UNASSIGNED: Heart failure with reduced ejection fraction (HFrEF) patients who have improved ejection fraction have a better prognosis than those with persistently reduced ejection fraction. This study aimed to analyze the predictors for progression of patients with HFrEF to heart failure with improved ejection fraction (HFimpEF), as well as their characteristics and analyze predictors for prognosis.
UNASSIGNED: A retrospective analysis was conducted on 1251 patients with HFrEF at baseline, who also had a second echocardiogram ≥ 3 months. After left ventricular ejection fraction (LVEF) reassessment, patients were separated into the HFimpEF group (n = 408) and the persistent HFrEF group (n = 611). The primary endpoint was a composite of cardiovascular death or heart failure hospitalization.
UNASSIGNED: Multivariate logistic regression showed that without history of alcohol consumption (OR: 0.47, 95% CI: 0.28-0.78), non-New York Heart Association (NYHA) class III-IV (OR: 0.28, 95% CI: 0.15-0.52), without dilated cardiomyopathy (OR: 0.47, 95% CI: 0.26-0.84), concomitant hypertension (OR: 1.53, 95% CI: 1.02-2.29), β -blockers use (OR: 2.29, 95% CI: 1.54-3.43), and lower uric acid (OR: 0.999, 95% CI: 0.997-1.000) could predict LVEF improvement. Kaplan-Meier curves demonstrated that HFimpEF patients had a significantly lower incidence of adverse events than HFrEF patients (log Rank p < 0.001). Multivariate Cox regression found that older age (HR: 1.04, 95% CI: 1.02-1.06), NYHA class III-IV (HR: 2.25, 95% CI: 1.28-3.95), concomitant valvular heart disease (HR: 1.98, 95% CI: 1.01-3.85), and higher creatinine (HR: 1.003, 95% CI: 1.001-1.004) were independent risk factors for the primary endpoint in HFimpEF patients.
UNASSIGNED: HFrEF patients without a history of alcohol consumption, non-NYHA class III-IV, without dilated cardiomyopathy, concomitant hypertension, β -blockers use, and lower uric acid were more likely to have LVEF improvement. Although the prognosis of HFimpEF patients was better than that of HFrEF patients, older age, NYHA class III-IV, concomitant valvular heart disease, and higher creatinine were still risk factors for cardiovascular events in HFimpEF patients.

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BACKGROUND: Delayed clinically important postoperative nausea and vomiting (CIPONV) could lead to significant consequences following surgery. We aimed to develop a prediction model for it using machine learning algorithms utilizing perioperative data from patients undergoing laparoscopic gastrointestinal surgery.
METHODS: All 1154 patients in the FDP-PONV trial were enrolled. The optimal features for model development were selected by least absolute shrinkage and selection operator and stepwise regression from 81 perioperative variables. The machine learning algorithm with the best area under the receiver operating characteristic curve (ROCAUC) was determined and assessed. The interpretation of the prediction model was performed by the SHapley Additive Explanations library.
RESULTS: Six important predictors were identified. The random forest model showed the best performance in predicting delayed CIPONV, achieving an ROCAUC of 0.737 in the validation cohort.
CONCLUSIONS: This study developed an interpretable model predicting personalized risk for delayed CIPONV, aiding high-risk patient identification and prevention strategies.

Stroke recurrence remains a critical challenge in clinical neurology, necessitating the identification of reliable predictive markers for better management and treatment strategies. This study investigates the interaction between lipoprotein-associated phospholipase A2 (Lp-PLA2) and platelets as a potential predictor for stroke recurrence, aiming to refine risk assessment and therapeutic approaches. In a retrospective cohort of 580 ischemic stroke patients, we analyzed clinical data with a focus on Lp-PLA2 and platelet levels. By using multivariable logistic regression, we identified independent predictors of stroke recurrence. These predictors were then used to develop a comprehensive nomogram. The study established diabetes mellitus, hypertension, low-density lipoprotein (LDL), Lp-PLA2 levels, and platelet counts as independent predictors of stroke recurrence. Crucially, the interaction parameter Lp-PLA2 * platelet (multiplication of Lp-PLA2 and platelet count) exhibited superior predictive power over each factor considered separately. Our nomogram incorporated diabetes mellitus, cerebral infarction causes, hypertension, LDL, and the Lp-PLA2 * platelet count interaction and demonstrated enhanced accuracy in predicting stroke recurrence compared to traditional risk models. The interaction between Lp-PLA2 and platelets emerged as a significant predictor for stroke recurrence when integrated with traditional risk factors. The developed nomogram offers a novel and practical tool in molecular neurobiology for assessing individual risks, facilitating personalized treatment strategies. This approach underscores the importance of multifactorial assessment in stroke management and opens avenues for targeted interventions to mitigate recurrence risks.

BACKGROUND: The predictive value of systemic inflammatory response index (SIRI) for stroke-associated pneumonia (SAP) risk in patients with acute ischemic stroke (AIS) treated by thrombectomy remains unclear. This study aimed to investigate the predictive value of SIRI for SAP in patients with AIS treated by thrombectomy.
METHODS: We included AIS patients treated by thrombectomy between August 2018 and August 2022 at our institute. We used multivariate logistic regression to construct the prediction model and performed a receiver operating characteristic curve analysis to evaluate the ability of SIRI to predict SAP and constructed a calibration curve to evaluate the prediction accuracy of the model. We evaluated the clinical application value of the nomogram using decision curve analysis.
RESULTS: We included 84 eligible patients with AIS in the analysis, among which 56 (66.7%) had SAP. In the univariate analysis, there were significant differences in sex (p = 0.035), National Institute of Health Stroke Scale score at admission ≥ 20 (p = 0.019) and SIRI (p < 0.001). The results of multivariable logistic analysis showed that the risk of SAP increased with the SIRI value (OR = 1.169, 95% CI = 1.049-1.344, p = 0.014). Age ≥ 60 (OR = 4.076, 95% CI = 1.251-14.841, p = 0.024) was also statistically significant. A nomogram with SIRI showed good prediction accuracy for SAP in AIS patients treated by thrombectomy (C-index value = 0.774).
CONCLUSIONS: SIRI is an independent predictor for SAP in patients with AIS treated by thrombectomy. A high SIRI value may allow for the early identification of patients with AIS treated by thrombectomy at high risk for SAP.

OBJECTIVE: To identify independent predictors of thoracic aortic growth in patients with type B aortic dissection (TBAD) undergoing thoracic endovascular aortic repair (TEVAR).
METHODS: A retrospective analysis of the patients undergoing TEVAR for TBAD or intramural hematoma (IMH) from April 2014 to April 2023 was performed. The baseline morphological data of TBAD was established through computed tomography angiography (CTA) before discharge. Patients were divided into two groups based on aortic growth: growth and no growth. Aortic growth defined as an increase ≥5 mm in thoracic maximal aortic diameter during any serial follow-up CTA measurement. Logistic regression following propensity score matching (PSM) was used to identify independent predictors for aortic growth. Receiver operating characteristic curve and cutoff value of independent predictors were calculated. Linear regression was used to establish a correlation between anatomical variables and follow-up aortic diameter.
RESULTS: A total of 145 patients with TBAD (n = 122) or IMH (n = 23) undergoing TEVAR were included, with a male of 83.4% and a mean age of 56 ± 14.1 years. Patients in growth group and no growth group was 26 (17.9%) and 119 (80.1%), respectively. After using PSM method, matched regression analysis showed residual maximal tear diameter (OR = 0.889, 95% CI 0.830-0.952, p = 0.001) and follow-up aortic diameter (OR = 0.977, 95% CI 0.965-0.989, p < 0.001) were independent predictors for aortic growth. The cutoff value was 8.55 mm for residual tear diameter and 40.65 mm for follow-up maximal aortic diameter. The residual maximal tear diameter showed a linear correlation with follow-up aortic diameter (DW = 1.74, R2 = 6.2%, p = 0.033).
CONCLUSIONS: This study suggested that residual maximal tear diameter >8.55 mm and follow-up aortic diameter >40.65 mm could predict aortic growth in patients with TBAD undergoing TEVAR.

UNASSIGNED: Rapid progression of coronary non-target lesions is essential for the determination of future cardiovascular events. Clinical factors that predict rapid progression of non-target lesions are unclear. The purpose of this study was to identify the clinical predictors of rapid progression and revascularization of coronary non-target lesions.
UNASSIGNED: Consecutive patients with coronary heart disease who had undergone two serial coronary angiograms were enrolled. All coronary non-target lesions were identified and evaluated at both procedures. Multivariable Cox regression analysis was used to investigate the clinical risk factors associated with rapid progression or revascularization of coronary non-target lesions.
UNASSIGNED: A total of 1255 patients and 1670 lesions were enrolled. In this cohort of patients, 239 (19%) had rapid progression and 186 (14.8%) underwent revascularization. At the lesion level, 251 (15.0%) had rapid progression and 194 (11.6%) underwent revascularization. The incidence of lesion revascularization and myocardial infarction was significantly higher in patients with rapid progression. In multivariable analyses, hypertension (hazard ratio [HR], 0.76; 95% confidence interval [95% CI], 0.58-1.00; p = 0.049), ST-segment elevation myocardial infarction (STEMI) (HR, 1.46; 95% CI, 1.03-2.07; p = 0.035), glycosylated hemoglobin (HR, 1.16; 95% CI, 1.01-1.33; p = 0.039) and lesion classification (B2/C versus A/B1) (HR, 1.73; 95% CI, 1.27-2.35; p = 0.001) were significant factors associated with rapid progression. The level of triglycerides (HR, 1.10; 95% CI, 1.00-1.20; p = 0.040) and lesion classification (B2/C versus A/B1) (HR, 1.53; 95% CI, 1.09-2.14; p = 0.014) were predictors of lesion revascularization.
UNASSIGNED: Hypertension, STEMI, glycosylated hemoglobin and lesion classification may be used as predictors of rapid progression of coronary non-target lesions. The level of triglyceride and lesion classification may predict the revascularization of non-target lesions. In order to prevent future cardiovascular events, increased attention should be paid to patients with these factors.

BACKGROUND: Residual symptoms of depressive disorders are serious health problems. However, the progression process is hardly predictable due to high heterogeneity of the disease. This study aims to: (1) classify the patterns of changes in residual symptoms based on homogeneous data, and (2) identify potential predictors for these patterns.
METHODS: In this study, we conducted a data-driven Latent Class Growth Analysis (LCGA) to identify distinct tendencies of changes in residual symptoms, which were longitudinally quantified using the QIDS-SR16 at baseline and 1/3/6 months post-baseline for depressed patients. The association between baseline characteristics (e.g. clinical features and cognitive functions) and different progression tendencies were also identified.
RESULTS: The tendency of changes in residual symptoms was categorized into four classes: \"light residual symptom decline (15.4%)\", \"residual symptom disappears (39.3%)\", \"steady residual symptom (6.3%)\" and \"severe residual symptom decline (39.0%)\". We observed that the second class displayed more favorable recuperation outcomes than the rest of patients. The severity, recurrence, polypharmacy, and medication adherence of symptoms are intricately linked to the duration of residual symptoms\' persistence. Additionally, clinical characteristics including sleep disturbances, depressive moods, alterations in appetite or weight, and difficulties with concentration have been identified as significant factors in the recovery process.
CONCLUSIONS: Our research findings indicate that certain clinical characteristics in patients with depressive disorders are associated with poor recovery from residual symptoms following acute treatment. This revelation holds significant value in the targeted attention to specific patients and the development of early intervention strategies for residual symptoms accordingly.

BACKGROUND: The remarkable advancements in surgical techniques over recent years have shifted the clinical focus from merely reducing mortality to enhancing the quality of postoperative recovery. The duration of a patient\'s hospital stay serves as a crucial indicator in evaluating postoperative recovery and surgical outcomes. This study aims to identify predictors of the length of hospital stay for children who have undergone corrective surgery for Ebstein Anomaly (EA).
METHODS: We conducted a retrospective cohort study on children (under 18 years of age) diagnosed with EA who were admitted for corrective surgery between January 2009 and November 2021 at Fuwai Hospital. The primary outcome was the Time to Hospital Discharge (THD). Cox proportional hazard models were utilized to identify predictors of THD. In the context of time-to-event analysis, discharge was considered an event. In cases where death occurred before discharge, it was defined as an extended THD, input as 100 days (exceeding the longest observed THD), and considered as a non-event.
RESULTS: A total of 270 children were included in this study, out of which three died in the hospital. Following the Cox proportional hazard analysis, six predictors of THD were identified. The hazard ratios and corresponding 95% confidence intervals were as follows: age, 1.030(1.005,1.055); C/R > 0.65, 0.507(0.364,0.707); Carpentier type C or D, 0.578(0.429,0.779); CPB time, 0.995(0.991,0.998); dexamethasone, 1.373(1.051,1.795); and transfusion, 0.680(0.529,0.875). The children were categorized into three groups based on the quartile of THD. Compared to children in the ≤ 6 days group, those in the ≥ 11 days group were associated with a higher incidence of adverse outcomes. Additionally, the duration of mechanical ventilation and ICU stay, as well as hospital costs, were significantly higher in this group.
CONCLUSIONS: We identified six predictors of THD for children undergoing corrective surgery for EA. Clinicians can utilize these variables to optimize perioperative management strategies, reduce adverse complications, improve postoperative recovery, and reduce unnecessary medical expenses.