Clinical Factors Associated with SFTS Diagnosis and Severity in Cats.

Severe fever with thrombocytopenia syndrome (SFTS) is a potentially fatal tick-borne zoonosis caused by SFTS virus (SFTSV). In addition to tick bites, animal-to-human transmission of SFTSV has been reported, but little is known about feline SFTSV infection. In this study, we analyzed data on 187 cats with suspected SFTS to identify biomarkers for SFTS diagnosis and clinical outcome. Body weight, red and white blood cell and platelet counts, and serum aspartate aminotransferase and total bilirubin levels were useful for SFTS diagnosis, whereas alanine aminotransferase, aspartate aminotransferase and serum SFTSV RNA levels were associated with clinical outcome. We developed a scoring model to predict SFTSV infection. In addition, we performed a phylogenetic analysis to reveal the relationship between disease severity and viral strain. This study provides comprehensive information on feline SFTS and could contribute to the protection of cat owners, community members, and veterinarians from the risk of cat-transmitted SFTSV infection.

Posterior circulation collaterals as predictors of outcome in basilar artery occlusion: a sub-analysis of the BASICS randomized trial.

Introduction and purpose: Basilar artery occlusion (BAO) is still one of the most devastating neurological conditions associated with high morbidity and mortality. In the present study, we aimed to assess the role of posterior circulation collaterals as predictors of outcome in the BASICS trial and to compare two grading systems (BATMAN score and PC-CS) in terms of prognostic value. Methods: We performed a sub-analysis of the BASICS trial. Baseline clinical and imaging variables were analyzed. For the imaging analysis, baseline CT and CTA were analyzed by a central core lab. Only those patients with good or moderate quality of baseline CTA and with confirmed BAO were included. Multivariable binary logistic regression analysis was used to test the independent association of clinical and imaging characteristics with a favorable outcome at 3 months (defined as a modified Rankin Score of ≤3). ROC curve analysis was used to assess and compare accuracy between the two collateral grading systems. Results: The mean age was 67.0 (±12.5) years, 196 (65.3%) patients were males and the median NIHSS was 21.5 (IQR 11-35). Median NCCT pc-ASPECTS was 10 (IQR10-10) and median collateral scores for BATMAN and PC-CS were 8 (IQR 7-9) and 7 (IQR 6-8) respectively. Collateral scores were associated with favorable outcome at 3 months for both BATMAN and PC-CS but only with a modest accuracy on ROC curve analysis (AUC 0.62, 95% CI [0.55-0.69] and 0.67, 95% CI [0.60-0.74] respectively). Age (OR 0.97, 95% CI [0.95-1.00]), NIHSS (OR 0.91, 95% CI [0.89-0.94]) and collateral score (PC-CS - OR 1.2495% CI [1.02-1.51]) were independently associated with clinical outcome. Conclusion: The two collateral grading systems presented modest prognostic accuracy. Only the PC-CS was independently associated with a favorable outcome at 3 months.

Parotid cancer: analysis of preoperative parameters for adaptation of the therapeutic strategy.

PURPOSE: To establish typical clinical and radiological profiles of primary low-grade parotid cancers in order to tailor therapeutic strategy. MATERIALS AND METHODS: Retrospective study of 57 patients operated on for primary parotid cancer between 2010 and 2021, with review of preoperative MRI and histopathology according to a standardized scoring grid. OBJECTIVE: To study prognostic factors and determine the preoperative clinical and radiological profile of low-grade cancers. RESULTS: Good prognostic factors for specific survival were: staging ≤ cT3 (p = 0.014), absence of adenopathy on cN0 MRI (p < 0.001), superficial lobe location (p = 0.033), pN0 (p < 0.001), absence of capsular rupture (p = 0.004), as well as the absence of peri-tumoral nodules (p = 0.033), intra-parotid adenopathies (p < 0.001), vascular emboli (p < 0.001), peri-neural sheathing (p = 0.016), nuclear atypia (p = 0.031), and necrosis (p = 0.002). It was not possible to define a reliable clinical and radiological profile for low-grade cancers (sensitivity 38%, specificity 79%). CONCLUSION: Our study demonstrated multiple factors of good prognosis, but it was not possible to define a clinical and radiological profile of patients likely to benefit from more limited surgery, nor to diagnose, a priori, low-grade cancers.

Construction and validation of a novel web-based nomogram for primary ocular adnexal lymphoma: a real-world analysis based on the Surveillance, Epidemiology, and End Results database.

Background: The occurrence rate of primary ocular adnexal lymphoma (POAL) is relatively low, and estimation of prognosis of these patients poses significant challenges. This study aims to investigate the independent prognostic factors of POAL patients and establish a predictive model to provide clinical data for the formulation of standardized treatment plans. Methods: We conducted a retrospective analysis by extracting data of POAL patients diagnosed between 2000 and 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. The enrolled patients were randomly divided into a training group and a testing group in a 7:3 ratio. To identify independent prognostic factors, we used both univariate and multivariate Cox regression analyses. Conditional survival (CS) pattern of these patients was analyzed. We formulated a nomogram model to forecast survival rates at intervals of 2, 5, 10, and 15 years. The reliability of the model's predictions was assessed through the concordance index (C-index) and the area under the receiver operating characteristic (ROC) curve (AUC). Moreover, we designed an online survival calculator using the nomogram model. Results: The study ultimately analyzed 3,324 patients with POAL, of which 2,327 and 997 were respectively assigned to a training group and a testing group. Important prognostic factors including age, sex, tumor site, tumor histology, coexistence of other malignancy, surgery, radiotherapy (RT), and marital status were identified. Based on these predictors, a novel nomogram model was successfully developed with excellent predictive performance, which can also be accessed on the website: https://helloshinyweb.shinyapps.io/eye_dynamic_nomogram/. The calibration curves demonstrated good consistency between the predicted and actual survival rates. Additionally, the C-index and AUC demonstrated good discriminative ability. Conclusions: This study has successfully developed and validated a prognostic nomogram model that accurately predicts the survival rate of patients with POAL. The model proves invaluable in enabling clinical doctors to assess patients' risk factors and formulate personalized treatment strategies, thereby enhancing survival assessment and clinical management for POAL patients.

Correlation between conventional ultrasound features combined with contrast-enhanced ultrasound patterns and pathological prognostic factors in malignant non-mass breast lesions.

OBJECTIVE: To investigate the correlation between ultrasound performance and prognostic factors in malignant non-mass breast lesions (NMLs). MATERIALS AND METHODS: This study included 106 malignant NMLs in 104 patients. Different US features and contrast enhancement patterns were evaluated. Prognostic factors, including histological types and grades, axillary lymph node and peritumoral lymphovascular status, estrogen and progesterone receptor status and the expression of HER-2 and Ki-67 were determined. A chi-square test and logistic regression analysis were used to analyse possible associations. RESULTS: Lesion size (OR: 3.08, p = 0.033) and posterior echo attenuation (OR: 8.38, p < 0.001) were useful in reflecting malignant NMLs containing an invasive carcinoma component. Posterior echo attenuation (OR: 7.51, p = 0.003) and unclear enhancement margin (OR: 6.50, p = 0.018) were often found in tumors with axillary lymph node metastases. Peritumoural lymphovascular invasion mostly exhibited posterior echo attenuation (OR: 3.84, p = 0.049) and unclear enhancement margin (OR: 8.68, p = 0.042) on ultrasound images. Perfusion defect was a comparatively accurate enhancement indicator for negative ER (OR: 2.57, p = 0.041) and PR (OR: 3.04, p = 0.008) expression. Calcifications (OR: 3.03, p = 0.025) and enlarged enhancement area (OR: 5.36, p = 0.033) imply an increased risk of positive HER-2 expression. Similarly, Calcifications (OR: 4.13, p = 0.003) and enlarged enhancement area (OR: 11.05, p < 0.001) were valid predictors of high Ki-67 proliferation index. CONCLUSION: Ultrasound performance is valuable for non-invasive prediction of prognostic factors in malignant NMLs.

Optimal cisplatin cycles in locally advanced cervical carcinoma patients treated with concurrent chemoradiotherapy

Purpose To analyze the effect of cisplatin cycles on the clinical outcomes of patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT). Methods This study included 749 patients with LACC treated with CCRT between January 2011 and December 2015. A receiver operating characteristic (ROC) curve was used to analyze the optimal cut-off of cisplatin cycles in predicting clinical outcomes. Clinicopathological features of the patients were compared using the Chi-square test. Prognosis was assessed using log-rank tests and Cox proportional hazard models. Toxicities were compared among different cisplatin cycle groups. Results Based on the ROC curve, the optimal cut-off of the cisplatin cycles was 4.5 (sensitivity, 64.3%; specificity, 54.3%). The 3-year overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival for patients with low-cycles (cisplatin cycles < 5) and high-cycles (≥ 5) were 81.5% and 89.0% (P < 0.001), 73.4% and 80.1% (P = 0.024), 83.0% and 90.8% (P = 0.005), and 84.9% and 86.8% (P = 0.271), respectively. In multivariate analysis, cisplatin cycles were an independent prognostic factor for overall survival. In the subgroup analysis of high-cycle patients, patients who received over five cisplatin cycles had similar overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival to patients treated with five cycles. Acute and late toxicities were not different between the two groups. Conclusion Cisplatin cycles were associated with overall, disease-free, and loco-regional relapse-free survival in LACC patients who received CCRT. Five cycles appeared to be the optimal number of cisplatin cycles during CCRT (AU)

Survival prediction of hepatocellular carcinoma by measuring the extracellular volume fraction with single-phase contrast-enhanced dual-energy CT imaging.

Purpose: This study aimed to investigate the value of quantified extracellular volume fraction (fECV) derived from dual-energy CT (DECT) for predicting the survival outcomes of patients with hepatocellular carcinoma (HCC) after transarterial chemoembolization (TACE). Materials and methods: A total of 63 patients with HCC who underwent DECT before treatment were retrospectively included. Virtual monochromatic images (VMI) (70 keV) and iodine density images (IDI) during the equilibrium phase (EP) were generated. The tumor VMI-fECV and IDI-fECV were measured and calculated on the whole tumor (Whole) and maximum enhancement of the tumor (Maximum), respectively. Univariate and multivariate Cox models were used to evaluate the effects of clinical and imaging predictors on overall survival (OS) and progression-free survival (PFS). Results: The correlation between tumor VMI-fECV and IDI-fECV was strong (both p< 0.001). The Bland-Altman plot between VMI-fECV and IDI-fECV showed a bias of 5.16% for the Whole and 6.89% for the Maximum modalities, respectively. Increasing tumor VMI-fECV and IDI-fECV were positively related to the effects on OS and PFS (both p< 0.05). The tumor IDI-fECV-Maximum was the only congruent independent predictor in patients with HCC after TACE in the multivariate analysis on OS (p = 0.000) and PFS (p = 0.028). Patients with higher IDI-fECV-Maximum values had better survival rates above the optimal cutoff values, which were 35.42% for OS and 29.37% for PFS. Conclusion: The quantified fECV determined by the equilibrium-phase contrast-enhanced DECT can potentially predict the survival outcomes of patients with HCC following TACE treatment.

Severe forms of influenza infections admitted in intensive care units: Analysis of mortality factors.

Background: The severe forms of influenza infection requiring intensive care unit (ICU) admission remain a medical challenge due to its high mortality. New H1N1 strains were hypothesized to increase mortality. The studies below represent a large series focusing on ICU-admitted influenza patients over the last decade with an emphasis on factors related to death. Methods: A retrospective study of patients admitted in ICU for influenza infection over the 2010-2019 period in Réunion Island (a French overseas territory) was conducted. Demographic data, underlying conditions, and therapeutic management were recorded. A univariate analysis was performed to assess factors related to ICU mortality. Results: Three hundred and fifty adult patients were analyzed. Overall mortality was 25.1%. Factors related to higher mortality were found to be patient age >65, cancer history, need for intubation, early intubation within 48 h after admission, invasive mechanical ventilation (MV), acute respiratory distress syndrome (ARDS), vaso-support drugs, extracorporal oxygenation by membrane (ECMO), dialysis, bacterial coinfection, leucopenia, anemia, and thrombopenia. History of asthma and oseltamivir therapy were correlated with a lower mortality. H1N1 did not impact mortality. Conclusion: Patient's underlying conditions influence hospital admission and secondary ICU admission but were not found to impact ICU mortality except in patients age >65, history of cancer, and bacterial coinfections. Pulmonary involvement was often present, required MV, and often evolved toward ARDS. ICU mortality was strongly related to ARDS severity. We recommend rapid ICU admission of patients with influenza-related pneumonia, management of bacterial coinfection, and early administration of oseltamivir.

Development and validation of a prognostic nomogram for gallbladder papillary adenocarcinoma.

Background: Gallbladder papillary adenocarcinoma (GBPA) is an uncharacteristically gallbladder cancer subtype. Although some studies have shown that the prognosis of GBPA patients is significantly better than that of gallbladder adenocarcinoma (GBA) and gallbladder mucinous adenocarcinoma (GBMA) due to its rarity, there is a lack of large sample studies necessary to confirm the clinical characteristics and survival rate of GBPA. Therefore, this study aimed to describe the clinicopathological characteristics affecting survival in GBPA. This data was then used to establish a prognostic nomogram for GBPA. Methods: The data of patients diagnosed with gallbladder cancer between 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The clinical features and survival of patients with GBPA were compared with those of GBA and GBMA after balancing the baseline characteristics using propensity score matching (PSM). Univariate and multivariate Cox analyses were used to identify the prognostic factors for GBPA. Subsequently, the overall survival (OS) and cancer-specific survival (CSS) nomograms were established to predict GBPA prognosis. The performance and discrimination of the nomogram were measured using concordance index (C-index), calibration curves, receptor operating characteristic curves(ROC), and decision curve analysis (DCA) was applied to examine the net benefit of tients with GBPA, 5798 patients with GBA, and 223 patients with GBMA. The mean 1-, 3- and 5-year OS rates for GBPA were 81.3%, 58.8%, and 49.1%, respectively, while the mean 1-, 3- and 5-year CSS rates were 85.0%, 68.1%, and 61.0%, respectively. The median OS rates was 58 months (95% CI: 43-88), while the median CSS was not reached. The PSM analysis showed a differ statistically significantly in the OS between GBPA and GBA. However, there has no statistically difference in CSS. Conversely, the OS and CSS between GBPA and GBMA have statistically significant differences. Age, marital, T stage, and M stage were strongly linked to the prognosis for OS, while T-stage, M-stage, and surgery were significantly associated with the prognosis for CSS in GBPA patients. The AUC for the 1-, 3-, and 5-year OS were 0.722 (95%CI: 0.630-0.813), 0.728 (95%CI: 0.665-0.790), and 0.706 (95%CI: 0.641-0.771), respectively. The AUC for the 1-, 3-, and 5-year CSS were 0.749 (95%CI: 0.659-0.840), 0.698 (95%CI: 0.627-0.770), and 0.665 (95%CI: 0.594-0.735), respectively. The C-indices for the OS and CSS nomograms were 0.701 (95% CI: 0.634-0.744) and 0.651 (95% CI: 0.598-0.703), respectively. The calibration curves showed that the nomograms were well consistency. The DCA showed that compared with the TNM system, the nomogram models had a significant positive net benefit in survival prediction. Conclusion: GBPA has distinct clinicopathological characteristics and survival compared to other gallbladder carcinomas. The established nomogram provided a better prediction of survival for GBPA patients than the traditional TNM models.

Optimal cisplatin cycles in locally advanced cervical carcinoma patients treated with concurrent chemoradiotherapy.

PURPOSE: To analyze the effect of cisplatin cycles on the clinical outcomes of patients with locally advanced cervical cancer (LACC) treated with concurrent chemoradiotherapy (CCRT). METHODS: This study included 749 patients with LACC treated with CCRT between January 2011 and December 2015. A receiver operating characteristic (ROC) curve was used to analyze the optimal cut-off of cisplatin cycles in predicting clinical outcomes. Clinicopathological features of the patients were compared using the Chi-square test. Prognosis was assessed using log-rank tests and Cox proportional hazard models. Toxicities were compared among different cisplatin cycle groups. RESULTS: Based on the ROC curve, the optimal cut-off of the cisplatin cycles was 4.5 (sensitivity, 64.3%; specificity, 54.3%). The 3-year overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival for patients with low-cycles (cisplatin cycles < 5) and high-cycles (≥ 5) were 81.5% and 89.0% (P < 0.001), 73.4% and 80.1% (P = 0.024), 83.0% and 90.8% (P = 0.005), and 84.9% and 86.8% (P = 0.271), respectively. In multivariate analysis, cisplatin cycles were an independent prognostic factor for overall survival. In the subgroup analysis of high-cycle patients, patients who received over five cisplatin cycles had similar overall, disease-free, loco-regional relapse-free, and distant metastasis-free survival to patients treated with five cycles. Acute and late toxicities were not different between the two groups. CONCLUSION: Cisplatin cycles were associated with overall, disease-free, and loco-regional relapse-free survival in LACC patients who received CCRT. Five cycles appeared to be the optimal number of cisplatin cycles during CCRT.

Adjuvant therapy for cholangiocarcinoma after surgery and prognosis factors for cholangiocarcinoma: A single-center retrospective cohort study.

Background: Cholangiocarcinoma (CCA) is a highly heterogeneous malignant tumor, and more than 60% of patients have recurrence and metastasis after surgery. The efficacy of postoperative adjuvant therapy for CCA remains unclear. This study aimed to explore whether adjuvant therapy benefits patients with CCA and examine the independent prognostic factors for overall survival (OS) and progression-free survival (PFS). Methods: Patients with CCA undergoing surgery were retrospectively enrolled in this study from June 2016 to June 2022. The chi-square test or Fisher exact test was used to analyze the correlation between clinicopathologic characteristics. Survival curves were plotted using the Kaplan-Meier method, and the Cox regression model was used for univariate and multivariate analysis to search for independent prognostic factors. Results: Of the 215 eligible patients, 119 patients received adjuvant therapy, and the other 96 patients did not. The median follow-up was 37.5 months. The median OS of CCA patients with and without adjuvant therapy was 45 and 18 months (P < 0.001), respectively. The median PFS of CCA patients with and without adjuvant therapy was 34 and 8 months (P < 0.001), respectively. The Cox univariate and multivariate regression analysis showed that preoperative aspartate transaminase and carbohydrate antigen 19-9, microvascular invasion, lymph node metastasis, differentiation degree, and adjuvant therapy were independent prognostic factors for OS (all P values < 0.05). Preoperative carbohydrate antigen 125, microvascular invasion, lymph node metastasis, differentiation degree, and adjuvant therapy were independent prognostic factors for PFS (all P values < 0.05). The stratified analysis by TMN stage detected significant differences in the early stages (median OS [mOS]: P = 0.0128; median PFS [mPFS]: P = 0.0209) and advanced stages (mOS and mPFS: both P values < 0.001). Adjuvant therapy was also identified as a significantly favorable prognostic factor for OS and PFS in the early stages and advanced stages. Conclusion: Postoperative adjuvant therapy can improve the prognosis of patients with CCA, even in the early stages and advanced stages. All data suggest that adjuvant therapy should be incorporated into the treatment of CCA in all cases, where appropriate.

Optimal Timing of Coronary Artery Bypass Grafting in Haemodynamically Stable Patients after Myocardial Infarction.

During the acute phase of myocardial infarction, the culprit artery must be revascularized quickly with angioplasty. Surgery then completes the procedure in a second stage. If emergency surgery is performed, the resulting death rate is high; 15-20% of patients are operated on within the first 48 h after the myocardial infarction. The timing of surgical revascularization and the patient's preoperative state influence the mortality rate. We aimed to evaluate the impact of surgery delay on morbimortality. Between 2007 and 2017, a retrospective monocentric study was conducted including 477 haemodynamically stable patients after myocardial infarction who underwent an urgent coronary bypass. Three groups were described, depending on the timing of the surgery: during the first 4 days (Group 1, n = 111, 23%), 5 to 10 days (Group 2, n = 242, 51%) and after 11 days (Group 3, n = 124, 26%). The overall thirty-day mortality was 7.1% (n = 34). The death rate was significantly higher in Group 1 (n = 16; 14% vs. n = 10; 4.0% vs. n = 8; 6%, p < 0.01). The mortality risk factors identified were age (OR: 1.08; CI 95%: 1.04-1.12; p < 0.001), peripheral arteriopathy (OR: 3.31; CI 95%: 1.16-9.43; p = 0.024), preoperative renal failure (OR: 6.39; CI 95%: 2.49-15.6; p < 0.001) and preoperative ischemic recurrence (OR: 3.47; CI 95%: 1.59-7.48; p < 0.01). Ninety-two patients presented with preoperative ischemic recurrence (19%), with no difference between the groups. The optimal timing for the surgical revascularization of MI seems to be after Day 4 in stable patients. However, timing is not the only factor influencing the death rate: the patient's health condition and disease severity must be considered in the individual management strategy.

A population-based study of synchronous distant metastases and prognosis in patients with PDAC at initial diagnosis.

Objective: Cancer of the pancreas is a life-threatening condition and has a high distant metastasis (DM) rate of over 50% at diagnosis. Therefore, this study aimed to determine whether patterns of distant metastases correlated with prognosis in pancreatic ductal adenocarcinoma (PDAC) with metastatic spread, and build a novel nomogram capable of predicting the 6, 12, 18-month survival rate with high accuracy. Methods: We analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database for cases of PDAC with DM. Kaplan-Meier analysis, log-rank tests and Cox-regression proportional hazards model were used to assess the impact of site and number of DM on the cancer-specific survival (CSS) and over survival (OS). A total of 2709 patients with DM were randomly assigned to the training group and validation group in a 7:3 ratio. A nomogram was constructed by the dependent risk factors which were determined by multivariate Cox-regression analysis. An assessment of the discrimination and ability of the prediction model was made by measuring AUC, C-index, calibration curve and decision curve analysis (DCA). In addition, we collected 98 patients with distant metastases at the time of initial diagnosis from Ningbo University Affiliated LiHuili Hospital to verify the efficacy of the prediction model. Results: There was a highest incidence of liver metastases from pancreatic cancer (2387,74.36%), followed by lung (625,19.47%), bone (190,5.92%), and brain (8,0.25%). The prognosis of liver metastases differed from that of lung metastases, and the presence of multiple organ metastases was associated with poorer prognosis. According to univariate and multivariate Cox-regression analyses, seven factors (i.e., diagnosis age, tumor location, grade of tumor differentiation, T-stage, receipt of surgery, receipt of chemotherapy status, presence of multiple organ metastases) were included in our nomogram model. In internal and external validation, the ROC curves, C-index, calibration curves and DCA were calculated, which confirmed that this nomogram can precisely predict prognosis of PDAC with DM. Conclusion: Metastatic PDAC patients with liver metastases tended to have a worse prognosis than those with lung metastases. The number of DM had significant effect on the overall survival rate of metastatic PDAC. This study had a high prediction accuracy, which was helpful clinicians to analyze the prognosis of PDAC with DM and implement individualized diagnosis and treatment.

Early Depressive Symptoms Predict Faster Dementia Progression in Autosomal-Dominant Alzheimer's Disease.

BACKGROUND: Depression is associated with Alzheimer's disease (AD). OBJECTIVE: To evaluate the association between depressive symptoms and age of onset of cognitive decline in autosomal dominant AD, and to determine possible factors associated to early depressive symptoms in this population. METHODS: We conducted a retrospective study to identify depressive symptoms among 190 presenilin 1 (PSEN1) E280A mutation carriers, subjected to comprehensive clinical evaluations in up to a 20-year longitudinal follow-up. We controlled for the following potential confounders: APOE, sex, hypothyroidism, education, marital status, residence, tobacco, alcohol, and drug abuse. RESULTS: PSEN1 E280A carriers with depressive symptoms before mild cognitive impairment (MCI) develop dementia faster than E280A carriers without depressive symptoms (Hazard Ratio, HR = 1.95; 95% CI, 1.15-3.31). Not having a stable partner accelerated the onset of MCI (HR = 1.60; 95 % CI, 1.03-2.47) and dementia (HR = 1.68; 95 % CI, 1.09-2.60). E280A carriers with controlled hypothyroidism had later age of onset of depressive symptoms (HR = 0.48; 95 % CI, 0.25-0.92), dementia (HR = 0.43; 95 % CI, 0.21-0.84), and death (HR = 0.35; 95 % CI, 0.13-0.95). APOEɛ2 significantly affected AD progression in all stages. APOE polymorphisms were not associate to depressive symptoms. Women had a higher frequency and developed earlier depressive symptoms than men throughout the illness (HR = 1.63; 95 % CI, 1.14-2.32). CONCLUSION: Depressive symptoms accelerated progress and faster cognitive decline of autosomal dominant AD. Not having a stable partner and factors associated with early depressive symptoms (e.g., in females and individuals with untreated hypothyroidism), could impact prognosis, burden, and costs.

Prediction of Acute Respiratory Distress Syndrome in Traumatic Brain Injury Patients Based on Machine Learning Algorithms.

Background: Acute respiratory distress syndrome (ARDS) commonly develops in traumatic brain injury (TBI) patients and is a risk factor for poor prognosis. We designed this study to evaluate the performance of several machine learning algorithms for predicting ARDS in TBI patients. Methods: TBI patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were eligible for this study. ARDS was identified according to the Berlin definition. Included TBI patients were divided into the training cohort and the validation cohort with a ratio of 7:3. Several machine learning algorithms were utilized to develop predictive models with five-fold cross validation for ARDS including extreme gradient boosting, light gradient boosting machine, Random Forest, adaptive boosting, complement naïve Bayes, and support vector machine. The performance of machine learning algorithms were evaluated by the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy and F score. Results: 649 TBI patients from the MIMIC-III database were included with an ARDS incidence of 49.5%. The random forest performed the best in predicting ARDS in the training cohort with an AUC of 1.000. The XGBoost and AdaBoost ranked the second and the third with an AUC of 0.989 and 0.815 in the training cohort. The random forest still performed the best in predicting ARDS in the validation cohort with an AUC of 0.652. AdaBoost and XGBoost ranked the second and the third with an AUC of 0.631 and 0.620 in the validation cohort. Several mutual top features in the random forest and AdaBoost were discovered including age, initial systolic blood pressure and heart rate, Abbreviated Injury Score chest, white blood cells, platelets, and international normalized ratio. Conclusions: The random forest and AdaBoost based models have stable and good performance for predicting ARDS in TBI patients. These models could help clinicians to evaluate the risk of ARDS in early stages after TBI and consequently adjust treatment decisions.

Clinical features and outcomes of pediatric intracranial gliomas: results from single center's 226 cases and corroborated with SEER database.

BACKGROUND: Pediatric gliomas are the most common central nervous system (CNS) tumors in children and adolescents and show different clinical and histopathological characteristics from the adult. The prognostic factors were poorly defined in pediatric intracranial gliomas. METHODS: We collected pediatric intracranial glioma cases in our institution between February 2011 and June 2022. The patient clinical data, tumor growth characteristics, treatments, and follow-up data were analyzed by Cox regression analysis to identify impact factors on the prognosis of pediatric intracranial glioma patients. To corroborate our data, an independent cohort of pediatric intracranial glioma from the Surveillance, Epidemiology, and End Results Program (SEER) database was analyzed. RESULTS: A total of 181 cases of pediatric low-grade glioma (PLGG) and 45 cases of pediatric high-grade glioma (PHGG) were included. In multivariate Cox regression analysis, tumor size > 59.5 mm (p = 0.006) and non-gross total resection (non-GTR; subtotal resection, STR, p = 0.042; biopsy, p = 0.012) were associated with decreased overall survival (OS) in PLGG patients. In PHGG patients, only chemotherapy (p = 0.023) was associated with OS while tumor size was marginally prognostic for OS (p = 0.051). Additional independent analysis of 2734 PLGG and 741 PHGG from the SEER database corroborated that larger tumor size was associated with decreased OS in LGG (p = 0.001) and HGG (p < 0.001) patients, separately. CONCLUSION: In this study, we found that tumor size was a significant prognostic factor for the OS of PLGG patients in our series. Besides the tumor size, the extent of resection also independently impacted the prognosis of PLGG patients. While in PHGG patients, only chemotherapy was associated with improved OS and tumor size was marginally prognostic.

Clinicopathological characteristics, survival outcome and prognostic factors of very young gastric cancer.

To explore the clinicopathological characteristics, survival outcomes, and prognosis of very young gastric cancer (GC). From January 1, 2011 to January 1, 2021, GC patients under 30 years old treated in three tertiary hospitals were enrolled. Clinicopathological characteristics were summarized, prognostic factors and survival outcomes including overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) were retrospectively analyzed. One hundred patients were finally included, with a median age of 23 years.73 (73.0%) were female. Most patients had initial symptoms of abdominal pain (66.0%). The most common tumor locations were gastric antrum (38.0%) and gastric body (37.0%). The main histological types were diffuse (81.0%) and poorly differentiated (91.0%). Most patients presented with stage III-IV disease (82.0%) at diagnosis and the common sites of metastasis were ovary (39.5%) and peritoneum (27.6%). The mOS of the whole group was 23.3 months (95% CI 17.2-29.4). Moreover, the mOS of patients at stage I-II was not reached. The mOS of patients at stage III and stage IV was 40.6 months (95% CI 10.2-70.9) and 10.3 months (95% CI 8.9-11.6), respectively. The mDFS of stage I-III patients was 28.5 months (95% CI 14.7-42.3), and the mPFS of the metastatic patients was 4.5 months (95% CI 4.0-5.0). TNM stage (P = 0.005) and radical surgery (P = 0.001) were independent prognostic factors of overall survival. The very young GC were predominantly female, diffuse type, and advanced diagnosis. TNM stage and radical surgery were independent prognosis factors for overall survival.

Prognostic factors for cancer-specific survival in 220 patients with breast cancer: A single center experience.

OBJECTIVES: Hospital-based breast cancer survival studies are scarce in western Iran. Furthermore, the relationship between breast cancer survival and clinical parameters has been extensively studied, but many of the findings come from developing countries. This paper aims to estimate the survival of hospital-based breast cancer patients and its predictor factors. METHOD: This retrospective analysis was conducted on 578 patients with primary breast cancer who underwent surgery between 2004 and 2020. Information was collected from medical reports by the Hospital information system in Imam Reza Hospital, Kermanshah, Iran. One-, 2-, 5-, and 10-year breast cancer-specific survival has been calculated using the Kaplan-Meier process. Crude and adjusted Hazard Ratios (HR) were calculated using the Cox proportional regression model. RESULT: One-, 2-, and 5-year overall breast cancer survival were 219 (99.54%), 196 (89.09%), 159 (72.27%), and 70 (31.81%), respectively. Univariate analysis of breast cancer patients with tumor-related variables revealed that factors such as age, menopause status, lymph node metastasis, number of lymph nodes, organ metastasis, and stage of disease were significantly associated with disease-specific survival (p < .05). Multivariate analysis demonstrated that metastasis (HR = 41.77, 95% CI: 15.3-114.15) and lymph node metastasis (HR = 5.26, 95% CI: 1.9-14.6) were significantly related to survival. CONCLUSION: The findings demonstrate that survival is relatively low and is consistent with late-stage disease diagnosis. It is believed that this is due to a poor level of awareness, lack of screening programs, and subsequent late access to treatment.