High Risk Score Research Articles

Development of a prognostic signature for overall survival using peripheral blood biomarkers in head and neck squamous cell carcinoma treated with immune checkpoint inhibitors.

We previously reported in recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) treated with immune checkpoint inhibitors (ICIs), pretreatment higher lactate dehydrogenase (LDH) and absolute (abx) neutrophils as well as lower percent (%) lymphocytes correlated with worse overall survival (OS). In this study we aimed to develop a prognostic signature for HNSCC treated with ICIs using these peripheral blood biomarkers (PBBMs). Adults with R/M HNSCC treated with ICIs at our institution from 08/2012 to 03/2021 with pretreatment PBBMs were included. Follow-up continued until 02/15/2022. The cohort (n = 151) was randomly split into training (n = 100) and testing (n = 51) datasets. A prognostic score incorporating LDH, % lymphocytes, and abx neutrophils was developed from the training dataset using Cox proportional hazards regression. In the training dataset, a grid search identified the optimal cutpoints classifying patients into high, medium, and low-risk groups (trichotomized signature) as well as high vs. low-risk groups (dichotomized signature). The prognostic score, dichotomized and trichotomized signatures were then validated in the testing dataset. Training and testing datasets showed no clinically meaningful differences in clinicodemographic characteristics or PBBMs. An OS prognostic model was developed from the training dataset: Risk score = 1.24*log10(LDH) - 1.95*log10(% lymphocytes) + 0.47*log10(abx neutrophils). Optimal risk score cutpoints for the dichotomized and trichotomized signatures were defined in the training dataset, and Kaplan-Meier curves for both dichotomized and trichotomized signatures showed good separation between risk groups. Risk scores were calculated in the testing dataset, where the trichotomized signature demonstrated overlap between low and medium-risk groups but good separation from the high-risk group while the dichotomized signature showed clear separation between low and high-risk groups. Higher risk score correlated with worse OS (HR 2.08, [95%CI 1.17-3.68], p = 0.012). Progression-free survival Kaplan-Meier curves likewise showed excellent separation between dichotomized risk groups in the training and testing datasets. We developed a prognostic signature for OS based on 3 previously identified PBBMs for HNSCC treated with ICIs and identified a high-risk group of patients least likely to have survival benefit from ICIs. This signature may improve ICI patient selection and warrants validation in an independent cohort as well as correlation with CPS.

Lipid metabolism-related gene signature predicts prognosis and unveils novel anti-tumor drugs in specific type of diffuse large B cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which possess highly aggressive and heterogeneous. Despite advances in understanding heterogeneity and development of novel targeted agents, the prognosis of DLBCL patients remains unsatisfied. Lipids are crucial components of biological membranes and signal transduction while accumulating evidence has supported the vital roles of abnormal lipid metabolism in tumorigenesis. Furthermore, some related pathways could serve as prognostic biomarkers and potential therapeutic targets. However, the clinical significance of abnormal lipid metabolism reprogramming in DLBCL has not been investigated. In the current study, we developed a prognostic risk model for DLBCL based on the abnormal expressed lipid metabolism genes and moreover based on our risk model we classified patients with DLBCL into novel subtypes and identified potential drugs for DLBCL patients with certain lipid metabolism profiles. We utilized univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO Cox regression to identify prognostic related lipid metabolism related genes. Multivariate cox regression was used to establish the prognostic model. Patients were divided in to high and low risk groups based on the median risk score. Immune cell infiltration and GSEA were used to identify the pathways between high and low risk groups. Oncopredict algorithm was utilized to identify potential drug for high-risk patients. In vitro cell apoptosis and viability analysis were employed to verify the specific tumor inhibition effects of AZD5153. Nineteen survival related lipid metabolism genes TMEM176B, LAYN, RAB6B, MMP9, ATAD3B, SLC2A11, CD3E, SLIT2, SLC2A13, SLC43A3, CD6, SIRPG, NEK6, LCP2, CTTN, CXCL2, SNX22, BCL6 and FABP4 were identified and subjected to build the prognostic model which was further verified in four external microarray cohorts and one RNA seq cohorts. Tumor immune microenvironment analysis and GSEA results showed that the activation of MYC targets genes rather than immunosuppression contribute to the poor survival outcome of patients in the high-risk group. AZD5153, a novel bivalent BET bromodomain inhibitor which could inhibit the transcription of MYC and E2F exhibited specific antitumor function for cells with high-risk score. Our results provide the first lipid metabolism-based gene signature for predicting the survival of patients with DLBCL. Furthermore, by determining novel subtypes with our lipid metabolism prognostic model we illustrated that drugs that compromising MYC target genes rather than immune checkpoint inhibitors may be beneficial to DLBCL patients with certain lipid metabolism profiles.

Arterial Stiffness as a New Predictor of Clinical Outcome in Patients with Polycythemia Vera

Background: Thrombotic adverse events and disease progression are crucial in Polycythemia Vera (PV), as it stands as the leading cause of mortality. The pulse wave velocity (PWV) is a valuable indicator of arterial aging and often plays a significant independent role in contributing to cardiovascular adverse events (CV-AEs). The aim of this study was to examine the relationship between PWV and critical vascular function parameters, with the goal of identifying new predictive factors of vascular damage and exploring a potential connection with disease progression. Methods: Non-invasive aortic stiffness was assessed through carotid–femoral PWV measurement. PWV was measured using the SphygmoCor device. History of arterial or venous thrombosis (TAEs) or other CV-AEs was collected at baseline. PWV measurements were repeated at baseline, at 6 and at 12 months. Results: The study involved 28 PV patients aged 27 to 77 years, with 57.1% being male. Fourteen patients (50%) reported a high-risk thrombotic score at diagnosis, and 60.7% had at least one comorbidity. Multivariable regression models showed that hemoglobin levels were independently associated with PWV (β: 0.68, SE 0.24, p < 0.01). During the follow-up period (median duration 21.3 months, range 6–33), a total of 13 events were documented. Specifically, two patients exhibited a loss of response to treatment, four patients presented an increase in spleen diameters, three patients displayed an escalation of systemic symptoms, and three patients had a clear progression to secondary myelofibrosis. PWV (per 1 m/s: OR 1.70, 95% CI 1.00–2.91, p = 0.047) and leukocyte count (per 1 × 103/μL: OR 1.47, 95% CI: 1.04–2.09, p = 0.043) were significant predictors of events, independently of waist circumference, blood pressure, treatment, and hematocrit. Conclusions: PWV has demonstrated its potential as an effective tool for monitoring PV patients. It stands as a clinical parameter that can predict the risk of progression in PV patients. Further investigation is essential to fully explore this potential. If successful, it could offer clinicians a valuable resource for effectively managing PV patients.

Identification of key programmed cell death genes for predicting prognosis and treatment sensitivity in colorectal cancer

Colorectal cancer (CRC) ranks third in global incidence and second in mortality. However, a comprehensive predictive model for CRC prognosis, immunotherapy response, and drug sensitivity is still lacking. Various types of programmed cell death (PCD) are crucial for cancer occurrence, progression, and treatment, indicating their potential as valuable predictors. Fourteen PCD genes were collected and subjected to dimensionality reduction using regression methods to identify key hub genes. Predictive models were constructed and validated based on bulk transcriptomes and single-cell transcriptomes. Furthermore, the tumor microenvironment, immunotherapy response, and drug sensitivity profiles among patients with CRC were explored and stratified by risk. A risk score incorporating the PCD genes FABP4, AQP8, and NAT1 was developed and validated across four independent datasets. Patients with CRC who had a high-risk score exhibited a poorer prognosis. Unsupervised clustering algorithms were used to identify two molecular subtypes of CRC with distinct features. The risk score was combined with the clinical features to create a nomogram model with superior predictive performance. Additionally, patients with high-risk scores exhibited decreased immune cell infiltration, higher stromal scores, and reduced responsiveness to immunotherapy and first-line clinical drugs compared with low-risk patients. Furthermore, the top ten non-clinical first-line drugs for treating CRC were selected based on their predicted IC50 values. Our results indicate the efficacy of the model and its potential value in predicting prognosis, response to immunotherapy, and sensitivity to different drugs in patients with CRC.

Abstract 4122120: Prospective Implementation of a Cardiovascular Implantable Electronic Device Algorithm-Based Management Pathway in Routine Heart Failure Care

Introduction: More than 1 million patients in the US are hospitalized annually with heart failure (HF), many of whom have cardiovascular implantable electronic devices (CIEDs). CIEDs monitor physiologic variables that could identify subacute HF decompensation and impending HF hospitalization (HFH). One such algorithm is Medtronic’s TriageHF TM , which integrates nine diagnostic inputs from remote monitoring data to stratify patients into categories of low-, medium-, or high-risk of HFH in the next 30 days. Goals/Aims: To implement and evaluate a program in which two Veterans Health Administration (VHA) cardiology clinics receive high-risk TriageHF TM scores for patients with CIEDs, followed by contacting and assessing patients and then taking appropriate clinical action. Methods: From 1/18/24 to 4/19/24, TriageHF TM risk scores were calculated from both HF-specific remote transmissions that were scheduled every 30 days and unscheduled remote transmissions. Clinicians then contacted patients with high-risk scores regarding possible symptoms and provided an empiric 3-day diuretic intervention (initiation or dose augmentation), adjusted guideline-directed medical therapy (GDMT), or performed another clinical action as appropriate. Results: Among 358 patients with 1140 transmissions, 72 (6%) patients had a high-risk transmission. Mean patient age was 72.8 years, 346 (97%) were male, and 221 (62%) had a pre-existing diagnosis of heart failure. Of the 72 patients with high-risk transmissions, 67 (93%) were successfully contacted; 34 (51%) had no HF symptoms, 24 (36%) had mild to moderate symptoms, 2 (3%) had severe symptoms, 4 (6%) had non-HF symptoms, and 3 (4%) could not report symptoms. Of the 67, 57 (85%) reported adherence to medications and 17 (25%) were identified as likely having a non-HF related high-risk score. Forty-six (69%) had a clinical action taken in response to the high-risk score, including 28 (42%) with a diuretic intervention, 12 (18%) with GDMT augmented, and 25 (37%) with other actions, such as being referred to HF clinic. Conclusions: In this implementation study, clinicians contacted and assessed nearly all patients at high-risk for HF decompensation based on CIED remote monitoring data. Approximately 70% of patients had an actionable high-risk score, with approximately half prescribed empiric diuretics or augmented GDMT. A randomized clinical trial is needed to determine whether this algorithm and subsequent intervention improves clinical outcomes.

Abstract 4115231: Higher Global Registry of Acute Coronary Events Score is Associated with Lower Invasive Coronary Angiograpy Use

Background: Use of invasive coronary angiography (ICA) and the selection of other interventions in patients who present with NSTEMI should be guided by clinical risk stratification. National guidelines recommend ICA use in patients with intermediate and high risk scores. The Global Registry of Acute Coronary Events (GRACE) score is a commonly used risk score that is based on clinical characteristics available at the time of admission. Aim: Examine if patients with NSTEMI with higher risk stratification scores are more likely to have ICA. Methods: This cross-sectional study included all patients who presented with NSTEMI to an academic medical center that serves a rural population over a 12-month period. Data were derived from the American College of Cardiology Chest Pain – MI Registry data collected by trained abstractors at the facility and were verifed by the study team. Additional data needed to calculate the GRACE Score were abstracted by the study team. GRACE Scores were categorized into low (1-88), moderate (89-118), and high (119-263) risk. Multivariable logistic regression was used to test if higher GRACE scores are more associated with ICA use controlling for patient factors not included in the GRACE Score and further examined by GRACE score category. Results: The total sample size was 434 patients (Mean age 65±13.8, 36% female and 36% Black). Patients transferred from outlying facilities accounted for 40% of the sample. ICA was performed for 94% of the patients. Increasing GRACE score was associated with lower ICA use (aOR 0.98, 95% CI 0.97-0.99). Odds of ICA use between the low-risk group and the intermediate risk group (aOR 0.60, 95% CI 0.19-1.91) did not significantly differ. Patients in the high-risk category were less likely to undergo ICA compated to low-risk patients (aOR 0.22, 95% CI 0.07-0.62). Conclusions: Use of ICA decreased as GRACE score increased in this patient sample, suggesting that additional factors beyond GRACE score likely influence ICA use in patients who presented with NSTEMI during this time period. Influence of patient factors as well as provider and patient risk aversion on ICA selection must be explored to better understand incongruence with guideline recommendations.

Maternal COVID-19 infection associated with offspring neurodevelopmental disorders.

Maternal COVID-19 infection increases the incidence of neurodevelopmental disorders (NDDs) in offspring, although the underlying mechanisms have not been elucidated. This study demonstrated that COVID-19 infection during pregnancy disrupted the balance of maternal and fetal immune environments, driving alterations in astrocytes, endothelial cells, and excitatory neurons. A risk score was established using 47 unique genes in the single-cell transcriptome of gestational mothers. The high risk score in CD4 proliferating T cell level served as an indicator for increased risk of offspring NDDs. Summary-based Mendelian randomization and phenome-wide association study analyses were conducted to identify the causal association of the transcriptional changes with the increased risk of offspring NDDs. Additionally, 10 drugs were identified as potential therapeutic candidates. Our findings support a model where the maternal COVID-19 infection changed the levels of CD4 proliferating T cells, leading to the alterations of astrocytes, endothelial cells, and excitatory neurons in offspring, contributing to the increased risk of NDDs in these individuals.

Comparing predictive validity of Youth Level of Service/Case Management Inventory scores in Indigenous and non-Indigenous Canadian youth.

There is an increasing recognition of the necessity to establish the predictive validity of risk assessment scores within specific population subgroups, particularly those (including Indigenous peoples) who are overrepresented in the criminal justice system. I compared measures of discrimination and calibration of the Youth Level of Service/Case Management Inventory (YLS/CMI) in Indigenous and non-Indigenous youth probationers in Ontario, Canada. Compared with non-Indigenous youth, Indigenous youth would have higher risk scores and reoffense rates. The YLS/CMI would predict reoffending and time to reoffense significantly and comparably for Indigenous and non-Indigenous youth, but there would be group difference discrimination (sensitivity, specificity) and calibration (positive predictive value, negative predictive value). Justice ministry-supplied data on 400 Indigenous and non-Indigenous youth (330 male, 70 female) individually matched on key background variables were analyzed to provide measures of discrimination and calibration of the YLS/CMI, with 3-year recidivism as the primary outcome. Indigenous youth were assessed at significantly higher risk than non-Indigenous youth (d = .60); 70% of Indigenous youth and 46% of non-Indigenous youth reoffended (ϕ = .24). Overall measures of discrimination (area under the curve) and calibration (logistic regression) were significant and did not differ across groups. Cross-area under the curve results indicated that the YLS/CMI discriminated Indigenous recidivists from non-Indigenous nonrecidivists but differentiated Indigenous nonrecidivists from non-Indigenous recidivists at chance level. In addition, recidivism was underestimated for low-risk Indigenous youth compared with non-Indigenous youth, but specificity was also low; only 28% of Indigenous youth who did not reoffend were assessed as low risk. Results were largely consistent across male and female youth. Examining subgroup predictive validity using multiple indices provides important information that should inform policy and practice discussions regarding fair use of risk assessment tools. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Acute Promyelocytic Leukemia: Long-Term Outcomes from the HARMONY Project

Treatment outcomes for acute promyelocytic leukemia (APL) have improved with the widespread use of targeted therapy with all-trans retinoic acid (ATRA) and arsenic trioxide (ATO). Our study aimed to validate these data in a large patient cohort, and to redefine prognostic factors.Leveraging the HARMONY Platform, we analyzed 1438 newly-diagnosed APL patients, diagnosed between 1999 to 2022. Patient data derived from the 2 international multicenter GIMEMA-APL0406 and NCRI-AML17 trials, and 4 European registries (HOVON, AMLSG, Swedish AML Registry and SAL). The study cohort included 721 males and 717 females, with a median age of 50.5 years (range 16-94 years). Of 1309 patients starting therapy, 562 received ATRA-ATO, and 747 AIDA-like chemotherapy. Early death (ED) occurred in 85 of 1438 patients (5.9%) at a median of 9 days after APL diagnosis and was independently associated with increasing age and high Sanz risk score (OR:1.06, 95% C.I: 1.04-1.08, and OR:4.65, 95% C.I.:2.55-8.51, respectively). The median follow-up was 5.5 years (IQR=3.2-7.5). ATRA-ATO regimen was associated with the best outcome, reaching 91% 7-year overall survival (vs 81% for AIDA-like, HR:2.14, 95%C.I.:1.51-3.05), 89% event-free survival (vs 71% for AIDA-like, HR:2.72 95%CI: 2.01–3.69) and 3% relapse (vs 13% for AIDA-like, HR:4.19, 95%CI:2.38–7.39, p<0.001 for all outcomes). The survival advantage of ATRA/ATO was independent of patients’ age, Sanz-risk score, and treatment scenario.Our study confirms the superiority of ATRA-ATO over ATRA-chemotherapy in APL patients. ED still represents an unmet medical need, in particular in older patients and in high-risk APL.

Evaluation of Autonomous Driving Safety by Operational Design Domains (ODD) in Mixed Traffic

This study derived effective driving behavior indicators to assess the driving safety of autonomous vehicles (AV). A variety of operation design domains (ODD) in urban road networks, which include intersections, illegal parking, bus stop, bicycle lanes, and pedestrian crossings, were taken into consideration in traffic simulation analyses. Both longitudinal and interaction driving indicators were investigated to identify the driving performance of AVs in terms of traffic safety in mixed traffic stream based on simulation experiments. As a result of identifying the appropriate evaluation indicator, time-varying stochastic volatility (VF) headway time was selected as a representative evaluation indicator for left turn and straight through signalized intersections among ODDs related to intersection types. VF headway time is suitable for evaluating driving ability by measuring the variation in driving safety in terms of interaction with the leading vehicle. In addition to ODDs associated with intersection type, U-turns, additional lane segments, illegal parking, bus stops, and merging lane have common characteristics that increase the likelihood of interactions with neighboring vehicles. The VF headway time for these ODDs was derived as driving safety in terms of interaction between vehicles. The results of this study would be valuable in establishing a guideline for driving performance evaluation of AVs. The study found that unsignalized left turns, signalized right turns, and roundabouts had the highest risk scores of 0.554, 0.525, and 0.501, respectively, indicating these as the most vulnerable ODDs for AVs. Additionally, intersection and mid-block crosswalks, as well as bicycle lanes, showed high risk scores due to frequent interactions with pedestrians and cyclists. These areas are particularly risky because they involve unpredictable movements from non-vehicular road users, which require AVs to make rapid adjustments in speed and trajectory. These findings provide a foundation for improving AV algorithms to enhance safety and establishing objective criteria for AV policy-making.

A novel hypoxia- and lactate metabolism-related prognostic signature to characterize the immune landscape and predict immunotherapy response in osteosarcoma

BackgroundImmunotherapy has shown considerable promise in cancer treatment, yet only a minority of osteosarcoma patients derive benefits from this approach. Hypoxia and lactate metabolism are two predominant characteristics of the tumor microenvironment. These features are crucial for molding the immune landscape and thus have the potential to act as predictive indicators for immunotherapy response.MethodsPrognostic modeled genes were identified through univariate and multivariate Cox regression as well as LASSO regression analyses. The tumor microenvironment was evaluated using ESTIMATE, CIBERSORT, and ImmuCellAI analyses. Tide prediction and expression of immune checkpoints, MHC molecules, chemokines, interleukins, interferons, receptors, and other cytokines were utilized to estimate immunotherapy efficacy. Single-cell analysis was performed to demonstrate the expression of modeled genes among various immune cell types. Experimental validation was carried out to verify the expression and functions of SFXN4 and SQOR.ResultsA potent signature was constructed with 8 genes related to hypoxia and lactate metabolism, including MAFF, COL5A2, FAM162A, SQOR, UQCRB, SFXN4, PFKFB2 and COX6A2. A nomogram incorporating risk scores and other clinical features demonstrated excellent predictive capacity. Osteosarcoma patients with high-risk scores exhibited poor prognosis and more “cold” tumor characteristics. According to the ESTIMATE algorithm, these patients displayed lower immune, stromal, and ESTIMATE scores, partially attributed to inadequate infiltration of key immunocytes. The Ciborsort analysis similarly indicated that high-risk individuals had diminished infiltration of critical anti-tumor immune cells such as Cytotoxic T cells, CD4+ T cells, and NK cells. The low expression levels of certain immune checkpoints, MHC molecules, chemokines, interleukins, interferons, receptors, and other cytokines in high-risk cases suggested their unsatisfactory responses to immune treatment. Tide prediction further demonstrated that fewer individuals classified as high risk may exhibit sensitivity to immune checkpoint inhibitor therapy. Notably, SFXN4 was found to be highly expressed in osteosarcoma tissues and cells; it promoted the growth, migration, and invasion of osteosarcoma cells, while SQOR had the opposite effect.ConclusionOur research has developed a robust hypoxia- and lactate metabolism-related gene signature, providing a solid theoretical foundation for prognosis prediction, classification of “cold” and “hot” tumors, accessing immunotherapy response, and directing personalized treatment for osteosarcoma.

Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The purpose was to develop a machine learning (ML) model for predicting the 30-day all-cause mortality risk in SAP patients and to explain the most important predictors. This research utilized six ML methods, including logistic regression (LR), k-nearest neighbors(KNN), support vector machines (SVM), naive Bayes (NB), random forests(RF), and extreme gradient boosting(XGBoost), to construct six predictive models for SAP. An extensive evaluation was conducted to determine the most effective model and then the Shapley Additive exPlanations (SHAP) method was applied to visualize key variables. Utilizing the optimized model, stratified predictions were made for patients with SAP. Further, the study employed multivariable Cox regression analysis and Kaplan-Meier survival curves, along with subgroup analysis, to explore the relationship between the machine learning-based score and 30-day mortality. Through LASSO regression and recursive feature elimination (RFE), 25 optimal feature variables are selected. The XGBoost model performed best, with an area under the curve (AUC) of 0.881, a sensitivity of 0.5714, a specificity of 0.9651 and an F1 score of 0.64. The first six most important feature variables were the use of vasopressor, high Charlson comorbidity index, low blood oxygen saturation, history of malignant tumor, hyperglycemia and high APSIII score. Based on the optimal threshold of 0.62, patients were divided into high and low-risk groups, and the 30-day survival rate in the high-risk group decreased significantly. COX regression analysis further confirmed the positive correlation between high-risk scores and 30-day mortality. In the subgroup analysis, the model showed good risk stratification ability in patients with different gender, renal replacement therapy and with or without a history of malignant tumor, but it was not effective in predicting peripheral vascular disease. the XGBoost model effectively predicts the severity of SAP, serving as a valuable tool for clinicians to identify SAP early.

Comprehensive Analysis and Verification of the Prognostic Significance of Cuproptosis-Related Genes in Colon Adenocarcinoma.

Colon adenocarcinoma (COAD) is a frequently occurring and lethal cancer. Cuproptosis is an emerging type of cell death, and the underlying pathways involved in this process in COAD remain poorly understood. Transcriptomic and clinical data for COAD patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We investigated alterations in DNA and chromatin of cuproptosis-related genes (CRGs) in COAD. In order to identify predictive differentially expressed genes (DEGs) and various molecular subtypes, we used consensus cluster analysis. Through univariate, multivariate, and Lasso Cox regression analyses, four CRGs were identified. A risk prognostic model for cuproptosis characteristics was constructed based on four CRGs. This study also examined the association between the risk score and the tumor microenvironment (TME), the immune landscape, and drug sensitivity. We distinguished two unique molecular subtypes using consensus clustering analysis. We discovered that the clinical characteristics, prognosis, and TME cell infiltration characteristics of patients with multilayer CRG subtypes were all connected. The internal and external evaluations of the predicted accuracy of the prognostic model built using data derived from a cuproptosis risk score were completed at the same time. A nomogram and a clinical pathological analysis make it more useful in the field of medicine. A significant rise in immunosuppressive cells was observed in the high cuproptosis risk score group, with a correlation identified between the cuproptosis risk score and immune cell infiltration. Despite generally poor prognoses, the patients with a high cuproptosis risk but low tumor mutation burden (TMB), cancer stem cell (CSC) index, or microsatellite instability (MSI) may still benefit from immunotherapy. Furthermore, the cuproptosis risk score positively correlated with immune checkpoint gene expression. Analyzing the potential sensitivity to medications could aid in the development of clinical chemotherapy regimens and decision-making. CRGs are the subject of our in-depth study, which exposed an array of regulatory mechanisms impacting TME. In addition, we performed additional data mining into clinical features, prognosis effectiveness, and possible treatment medications. COAD's molecular pathways will be better understood, leading to more precise treatment options.

Prognostic Value of Hospital Frailty Risk Score and Clinical Outcomes in Critical Limb-Threatening Ischemia and End-Stage Kidney Disease.

End-stage kidney disease (ESKD) is commonly associated with critical limb-threatening ischemia (CLTI) and frailty. Yet there are no specific tools to predict outcomes of CLTI in ESKD, particularly those that incorporate frailty. We aimed to assess the utility of the medical record-based Hospital Frailty Risk (HFR) score in predicting outcomes of CLTI in ESKD. We identified patients with ESKD diagnosed with CLTI from the US Renal Data System from 2015 to 2018. These patients were categorized into 3 frailty risk groups on the basis of their HFR scores: low (<5), intermediate (5-10), high-risk (>10), and on the basis of whether they underwent revascularization (endovascular revascularization [ER]/surgical revascularization [SR]) or not (no revascularization). Primary outcomes of interest included in-hospital composite of death or major amputation and in-hospital death. We included 49 454 eligible patients, with ER/SR cohort including 19.8% (n=9777). A total of 88.4% (ER/SR) and 90.0% (no revascularization) were frail on the HFR scale. We found a nonlinear association between HFR score and in-hospital adverse outcomes. In both cohorts, intermediate and high-risk HFR scores were associated with greater risk of in-hospital death (high-risk, ER/SR: odds ratio, 2.7 [95% CI, 1.6-4.8]; P<0.0001; no revascularization: odds ratio, 7.8 [95% CI, 5.3-11.6]; P<0.01) and composite of in-hospital major amputation or death (high-risk, ER/SR: odds ratio, 2.4 [95% CI, 1.9-3.1]; P<0.0001; no revascularization: odds ratio, 1.7 [95% CI, 1.5-1.9]; P<0.0001). The HFR score can predict risk of in-hospital death and composite ofdeath or major amputation in patients with ESKD and CLTI. Further data are needed to determine the utility of the HFR score in this population.

Outdoor worker knowledge of ticks and Lyme disease in Québec.

Lyme disease is a well-known occupational risk across North America caused by exposure to Borrelia burgdorferi via blacklegged ticks (Ixodes scapularis). As the geographic range of B. burgdorferi advances with the increasing distribution of blacklegged ticks, more outdoor workers are at risk of contracting Lyme disease. In this study, we examined the demography and personal perceptions of outdoor workers within one framework to better determine the overall risk for those working outdoors. We analysed outdoor worker knowledge of ticks and of behaviours that can prevent tick bites and Lyme disease. We then compared these risk perceptions of individuals across age, sex, education, and industry, as well as time spent outdoors. We tested the hypothesis that the risk perception of an individual and their knowledge of Lyme disease transmission was dependent on their demographics, experience in their job, and the region in which they spend time outdoors. We estimated a knowledge-based risk score based on individuals' answers to a questionnaire on risk perception given to voluntary participants who work outdoors. Those who had higher risk scores were more at risk. We found that knowledge-based risk scores were correlated with geographic risk levels and with the number of hours per day spent outdoors. Those who work longer hours and who work in areas with mid-level risk had higher risk scores. Those who spend more time outdoors recreationally had lower risk scores. Further examination and acknowledgment of the reasoning behind why these factors are affecting workers' risks must be considered to recognize that it is not necessarily demographics or geographically high-risk areas that affect an individual's risk. Workers' knowledge of these risks is affected by several variables that should be taken into consideration when implementing safety measures and awareness programs.

Risk assessment models and survival in pulmonary arterial hypertension: a SPAHR analysis

BackgroundMulticomponent improvement (MCI) is a novel endpoint for predicting survival in patients with pulmonary arterial hypertension (PAH), included in the sotatercept clinical program. For the first time, we investigated the prognostic value of MCI, ESC/ERS 4-strata risk (4SR) assessment, and the non-invasive French risk stratification score (FRS), for predicting survival in PAH patients in Sweden. All risk prediction models are based on three parameters: WHO-FC (World Health Organization Functional Class), NT-proBNP, and 6MWD (6-minute walk distance). MethodsData from the Swedish PAH & CTEPH Registry (SPAHR) collected 2008-2021 were used for the analyses. The association of MCI achievement, 4SR, and FRS calculated at 6 months (6M), with transplant-free (TF) survival was investigated in the whole cohort, as well as categorized by age (<65 and ≥65 years). All risk prediction models are based on three parameters: WHO-FC (World Health Organization Function Class), NT-proBNP, and 6MWD (6-minute walk distance). Kaplan-Meier estimate/Log-Rank test and Cox proportional model were used for survival analyses. ResultsThe study included 411 patients (70% women) with a median [IQR] age of 66y.21 At 6M, the mean (SD) NT-proBNP decrease was 808 (603) and the mean 6MWD increase was 44 (11) meters. Median survival/follow-up time was 3.5y [1.7, 5.4]. After adjustment for sex and comorbidities, achievement of MCI independently predicted TF-survival; one MCI-criterion met (HR 0.65; CI 0.46-0.92, p=0.015); two MCI-criteria met (HR 0.45; CI 0.31-0.66, p<0.001); all three MCI-criteria met (HR 0.32; CI 0.21-0.52, p<0.001). Likewise, 4SR and FRS demonstrated a strong association with TF-survival with patients achieving lower risk scores exhibiting longer survival compared to those with higher risk scores. Patients ≥65Y more often had connective tissue disease-associated PAH, lower DLCO, more pronounced comorbidity burden, higher risk at baseline, less improvement during follow-up, and worse TF-survival then patients <65Y. ConclusionAll models were found to have prognostic relevance for TF-survival. Risk prediction was incremental with the number of low-risk criteria met, while improvements in only one of 6MWD, NT-proBNP, or FC showed a modest association with survival. The risk assessment tools predicted outcome in patients across both age categories.

Understanding long-term risk in Percutaneous Coronary Intervention (PCI) in the Australian contemporary era with a focus on defining Complex Revascularisation in High-Risk Indicated Patients (CHIP)

BackgroundComplex Revascularisation in High-Risk Indicated Patients (CHIP) is emerging in Percutaneous Coronary Intervention (PCI). We document the frequency and outcomes following CHIP PCI in the Australian population, to understand risk and guide clinical decision-making. We propose a scoring system to define CHIP procedures. MethodsPatients undergoing PCI from Melbourne Intervention Group registry between 2005 and 2018 were analysed. Patients were stratified based on the number of high-risk features defined as 1)presence of ≥3 patient factors including age > 75yo, COPD, diabetes, renal impairment (eGFR<60 mL/min/1.73 m2), PVD, and 2)LVEF<30 %, and/or 3)having one complex coronary anatomical feature such as LMCA PCI, ACC/AHA B2/C lesion PCI, presence of multi-vessel disease or CTO PCI. National Death Index linkage was performed for long-term mortality analysis. Outcomes were analysed according to 4 risk categories – low risk(score 0), intermediate risk(score 1), high-risk(score 2), and very high-risk(score 3). Results20,973patients were analysed. Majority of patients underwent intermediate-risk procedures(71.7 %), with low rates of high-risk(6.6 %), and very high-risk(0.2 %). Lesion success inversely correlates with risk; low-risk(99.4 %), intermediate-risk(95.1 %), high-risk(94.3 %), very high-risk(92.5 %),p < 0.001. In-hospital and 30-day death correlates with risk; low-risk(0.0 %/0.1 %), intermediate-risk(0.3 %/0.5 %), high-risk(1.5 %/2.9 %), very high-risk(2.4 %/7.1 %),p < 0.001. Long-term mortality correlates with risk; low-risk(12.3 %), intermediate-risk(15.8 %), high-risk(49.3 %), very high-risk(76.2 %),p < 0.001. On multivariate analysis, increasing risk correlates with long-term mortality; intermediate-risk(HR1.41), high-risk(HR6.42), and very high-risk(14.05). ConclusionIn the Australian practice, proportion of patients undergoing high and very high-risk PCI procedures are low. Despite good procedural success and in-hospital outcomes, long-term mortality is poor. Further research into appropriate patient selection, and direct comparison of CHIP PCI to those treated medically and surgically should be considered.

Risk Factors of Post-Traumatic Stress in Pediatric Solid Organ Transplant Recipients.

Life with end-stage organ failure is accompanied by an accumulation of traumatic medical or surgical experiences. Despite recovery after solid organ transplantation (SOT), many children and adolescents develop post-traumatic stress symptoms (PTSS). PTSS remain underappreciated as a major comorbidity in SOT programs, despite their association with decreased quality of life. We conducted a retrospective, cross-sectional study of 86 pediatric SOT recipients (17 heart, 44 kidney, and 25 liver) to evaluate potential determinants of PTSS. Trauma symptoms were measured by the Child Trauma Screening Questionnaire (CTSQ). Demographic, baseline, and contemporaneous factors were tested for independent association with CTSQ scores. The median post-transplant CTSQ score was 2 (IQR 1-4), and 22% were identified as high risk (score ≥5) for PTSD. Higher CTSQ scores were independently associated with the number of ICU days within the previous 12 months, the number of medications (complexity), and involvement with foster care in the primary model (R2 [adj.] = 0.26). The addition of the Family Impact Module improved the overall model (R2 [adj.] = 0.33), wherein higher family functioning was independently associated with lower CTSQ scores. An exploratory analysis of pre-transplant patients (n = 34) found a median pre-transplant CTSQ of 2 (IQR 1-6), suggesting that PTSS are onset before transplant and persist afterward. PTSS are highly prevalent in the SOT population. Risk factors include recent adverse medical experiences and complexity, whereas family stability may be protective. Additional research is needed to improve early ascertainment and support for patients at high risk of developing PTSS throughout their transplant journey.

An improved invagination pancreaticojejunostomy technique associated with a lower incidence of pancreatic fistula: A single-center study

PurposeThis study compared the incidence of postoperative pancreatic fistula (POPF) between standard invagination pancreaticojejunostomy (PJ) and an improved PJ technique after pancreaticoduodenectomy and evaluated the clinical utility of the improved PJ procedure. MethodsClinical and postoperative data of 363 patients who underwent pancreaticoduodenectomy at the First Affiliated Hospital of Soochow University from February 2018 to October 2021 were analyzed retrospectively. In our cohort, 155 patients underwent the improved PJ technique (group A), and 208 underwent standard invagination PJ (group B). Data on demographic characteristics, pathological nature, intraoperative factors, and postoperative complications, including POPF, were collected and analyzed. ResultsThere were no significant between-group differences in demographic characteristics (p > 0.05). The improved PJ technique was associated with a significantly lower incidence of clinically relevant POPF (CR-POPF) in the total cohort (11.6 % vs. 26.4 %, p < 0.001) and in the subgroup with high fistula risk scores (16.0 % vs. 38.6 %, p < 0.001). ConclusionThe improved invagination PJ technique reduces the incidence of CR-POPF and improves prognosis.

Identification of PANoptosis-based signature for predicting the prognosis and immunotherapy response in AML

BackgroundIn recent years, the incidence of acute myeloid leukemia (AML) has increased rapidly with a suboptimal prognosis. In AML, cell death is independent of tumorigenesis, tumor invasion, and drug resistance. PANoptosis is a newly discovered form of cell death that combines pyroptosis, apoptosis, and necroptosis. However, no studies have explored the role of PANoptosis-based signatures in AML. MethodsWe screened for PANoptosis-related genes and established a PANoptosis-risk signature using the least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. We combined TCGA, bulk RNA sequencing, and single-cell sequencing to investigate the correlation between candidate genes and the AML tumor microenvironment. ResultsThe PANoptosis risk signature effectively predicted prognosis with good sensitivity and specificity. The risk score emerged as an independent prognostic factor. Functional enrichment analysis of PANoptosis-related differentially expressed genes suggested that the risk score may be related to cell immunity. Patients with high-risk scores exhibited increased immune cell infiltration, implying a hot tumor immune microenvironment. The risk score was positively correlated with the immune scores and expression levels of immune checkpoints. Therefore, we identified three model factors, BIRC3, PELI1, and PRKACG, as predictors for immunotherapy efficacy. Single-cell sequencing analysis demonstrated that PELI1 and BIRC3 may participate in the regulation of the AML immune microenvironment. Finally, we performed a drug sensitivity analysis to target BIRC3 and PELI1 using molecular docking and molecular dynamics simulations. ConclusionOur study established and verified a PANoptosis risk signature to predict the survival and immunological treatment response in AML.