality for NSTEMI and need for platelet transfusion with no difference in rates of diagnostic angiogram or PCI.
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BACKGROUND: Carotid-femoral pulse wave velocity has been identified as an autonomous predictor of cardiovascular mortality and kidney injury. This important clinical parameter can be non-invasively estimated using the calculated pulse wave velocity (ePWV). The objective of this study was to examine the correlation between ePWV and in-hospital as well as one-year mortality among critically ill patients with chronic kidney disease (CKD) and atherosclerotic heart disease (ASHD). METHODS: This study included a cohort of 1173 patients diagnosed with both CKD and ASHD, sourced from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The four groups divided into quartiles according to ePWV were compared using a Kaplan-Meier survival curve to assess variations in survival rates. Cox proportional hazards models were employed to analyze the correlation between ePWV and in-hospital as well as one-year mortality among critically ill patients with both CKD and ASHD. To further investigate the dose-response relationship, a restricted cubic splines (RCS) model was utilized. Additionally, stratification analyses were performed to examine the impact of ePWV on hospital and one-year mortality across different subgroups. RESULTS: The survival analysis results revealed a negative correlation between higher ePWV and survival rate. After adjusting for confounding factors, higher ePWV level (ePWV > 11.90 m/s) exhibited a statistically significant association with an increased risk of both in-hospital and one-year mortality among patients diagnosed with both CKD and ASHD (HR = 4.72, 95% CI = 3.01-7.39, p < 0.001; HR = 2.04, 95% CI = 1.31-3.19, p = 0.002). The analysis incorporating an RCS model confirmed a linear escalation in the risk of both in-hospital and one-year mortality with rising ePWV values (P for nonlinearity = 0.619; P for nonlinearity = 0.267). CONCLUSIONS: The ePWV may be a potential marker for the in-hospital and one-year mortality assessment of CKD with ASHD, and elevated ePWV was strongly correlated with an elevated mortality risk in patients diagnosed with both CKD and ASHD.
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Mortalidade Hospitalar , Análise de Onda de Pulso , Insuficiência Renal Crônica , Humanos , Masculino , Feminino , Estudos Retrospectivos , Pessoa de Meia-Idade , Insuficiência Renal Crônica/mortalidade , Insuficiência Renal Crônica/fisiopatologia , Insuficiência Renal Crônica/complicações , Idoso , Estado Terminal/mortalidade , Aterosclerose/mortalidade , Bases de Dados Factuais , Estimativa de Kaplan-Meier , Modelos de Riscos Proporcionais , Fatores de RiscoRESUMO
Purpose: The inflammatory response of the body is intimately linked to the quick onset and high in-hospital mortality of Acute Type A Aortic Dissection (ATAAD). The purpose of the study was to examine the connection between in-hospital mortality in patients with ATAAD upon admission and the Pan-Immune-Inflammation Value (PIV). Patients and Methods: 308 patients who were diagnosed with ATAAD between September 2018 and October 2021 at Fujian Provincial Center for Cardiovascular Medicine had their clinical data retrospectively examined. PIV was assessed at the time of study population admission, with in-hospital mortality serving as the main outcome measure. Patients were divided into two groups, the high PIV group (PIV > 1807.704) and the low PIV group (PIV < 1807.704), based on the PIV ROC curve and the best threshold of the Youden index. The clinical results of the two groups were then compared. Results: Among ATAAD patients, postoperative in-hospital mortality was higher in the high PIV group (54.7% vs 10.6%, P < 0.001), and the high PIV group had significantly higher rates of postoperative acute kidney injury, acute liver insufficiency, and gastrointestinal hemorrhage (P < 0.05). Additionally, the high PIV group's ICU stays lasted longer than the low PIV group's (P < 0.05). The results of multifactorial logistic regression analysis, which controlled for other variables, indicated that the mechanical ventilation time (OR = 1.860, 95% CI: 1.437, 2.408; P < 0.001), the high PIV group (> 1807.704) (OR = 1.939, 95% CI: 1.257, 2.990; P = 0.003), the cardiopulmonary bypass time (OR = 1.011, 95% CI: 1.004, 1.018; P = 0.002), and the white blood cell count (OR = 1.188, 95% CI: 1.054, 1.340; P = 0.005) were independent risk factors for postoperative in-hospital mortality in ATAAD patients. Conclusion: Postoperative death in ATAAD patients was independently predicted by high PIV levels at admission. Patients should be informed about their preoperative inflammatory status and actively participate in prompt clinical decision-making and treatment.
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Aims Hepatocellular carcinoma (HCC) is one of the common liver malignancies that presents a challenge to global healthcare. The impact and outcomes of hypoglycemia in HCC have not been studied in detail before. This study aimed to investigate the outcomes and prognosis associated with hypoglycemia in patients diagnosed with HCC, utilizing a large-scale database approach. Methods Using the Nationwide Inpatient Sample (NIS) database from 2017 to 2020, we conducted a comprehensive retrospective analysis to examine the incidence, risk factors, and clinical implications of hypoglycemia on HCC patients. The patients were divided into two groups: those with hypoglycemia and those without hypoglycemia. Univariate and multivariate logistic regression were used to conduct the analysis. STATA® version 17.0 software (StataCorp LLC, College Station, TX) was used for this purpose. Results Out of a total of 343,895 patients with HCC, the prevalence of hypoglycemia was present in 1.5% of this patient population. We found that hypoglycemia was common in the male population (68%). Compared with patients without hypoglycemia, patients who had hypoglycemia with HCC had higher mortality (42%, p-value < 0.05) and higher risks of secondary outcomes such as hepatic failure, spontaneous bacterial peritonitis (SBP), ascites, and portal vein thrombosis compared to patients who did not have hypoglycemia. The multivariate-adjusted odds ratio for hepatic failure was 2.7 (2.3-3.1), for SBP was 2.9 (1.8-3.0), for ascites was 1.6 (1.4-1.9), and for portal vein thrombosis was 1.2 (0.9-1.4). Conclusion In conclusion, hypoglycemia in HCC is associated with increased mortality and worse outcomes.
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BACKGROUND: Fasudil and ozagrel are drugs with the same indications for the treatment of cerebral vasospasm in Japan. However, there have been no definitive conclusions on the clinical efficacy of fasudil hydrochloride and ozagrel sodium monotherapy or their combination. Therefore, we aimed to investigate the effectiveness of the combined administration of fasudil hydrochloride and ozagrel sodium in Japanese patients with subarachnoid hemorrhage (SAH). METHODS: This cross-sectional study used Diagnosis Procedure Combination data to assess patients who were hospitalized with SAH and received fasudil hydrochloride or ozagrel sodium between April 2016 and March 2020 (n = 17,346). The participants were divided into three groups based on the treatment received: fasudil hydrochloride monotherapy (F group, n = 10,484), ozagrel sodium monotherapy (O group, n = 465), and fasudil hydrochloride and ozagrel sodium combination therapy (FO group, n = 6,397). The primary outcome was in-hospital mortality. Multivariable adjusted logistic regression analysis (significance level, 5%) was used for data analyses. RESULTS: The results of the multivariable analysis, adjusted for factors considered to impact prognosis, showed that the adjusted odds ratio (OR) with the F group as the reference for in-hospital mortality was 0.94 in the FO group (95% confidence interval [CI]: 0.81-1.08, p = 0.355), with no differences compared to the F group. CONCLUSION: Fasudil hydrochloride and ozagrel sodium had different mechanisms of action, suggesting a synergistic effect of combination therapy. However, a comparison of fasudil hydrochloride monotherapy and combination therapy of fasudil hydrochloride and ozagrel sodium showed no difference in the prognostic effect. Therefore, it was suggested that fasudil hydrochloride monotherapy may be sufficient.
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Background: This study examines serum calcium levels and in-hospital mortality in patients with sepsis, a subject with contradictory findings in the existing literature. Methods: This retrospective cohort study utilized data from the MIMIC-IV database, focusing on adult patients diagnosed with sepsis between 2008 and 2019. The serum calcium levels were taken as the highest value within the first 24 h of Intensive Care Unit (ICU) admission. We performed Cox proportional hazards regression analyses in multivariable-adjusted models to investigate the association between serum calcium levels and in-hospital mortality. Restricted cubic spline functions were used to assess the nonlinear relationship, and threshold effect analysis was conducted to identify potential inflection points. Results: A total of 18,546 patients with sepsis were included in the study, and an in-hospital mortality rate of 16.9 % (3,126 out of 18,546) was obtained. Furthermore, a U-shaped relationship was observed between serum calcium concentrations and in-hospital mortality, with the lowest point at approximately 8.23 mg/dL. Hazard ratios were calculated as 0.75 (95 % CI: 0.67-0.85, P < 0.001) on the left side and 1.10 (95 % CI: 1.04-1.16, P < 0.001) on the right side of the inflection point. Sensitivity analyses corroborated these results. Conclusion: The research identified a U-shaped correlation between serum calcium concentrations and in-hospital mortality rates among patients with sepsis, underscoring the importance of serum calcium monitoring in this patient population upon hospital admission.
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OBJECTIVE: To explore mortality risk factors and to construct an online nomogram for predicting in-hospital mortality in traumatic brain injury (TBI) patients receiving invasive mechanical ventilation (IMV) in intensive care unit (ICU). METHODS: We retrospectively analysed TBI patients on IMV in ICU from MIMIC-â £ database and two hospitals. Least Absolute Shrinkage and Selection Operation (LASSO) regression and multiple logistic regression were used to detect predictors of in-hospital mortality and to construct an online nomogram. The predictive performance of nomogram was evaluated using area under the receiver operating characteristic curves (AUC), calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC). RESULTS: 510 from MIMIC-â £ database were enrolled for nomogram construction (80%, n=408) and internal validation (20%, n=102). 185 from two hospitals were enrolled for external validation. LASSO-Logistic regression revealed predictors of in-hospital mortality among TBI patients on IMV in ICU included Glasgow Coma Scale (GCS) after ICU admission, Acute Physiology Score â ¢ (APS â ¢) after ICU admission, neutrophil and lymphocyte ratio after IMV, blood urea nitrogen after IMV, arterial serum lactate after IMV, and in-hospital tracheotomy. The AUC, calibration curves, DCA, and CIC indicated the nomogram had good discrimination, calibration, clinical benefit, and applicability. The multi-model comparisons revealed the nomogram had higher AUC than GCS, APS â ¢, and Simplified Acute Physiology Score â ¡. CONCLUSION: We constructed and validated an online nomogram based on routinely recorded factors at admission to ICU and at the beginning of IMV to target prediction of in-hospital mortality among TBI patients on IMV in ICU.
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Iron deficiency (ID) is common in patients with acute myocardial infarction (AMI). It is unknown whether patients with AMI combined with ID will benefit from iron supplementation therapy. This study aimed to assess the relationship between iron therapy and mortality in AMI patients. Retrospective analysis was performed in subjects screened from the Medical Information Mart in Intensive Care-IV database. The data were obtained from ICU patients admitted to Beth Israel Deaconess Medical Center between 2008 and 2019. The patients were divided into two groups according to iron treatment exposure. Propensity score matching (PSM) was performed in the original cohort at a 1:1 ratio. Univariate and multivariate analyses were performed to adjust for confounding factors. The primary outcome was 28-day mortality. A total of 426 patients were included in this study. After 1:1 PSM, 208 patients were analyzed. Iron treatment was associated with a lower risk of 28-day mortality (9 deaths (8.65%) in the iron treatment group vs. 21 deaths (20.19%) in the non-iron treatment group; HR = 0.39; 95% CI = 0.17-0.89; p = 0.025) and in-hospital mortality (4 deaths (3.85%) in the iron treatment group vs. 12 deaths (11.54%) in the non-iron treatment group; OR, 0.15; 95% CI, 0.03-0.74; p = 0.029). Iron treatment was associated with reduced 28-day mortality in patients with AMI combined with ID. Iron treatment had no significant effect on the length of hospitalization or the length of ICU stay. Prospective studies are needed to verify this conclusion.
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Background: Connective tissue diseases (CTDs) are characterized by immune system dysregulation, which can profoundly impact the gastrointestinal (GI) system. While GI bleeding is a well-recognized cause of mortality and morbidity in the USA, its occurrence in patients with CTD remains documented but underexplored in terms of inpatient outcomes. GI bleeding in CTD is attributed to factors such as vasculopathy and drug-related risks, notably steroids and non-steroidal anti-inflammatory drugs (NSAIDs). This research seeks to conduct a comprehensive national-level analysis, utilizing the National Inpatient Sample (NIS), to compare GI bleeding outcomes between patients with CTD and those without this condition. Methods: Utilizing the extensive NIS database covering 2020, we conducted a retrospective analysis of GI bleeding patients with CTD, identified through the International Classification of Diseases, 10th Revision (ICD-10). The primary outcome was in-hospital mortality. The secondary outcomes included rate of urgent esophagogastroduodenoscopy (EGD) and colonoscopy-endoscopy in 1 day or less, total rate of EGD and colonoscopy, rate of EGD and Colonoscopy with intervention, rate of complications including acute kidney injury (AKI), blood transfusion, sepsis, pneumonia, pulmonary embolism (PE) and healthcare utilization. Employing Stata software, we utilized multivariate logistic and linear regression analyses to adjust for confounders. Results: There were 455,494 hospitalizations for GI bleeding and 19,874 involved patients with CTDs. The in-hospital mortality rate was significantly lower for CTD patients at 2.1%, compared to 2.4% for non-CTD patients [adjusted odds ratio (aOR): 0.79, 95% confidence interval (CI): 0.63-0.99, P=0.04]. CTD patients showed increased odds of total EGD, urgent colonoscopy, and total colonoscopy; however, these changes were not statistically significant. CTD patients had higher odds of complications, including PE (6.87% vs. 4.12%, P=0.009). However, there were no significant differences in mean length of hospital stay and total hospital charges (THCs) compared to non-CTD patients. Conclusions: Patients with CTD exhibited a lower in-hospital mortality rate compared to those without CTD. The elevated risk of PE underscores the importance of implementing prophylactic measures for these patients.
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Aim: To compare the effects of midazolam, propofol, and dexmedetomidine monotherapy and combination therapy on the prognosis of intensive care unit (ICU) patients receiving continuous mechanical ventilation (MV). Methods: 11,491 participants from the Medical Information Mart for Intensive Care (MIMIC)-IV database 2008-2019 was included in this retrospective cohort study. The primary outcome was defined as incidence of ventilator-associated pneumonia (VAP), in-hospital mortality, and duration of MV. Univariate and multivariate logistic regression analyses were utilized to evaluate the association between sedation and the incidence of VAP. Univariate and multivariate Cox analyses were performed to investigate the correlation between sedative therapy and in-hospital mortality. Additionally, univariate and multivariate linear analyses were conducted to explore the relationship between sedation and duration of MV. Results: Compared to patients not receiving these medications, propofol alone, dexmedetomidine alone, combination of midazolam and dexmedetomidine, combination of propofol and dexmedetomidine, combination of midazolam, propofol and dexmedetomidine were all association with an increased risk of VAP; dexmedetomidine alone, combination of midazolam and dexmedetomidine, combination of propofol and dexmedetomidine, combination of midazolam, propofol and dexmedetomidine may be protective factor for in-hospital mortality, while propofol alone was risk factor. There was a positive correlation between all types of tranquilizers and the duration of MV. Taking dexmedetomidine alone as the reference, all other drug groups were found to be associated with an increased risk of in-hospital mortality. The administration of propofol alone, in combination with midazolam and dexmedetomidine, in combination with propofol and dexmedetomidine, in combination with midazolam, propofol and dexmedetomidine were associated with an increased risk of VAP compared to the use of dexmedetomidine alone. Conclusion: Dexmedetomidine alone may present as a favorable prognostic option for ICU patients with mechanical ventilation MV.
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BACKGROUND: Nosocomial infections (NIs) frequently occur and adversely impact prognosis for hospitalized patients with cirrhosis. This study aims to develop and validate two machine learning models for NIs and in-hospital mortality risk prediction. METHODS: The Prediction of Nosocomial Infection and Prognosis in Cirrhotic patients (PIPC) study included hospitalized patients with cirrhosis at the Qingchun Campus of the First Affiliated Hospital of Zhejiang University. We then assessed several machine learning algorithms to construct predictive models for NIs and prognosis. We validated the best-performing models with bootstrapping techniques and an external validation dataset. The accuracy of the predictions was evaluated through sensitivity, specificity, predictive values, and likelihood ratios, while predictive robustness was examined through subgroup analyses and comparisons between models. RESULTS: We enrolled 1,297 patients into derivation cohort and 496 patients into external validation cohort. Among the six algorithms assessed, the Random Forest algorithm performed best. For NIs, the PIPC-NI model achieved an area under the curve (AUC) of 0.784 (95% confidence interval [CI] 0.741-0.826), a sensitivity of 0.712, and a specificity of 0.702. For in-hospital mortality, the PIPC- mortality model achieved an AUC of 0.793 (95% CI 0.749-0.836), a sensitivity of 0.769, and a specificity of 0.701. Moreover, our PIPC models demonstrated superior predictive performance compared to the existing MELD, MELD-Na, and Child-Pugh scores. CONCLUSIONS: The PIPC models showed good predictive power and may facilitate healthcare providers in easily assessing the risk of NIs and prognosis among hospitalized patients with cirrhosis.
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Infecção Hospitalar , Mortalidade Hospitalar , Cirrose Hepática , Aprendizado de Máquina , Humanos , Infecção Hospitalar/mortalidade , Cirrose Hepática/complicações , Cirrose Hepática/mortalidade , Masculino , Feminino , Pessoa de Meia-Idade , Prognóstico , Idoso , Hospitalização , Algoritmos , Medição de Risco/métodos , Fatores de Risco , Área Sob a CurvaRESUMO
Background: Coronavirus disease 2019 (COVID-19) infection has been associated with severe neurological consequences, including stroke or seizures, and less severe neurological sequelae, including headaches, dizziness, and anosmia. Earlier COVID-19 variants were associated with high morbidity and mortality; however, knowledge of the impact of neurological conditions in the setting of COVID-19 on healthcare outcomes is limited. We sought to determine the impact of acute neurological conditions and acute COVID-19 infection on inpatient hospitalization outcomes. Methods: This was a retrospective, observational study of adult patients who were admitted to a large academic medical center in the Southeastern US between April 2020 and December 2021 with acute COVID-19 infection and a neurological diagnosis. Patient demographics, medical history, neurological diagnoses, and hospitalization outcomes were obtained from the medical record. Descriptive statistics and unadjusted and adjusted logistic regression analyses were performed. Results: Of the 1,387 patients included in this study, 27% died and 23% were kept under ventilation during hospitalization. The mean +/- standard deviation (SD) age was 64.6+/-16.9 years, with 52.8% women and 30.1% identifying as Black/African American. The most common neurological conditions included ischemic stroke (35.0%), movement disorder (12.0%), and hemorrhagic stroke (10.7%). In-hospital death was most common among those with epilepsy (p = 0.024), headache (p = 0.026), and dementia (p < 0.0001) compared to individuals without those conditions. Ventilation support was given more commonly to dementia patients (p = 0.020). Age was a significant risk factor for death (p < 0.001) and hospital length of stay (LOS) for ventilation (p < 0.001), but no neurological condition was a significant factor in adjusted logistic regression analyses. Discussion: Mortality was high in this study, with more than one-quarter of patients dying in the hospital. Death was the most common among those with epilepsy, headache, or dementia, but no neurological condition increased the risk of in-hospital mortality or ventilation. Future studies would determine the long-term neurological sequelae of those discharged from the hospital with COVID-19 and a neurological condition.
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Objective: Nutritional status is closely associated with the prognosis of heart failure. This study aims to assess the relationship between the Controlling Nutritional Status (CONUT) score and in-hospital mortality among patients with acute decompensated heart failure (ADHF) in Jiangxi, China. Methods: A retrospective cohort study was conducted. Multivariable Cox regression models and restricted cubic spline regression were employed to evaluate the relationship between the CONUT score and in-hospital mortality in ADHF patients from Jiangxi, China. The predictive value of the CONUT score for in-hospital mortality in ADHF patients was analyzed using receiver operating characteristic curves. Subgroup analyses were performed to identify risk dependencies of the CONUT score in specific populations. Results: The study included 1,230 ADHF patients, among whom 44 (3.58%) mortality events were recorded. After adjusting for confounding factors, a positive correlation was found between the CONUT score and the risk of in-hospital mortality in ADHF patients. Restricted cubic spline regression analysis indicated a non-linear relationship between the CONUT score and the risk of in-hospital mortality in ADHF patients, estimating a rapid increase in mortality risk when the CONUT score exceeded 5. Receiver operating characteristic analysis demonstrated a good predictive value of the CONUT score for all-cause mortality events in ADHF patients [area under the curve = 0.7625, optimal threshold = 5.5]. Additionally, a relatively higher risk associated with the CONUT score was observed in male patients and those with concomitant cerebral infarction. Conclusion: This study reveals a positive correlation between the CONUT score and the risk of in-hospital mortality in ADHF patients. Based on the findings of this study, we recommend maintaining a CONUT score below 5 for patients with ADHF in Jiangxi, China, as it may significantly contribute to reducing the risk of in-hospital all-cause mortality.
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BACKGROUND: There is dearth of literature addressing early outcomes of acute coronary syndrome (ACS) among young patients, particularly South Asians descent who are predisposed to premature coronary artery disease (CAD). Therefore, we compared presentation, management, and early outcomes of young vs. old ACS patients and explored predictors of in-hospital mortality. METHODS: We extracted data of 23,560 ACS patients who presented at Tabba Heart Institute, Karachi, Pakistan, from July 2012-June 2020, from the Chest pain-MI-Registry™. We categorized data into young ≤ 45 and old ACS patients > 45 years. Chi-sq/Fischer exact tests were used to assess the difference between presentation, disease management, and in-hospital mortality between both groups. Logistic regression was used to determine odds ratio along with 95% confidence interval of factors associated with early mortality. RESULTS: The younger patients were 12.2% and women 23.5%. The prevalence of dyslipidemia (34.5% vs. 22.4%), diabetes (52.1% vs. 27.4%), and hypertension (68.3% vs. 42.9%) was higher in older patients. Family history of premature CAD (18.1% vs. 32.7%), smoking (40.0% vs. 22.9%), and smokeless tobacco use (6.5% vs. 8.4%) were lower in older patients compared to younger ones. Younger patients were more likely to present with STEMI (33.2% vs. 45%). The median symptom-to-door time was 125 min longer (p-value < 0.01) in the young patients compared to the older age group. In-hospital mortality (4.3% vs. 1.7%), cardiac arrest (1.9% vs. 0.7%), cardiogenic shock (1.9% vs. 0.9%), and heart failure (1% vs. 0.6%) were more common in older patients. After adjusting for other factors, younger age (AOR 0.6, 95% CI 1.5-3.7) had significantly lesser odds of in-hospital mortality. Other factors associated with early mortality included women, family history of premature CAD, STEMI, Killip class III and IV, coronary angiography, revascularization, CABG, and use of aspirin and beta blockers within the first 24 h. CONCLUSION: We found every tenth ACS patient was younger than 45 years of age despite a lesser number of comorbidities such as hypertension and diabetes. Overall, the in-hospital prognosis of young patients was more favorable than that of older patients. The study emphasizes the need for tailored primary prevention programs for ACS, considering the varying risks among different age groups.
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Síndrome Coronariana Aguda , Mortalidade Hospitalar , Sistema de Registros , Humanos , Feminino , Masculino , Síndrome Coronariana Aguda/terapia , Síndrome Coronariana Aguda/mortalidade , Síndrome Coronariana Aguda/etnologia , Síndrome Coronariana Aguda/diagnóstico , Pessoa de Meia-Idade , Fatores de Tempo , Fatores Etários , Adulto , Fatores de Risco , Medição de Risco , Paquistão/etnologia , Resultado do Tratamento , Idoso , Prevalência , Povo AsiáticoRESUMO
OBJECTIVE: This paper presents a comprehensive analysis of perioperative patient deterioration by developing predictive models that evaluate unanticipated ICU admissions and in-hospital mortality both as distinct and combined outcomes. MATERIALS AND METHODS: With less than 1% of cases resulting in at least one of these outcomes, we investigated 98 features to identify their role in predicting patient deterioration, using univariate analyses. Additionally, multivariate analyses were performed by employing logistic regression (LR) with LASSO regularization. We also assessed classification models, including non-linear classifiers like Support Vector Machines, Random Forest, and XGBoost. RESULTS: During evaluation, careful attention was paid to the data imbalance therefore multiple evaluation metrics were used, which are less sensitive to imbalance. These metrics included the area under the receiver operating characteristics, precision-recall and kappa curves, and the precision, sensitivity, kappa, and F1-score. Combining unanticipated ICU admissions and mortality into a single outcome improved predictive performance overall. However, this led to reduced accuracy in predicting individual forms of deterioration, with LR showing the best performance for the combined prediction. DISCUSSION: The study underscores the significance of specific perioperative features in predicting patient deterioration, especially revealed by univariate analysis. Importantly, interpretable models like logistic regression outperformed complex classifiers, suggesting their practicality. Especially, when combined in an ensemble model for predicting multiple forms of deterioration. These findings were mostly limited by the large imbalance in data as post-operative deterioration is a rare occurrence. Future research should therefore focus on capturing more deterioration events and possibly extending validation to multi-center studies. CONCLUSIONS: This work demonstrates the potential for accurate prediction of perioperative patient deterioration, highlighting the importance of several perioperative features and the practicality of interpretable models like logistic regression, and ensemble models for the prediction of several outcome types. In future clinical practice these data-driven prediction models might form the basis for post-operative risk stratification by providing an evidence-based assessment of risk.
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AIMS: Heart failure (HF) and chronic kidney disease (CKD) place significant challenges on the healthcare system, and their co-existence is associated with shared adverse outcomes. The multinational CaReMe project was initiated to provide contemporary, real-world epidemiological data on cardiovascular and reno-metabolic diseases. Utilizing data from the German CaReMe cohort, we characterize a multicentric HF population and describe in-hospital outcomes stratified for co-morbid CKD. METHODS AND RESULTS: This retrospective, observational study analysed administrative data from inpatient cases hospitalized in 87 German Helios hospitals between 1 January 2016 and 31 August 2022. The first hospitalization of patients aged ≥18 years with a primary discharge diagnosis of HF, based on ICD-10 codes, were considered the index cases, and subsequent hospitalizations were considered as readmissions. Baseline characteristics and outcomes were stratified for co-morbid CKD using ICD-10-encoding from the index cases. Cox regression was utilized for readmission endpoints and in-hospital mortality. In total, 174 829 index cases (mean age 79 ± 15 years, 49.9% female) were included; of these, 55.0% had coexisting CKD. Patients with CKD were older, suffered from worse HF-related symptoms, had a higher co-morbidity burden, and in-hospital mortality was increased at index and during follow-up. Prevalent CKD was associated with higher rehospitalization rates and was an independent predictor for in-hospital death. CONCLUSIONS: Within this HF inpatient cohort from a multicentric German database, CKD was diagnosed in more than half of the patients and was associated with increased in-hospital mortality at baseline and during follow-up. Rehospitalizations were observed earlier and more frequently in patients with HF and co-morbid CKD.
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BACKGROUND: This study aimed to analyse the baseline characteristics of patients admitted with acute type A aortic syndrome (ATAAS) and to identify the potential predictors of in-hospital mortality in surgically managed patients. METHODS: Data regarding demographics, clinical presentation, laboratory work-up, and management of 501 patients with ATAAS enrolled in the National Registry of Aortic Dissections-Romania registry from January 2011 to December 2022 were evaluated. The primary endpoint was in-hospital all-cause mortality. Multivariate logistic regression was conducted to identify independent predictors of mortality in patients with acute Type A aortic dissection (ATAAD) who underwent surgery. RESULTS: The mean age was 60±11 years and 65% were male. Computed tomography was the first-line diagnostic tool (79%), followed by transoesophageal echocardiography (21%). Cardiac surgery was performed in 88% of the patients. The overall mortality in the entire cohort was 37.9%, while surgically managed ATAAD patients had an in-hospital mortality rate of 29%. In multivariate logistic regression, creatinine value (OR 6.76), ST depression on ECG (OR 6.3), preoperative malperfusion (OR 5.77), cardiogenic shock (OR 5.77), abdominal pain (OR 4.27), age ≥70 years (OR 3.76), and syncope (OR 3.43) were independently associated with in-hospital mortality in surgically managed ATAAD patients. CONCLUSIONS: Risk stratification based on the variables collected at admission may help to identify ATAAS patients with high risk of death following cardiac surgery.
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BACKGROUND: Elective cholecystectomy (CCY) is recommended for patients with gallstone-related acute cholangitis (AC) following endoscopic decompression to prevent recurrent biliary events. However, the optimal timing and implications of CCY remain unclear. AIM: To examine the impact of same-admission CCY compared to interval CCY on patients with gallstone-related AC using the National Readmission Database (NRD). METHODS: We queried the NRD to identify all gallstone-related AC hospitalizations in adult patients with and without the same admission CCY between 2016 and 2020. Our primary outcome was all-cause 30-d readmission rates, and secondary outcomes included in-hospital mortality, length of stay (LOS), and hospitalization cost. RESULTS: Among the 124964 gallstone-related AC hospitalizations, only 14.67% underwent the same admission CCY. The all-cause 30-d readmissions in the same admission CCY group were almost half that of the non-CCY group (5.56% vs 11.50%). Patients in the same admission CCY group had a longer mean LOS and higher hospitalization costs attributable to surgery. Although the most common reason for readmission was sepsis in both groups, the second most common reason was AC in the interval CCY group. CONCLUSION: Our study suggests that patients with gallstone-related AC who do not undergo the same admission CCY have twice the risk of readmission compared to those who undergo CCY during the same admission. These readmissions can potentially be prevented by performing same-admission CCY in appropriate patients, which may reduce subsequent hospitalization costs secondary to readmissions.
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Background: Traumatic cervical spine injury is common among spinal cord injury which requires an intensive, multidisciplinary approach which can affect the immediate postoperative hospital survival rate. By identifying the risk factors leading to early mortality in cervical spine trauma patients, the prognosis of patients with TCSCI can be better predicted. Objective: The study aims to analyze the variables influencing in-hospital mortality in cervical spine trauma patients treated at a Level I trauma Center. Methods: Prospective study was conducted on subaxial cervical spine injuries from July 2019 to March 2022. Patients were divided into two groups: Group A, with in-hospital mortality, and Group B, who got discharged from hospital, and mortality predictors were reviewed and analyzed for as potential risk factors for in-hospital mortality. Results: Out of 105 patients, 83.8 % were male with mean age of 40.43 ± 12.62 years. On univariate analysis, AIS (p-value: <0.01), ICU stay (p-value: <0.01), level of injury (p-value: <0.01), and MRI parameters like the extent of Parenchymal damage (p-value: <0.01), MSCC (p-value: <0.01), and MCC (p-value: <0.01) were potential risk factors for in-hospital mortality. On multivariate regression analysis AIS at presentation (p-value: 0.02) was the only significant independent parameter for in-hospital mortality. Conclusions: AIS grading at presentation, duration of ICU stay, level of injury, rate of tracheostomy, and MRI parameters like the extent of parenchymal damage, MCC, and MSCC influence and predicts in-hospital mortality, whereas AIS is the only independent risk factor.
RESUMO
BACKGROUND: Cerebrovascular accidents (CVA) represent a major complication in diabetes (DM). Real-life evidence as to whether modern management of CVA and DM have softened this relationship is limited. Therefore, we estimated prevalence and impact of DM on in-hospital survival and complications in a contemporary cohort of subjects with CVA. METHODS: We retrospectively evaluated the records of 937 patients admitted for CVA at the Stroke Unit of Verona University Hospital during a 3-year period. Pre-existing or de novo DM was ascertained by prior diagnosis, glucose-lowering therapy at admission/discharge or admittance plasma glucose ≥ 200 mg/dL. Multiple regressions were applied to test DM as predictor of in-hospital mortality, complications (composite of infections, cardio- and cerebrovascular complications, major bleeding and pulmonary complications), duration and costs of hospitalization. RESULTS: Diabetes prevalence was 21%, of which 22% de novo diagnoses. Compared to non-DM, diabetic individuals were older and carried an increased burden of cardiovascular risk factors. Compared to known DM, de novo DM individuals were younger, had higher admittance plasma glucose and poorer cardiovascular comorbidities. Overall, DM versus non-DM individuals did not show significantly increased risk of death (14.0 vs. 9.3%; crude-OR 1.59 95% CI 0.99-2.56). Controlling for confounders did not improve significance. DM resulted independent predictor for in-hospital complications (36.2% vs. 26.9%; adj-OR 1.49, 1.04-2.13), but not for duration and costs of hospitalization. CONCLUSION: DM frequently occurs in patients admitted for stroke and carries an excess burden of adverse in-hospital complications, urgently calling for strategies to anticipate DM diagnosis and tailored treatment in high-risk individuals.