Low-risk Population Research Articles

The Impact of Non-trauma Factors on Trauma Patient Mortality and Hospital Resource Utilization: Population-Based Retrospective Review.

The death of trauma patients with low injury severity scores (ISS) may not be fully explained by the severity of their injuries. Our objective was to evaluate preexisting conditions (PECs) that may contribute to the mortality rate of and hospital resources consumed by patients with low ISS. Trauma patients with ISS <9 were selected from the National Trauma Database Bank [NTDB] [2019-21]. Bivariate and multivariate analysis identified the risk factors associated with mortality, adjusting for secondary PECs, mechanism of injury, AIS body region, vital signs, and blood transfusion. A t test was used to compare PEC status with intensive care unit (ICU) and hospital length of stay (LOS) for significant differences (P < .05). 1,689,392 patients suffered mild injuries [59.1% male, mean age 45.2, 8579 expired (0.5%)]. Mortality was associated with the presence of several risk factors, especially advanced directive [OR = 9.13, P < .001], cirrhosis [OR = 8.55, P < .001], disseminated cancer [OR = 8.53, P < .001], congestive heart failure (CHF) [OR = 6.62, P < .001], chronic renal failure (CRF) [OR = 6.16, P < .001], chemotherapy for cancer [OR = 5.64, P < .001], peripheral arterial disease (PAD) [OR = 5.32, P < .001], myocardial infarction (MI) [OR = 4.96, P < .001], dementia [OR = 4.62, P < .001], and functionally dependent health [OR = 4.57, P < .001]. In addition, there was a relationship between the presence of several PECs and increased ICU and hospital LOS, especially cirrhosis, CRF, CHF, and PAD. Nontraumatic factors and preexisting conditions are associated with increased mortality and hospital resource consumption in trauma patients with a low ISS. They should be considered during clinical decision-making for these patients, who may otherwise masquerade as part of a low-risk population.

Establishment and validation of a predictive model for lower extremity deep vein thrombosis in patients with traumatic pelvic fractures

BackgroundPatients with traumatic pelvic fracture (TPF) are at high risk for developing deep vein thrombosis (DVT). However, there is still no unified standard on how to distinguish high-risk groups for DVT in patients with TPF and how to accurately use anticoagulants at present.ObjectivesThis observational study aimed to establish a DVT risk nomogram score (DRNS) model for TPF patients, and to explore the value of the DRNS model as a clinical guideline in the prevention of DVT with low molecular weight heparin (LMWH).MethodsIndependent risk factors of lower extremity DVT were screened through Lasso regression and logistic regression. A DRNS model was established per this.ResultsThe independent risk factors of DVT included combined femoral fractures, age ≥ 40 years old, BMI (body mass index) ≥ 24 kg/m2, ISS score, fibrinogen concentration, and the minimum concentration of ionized calcium within 48 h after admission. The optimal cutoff value for DRNS was 78.5. In the low-risk population of DVT (DRNS < 78.5), there was no statistical significance of variation about the incidence of DVT progression between the LMWH once a day (qd) group and the LMWH once every 12 h (q12h) group, with P = 0.323. In the high-risk population of DVT (DRNS ≥ 78.5), the incidence of DVT progression in the LMWH qd group was significantly higher than that in the LMWH q12h group, with P = 0.002.ConclusionsThe DRNS model based on independent risk factors of DVT could stratify the risk of DVT for TPF patients, and it was able to provide more precise DVT drug prevention plans for clinicians.

Refining the CHA2DS2VASc risk stratification scheme: Shall we drop the Sex Category criterion?

The CHA2DS2VASc score is recommended for stroke risk stratification in patients with atrial fibrillation (AF). This score assigns one extra point to female sex based on evidence from the early 2000s suggesting higher thromboembolic risk in women. This incremental risk of thromboembolism in women has decreased over time between 2007 and 2018, becoming non-significant in recent years. To assess the impact of removing the sex category (Sc) from the CHA2DS2VASc score, thus validating a non-sex CHA2DS2VASc (i.e., CHA2DS2VA) score. We analysed UK primary and secondary care data comprising 195,719 patients with AF followed between 1998-2016 (mean age: 75.9±12.3 years; 49.2% women). Among 126,428 non-anticoagulated patients, we compared the CHA2DS2VASc vs. CHA2DS2VA scores every calendar year. Throughout 413,007 patient-years, a total of 8,742 events of ischaemic stroke or systemic embolism were recorded. Sex differences in thromboembolic risk were not observed in the lower-risk population, but higher stroke rates were consistently seen in female patients in the higher-risk category (i.e., CHA2DS2VA ≥2). C-statistics for both CHA2DS2VA and CHA2DS2VASc scores were similar over the years (ranging from 0.62 to 0.71). With CHA2DS2VA no relevant differences were observed in IDI, and NRI resulted in improved reclassification (11%) in lower thromboembolic risk groups. NRI suggested misclassification in higher thromboembolic risk patients (-7%), but this did not affect their indication for anticoagulation (i.e., patients retained their high-risk status). Removing Sc from the CHA2DS2VASc score does not affect its ability to discriminate thromboembolic events in the AF population. Use of CHA2DS2VA may simplify initial decision-making for thromboprophylaxis.

Efficacy and safety of Shengjiang Xiexin decoction on irinotecan-induced diarrhea in small cell lung cancer patients: a multicenter, randomized, double-blind, placebo-controlled trial

BackgroundIrinotecan is a standard chemotherapeutic agent in small cell lung cancer (SCLC), however, as a common adverse reaction, diarrhea limits the use of irinotecan. Shengjiang Xiexin decoction (SXD) has been used in various gastrointestinal diseases in China two thousand years ago. We designed this clinical trial to supply more evidences on the use of SXD as prophylaxis for irinotecan-induced diarrhea, especially for high-risk population predicted by gene testing of uridine diphosphate glucuronosyl transferase 1A1 (UGT1A1).MethodsIn this clinical trial, 120 patients with SCLC were recruited from six hospitals in China. They received two cycles of chemotherapy, meanwhile they were randomized to receive SXD or placebo for 14 days of oral administration in each cycle of chemotherapy. The primary outcome is the incidence of diarrhea. And secondary outcomes include the the degree of diarrhea and neutropenia, the number of chemotherapy cycles with diarrhea, first occurrence time and duration of diarrhea. To evaluate the effect of SXD on the intestine, a rat model with delayed-onset diarrhea induced by irinotecan was established, and the expression of inflammatory factors including IL-1β, IL-6 and TNF-α, anti-inflammatory factors including IL-10, TGF- β in jejunal tissue was detected by ELISA.Results101 patients (53 in SXD group, 48 in placebo group) completed the trial. The incidence of diarrhea in SXD group and placebo group were 26.42% (14/53) and 52.08% (25/48), respectively (P < 0.05), and the degree of diarrhea also had significant differences (P < 0.05). In UGT1A1 high-risk population, the incidence of diarrhea in two groups were 9.09% and 66.67% (P < 0.05), but there was no significant differences in UGT1A1 low-risk population. The incidence of neutropenia with degree 1–3 between two groups was 20.75% vs 20.83%, 13.21% vs 18.57%, 9.43% vs 20.83% (P < 0.05). No severe adverse events were reported in any group. And animal studies had shown SXD reduced content of IL-1β, IL-6, TNF-α, increased content of IL-10, TGF-β in jejunum tissue.ConclusionsSXD had a prophylactic effect in the diarrhea induced by irinotecan, especially for UGT1A1 high-risk population, and this effect from SXD appeared to be maintained the completion of chemotherapy schedule. The mechanism of action of SXD was related to the regulation of inflammatory factors.Trial registration Chinese Clinical Trial Register: ChiCTR1800018490. Registered on 20 September 2018. https://www.chictr.org.cn/showproj.html?proj=25250. The preliminary protocol of this clinical study has been published in the journal “Trials” in the form of protocol before this paper (Deng et al. in Trials 21:370, 2020).

Nomograms combining clinical factors and apparent diffusion coefficient to predict downstaging and progression-free survival after concurrent chemoradiotherapy in patients with cervical cancer.

Concurrent chemoradiotherapy (CCRT) is used as the primary treatment modality for currently limited cervical cancer and lacks non-invasive quantitative parameters to assess clinical outcomes of treatment for cervical cancer treatment. To develop nomograms based on clinical prognostic factors and apparent diffusion coefficient (ADC) in predicting downstaging and progression-free survival (PFS) after CCRT for cervical cancer. X-tile was used to calculate the optimal threshold for ΔADCmean(%) for prognostic stratification. Kaplan-Meier curves were used to calculate the difference in PFS between high- and low-risk groups. Univariate and multivariate Cox proportional risk regression models were used to identify clinical and radiological risk factors for prognosis and construct a prognostic nomogram model. ΔADCmean(%) was significantly correlated with tumor downstaging; the area under the receiver operating characteristic curve (AUC) was 0.868. X-tile showed that the optimal threshold for ΔADCmean(%) to diagnose prognosis was 40.8. Kaplan-Meier curves showed that the low-risk population in the training group had significantly longer PFS within 3 years (P < 0.001). Multivariate Cox regression showed that ΔADC (%) is independent risk factor for PFS. The C-index of ΔADC(%) predicting 3-year PFS in the training set is 0.761 and the C-index of the nomogram model is 0.862. ΔADCmean(%) is a non-invasive biomarker for predicting tumor downstaging in cervical cancer after CCRT. The nomograms based on ΔADCmean(%) predict PFS of patients with cervical cancer with moderate accuracy.

Deciphering the Intricate Relationship Between Macrophages, Pigmentation, and Prognosis in Uveal Melanoma

High pigmentation and the abundance of M2 macrophages have been identified as negative predictors in uveal melanoma (UM). Risk factors associated with UM that are prevalent in high-risk White populations are still present, although less common, in relatively low-risk Asian populations. Research indicates that proangiogenic M2 macrophages and monosomy 3 play significant roles in UM progression. Our aim was to investigate the impact of tumor-associated macrophages in UM and examine their correlation with monosomy 3 and pigmentation. Transmission electron microscopy was used to analyze the morphology of macrophages in UM. Forty UM samples underwent fluorescent in situ hybridization for monosomy 3 identification. Immunohistochemistry was done to assess M2/M1 macrophages on 82 UM tissue samples. IL-10 and IL-12 expressions were quantified in UM serum samples by enzyme-linked immunosorbent assay. The expression of all markers was correlated with pigmentation markers (tyrosinase-related protein 1, tyrosinase-related protein 2, silver protein, and microphthalmia-associated transcription factor). Prognostic outcomes were determined using the Cox proportional hazard model and log-rank tests. Increased expression of M2/M1 macrophages was observed in 31 UM cases, which correlated with the high expression of pigmentation markers. IL-10 concentration was high in UM cases. Monosomy 3 was evident in 50% of UM cases and significantly associated with increased immunoexpression of M2/M1 macrophages and pigmentation markers. Reduced metastasis-free survival was observed in patients with UM with high M2/M1 macrophage expression (P = .001). High pigmentation and increased M2 macrophage density could impact the tumor microenvironment in UM. This could contribute to ineffective antitumor immune responses in patients with UM. Our findings suggest avenues for developing novel therapeutic approaches to counteract these immunosuppressive effects in UM.

How do we safely preserve ovaries in patients with cervical adenocarcinoma: risk factors and predictive models.

To study and predict the risk of ovarian metastasis (OM) in patients with cervical adenocarcinoma (ADC). Patients with ADC who received surgical treatment from January 2015 to December 2022 in the Obstetrics and Gynecology Hospital of Fudan University were included in the study. Patients were further divided into OP (ovaries were preserved in surgery) and BSO (bilateral salpingo-oophorectomy) groups. For the patients who accepted BSO, 60% of the patients were randomly grouped into a training cohort, and predictive prognostic models were constructed with 10-fold cross-validation through random forest, LASSO, stepwise, and optimum subset analysis. The model with the highest area under receiver operator curve (AUC) was screened out in the testing cohort. The nomogram and its calibration curve presented the possibility of OM in future patients. The prognoses between the different populations were compared using Kaplan-Meier analysis. All data processing was carried out in R 4.2.0 software. A total of 934 patients were enrolled in our cohort; 266 patients had their ovaries preserved and 668 patients had BSO according to the previous criteria reported The clinical safety with these criteria was secured, while the 5-year overall survival had no significant difference between the BSO and OP groups (p = 0.069), which suggested that the current criteria could be extended and are more precise. Four predictive models for ovarian metastasis by machine learning were constructed in our study, and the random forest model that obtained the highest AUC in both training and testing sets (0.971 for training and 0.962 for testing set) was taken as the best model. The optimal cut-off point of the ROC curve (specificity 99.5% and 90% sensitivity) was utilized to stratify the patients into high- and low-risk OM. Further comparing the survival curves of the high and low-OM risk groups, it was found that both DFS and OS were significantly prolonged in the low-risk group (p < 0.01). On the basis of this random forest model, a nomogram was used to calculate the OM risk, and the results were validated with calibration. The predictive model was further applied to the whole cohort (934 patients), and we identified the OM low-risk population (n = 822) and the patients with high risk who should be recommended for BSO (n = 112). No significant difference was found in the 5-year survival between the low-risk group with our model and the patients who already had ovaries preserved according to the previous criteria (n = 266). The predictive model constructed in our study could identify the low-risk population of OM in patients with ADC, which remarkably extended the number with the previous criteria, for whom we could potentially preserve ovaries to help improve their life quality.

Left ventricular pressure-strain loops for the assessment of myocardial work in a low-risk community-based cohort: associations with long-term prognosis

Abstract Background Non-invasive left ventricular (LV) pressure-strain loop analysis is a novel technique for the evaluation of global myocardial work (GMW) that provides additional insights on LV contractility and energetics beyond traditional metrics, such as ejection fraction (EF) and global longitudinal strain (GLS). Despite its established value in numerous cardiac diseases, there remains limited data on its predictive power in a low-risk population. Purpose Our objective was to determine the long-term prognostic value of GMW in a population-based screening sample comprising low-risk adult individuals. Methods We retrospectively identified 1562 volunteers from a population-based screening program (mean age 54±15 years, 59% female), with a median follow-up time of 11 years. All subjects underwent 2D echocardiography to measure LV EF, GLS, peak atrial longitudinal strain (PALS), GMW index (GMWI), global wasted work (GWW), and GMW efficiency (GMWE). The primary endpoint was all-cause mortality. Results 191 subjects (12,2%) met the primary endpoint. Subjects who experienced adverse outcomes exhibited significantly lower LV EF (dead vs. alive; 49.7±8.3 vs. 52.7 ±6.4 %, p&amp;lt;0.001), GLS (-18.7±4.1 vs. -20.4±3.6 %, p&amp;lt;0.001), PALS (33.6±15.7 vs. 44.2±15.2 %, p&amp;lt;0.001), and GMWI (2181.7±591.3 vs. 2286.8±482.5 mmHg%, p=0.008). Furthermore, subjects with adverse outcomes had significantly higher GWW (132.6±249.4 vs 95.1±113.4 mmHg%, p&amp;lt;0.001) and, consequently, lower GMWE (0.95±0.05 vs. 0.96±0.03, p&amp;lt;0.001). Univariate Cox regression analysis revealed GMWI to be a significant predictor of mortality (hazard ratio for 100 units 0.957 [95% CI: 0.929-0.986], p=0.004), alongside GMWE (hazard ratio for 1 percent 0.940 [95% CI: 0.912-0.968], p&amp;lt;0.001), and GWW (hazard ratio for 100 units 1.124 [95% CI: 1.063-1.188], p&amp;lt;0.001). By multivariable Cox regression encompassing age, sex, GMWI, LVEF, GLS, PALS, and systolic blood pressure, GMWI remained an independent predictor of all-cause mortality (hazard ratio 0.932 [95% CI: 0.874-0.995], p=0.035), while GLS was not an independent predictor. Moreover, integrating the Atherosclerosis Risk in Communities (ARIC)-HF risk factors (age, sex, race, coronary artery disease, antihypertensive medication, blood pressure, diabetes mellitus, body mass index, heart rate, and smoking status), we constructed a multivariate model with GMWI. GMWI was still an independent predictor of mortality (hazard ratio for 100 units 0.941 [95% CI: 0.903-0.980], p=0.004). Using the GMWI cut-off value of 1576 mm Hg% (based on a large-scale healthy population study), the population was divided into 2 groups. Using Kaplan-Meier curves (Figure), the outcomes of the groups differed significantly (log-rank p&amp;lt;0.001). Conclusions GMW provides added value in clinical outcome prediction, even in low-risk individuals. Myocardial work analysis is a promising approach for a comprehensive evaluation of cardiac function and for cardiovascular risk stratification.

Coronary bypass surgery guided by multislice computed tomography angiography in a low surgical risk population

Abstract Background In patients with three-vessel disease and/or left main disease, selecting revascularization strategies based on coronary computed tomography angiography (CCTA) has a high level of virtual agreement with treatment decisions based on invasive coronary angiography(ICA).(1) Purpose The FASTTRACK CABG trial aims to assess the feasibility and safety of using CCTA and FFRCT as guidance for planning and performing CABG in patients with 3VD and/or LMCAD. Methods In this multicentre study, coronary artery bypass grafts (CABG) were planned and performed based on CCTA without knowledge of ICA. CABG strategy was recommended by a central Core laboratory assessing the anatomy and functionality of the coronary circulation. The primary feasibility endpoint was the percentage of operations performed without access to the ICA. The primary safety endpoint was graft patency on 30-day follow-up CCTA. Secondary endpoints included topographical adequacy of grafting, major adverse cardiac and cerebrovascular events (MACCE), and major bleeding events at 30 days. The study was considered positive if the lower boundary of confidence intervals(CI) for feasibility ≥75%.(2) Results The study enrolled 114 patients with a mean (standard deviation) anatomical SYNTAX Score and Society of Thoracic Surgery score of 43.6 (15.3) and 0.81 (0.63), respectively. Three patients did not undergo CABG due to the patient’s preference for percutaneous treatment (n=1) or lack of graft material. Unblinding ICA was required in one case, yielding a feasibility of 99.1% (95%CI: 95.2%-100%). The concordance and agreement in revascularization planning between the ICA- and CCTA-Heart Team was 82.9% with a moderate kappa of 0.58 (95%CI:0.50-0.66). The concordance and agreement in revascularization planning between the CCTA-Heart Team and actual treatment was 83.7% with a substantial kappa of 0.61 (95%CI:0.53-0.68). The 30-day follow-up CCTA was performed in 102 (91.9%) of the 111 operated patients, which showed an anastomosis patency rate of 92.6%. At 30 days, the incidence of MACCE was 7.2% whereas major bleeding was 2.7%. Conclusions CABG guided by CCTA is feasible and has an acceptable safety profile in a selected population of complex coronary artery disease.

Usefulness of left ventricular mechanical dyssynchrony for predicting atrial fibrillation and adverse outcomes following first atrial fibrillation event

Abstract Background Left ventricular mechanical dyssynchrony (LVMD) has shown to predict many cardiovascular outcomes including ventricular arrhythmias. Our hypothesis is that LVMD can reveal early atrial dysfunction. Purpose The aim of this study was to investigate whether LVMD can be used to predict atrial fibrillation (AF) and adverse outcomes following first AF event in individuals from the general population. Methods A total of 3785 individuals (mean age 55±17 years, 57% women) from the general population free of AF, heart failure (HF) and prior stroke had an echocardiographic examination performed including two-dimensional speckle tracking echocardiography. LVMD was calculated as the standard deviation of the regional time-to-peak strain from the three apical views. The primary endpoint was AF, and the secondary endpoint was complicated AF as assessed by the occurrence of either stroke or HF after the diagnosis of AF. Results During a median follow-up of 5 years (interquartile range, 4.4-6.2 years), 142 (4%) individuals were diagnosed with AF, and of these 22 (15%) individuals developed HF or stroke. LVMD was a univariable predictor of AF (per 10ms increase: HR 1.03; 95% CI (1.02-1.05), p&amp;lt;0.001, Figure). The association remained significant even after multivariable adjustment for age, sex, body mass index, diabetes, hypertension, heart rate, previous ischaemic heart disease, systolic blood pressure, diastolic blood pressure, smoking, left ventricular ejection fraction, global longitudinal strain, left atrial volume index (LAVI), and E/e’ (per 10ms increase: HR 1.02; 95% CI (1.00-1.04), p=0.042). LVMD also predicted complicated AF, and the association remained significant even after multivariable adjustment (per 10ms increase: HR 1.05; 95% CI (1.01-1.09), p=0.026). Furthermore, LVMD provided incremental prognostic information over the LAVI with regard to predicting AF (Harrell’s C-statistics 0.66 vs. 0.70, p=0.012). Conclusion In a low-risk general population, LVMD provides prognostic information on the risk of AF. Additionally, LVMD can identify individuals with complicated AF defined as occurrence of either stroke or HF following the diagnosis of incident AF. Furthermore, LVMD provides incremental prognostic information over the LAVI in predicting AF.

Improving prognostic accuracy in ischemic cardiomyopathy: the CMR-LGE score

Abstract Background There is a need for accurate prognostic stratification tools in patients with ischemic cardiomyopathy (ICM). Several studies have shown the considerable impact of cardiac magnetic resonance (CMR) imaging findings notably late gadolinium enhancement (LGE) but an easy interpretable score to guide clinical practice is lacking. Purpose To determine the CMR parameters most predictive of mortality in a cohort of ICM patients with left ventricular ejection fraction (LVEF) less than 50%, and then to develop a readily interpretable score based on these parameters. Methods Between 2008 and 2022, all consecutive patients with a history of ICM with LVEF&amp;lt;50% and presence of ischemic LGE on viability CMR examination, were recruited by two independent centers. The primary outcome was all-cause death using French National Registry of Death. The first center (N=2,900) was designated as the derivation cohort for variable selection and score development, and the second center (N=691) was used as the validation cohort to evaluate the performance of the final score. Thirty-two variables (17 clinical and 15 CMR) were initially assessed. Automatic feature selection was performed using a machine-learning approach with a Random Survival Forest (RSF) algorithm. Using the selected variables, our proposed score, the CMR-LGE score, was derived from coefficients of the Cox regression. Performance evaluation on the validation cohort was conducted using Harrel’s C index compared with traditional prognostic factors associated with poor outcomes in ICM. Categories for the prognostic score were identified using a survival conditional inference tree analysis on the derivation cohort, aiming to maximize the log-rank score. Results Among the 3,591 patients included (mean age 65±12 years; 75% male; mean LVEF 44±6%), 549 (15.3%) died over a median follow-up of 9 (interquartile range: 7–12) years. Feature selection with RSF highlighted that the most important variables to predict death were LGE variables: the extent, the location (septal and anterior) and the transmurality of ischemic LGE as well as the extent of additional midwall LGE (Figure 1). Following these findings, we developed the CMR-LGE score by rounding the coefficient of a Cox regression (Figure 2A). Harrel’s C index of CMR-LGE score outperformed traditional prognostic factors, including LVEF (0.88 vs 0.69). Finally, based on our CMR-LGE score, we identified a low-risk population (CMR-LGE score below 6) and a high-risk population (CMR-LGE above 8), validated using survival curves in the validation cohort (Figure 2B). Conclusion Using RSF, we identified that the 5 most important CMR variables to predict mortality in ICM were all LGE features. Our CMR-LGE score showed excellent performance to stratify patient risk compared to traditional prognostic factors including LVEF.Variable selectionModel building and evaluation

Projecting the benefit of vericiguat in PARADIGM-HF and DAPA-HF populations: Insights from the VICTORIA trial.

The VICTORIA trial demonstrated a significant reduction in the primary composite outcome of heart failure (HF) hospitalization or cardiovascular death with vericiguat relative to placebo in high-risk HF. This study aimed to contextualize treatment effects of vericiguat in populations with varying risk profiles simulated from the PARADIGM-HF and DAPA-HF trials. Subgroups of VICTORIA participants (n=5050) were generated to simulate PARADIGM-HF and DAPA-HF trial populations. The PARADIGM-HF-eligible population excluded participants not meeting left ventricular ejection fraction (LVEF), estimated glomerular filtration rate (eGFR), and minimal dose criteria and those with high predicted probability of run-in failure. The DAPA-HF-eligible population excluded those not meeting LVEF and eGFR criteria or with recent (<30days) HF hospitalization. The time-to-first-event analysis was performed using an unadjusted Cox proportional hazards model. A total of 1982 (39.2%) and 2543 (50.4%) VICTORIA participants were respectively deemed eligible for PARADIGM-HF and DAPA-HF. Vericiguat was associated with numerically larger reductions in the primary outcome of HF hospitalization or cardiovascular death in populations simulated from PARADIGM-HF [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.72-0.99] and DAPA-HF (HR 0.82, 95% CI 0.71-0.94) compared with the overall VICTORIA trial (HR 0.90). Significant reduction in HF hospitalization with vericiguat was also observed in the DAPA-HF-eligible population (HR 0.83, 95%CI 0.73-0.95) and with a nominal reduction in the PARADIGM-HF-eligible population (HR 0.86, 95% CI 0.74-1.01). A trend towards enhanced efficacy of vericiguat in populations simulated from PARADIGM-HF and DAPA-HF was observed. These findings support further exploration of vericiguat in lower-risk HF populations as is being investigated in the ongoing VICTOR (a study of vericiguat in participants with chronic heart failure with reduced ejection fraction) trial.

Comparative Outcomes of Transcatheter Versus Surgical Aortic Valve Replacement in Elderly Patients With Severe Symptomatic Aortic Stenosis: A Systematic Review.

Aortic stenosis is the most common valvular heart disease globally; while transcatheter aortic valve replacement (TAVR) has proven to be a competitive alternative to surgical aortic valve replacement (SAVR) and revolutionized treatment, its safety and efficacy has yet to be comprehensively assessed against SAVR for certain subsets of aortic stenosis patients; therefore, this study aims to systematically analyze all the available clinical evidence from randomized clinical trials on TAVR versus SAVR among intermediate and low-risk patients with severe symptomatic aortic stenosis. We performed a systematic review of the randomized controlled trials (RCT), studies comparing TAVR and SAVR in low- and intermediate-risk patients were identified by a comprehensive search of the major databases. Mortality, stroke, length of stay, and other perioperative outcomes were assessed. A comprehensive screening of 14,384 records identified 9 studies, encompassing 8884 patients with a mean age of 77.76 years and 49.47% male. TAVR demonstrated a significantly lower all-cause mortality at both 30 days and 1 year compared to SAVR, with comparable outcomes at 2 years, underscoring its potential for enhanced survival. Stroke incidence was markedly lower with TAVR at both 30 days and 1 year, highlighting its favorable neurological safety profile. Additionally, TAVR showed a reduced rate of myocardial infarction within the initial 30 days post-procedure. Prosthetic valve endocarditis rates remained low and comparable between the two approaches at both 30 days and 1 year. Notably, TAVR was associated with a significantly shorter hospital stay, suggesting a faster recovery trajectory and improved patient throughput. These findings collectively emphasize the superior efficacy and safety profile of TAVR over SAVR. TAVR may serve as a viable therapeutic option for intermediate and low-risk patients with severe symptomatic aortic stenosis. Future research should focus on long-term outcomes and TAVR device durability, especially in younger, lower-risk populations.

Bovine aortic arch: a potential indicator that may not serve in prenatal diagnosis - a study based on fetal anatomy, genetics, and postnatal clinical outcomes

ObjectiveTo investigate the structural abnormalities, genetic results, and postnatal clinical outcomes of fetuses with bovine aortic arch (Bovine Aortic Arch, BAA) to provide a basis for prenatal counseling and management.MethodsA retrospective analysis was conducted on 216 fetuses diagnosed with bovine aortic arch through prenatal ultrasound screening at the First Affiliated Hospital of Anhui Medical University and the No.901 Hospital of the Joint Service of the People’s Liberation Army from January 2019 to February 2023. Their family history of genetic diseases, prenatal screening results, and postnatal follow-up data were collected. The fetuses were divided into an isolated BAA group (n = 192) and a non-isolated BAA group (n = 24). Chromosomal karyotyping and copy number variation (CNV) testing were conducted, and statistical analysis was performed using SPSS 22.0 software.ResultsOf the 216 fetuses with BAA, 192 were isolated BAA (88.89%), and 24 were non-isolated BAA (11.11%). Among the isolated BAA fetuses, only 1 case (0.52%) had chromosomal karyotype and pathogenic CNV abnormalities. Among the non-isolated BAA fetuses, 4 cases (16.67%) had chromosomal or CNV abnormalities, but the overall risk was low. The postnatal outcomes of isolated BAA fetuses were good (99.48%), while 79.17% of non-isolated BAA fetuses had good postnatal outcomes.ConclusionMost BAA fetuses are isolated, with a very low incidence of chromosomal abnormalities and pathogenic CNVs, and have good postnatal outcomes. The clinical value of isolated BAA is limited, and invasive prenatal diagnosis is not recommended for low-risk populations. Prenatal screening should focus on the risk of concurrent severe structural anomalies and chromosomal abnormalities.

Artificial intelligence-enhanced detection of subclinical coronary artery disease in athletes: diagnostic performance and limitations.

This study evaluates the diagnostic performance of artificial intelligence (AI)-based coronary computed tomography angiography (CCTA) for detecting coronary artery disease (CAD) and assessing fractional flow reserve (FFR) in asymptomatic male marathon runners. We prospectively recruited 100 asymptomatic male marathon runners over the age of 45 for CAD screening. CCTA was analyzed using AI models (CorEx and Spimed-AI) on a local server. The models focused on detecting significant CAD (≥ 50% diameter stenosis, CAD-RADS 3, 4, or 5) and distinguishing hemodynamically significant stenosis (FFR ≤ 0.8) from non-significant stenosis (FFR > 0.8). Statistical analysis included sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy. The AI model demonstrated high sensitivity, with 91.2% for any CAD and 100% for significant CAD, and high NPV, with 92.7% for any CAD and 100% for significant CAD. The diagnostic accuracy was 73.4% for any CAD and 90.4% for significant CAD. However, the PPV was lower, particularly for significant CAD (25.0%), indicating a higher incidence of false positives. AI-enhanced CCTA is a valuable non-invasive tool for detecting CAD in asymptomatic, low-risk populations. The AI model exhibited high sensitivity and NPV, particularly for identifying significant stenosis, reinforcing its potential role in screening. However, limitations such as a lower PPV and overestimation of disease indicate that further refinement of AI algorithms is needed to improve specificity. Despite these challenges, AI-based CCTA offers significant promise when integrated with clinical expertise, enhancing diagnostic accuracy and guiding patient management in low-risk groups.

Prediction of surgical benefit in gastric cancer patients with peritoneal metastasis treated with hyperthermic intraperitoneal chemotherapy.

The objective is to evaluate whether gastric cancer patients with peritoneal metastasis can benefit from surgery through a comprehensive analysis of different clinical factors and perioperative treatment methods. A total of 135 gastric cancer patients with peritoneal metastasis were treated with Hyperthermic intraperitoneal chemotherapy (HIPEC). Patients were divided into either training group (without surgery, n = 90) or test group (with surgery, n = 45). A nomogram was constructed based on significant prognostic factors. The patients were divided into high- and low-risk groups using a nomogram. Overall survival were then compared according to whether surgery was performed in both groups. Alpha-fetoprotein (AFP), complications, conversion chemotherapy, and postoperative chemotherapy were significantly associated with overall survival (p < 0.05). A nomogram was constructed using the above four factors and validated using the test set. The area under the curve (AUC) of the model was 0.752 (95% CI 0.525-978). In the group that did not undergo surgery, the median survival times for the high-risk and low-risk groups were 7 and 11months, respectively. In the surgery group, the median survival times for the high-risk and low-risk groups were 11 and 19months, respectively. The difference was statistically significant (p < 0.0001). The four-factor nomogram can accurately predict high-risk and low-risk populations. Our findings suggest that cytoreductive surgery combined with HIPEC can improve the survival time of patients in both groups.

Emotional competence self-help mobile phone app versus cognitive behavioural self-help app versus self-monitoring app to promote mental wellbeing in healthy young adults (ECoWeB PROMOTE): an international, multicentre, parallel, open-label, randomised controlled trial.

Based on evidence that mental health is more than an absence of mental disorders, there have been calls to find ways to promote flourishing at a population level, especially in young people, which requires effective and scalable interventions. Despite their potential for scalability, few mental wellbeing apps have been rigorously tested in high-powered trials, derived from models of healthy emotional functioning, or tailored to individual profiles. We aimed to test a personalised emotional competence self-help app versus a cognitive behavioural therapy (CBT) self-help app versus a self-monitoring app to promote mental wellbeing in healthy young people. This international, multicentre, parallel, open-label, randomised controlled trial within a cohort multiple randomised trial (including a parallel trial of depression prevention) was done at four university trial sites in four countries (the UK, Germany, Spain, and Belgium). Participants were recruited from schools and universities and via social media from the four respective countries. Eligible participants were aged 16-22 years with well adjusted emotional competence profiles and no current or past diagnosis of major depression. Participants were randomised (1:1:1) to usual practice plus either the emotional competence app, the CBT app or the self-monitoring app, by an independent computerised system, minimised by country, age, and self-reported gender, and followed up for 12 months post-randomisation. The primary outcome was mental wellbeing (indexed by the Warwick-Edinburgh Mental Well Being Scale [WEMWBS]) at 3-month follow-up, analysed in participants who completed the 3-month follow-up assessment. Outcome assessors were masked to group allocation. The study is registered with ClinicalTrials.gov, NCT04148508, and is closed. Between Oct 15, 2020, and Aug 3, 2021, 2532 participants were enrolled, and 847 were randomly assigned to the emotional competence app, 841 to the CBT app, and 844 to the self-monitoring app. Mean age was 19·2 years (SD 1·8). Of 2532 participants self-reporting gender, 1896 (74·9%) were female, 613 (24·2%) were male, 16 (0·6%) were neither, and seven (0·3%) were both. 425 participants in the emotional competence app group, 443 in the CT app group, and 447 in the self-monitoring app group completed the follow-up assessment at 3 months. There was no difference in mental wellbeing between the groups at 3 months (global p=0·47). The emotional competence app did not differ from the CBT app (mean difference in WEMWBS -0·21 [95% CI -1·08 to 0·66]) or the self-monitoring app (0·32 [-0·54 to 1·19]) and the CBT app did not differ from the self-monitoring app (0·53 [-0·33 to 1·39]). 14 of 1315 participants were admitted to or treated in hospital (or both) for mental health-related reasons, which were considered unrelated to the interventions (five participants in the emotional competence app group, eight in the CBT app group, and one in the self-monitoring app group). No deaths occurred. The emotional competence app and the CBT app provided limited benefit in promoting mental wellbeing in healthy young people. This finding might reflect the low intensity of these interventions and the difficulty improving mental wellbeing via universal digital interventions implemented in low-risk populations. European Commission.

Machine learning model to predict early recurrence in patients with perihilar cholangiocarcinoma planned treatment with curative resection: a multicenter study

BackgroundEarly recurrence is the leading cause of death for patients with perihilar cholangiocarcinoma (pCCA) after surgery. Identifying high-risk patients preoperatively is important. This study aimed to construct a preoperative prediction model for the early recurrence of patients with pCCA to facilitate planned treatment with curative resection. MethodsThis study ultimately enrolled 400 patients with pCCA after curative resection in 5 hospitals between 2013 and 2019. They were randomly divided into training (n = 300) and testing groups (n = 100) at a ratio of 3:1. Associated variables were identified via least absolute shrinkage and selection operator (LASSO) regression. Four machine learning models were constructed: support vector machine, random forest (RF), logistic regression, and K-nearest neighbors. The predictive ability of the models was evaluated via receiving operating characteristic (ROC) curves, precision-recall curve (PRC) curves, and decision curve analysis. Kaplan-Meier (K-M) survival curves were drawn for the high-/low-risk population. ResultsFive factors: carbohydrate antigen 19–9, tumor size, total bilirubin, hepatic artery invasion, and portal vein invasion, were selected by LASSO regression. In both the training and testing groups, the ROC curve (area under the curve: 0.983 vs 0.952) and the PRC (0.981 vs 0.939) showed that RF was the best. The cutoff value for distinguishing high- and low-risk patients was 0.51. K-M survival curves revealed that in both groups, there was a significant difference in RFS between high- and low-risk patients (P < .001). ConclusionThis study used preoperative variables from a large, multicenter database to construct a machine learning model that could effectively predict the early recurrence of pCCA in patients to facilitate planned treatment with curative resection and help clinicians make better treatment decisions.

Breaking Down SCAD: A Deep Dive into Spontaneous Coronary Artery Dissection (SCAD)

Spontaneous Coronary Artery Dissection (SCAD) is a rare, non-atherosclerotic cause of acute coronary syndrome, mainly seen in females with non-traditional cardiovascular risk factors. This case report follows a 44-year-old female who experienced a sudden onset of severe chest pain, which was attributed to SCAD following a coronary angiogram. This case emphasizes the importance of recognizing such presentations within the emergency department, particularly regarding differential diagnosis of chest pain following emotional or physical stressors. It also highlights the need for a multidisciplinary approach in terms of proper management with cardiology, emergency medicine, and mental health care to reduce the risk of reoccurrence. This case report aids in underscoring SCAD’s significance as a potential cause of ST Elevation Myocardial Infarction in what is noted as a low-risk population and the critical role of awareness and education in terms of its diagnosis and management.

Oligohydramnios at term in the high-risk population- how severe is severe?

The term oligohydramnios is linked to pregnancy complications. We previously presented the outcome of the low-risk population (no pregnancy complications) with term oligohydramnios. This study aims to address the high-risk group (Any maternal complication during pregnancy, such as gestational diabetes, pre-gestational diabetes, chronic hypertension, preeclampsia, anemia, asthma, obesity, and multi parity.). This retrospective cohort study of 1,114 singleton term (≥37), oligohydramnios (AFI <50 mm) pregnancies from Shamir Medical Center between 2017 and 2021. Compering the low-risk to high-risk groups with subdivision by severity of oligohydramnios. A total of 211 subjects (19 %) were high-risk cases and 903 (81 %) low-risk cases. Comparing these two groups, subjects of the high-risk group were older (31.34±5.85 vs. 29.51 vs. 4.96), had earlier gestational age at delivery 39.53±1.18 vs. 40, had higher mean AFI (35±12.7 vs. 33±14.5), were subject to more labor inductions (81 vs. 69.7 %), and CS rate (19.9 vs. 12.4 %). Logistic regression revealed a need for more cesarean sections in the high-risk group. Additionally, more labor inductions and a higher risk of negative fetal outcomes. This study highlights the importance of considering pregnancy risk factors when we are approaching oligohydramnios in high-risk pregnancies.