Open surgical repair of thoracoabdominal aortic aneurysm remains an important treatment option and continues to be challenging. The objective of this study was to investigate the results after open ...repair of thoracoabdominal aortic aneurysms in a contemporary non–high-volume center collective.
A total of 38 patients underwent operation for thoracoabdominal aortic aneurysm between August 2007 and April 2017. Patients had aortic aneurysm and chronic aortic dissection. The majority of patients had already undergone previous aortic interventions.
The mean age was 54.4 ± 13.4 years (range, 29-72.5 years), and 22 patients (57.9%) were female. Most commonly, patients (57.9%) presented with Crawford type II aneurysms. The mean cardiopulmonary bypass time was 159 ± 65 minutes. The operative mortality was 10.5% (n = 4). The paraplegia rate and the incidence of stroke were 7.9% (n = 3). Postoperatively, 4 patients (10.5%) required temporary hemodialysis. In 4 patients (10.5%), reexploration due to bleeding was necessary. Sepsis developed in 4 patients (10.5%). Preoperative renal insufficiency was identified as a predictor of mortality. The patients were discharged from the hospital after a median length of stay of 21.5 days. The 1-year survival was 83%.
Despite the invasiveness of open thoracoabdominal aortic repair and significant risk of major complications, surgical repair can be accomplished in a non–high-volume center with acceptable results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract Acinetobacter baumannii (AB) has emerged as a major pathogen in vulnerable and severely ill patients. It remains unclear whether early mortality (EM) due to AB bacteremia is because of worse ...clinical characteristics of the infected patients or the virulence of the pathogen. In this study, we aimed to investigate the effect of AB virulence on EM due to bacteremia. This retrospective study included 138 patients with AB bacteremia (age: ≥ 18 years) who were admitted to a tertiary care teaching hospital in South Korea between 2015 and 2019. EM was defined as death occurring within 7 days of bacteremia onset. The AB clinical isolates obtained from the patients’ blood cultures were injected into 15 Galleria mellonella larvae each, which were incubated for 5 days. Clinical isolates were classified into high- and low-virulence groups based on the number of dead larvae. Patients’ clinical data were combined and subjected to multivariate Cox regression analyses to identify the risk factors for EM. In total, 48/138 (34.8%) patients died within 7 days of bacteremia onset. The Pitt bacteremia score was the only risk factor associated with EM. In conclusion, AB virulence had no independent effect on EM in patients with AB bacteremia.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Using an ensemble machine learning technique that incorporates the results of multiple machine learning algorithms, the study's objective is to build a reliable model to predict the early mortality ...among hepatocellular carcinoma (HCC) patients with bone metastases.
We extracted a cohort of 124,770 patients with a diagnosis of hepatocellular carcinoma from the Surveillance, Epidemiology, and End Results (SEER) program and enrolled a cohort of 1897 patients who were diagnosed as having bone metastases. Patients with a survival time of 3 months or less were considered to have had early death. To compare patients with and without early mortality, subgroup analysis was used. Patients were randomly divided into two groups: a training cohort (n = 1509, 80%) and an internal testing cohort (n = 388, 20%). In the training cohort, five machine learning techniques were employed to train and optimize models for predicting early mortality, and an ensemble machine learning technique was used to generate risk probability in a way of soft voting, and it was able to combine the results from the multiply machine learning algorithms. The study employed both internal and external validations, and the key performance indicators included the area under the receiver operating characteristic curve (AUROC), Brier score, and calibration curve. Patients from two tertiary hospitals were chosen as the external testing cohorts (n = 98). Feature importance and reclassification were both operated in the study.
The early mortality was 55.5% (1052/1897). Eleven clinical characteristics were included as input features of machine learning models: sex (p = 0.019), marital status (p = 0.004), tumor stage (p = 0.025), node stage (p = 0.001), fibrosis score (p = 0.040), AFP level (p = 0.032), tumor size (p = 0.001), lung metastases (p < 0.001), cancer-directed surgery (p < 0.001), radiation (p < 0.001), and chemotherapy (p < 0.001). Application of the ensemble model in the internal testing population yielded an AUROC of 0.779 (95% confidence interval CI: 0.727-0.820), which was the largest AUROC among all models. Additionally, the ensemble model (0.191) outperformed the other five machine learning models in terms of Brier score. In terms of decision curves, the ensemble model also showed favorable clinical usefulness. External validation showed similar results; with an AUROC of 0.764 and Brier score of 0.195, the prediction performance was further improved after revision of the model. Feature importance demonstrated that the top three most crucial features were chemotherapy, radiation, and lung metastases based on the ensemble model. Reclassification of patients revealed a substantial difference in the two risk groups' actual probabilities of early mortality (74.38% vs. 31.35%, p < 0.001). Patients in the high-risk group had significantly shorter survival time than patients in the low-risk group (p < 0.001), according to the Kaplan-Meier survival curve.
The ensemble machine learning model exhibits promising prediction performance for early mortality among HCC patients with bone metastases. With the aid of routinely accessible clinical characteristics, this model can be a trustworthy prognostic tool to predict the early death of those patients and facilitate clinical decision-making.
Ascending aortic replacement is a challenging and complex surgery. The mortality, morbidity, and outcomes depend on the causes of the ascending aortic pathology and the type of operation. The ...research was conducted in a single-center, prospective, observational cohort study of patients undergoing ascending aortic replacement due to dissection or aneurysm. In the hospital, mortality, morbidity, and short-term outcomes were measured. A total of 85 patients were included in this study. Of them, 65.9% were male, and 34.1% were female. Thirty-three patients had Stanford type A aortic dissection (STAAD), whereas 52 had ascending aortic aneurysm (ASAA). Early mortality was (21.21% and 1.9%) for STAAD and ASAA, respectively, while the survival rate after one year was (75.8% and 96.15 %) for ascending dissection and aneurysm, respectively. The results of our study show higher early surgical mortality and morbidity and a lower short-term survival rate for STAAD surgery compared with ASAA surgery.
Inflammation-based scores have been increasingly used for prognosis prediction in neurological diseases. This study aimed to investigate the predictive value of inflammation-based scores combined ...with radiological characteristics in children with moderate or severe traumatic brain injury (MS-TBI). A total of 104 pediatric patients with MS-TBI were retrospectively enrolled and randomly divided into training and validation cohorts at a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed to identify independent predictors of prognosis in pediatric patients with MS-TBI. A prognostic nomogram was constructed, and its predictive performance was validated in both the training and validation cohorts. Sex, admission platelet-to-lymphocyte ratio, and basal cistern status from initial CT findings were identified as independent prognostic predictors for children with MS-TBI in multivariate logistic analysis. Based on these findings, a nomogram was then developed and its concordance index values were 0.918 95% confidence interval (CI): 0.837-0.999 in the training cohort and 0.86 (95% CI: 0.70-1.00) in the validation cohort, which significantly outperformed those of the Rotterdam, Marshall, and Helsinki CT scores. The proposed nomogram, based on routine complete blood count and initial CT scan findings, can contribute to individualized prognosis prediction and clinical decision-making in children with MS-TBI.
Coagulation disorders frequently complicate the clinical course of acute myeloid leukemia (AML) patients. This study examined the frequency and prognostic significance, with regards of early ...mortality, of the presence of overt disseminated intravascular coagulation (DIC) at AML diagnosis and its correlation with clinical and biological characteristics.
A retrospective analysis of 351 newly diagnosed non-promyelocytic AML patients was conducted, utilizing the 2018 ISTH DIC-Score criteria to evaluate the presence of overt DIC at AML onset. The study cohort had a median age of 65 years with a predominance of male gender (59 %). Overt DIC was present in 21 % of cases and was associated with advanced age, comorbidities, poor performance status, hyperleukocytosis, LDH levels, NPM1 mutations, expression of CD33 and CD4, and lack of expression of CD34. With a median follow-up of 72 months (3–147 months), the 6-year overall survival (OS) was 17.4 %, with patients having overt DIC showing significantly poorer outcomes (7.2 % compared to 20.3 % of those without DIC, p < 0.001). Patients with overt DIC showed markedly high early mortality rates at 30 (42.5 % vs 8 %), 60 (49.3 % vs 16.9 %), and 120 days (64.4 % vs 25.6 %) from disease onset. In multivariate analysis overt DIC retained its independent prognostic value for early mortality.
In conclusion, the prevalence and clinical relevance of DIC in non-promyelocytic AML is not negligible, underlining its potential as an unfavorable prognostic marker. In newly diagnosed patients with AML, early recognition and measure to counteract coagulation disturbances might help mitigate the elevated mortality risk associated with DIC.
•Disseminated intravascular coagulation frequently complicates acute leukemias.•The 2018 ISTH DIC-Score criteria serve as a simple tool to diagnose disseminated intravascular coagulation in acute myeloid leukemia patients.•Acute myeloid leukemia patients with disseminated intravascular coagulation at presentation have a 14-fold increased risk of major bleeding.•Disseminated intravascular coagulation has independent prognostic value for early death.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Background: We aimed to analyze in-hospital timing and risk factors for mortality in a level 1 trauma center. Methods: This is a retrospective analysis of all trauma-related mortality between 2013 ...and 2018. Patients were divided and analyzed based on the time of mortality (early (≤48 h) vs late (>48 h)), and within different age groups. Multivariate regression analysis was performed to predict in-hospital mortality. Results: 8624 trauma admissions and 677 trauma-related deaths occurred (47.7% at the scene and 52.3% in-hospital). Among in-hospital mortality, the majority were males, with a mean age of 35.8 ± 17.2 years. Most deaths occurred within 3–7 days (35%), followed by 33% after 1 week, 20% on the first day, and 12% on the second day of admission. Patients with early mortality were more likely to have a lower Glasgow coma scale, a higher shock index, a higher chest and abdominal abbreviated injury score, and frequently required exploratory laparotomy and massive blood transfusion (P < .005). The injury severity scores and proportions of head injuries were higher in the late mortality group than in the early group. The severity of injuries, blood transfusion, in-hospital complications, and length of intensive care unit stay were comparable among the age groups, whereas mortality was higher in the age group of 19 to 44. The higher proportions of early and late in-hospital deaths were evident in the age group of 24 to 29. In multivariate analysis, the shock index (OR 2.26; 95%CI 1.04-4.925; P = .04) was an independent predictor of early death, whereas head injury was a predictor of late death (OR 4.54; 95%CI 1.92-11.11; P = .001). Conclusion: One-third of trauma-related mortalities occur early after injury. The initial shock index appears to be a reliable hemodynamic indicator for predicting early mortality. Therefore, timely hemostatic resuscitation and appropriate interventions for bleeding control may prevent early mortality.
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NUK, OILJ, SAZU, UKNU, UL, UM, UPUK
Objective The aim of this study was to identify patients with a high risk of early mortality after acute esophageal variceal bleeding by measuring the C-reactive protein (CRP) level. Methods We ...retrospectively evaluated 154 consecutive cirrhotic patients admitted with esophageal variceal bleeding. Differences between categorical variables were assessed by the chi-square test. Continuous variables were compared using the Mann-Whitney U-test. Multivariate logistic regression analyses consisting of clinical laboratory parameters were performed to identify risk factors associated with the six-week mortality. The discriminative ability and the best cut-off value were assessed by a receiving-operator characteristic (ROC) curve analysis. Results Child-Pugh C patients showed a significantly higher 6-week mortality than Child-Pugh A or B patients (38% vs. 6%, p<0.0001). The 6-week mortality in Child-Pugh C patients was associated with the age (p<0.0001), etiology of cirrhosis (p=0.003), hepatocellular carcinoma (p=0.0003), portal vein thrombosis (p=0.005), baseline creatinine (p=0.0001), albumin (p=0.001), white blood cell count (p=0.038), baseline CRP (p=0.0004; area under the ROC AUROC=0.765; optimum cut-off value at 1.30 mg/dL) and bacterial infection (p=0.019). We determined that CRP ≥1.30 mg/dl was an independent predictor for 6-week mortality in Child-Pugh C patients (odds ratio OR=8.789; 95% confidence interval CI: 2.080-47.496; p=0.003), along with a creatinine level of 0.71 mg/dL (OR=17.628; 95% CI: 2.349-384.426; p=0.004) (73% mortality if CRP ≥1.30 mg/dL vs. 19% if CRp<1.30 mg/dL, p<0.0001). Conclusion In Child-Pugh C patients with esophageal variceal bleeding, a baseline CRP ≥1.30 mg/dl can help identify patients with an increased risk of mortality.
Socioeconomic differences in overall survival from childhood cancer have been shown previously, but the underlying mechanisms remain unclear. We aimed to investigate if social inequalities were seen ...already for early mortality in settings with universal healthcare. From national registers, all children diagnosed with cancer at ages 0-19 years, during 1991-2014, in Sweden and Denmark, were identified, and information on parental social characteristics was collected. We estimated odds ratios (OR) and 95% confidence intervals (CI) of early mortality (death within 90 days after cancer diagnosis) by parental education, income, employment, cohabitation, and country of birth using logistic regression. For children with acute lymphoblastic leukaemia (ALL), clinical characteristics were obtained. Among 13,926 included children, 355 (2.5%) died within 90 days after diagnosis. Indications of higher early mortality were seen among the disadvantaged groups, with the most pronounced associations observed for maternal education (OR
1.65 95% CI 1.22-2.23) and income (OR
1.77 1.25-2.49). We found attenuated or null associations between social characteristics and later mortality (deaths occurring 1-5 years after cancer diagnosis). In children with ALL, the associations between social factors and early mortality remained unchanged when adjusting for potential mediation by clinical characteristics. In conclusion, this population-based cohort study indicated differences in early mortality after childhood cancer by social background, also in countries with universal healthcare. Social differences occurring this early in the disease course requires further investigation, also regarding the timing of diagnosis.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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