Low Risk Score Research Articles

Retrospective study on the correlation between MASCC score and the evolution of febrile neutropenia for patients with solid cancer.

e13570 Retrospective study on the correlation between MASCC score and the evolution of febrile neutropenia for patients with solid cancer. Background: The Multinational Association for Supportive Care in Cancer (MASCC) score is used to risk-stratify outpatients with febrile neutropenia. Currently, data on the use of the MASCC score are based on studies with a small number of patients. Our primary aim was to determine whether a MASCC score ≥ 21 identifies patients with solid tumors who would evolve without complications. Methods: We conducted a retrospective cohort study of patients admitted with febrile neutropenia and solid cancer at Sherbrooke University Hospital from 2011 to 2022. We collected patients' demographics, type of cancer, current chemotherapy regimen, whether patients were candidates for outpatient treatment, MASCC score, duration of IV antibiotic therapy, complications (intensive care unit admission, hypotension, hypoxemia, acute kidney failure, bacteriemia (persistent or developing after 48h of IV antibiotics) and escalation in antimicrobial regimen after hospital admission), and inpatient deaths. We used chi-square analysis and multivariate analysis to determine factors other than MASCC that predict complications. Results: A total of 290 febrile neutropenia patients with solid tumors were identified. 93 patients had a MASCC score <21 and 196 were identified as low risk (MASCC score ≥ 21). The preliminary results showed that the MASCC score had a specificity of 58,3% [95% CI 48,4%-67,8%], a sensibility of 83,0% [95% CI 76,7%-88,1%], a positive predictive value of 77,0% [95% CI 72,7%-80,9%] and a negative predictive value of 67,0 [95% CI 58,7%-74,4%] to identify complications. A low risk MASCC score showed statistically significative reduction in duration of neutropenia, IV antibiotics, fever and length of hospitalisation. Conclusions: The MASCC score did not demonstrate high enough accuracy to precisely identify patients which would have evolved without complications. However, a low-risk score identified by using the MASCC score was found to have strong association with reduction of duration of hospitalisation burden. Furter data will be collected to increase the strength of the study.

Comparative Analysis of Methods of Evaluating Human Fatigue

AbstractThe present study used four different methods to estimate fatigue. Forty-seven volunteers (45 men and 2 women), 41.3 ± 7.5 years old, truck operators for 11.5 ± 6.0 years, were included. All participants accepted the invitation to be included in the study. Actigraphy and core temperature were evaluated. The 5-minute psychomotor vigilance test, the Karolinksa Sleepiness Scale (KSS), and the postural assessment using the Light Sonometer™ (Belo Horizonte, Minas Gerais, Brazil) were performed. Fatigue prediction was performed using the Fatigue Avoidance Scheduling Tool (FAST) program. In response to the Pittsburgh Sleep Quality Index (PSQI), 51.06% had good sleep quality and 48.94% had poor sleep quality with an average efficiency of 81.6%. In response to the actigraphy, workers slept an average of 7.2 hours a day with 93.5% efficiency. The workers' core body temperature (CBT) cosinor analysis showed a preserved circadian curve. Core body temperature showed differences between the 6 hours worked in each shift. Similarly, the light sound level meter showed lower risk scores for fatigue in day shifts. Only the variable of the fastest 10% of the Psychomotor Vigilance Test (PVT) showed worse results, while no significant differences were observed by the KSS. The risk analysis by FAST showed a strong influence of the circadian factor. In conclusion, each method has positive and negative points, and it is up to the evaluator/manager to identify the method that best suits the purpose of the evaluation, as well as the local culture and conditions. We recommend using different methods of risk assessment and management in combination with fatigue prediction by Sonometer as well as carrying out assessments, which enable researchers to estimate performance and fatigue throughout the working day, since these may change over the duration of the working day.

Understanding Health Beliefs and Health Behaviors in Older Adults at Risk for Alzheimer's Disease.

There are significant public health benefits to delaying the onset of Alzheimer's disease (AD) in individuals at risk. However, adherence to brain healthy behaviors is low. The Health Belief Model proposes that specific beliefs are mediators of behavior change. To characterize health belief measures from the Science of Behavior Change Research Network (SBCRN) in an older adult population and associations between health beliefs, AD risk, and current health behaviors. A total of 172 individuals from the Rhode Island AD Prevention Registry participated. SBCRN health belief measures included assessments of future time perspective, self-efficacy, deferment of gratification, and consideration of future consequences. Outcome measures included individual AD risk index score, dementia risk awareness, and lifestyle behaviors including physical, cognitive, and social activity. Participants who were older had higher scores for AD risk, lower future time perspective, and lower generalized self-efficacy (all at p < 0.001). Higher generalized self-efficacy was related to increased physical activity (p < 0.010). Higher future time perspective (p < 0.001) and generalized self-efficacy (p = 0.48) were associated with lower AD risk score. Subjective cognitive decline (SCD) was associated with lower self-efficacy, ability to delay gratification, and a less expansive future time perspective. Greater self-efficacy and perceived future time remaining were associated with lower AD risk and greater engagement in physical activity. SCD was associated with health beliefs that may negatively affect engagement in positive brain health behaviors. Assessment of and psychoeducation about these intrapersonal health belief constructs may be important targets for behavioral interventions to reduce AD risk.

Comparison of the efficacy of auricular vagus nerve stimulation and conventional low back rehabilitation in patients with chronic low back pain

BackgroundIn recent years, human and animal studies have provided increasing evidence that vagus nerve stimulation (VNS) can produce analgesic effects as well as alleviating resistant epilepsy and depression. Our study was designed to compare the efficacy of transcutaneous auricular vagus nerve stimulation with conventional low back rehabilitation in patients with chronic low back pain (CLBP). MethodsSixty patients with LBP were randomly divided into two groups. Group 1 received conventional rehabilitation and home exercise, and Group 2 received transcutaneous auricular VNS and home exercise. Both groups received treatment five days a week for three weeks. Trunk mobility (Modified Schober test, fingertip-to-floor test), muscle strength (CSMI-Cybex Humac-Norm isokinetic dynamometer and Lafayette manual muscle strength measuring device), trunk endurance, balance tests, Visual Analog Scale, Beck Depression Scale, Pittsburgh Sleep Quality Index, Oswestry Disability Index were evaluated. ResultsAt the end of three weeks, within-group assessment results showed positive effects on mobility, functional status, depression and sleep in all groups (p < 0.05). Pain level, endurance time and flexion trunk muscle strength results showed more improvement in Group 2 (p < 0.05). Some parameters of isokinetic lower extremity quadriceps muscle strength and fall risk scores showed a significant improvement in Group 1 (p < 0.05). DiscussionVNS has been observed to be more effective on pain, trunk muscle strength and endurance duration and sleep status. Auricular VNS may be included in the treatment of patients with CLBP in whom conventional physical therapy is inadequate or not applicable.

Evaluation of Adolescents' Awareness of Seat Belt Use and the Relationship with Risky Behaviors.

The one of the leading causes of adolescent morbidity and mortality worldwide is motor vehicle accidents (MVA). The use of seat belts significantly lowers MVA fatalities and injuries. The aim of this study is to investigate adolescent seat belt usage patterns and relation with risky behaviors. The study conducted at two medical institutions with non-immigrant and literate adolescents aged 12-18. Demographics, seat belt use, and risk-taking behavior were collected through questionnaires. 726 teenagers (422 girls and 304 boys) with an average age of 176.7 ± 23.37 months participated in the study. Parents' educational levels and front-seat belt use have been found to be correlated. Comparatively to non-users, seat belt users demonstrated lower risk scores (total, traffic, substance, and social). The use of seat belts was significantly predicted by traffic risk, according to logistic regression. The frequency of seatbelt use was higher among participants from cities with higher socioeconomic status. As a result, it was found that adolescents who exhibited more risky behaviors had a lower frequency of seat belt use and seat belt use was associated with socioeconomic level and parental education level. It is thought that population-based studies to be conducted on this subject are important.

Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study.

Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.

The N6-methyladenosine methylation landscape stratifies breast cancer into two subtypes with distinct immunological characteristics.

N6-methyladenosine (m6A) methylation modification affects the tumorigenesis and metastasis of breast cancer (BC). This study investigated the association between m6A regulator-mediated methylation modification patterns and characterization of the tumour microenvironment in BC, as well as their prognostic importance. Public gene expression data and clinical annotations were collected from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus website and the METABRIC program. We analysed the genetic expression, gene-gene interactions, gene mutations and copy number variations using R software. The data were screened for risk genes using the Cox risk regression model, and we developed an algorithm for risk score and its predictive value. Compared to adjacent normal tissue, we identified 16 differentially expressed m6A regulators in BC, including six writers and 10 readers. Under unsupervised clustering, two distinguished modification patterns were identified, cluster C1 and C2. Compared to m6A cluster C2, cluster C1 was found to be more involved in immune-related pathways, with a relatively higher immune score and stromal score (P < 0.05). Patients were divided into two groups based on their risk scores for survival analysis. The patients in the high-risk score group had significantly worse overall survival than patients in the low-risk score group, (P < 0.0001). The TCGA database validation revealed the same prognostic tendency. In summary, our study showed distinct m6A regulator modification patterns contribute to the immunological heterogeneity and diversity of BC. The development of m6A gene signatures and the m6A score aid in the prognostic prediction of patients with BC.

Diagnostic Accuracy of American College of Radiology Thyroid Imaging Reporting Data System: A Single-center Cross-sectional Study.

This study aims to evaluate the diagnostic accuracy of the American College of Radiology Thyroid Imaging Reporting Data System (ACR TI-RADS) in identifying nodules that need to undergo fine-needle aspiration biopsy (FNAB) and identify specific thyroid ultrasound characteristics of nodules associated with thyroid malignancy in Filipinos in a single tertiary center. One hundred seventy-six thyroid nodules from 130 patients who underwent FNAB from January 2018 to December 2018 were included. The sonographic features were described and scored using the ACR TI-RADS risk classification system, and the score was correlated to their final cytopathology results. The calculated malignancy rates for TI-RADS 2 to TI-RADS 5 were 0%, 3.13%, 7.14%, and 38.23%, respectively, which were within the TI-RADS risk stratification thresholds. The ACR TI-RADS had a sensitivity of 89.5% and specificity of 54%, LR + of 1.95 and LR - of 0.194, NPV of 97.7%, PPV of 19.1%, and accuracy of 58%. The ACR TI-RADS may provide an effective malignancy risk stratification for thyroid nodules and may help guide the decision for FNAB among Filipino patients. The classification system may decrease the number of unnecessary FNABs for nodules with low-risk scores.

Simplified Risk Stratification Model for Patients With Waldenström Macroglobulinemia.

Patients with Waldenström macroglobulinemia (WM) have disparate outcomes. Newer therapies have emerged since the development of International Prognostic Scoring System, and MYD88L265P mutation is now frequently assessed at diagnosis, warranting reexamination of the prognostic parameters. We reviewed records of 889 treatment-naïve patients with active WM, consecutively seen between January 01, 1996, and December 31, 2017, to identify clinical predictors of overall survival (OS) in univariate analyses. Patients with complete data for the parameters significant on the univariate analyses (n = 341) were included in a multivariable analysis to derive a prognostic model, subsequently validated in a multi-institutional cohort. In the derivation cohort (n = 341), age (hazard ratio [HR], 1.9 [95% CI, 1.2 to 2.1]; P = .0009), serum lactate dehydrogenase (LDH) above upper limit of normal (HR, 2.3 [95% CI, 1.3 to 4.5]; P = .007), and serum albumin <3.5 g/dL (HR, 1.5 [95% CI, 0.99 to 2.3]; P = .056) were independently prognostic. By assigning a score of 1 point each to albumin <3.5 g/dL (HR, 1.5) and age 66-75 years (HR 1.4) and 2 points for age >75 years (HR, 2.6) or elevated LDH (HR, 2.3), four groups with distinct outcomes were observed on the basis of the composite scores. Five-year OS was 93% for the low-risk (score 0), 82% for low-intermediate risk (score 1), 69% for intermediate-risk (score 2), and 55% for the high-risk (score ≥3; P < .0001) groups. In the validation cohort (N = 335), the model maintained its prognostic value, with a 5-year OS of 93%, 90%, 75%, and 57% for the four groups, respectively (P < .0001). Modified Staging System for WM (MSS-WM), utilizing age, albumin, and LDH is a simple, clinically useful, and externally validated prognostic model that reliably risk-stratifies patients with symptomatic WM into four groups with distinct prognosis.

#1232 Integrating genotype and phenotype data is required for renal survival prediction in autosomal dominant polycystic kidney disease

Abstract Background and Aims Autosomal dominant polycystic kidney disease (ADPKD) is the cause for 5-10% of end stage kidney disease (ESKD) worldwide. Accurate renal prognosis is essential for effective disease management. Investigation of the prognostic value of combining genetic and phenotypic characteristics in a cohort of ADPKD patients is attempted. Method In 66 ADPKD patients (mean age 33 ± 12 years, 32 males) the genetic diagnosis (using targeted Next Generation, tNGS, or Sanger Sequencing or Multiplex ligation-dependent probe amplification, MLPA) and the Mayo Clinic Imaging Category (MCIC) (through Renal Magnetic Resonance Imaging, MRI, for Total Kidney Volume measurement) were assessed. The prediction of ESKD was performed using the Mayo Clinic formula (Irazabal MV et al JASN, 2015). The calculation incorporated variables such as sex, age, e-GFR, and the MCIC. The PROPKD score was derived by considering both phenotypic factors (sex, hypertension and urologic events before the age of 35 years) and genetic data (PKD1-truncating, PKD1-nontruncating and PKD2). Results Adjusted for age, the e-GFR was on average, 26 and 27 ml/min higher in PKD2 patients compared to ADPKD-PKD1-truncating and ADPKD-PKD1-non-truncating patients, respectively (p = 0.001). The median prediction of ESKD for ADPKD-PKD1-truncating, ADPKD-PKD1-non-truncating and PKD2 patients was 22 (11-31) years, 22 (11-34) years and 31 (21-59) years, respectively (NS). In patients categorized as high risk according to PROPKD (score 7-9) the predicted time to ESKD was 16 (9-30) years, for those at intermediate risk (score 4-6), 25 (13-34) years and for those at low risk (score 0-3), 28 (16-55) years (NS). Finally, the PROPKD score showed an inverse correlation to the years of ESKD prediction, as determined by the Mayo Clinic formula; a higher PROPKD score was associated with a shorter prediction period for ESKD (Spearman r = −0.3, p = 0.04). Conclusion Prognosis of renal survival in ADPKD patients requires not only a specific genetic diagnosis but also consideration of the phenotypic data, as incorporated in the PROPKD score, enhancing the accuracy of renal survival prediction.

Assessing Risk Literacy Skills: Enhancing Healthcare Management among University Students.

The purpose of this study was to explore the determinants of risk literacy among university students in the United States by utilizing the Berlin Numeracy Test. Risk literacy skills are essential for decision-making and communication of risks, but few studies consider university students. This study aims to evaluate the association of sociodemographic factors with individual risk literacy levels. An observational cross-sectional survey study was used with a convenience sample of 184 undergraduate and graduate university students. Statistical analysis revealed significant differences for demographics at risk for negative outcomes associated with lower risk literacy. For this group of students, the majority had below-average numeracy. These findings can guide healthcare professionals to focus on college-age individuals with low-risk literacy scores to enhance patient understanding, facilitate communication, and promote healthier behaviors.

A CASE REPORT OF AN ASYMPTOMATIC PATIENT WITH TYPE 2 WELLENS’ SYNDROME AND RENAL CARCINOMA

Abstract A 65–year–old male with renal cell carcinoma, previously treated with nephrectomy and recently diagnosed with lung metastases, presented to the cardiology clinic for investigations before starting chemotherapy. He reported a history of ischemic heart disease, a non–ST–elevation myocardial infarction for which he refused coronary angiography in 2005, and a negative maximal stress test for ischemia in 2017. Additionally, the patient reported insulin–dependent type 2 diabetes mellitus and well–controlled arterial hypertension. The patient was referred for a cardiological evaluation due to a reported short–term rhythmic heartbeat without other cardiological symptoms. Cardiological parameters were stable (blood pressure: 140/95 mmHg; heart rate: 42 bpm, and oxygen saturation without oxygen supplementation: 98%). Physical examination was normal. Laboratory investigations did not show elevated levels of high–sensitivity troponin I, and only signs of mild chronic kidney disease were observed. The initial ECG showed sinus bradycardia with deeply inverted T–waves in the extended anterior area (Fig. 1), which were not present in an ECG performed one month earlier. There was no reported chest pain. An echocardiogram examination demonstrated hypertensive heart disease with marked hypokinesia of the mid–apical portion of the anterior wall and anterior interventricular septum, together with a moderate reduction in global systolic function (LV ejection fraction: 40%). The patient was hospitalized, and underwent coronary angiography the following day. He had a low–risk score (GRACE: 95 pts) As shown in Fig. 2, there was evidence of long sub–occlusive stenosis of the proximal part of the anterior descending coronary artery that was treated with angioplasty and a single drug–eluted stent placement, resulting in a good angiographic result. After the procedure, there was a rapid recovery of regional kinetics but a slower normalization of the electrocardiographic morphology (Fig. 3). Comment Wellens‘ syndrome identifies a particular subtype of unstable angina characterized by the appearance of ischemic changes on the ECG,. The clinical risk assessment of this subgroup of patients with ACS, apparently having a more benign prognosis due to their definition as unstable angina with a low GRACE risk score, potentially has an evolution toward a large myocardial infarction if not promptly diagnosed.

The CNS relapse in T-cell lymphoma index predicts CNS relapse in patients with T- and NK-cell lymphomas

AbstractLittle is known about risk factors for central nervous system (CNS) relapse in mature T-cell and natural killer cell neoplasms (MTNKNs). We aimed to describe the clinical epidemiology of CNS relapse in patients with MTNKN and developed the CNS relapse In T-cell lymphoma Index (CITI) to predict patients at the highest risk of CNS relapse. We reviewed data from 135 patients with MTNKN and CNS relapse from 19 North American institutions. After exclusion of leukemic and most cutaneous forms of MTNKNs, patients were pooled with non-CNS relapse control patients from a single institution to create a CNS relapse–enriched training set. Using a complete case analysis (n = 182), including 91 with CNS relapse, we applied a least absolute shrinkage and selection operator Cox regression model to select weighted clinicopathologic variables for the CITI score, which we validated in an external cohort from the Swedish Lymphoma Registry (n = 566). CNS relapse was most frequently observed in patients with peripheral T-cell lymphoma, not otherwise specified (25%). Median time to CNS relapse and median overall survival after CNS relapse were 8.0 and 4.7 months, respectively. We calculated unique CITI risk scores for individual training set patients and stratified them into risk terciles. Validation set patients with low-risk (n = 158) and high-risk (n = 188) CITI scores had a 10-year cumulative risk of CNS relapse of 2.2% and 13.4%, respectively (hazard ratio, 5.24; 95% confidence interval, 1.50-18.26; P = .018). We developed an open-access web-based CITI calculator (https://redcap.link/citicalc) to provide an easy tool for clinical practice. The CITI score is a validated model to predict patients with MTNKN at the highest risk of developing CNS relapse.

Identification of vitamin D-related signature for predicting the clinical outcome and immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common cancers globally, seriously endangering people health. Vitamin D was significantly associated with tumor progression and patients' prognosis. Integrative 10 machine learning algorithms were used to develop a Vitamin D-related signature (VRS) with one training cohort and 3 testing cohorts. The performance of VRS in predicting the immunology response was verified using several predicting approaches. The optimal VRS was constructed by stepCox + superPC algorithm. VRS acted as a risk factor for HCC patients. HCC patients with high-risk score had a poor clinical outcome and the AUCs of 1-, 3-, and 5-year ROC were 0.786, 0.755, and 0.786, respectively. A higher level of CD8 + cytotoxic T cells and B cells was obtained in HCC patients with low-risk score. There is higher PD1&CTLA4 immunophenoscore and TMB score in low-risk score in HCC patients. Lower TIDE score and tumor escape score was found in HCC cases with low-risk score. The IC50 value of camptothecin, docetaxel, crizotinib, dasatinib, and erlotinib was lower in HCC cases with high-risk score. HCC patients with high-risk score had a higher score of cancer-related hallmarks, including angiogenesis, glycolysis, and NOTCH signaling. Our study proposed a novel VRS for HCC, which served as an indicator for predicting clinical outcome and immunotherapy responses in HCC.

Reclassification of CADILLAC risk score with lung ultrasound at admission in patients with STEMI in a one-year follow-up

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): JC-M received Original Research Projects Grant from the Catalan Society of Cardiology and LR-S received Scholarship for Training and Research from the Association of Ischemic Heart Disease and Cardiological Critical Care of the Spanish Society of Cardiology. Introduction Lung ultrasound (LUS) has emerged as a valuable diagnostic and prognostic tool in heart failure (HF) and shows promise in risk stratification for ST-segment elevation myocardial infarction (STEMI) during the acute phase. Current risk stratification scales for STEMI primarily rely on the Killip scale to assess the severity of heart failure (HF) upon admission. However, these scales were developed before the widespread use of LUS, and as a result, LUS findings have not been incorporated into any existing risk stratification scales for STEMI. Purpose To assess the potential improvement in prognostic predictive value achieved by incorporating LUS findings into a current risk score for STEMI. Methods In a prospective multicenter cohort study, an independent operator conducted LUS, and offline B-line counting was performed upon admission. Patients were categorized as having wet lung (at least one site with ≥3 B-lines) or dry lung based on LUS results. The CADILLAC score was calculated, and patients were classified as either low risk (≤2 points) or medium/high risk (&amp;gt;2 points). We evaluated the Net Reclassification Index (NRI) and conducted a Receiver Operating Characteristics (ROC) comparison based on the prediction of a composite endpoint which included death, hospitalization for HF, acute coronary syndrome, or stroke within one year following revascularization. Results The CADILLAC score was computed for 353 patients after excluding those admitted with Killip IV. Among these, 216 (61.2%) had a low-risk score (≤2), and 137 (38.8%) had a medium-high score. LUS significantly reclassified CADILLAC results, resulting in an absolute NRI of 12.4%. ROC comparison of models comprising CADILLAC and CADILLAC + LUS demonstrated that the addition of LUS significantly improved the accuracy of predicted risk (0.722 vs. 0.770, p=0.05). Conclusion The inclusion of LUS findings in the CADILLAC score enhances its prognostic capacity.Figure 1

Machine learning with electrocardiograms to optimize mortality risk stratification in patients with suspected acute coronary syndrome

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): National Heart, Lung, and Blood Institute (NHLBI) and National Center for Advancing Translational Sciences (NCATS). Background The importance of risk stratification in patients with suspected acute coronary syndrome (ACS) extends beyond diagnosis and immediate treatment. It influences the precision of care delivery and the allocation of resources to those at highest risk of adverse events. Purpose We sought to evaluate the prognostic value of electrocardiogram (ECG) feature-based machine learning models to risk-stratify long-term mortality in those with suspected ACS. Methods This was a multicenter prospective observational cohort study of consecutive, non-traumatic patients evaluated at the emergency department for suspected ACS. The derivation cohort included 4,015 patients from a University Medical Center (age 59±16 years, 47% women, 80% training with 10-fold cross-validation and 20% testing). Ascertainment of all-cause death was based on numerous data sources, including the Centers for Disease Control and Prevention’s National Death Index registry. We trained six machine learning methods for survival analysis using 73 morphological ECG features from presenting prehospital 10-second 12-lead ECGs. We used predicted risk scores in a variational Bayesian Gaussian mixture model to define three risk groups corresponding to low, moderate, and high-risk and compared the resulting classification performance against the HEART score. The external testing cohort included 3,095 patients from a University (age 59±15 years, 44% women). Results The mortality rate was 20.3% in the derivation cohort after an average follow-up period of 3.53 years (IQR 1.75 - 5.32). Extra Survival Trees outperformed other forecasting models during cross-validation. In the internal testing cohort, the derived risk groups were significantly predictive of survival (Kaplan-Meier log-rank test statistic = 121.14, p&amp;lt;0.001), outperforming the classification performance using the HEART score (Figure 1). Our machine learning-based risk stratification model detected &amp;gt;90% of death events missed by low-risk HEART score (Figure 2). Ruling-out the low-risk group, it achieved a negative predictive value of 93.4% with a sensitivity of 85.9% (compared to 89.0% and 75.0%, respectively, for the HEART score). This classification performance generalized well to our external testing cohort. Compared to those in the low-risk group, patients at moderate (OR = 3.62 [1.35-9.74]) and high (OR = 6.12 [2.38-15.75]) risk had significantly higher odds of 30-day cardiovascular death (n=109, 3.5%). Conclusions Using only features from the 10-second 12-lead ECG, we derived and externally validated a machine learning model that stratifies the mortality risk of patients during long-term follow up. This model outperformed current standard of care based on the HEART score. Future work should validate the potential of this decision-support tool in influencing treatment plans and resource allocation.Figure 1.Clustering performanceFigure 2.Sankey diagram

Bioinformatics Analysis Reveals Prognostic Significance of the Macrophage Marker Gene Signature in Gastric Adenocarcinoma.

Gastric adenocarcinoma (GAC) is a malignant tumor with the highest incidence in the digestive system. Macrophages have been proven to play important roles in tumor microenvironment. Herein, single-cell RNA sequencing (scRNA-seq) profiles from the Gene Expression Omnibus (GEO) and bulk RNA-seq data from the Cancer Genome Atlas (TCGA) database were utilized to construct a macrophage marker gene signature (MMGS) to predict the prognosis of GAC patients. Subsequently, a risk score model based on the MMGS was built to predict the prognosis of GAC patients; further, this was validated in the GEO cohort. The risk score categorized patients into the high- and low-risk groups. A nomogram model based on the risk score and clinic-pathological characteristics was developed. Seven genes, ABCA1, CTHRC1, GADD45B, NPC2, PLTP, PRSS23, and RNASE1, were included in the risk score model. Patients with a low-risk score showed a better prognosis. The MMGS had good sensitivity and specificity for predicting the prognosis inGAC patients. The risk score was an independent prognostic factor. The constructed nomogram exhibited favorable predictability and reliability for predicting GAC prognosis. In conclusion, the risk score model based on the seven MMGSs performed well in the predicting prognosis of GAC patients. Our study may provide new insights into clinical decision-making for the personalized treatment of patients with gastric cancer (GC).

A simple risk stratification model for prostate cancer using histopathologic findings of radical prostatectomy.

To develop a simple postoperative risk stratification based on histopathologic findings from radical prostatectomy specimens. This study included 3 cohorts of patients with a preoperative diagnosis of clinically localized prostate cancer: 1 derivation cohort (n = 432) and 2 validation cohorts (n = 506 and n = 720). First, a postoperative risk stratification model was developed in the derivation cohort using the factors extraprostatic extension, surgical margin status, seminal vesicle invasion, and lymph node involvement. Each of the first 3 factors was assigned 0 or 1 point for negative or positive results, respectively, and the sum of the points, ranging from 0 to 3, was scored. pN1 was not scored but was analyzed separately. Validation cohorts were then used to evaluate the predictive accuracy of the model. Additionally, we compared the model with the Cancer of the Prostate Risk Assessment (CAPRA) score. Because the log-rank test showed no statistically significant differences between scores 1 vs 2 or score 3 vs pN1 in the derivation cohort, the following 3-level risk stratification was created: low risk (score 0), intermediate risk (score 1-2), and high risk (score 3 or pN1). There were statistically significant differences in recurrence-free survival between any of 2 groups of 3-level risk stratification. This model similarly worked in both validation cohorts. The C indexes for the model were higher than those for the CAPRA score. This simple postoperative risk stratification model, based on radical prostatectomy findings, has a prognostic impact that has been validated in a multicenter population.

Cross-Cultural Generalizability of the First Year Inventory for Early ASD Screening in China.

The First Year Inventory (FYI) is a parent report screening measure, aimed at identifying the risk of autism spectrum disorder (ASD) in 12-month-old infants. This study aimed to investigate the utility of FYI within the Chinese community and develop a short version, encompassing both a low-risk sample and a high-risk sample comprising infants with older siblings diagnosed with ASD. Parents of 53 high-risk (HR) infants and 519 low-risk (LR) infants, aged 11 to 13 months, were recruited. After comparing response distributions across Chinese and American samples, a new factorial structure was developed according to the factor analyses. The construct validity and internal consistency of the two FYI versions were examined. The implementation of FYI in the HR sample was also assessed. Noteworthy disparities in response distribution were observed between the Chinese and American samples. Both FYI 2.0 and the FYI short version demonstrated moderate construct validity and internal consistency, with the FYI short version exhibiting better predictive ability in the HR sample. Significant lower risk scores was observed in the HR sample compared to the LR sample. These findings substantiate the applicability and validity of the Chinese short version of FYI. Future research should include follow-up assessments with the Chinese sample to evaluate cutoff scores, considering the cutoff between sensitivity and specificity and the sample?s characteristics.

Association of plasma ceramide with decline in kidney function in patients with type 2 diabetes

Circulating ceramide levels are dysregulated in kidney disease. However, their associations with rapid decline in kidney function (RDKF) and end-stage kidney disease (ESKD) in patients with type 2 diabetes (T2D) are unknown. In this prospective study of 1746 T2D participants, we examined the association of plasma ceramide Cer16:0, Cer18:0, Cer24:0, and Cer24:1 with RDKF, defined as an estimated glomerular filtration rate (eGFR) decline of 5 ml/min/1.73 m2 per year or greater, and ESKD defined as eGFR <15/min/1.73 m2 for at least 3 months, on dialysis or renal death at follow-up. During a median follow-up period of 7.7 years, 197 patients experienced RDKF. Ceramide Cer24:0 (odds ratio [OR] = 0.71, 95% CI 0.56–0.90) and ratios Cer16:0/Cer24:0 (OR = 3.54 [1.70–7.35]), Cer18:0/Cer24:0 (OR = 1.89 [1.10–3.25]), and Cer24:1/Cer24:0 (OR = 4.01 [1.93–8.31]) significantly associated with RDKF in multivariable analysis; 124 patients developed ESKD. The ratios Cer16:0/Cer24:0 (hazard ratio [HR] = 3.10 [1.44–6.64]) and Cer24:1/Cer24:0 (HR = 4.66 [1.93–11.24]) significantly associated with a higher risk of ESKD. The Cer24:1/Cer24:0 ratio improved risk discrimination for ESKD beyond traditional risk factors by small but statistically significant margin (Harrell C-index difference: 0.01; P = 0.022). A high ceramide risk score also associated with RDKF (OR = 2.28 [1.26–4.13]) compared to lower risk score. In conclusion, specific ceramide levels and their ratios are associated with RDKF and conferred an increased risk of ESKD, independently of traditional risk factors, including baseline renal functions in patients with T2D.