Stratification Method Research Articles

CMR-derived left atrial strain predicts adverse events in dilated cardiomyopathy

Abstract Background Dilated cardiomyopathy (DCM) is associated with an increased risk of major adverse cardiovascular events (MACE). However, current risk stratification methods are imperfect. Left atrial global longitudinal strain (LA GLS) is an increasingly acknowledged predictive parameter, yet its potential role in DCM is not well defined. Purpose This study aims to investigate the prognostic role of cardiac magnetic resonance (CMR)-derived LA GLS for the occurrence of MACE in patients with DCM. Methods A retrospective, longitudinal, single-centre CMR study of DCM patients was conducted. DCM was defined according to current guidelines. Clinical data was collected from electronic medical records and a blinded CMR analysis was performed. LA GLS was derived from CMR two-chamber cine images by a semiautomatic method and was categorized according to its median value. A composite MACE endpoint was defined as: heart failure (HF) (including unplanned HF visit or hospitalization, CRT implant, LVAD implant, heart transplantation), ventricular arrhythmias (including sudden cardiac death, ventricular fibrillation, sustained and non-sustained ventricular tachycardias, appropriate ICD shocks), systemic embolisms and/or all-cause death. The HF endpoint was also independently analysed due to its prevalence. Cox regression analysis was performed. Results A total of 181 DCM patients were included. The mean age was 55±15 years, and 34% were female. The indexed left ventricular end diastolic volume was 126±43 mL/m2, left ventricular ejection fraction was 35±13% and 67 patients (37%) had late gadolinium enhancement. Mean LA GLS was 22.2±16.3%. After a median follow-up of 3,6 (IQR 2,1- 5,6) years, 52 patients (29%) experienced at least one MACE: 32 (18%) HF events, 9 (5%) ventricular arrhythmias, 2 (1%) embolic strokes and 11 (6%) deaths. LA GLS was significantly lower in patients with MACE (17.7±12.7% vs 24.0±17.2%, p=0.019) and HF events (14.6±9.7% vs 23.9±16.9%, p=0.004) compared to those without. Univariable and multivariable Cox regression analyses for MACE are shown in Table 1A. LA GLS was independently associated with MACE (HR 1.03; 95% CI: 1.01-1.05; p= 0.048; higher risk when lower LA GLS). Patients with a LA GLS below the median (18.7%) showed a 2-fold increased risk of MACE (Figure 1A). Univariable and multivariable Cox regression analyses for HF events are shown in Table 1B. LA GLS (HR 1.04; 95% CI: 1.01-1.08; p= 0.036) and LVESVi (HR 1.01; 95% CI: 1.01-1.03; p= 0.025) were independently associated with HF events. Patients with a LA GLS < 18.7% showed a 3-fold increased risk of HF (Figure 1B). Conclusions CMR-derived LA GLS is a predictor of outcomes in DCM beyond established prognostic variables. Patients with normal LA GLS show a better prognosis. If confirmed in larger studies, LA GLS could be used to enhance current risk stratification in DCM. Table 1A-B Figure 1A-B

Left atrial strain identifies low-risk hypertrophic cardiomyopathy patients: a CMR study

Abstract Background Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of major adverse cardiovascular events (MACE), however, current risk stratification methods are imperfect. Left atrial global longitudinal strain (LA GLS) is an increasingly acknowledged predictive parameter, yet its potential role in HCM is not well defined. Purpose This study aims to investigate the prognostic role of cardiac magnetic resonance (CMR)-derived LA GLS for the occurrence of MACE in patients with HCM. Methods A retrospective, single-centre, CMR study of HCM patients was conducted. CMR images were analysed by two blinded investigators. LA GLS was derived from CMR two-chamber cine images by a semiautomatic method, and was categorized according to its median value. The endpoint was a composite of major adverse cardiovascular events (MACE), including all-cause death, sudden cardiac death (SCD), sustained and non-sustained ventricular tachycardias, appropriate implantable cardiac defibrillator shocks, heart failure hospitalization, syncope, stroke and new-onset atrial fibrillation. Cox regression analysis was performed. Results A total of 135 HCM patients were included, mean age was 57 years ± 17 and 41% were female. Average maximal wall thickness (MWT) was 17.7 ± 4.6 mm, 39% had left ventricular outflow obstruction (LVOTO) and 46% had positive late gadolinium enhancement (LGE). After a mean follow-up of 6.6 ± 3.4 years, 61 patients (45%) experienced the composite endpoint. Figure 1 shows the clinical and CMR differences according to the occurrence of MACE. LA GLS was significantly lower in patients with MACE compared to those without (26.4 ± 15% vs 30.4 ± 14%, p=0.046). Multivariate Cox regression analysis revealed that an LA GLS below the median value of 28.2% showed a tendency to be independently associated with MACE (HR 1.57, 95% CI: 0.877-2.814, p=0.128). Additionally, the presence of LGE (HR 2.2, CI: 1.233-3.801, p=0.007) and an left ventricular ejection fraction (LVEF) < 50% (HR 5.4, 95%, CI: 1.451-19.831, p=0.012) were also independently associated. Among low risk HCM patients (LVEF > 50%, MWT < 30 mm, absence of LGE and/or LVOTO), LA GLS demonstrated an additional prognostic role: those with an LA GLS above the median value exhibited a more favourable prognosis (Figure 2A-D). In fact, among patients considered at low risk according to the European Society of Cardiology HCM risk score (< 4% risk of SCD at 5 years) (n = 83), LA GLS < 28.2% (HR 2.6, 95% CI:1.037-6.461, p=0.042) and LVEF < 50% (HR 15.1, 95% CI: 2.877- 79.530, p=0.001) remained the only variables independently associated with MACE. Conclusions CMR-derived LA GLS is a predictor of outcomes in HCM beyond established imaging prognostic factors. Particularly, LA GLS appears to be useful in risk-stratifying low risk HCM patients: those with a normal LA GLS show a favourable prognosis. If confirmed in larger studies, LA GLS could be used to individualise HCM management.

Relationship between Topographic Wetness Index and Soil Physical Properties in Cikapundung Sub-watershed Using Geographic Information Systems

Purpose: This study aimed to analyze the relationship between Topographic Wetness Index (TWI) and soil physical properties (permeability, porosity, bulk density, and soil moisture content) and their spatial distribution in the Cikapundung Sub-watershed. Methods: A survey method was conducted through descriptive, correlation, and interpolation approaches. Thirty soil samples were collected based on a two-way stratification method using TWI and slope gradient. TWI was derived from Digital Elevation Model (DEM) data using GIS. Soil physical properties were analyzed in laboratory and their spatial distribution was mapped using interpolation techniques. Results: TWI showed varying degrees of correlation with soil physical properties: significant positive correlation with soil permeability (r = 0.37), weak negative correlation with soil moisture content (r = -0.30), and very weak correlations with bulk density and soil porosity (r = -0.03 and r = 0.03). Spatial analysis revealed heterogeneous distribution patterns of soil physical properties across the sub-watershed. Conclusion: TWI can only be effectively used as a single predictor for soil permeability, but not for bulk density, porosity, and soil moisture content in the Cikapundung Sub-watershed. This suggests the need for additional environmental parameters when predicting these soil physical properties.

Cardiovascular Disease and Dialysis: A Review of the Underlying Mechanisms, Methods of Risk Stratification, and Impact of Dialysis Modality Selection on Cardiovascular Outcomes

Cardiovascular Disease and Dialysis: A Review of the Underlying Mechanisms, Methods of Risk Stratification, and Impact of Dialysis Modality Selection on Cardiovascular Outcomes

Insights into the use of DNA content in head and neck squamous cell carcinoma as a method for patient stratification and targeted therapy: Revisiting old concepts and exploring new possibilities.

This review aimed to emphasize the implications of DNA content in head and neck squamous cell carcinoma (HNSCC), focusing on its predictive value, role in patient stratification, and potential as a therapeutic target for this malignancy. A narrative review of the literature was conducted through electronic database searches. In conventional HNSCC, aneuploid tumors are associated with increased lymph node metastasis, locoregional recurrences, poor response to radiotherapy and chemotherapy, and worse prognosis. Few studies specifically address the role of DNA content in young HNSCC patients. These studies reveal that young patients exhibit high DNA content abnormalities, suggesting significant genomic instability and potential genetic differences compared to older patients. Regarding HPV and DNA content, no difference was found between HPV-associated and HPV-independent tumors. More research is needed to understand the role of DNA content in histological subtypes, surgical margins, and targeted therapy. This review highlights the findings related to DNA content in HNSCC, suggesting its usefulness in patient stratification and outcome prediction.

Risk Stratification in HPV-Associated Oropharyngeal Cancer: Limitations of Current Approaches and the Search for Better Solutions

The rising incidence of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC) necessitates advancements in risk stratification to optimize treatment outcomes and improve the quality of life for patients. Despite its favorable prognosis compared to HPV-negative OPSCC, current clinical staging and biomarkers, such as p16 status, are limited in their ability to distinguish between high- and low-risk patients within HPV-associated OPSCC. This limitation results in the overtreatment of low-risk patients, exposing them to unnecessary toxicity, and the undertreatment of high-risk patients who require more aggressive interventions. This review critically evaluates current stratification methods, including clinical assessments, de-escalation trials, and candidate molecular biomarkers for risk stratification. Emerging approaches such as immune markers, viral genomic integration patterns, and other molecular markers offer promising avenues for enhanced prognostic accuracy. By integrating advanced risk stratification methods, tailored treatment approaches may one day be developed to balance oncologic efficacy with reduced treatment-related morbidity. This review underscores the need for continued research into predictive biomarkers and adaptive treatment strategies to better address the diverse risk profiles of HPV-associated OPSCC patients.

Liver Injury as a Risk Factor for Post-Traumatic Venous Thromboembolism.

Venous thromboembolism (VTE) remains a major source of morbidity and mortality in severely injured patients despite current methods of risk stratification and prophylaxis, suggesting incomplete understanding of VTE risk factors. Given the liver's role in coagulation, we hypothesized that liver injury (LI) is associated with increased rates of VTE in severely injured patients. The American College of Surgeons Trauma Quality Improvement Project database (TQIP) 2017-2021 was retrospectively reviewed for patients with a maximum abdominal Abbreviated Injury Score (AIS) ≥ 4 with or without LI. Transfers, burns, all deaths, and patients < 18 years of age were excluded. Logistic regression was performed to assess the independent effect of LI on development of pulmonary embolism (PE) and deep venous thrombosis (DVT) while controlling for potential confounding variables. In 44,506 patients, there were 1,736 (3.9%) 890 (2.0%), and 18,642 patients (41.9%) with DVT, PE, and LI, respectively. After controlling for potential confounders, LI was independently associated with PE (aOR 1.279 [95% CI 1.088-1.504]) but was not associated with DVT (aOR 1.011 [95% CI 0.897-1.140]). In severely injured patients, LI is an independent predictor of PE, but not DVT, suggesting LI is the source of either emboli or a more complex locally prothrombotic focus leading to downstream thrombi in the lung without causing upstream systemic venous thrombi. Further work should focus on elucidation of mechanisms including the portal venous blood coagulation profile, endothelial injury in the liver, and the potential for stasis of venous blood traversing an injured liver as well as the role for including LI in VTE risk stratification.

High-sensitivity Troponin I Measurement in a Large Contemporary Cohort: Implications for Clinical Care.

Contemporary methods of cardiovascular risk stratification are frequently inaccurate. Biomarkers such as high-sensitivity troponin I (hsTnI) have the potential to improve risk stratification. However, uncertainties exist regarding factors that determine hsTnI concentration. Our aim was to investigate the prevalence of elevated hsTnI in a large, contemporary Canadian cohort and describe the effect of comorbidities on hsTnI concentration. We report a large dataset of 41,602 visits in which hsTnI was measured routinely in ambulatory outpatients. hsTnI was remeasured in 28% of patients, with a mean time between measurements of 387 days (IQR 364-441). Low-, medium-, and high-risk categories were created based on hsTnI cutoffs for each sex. Laboratory data, blood pressure, and anthropomorphic measures were extracted from the electronic medical record Results: Remeasurement of hsTnI did not change risk category in 92.7% of cases. Male sex, higher HDL-C, higher Hgb A1c, decreasing eGFR, and increasing systolic blood pressure were significant predictors of increased hsTnI. High non-HDL-C and the use of statins were associated with lower hsTnI. The inverse relationship between hsTnI and non-HDL-C was partially corrected when the confounding effect of statin therapy was considered. Model fit was poor (adjusted R-Squared = 0.0091). Traditional cardiovascular risk factors were predictors of serum hsTnI levels, however a significant amount of the variance in hsTnI cannot be explained by these factors alone. This suggests that hsTnI adds additional information that is not provided by traditional risk stratification methods and supports ongoing study of hsTnI as a biomarker for cardiovascular risk stratification.

Association of Frailty with Intraoperative Complications in Older Patients Undergoing Elective Non-Cardiac Surgery.

Background: Frailty is increasingly being recognized as a risk factor for adverse outcomes in older surgical patients undergoing surgery. We investigated the association between frailty and intraoperative complications using multiple frailty assessment tools in older patients undergoing elective intermediate- to high-risk non-cardiac surgery. Methods: This retrospective cohort study included 637 older patients scheduled for elective non-cardiac surgery. Frailty was assessed using the Clinical Frailty Scale (CFS), FRAIL scale, and modified Frailty Index-11 (mFI-11). The predictive ability of frailty tools was analyzed and compared using the area under the receiver operating characteristic curve (AUC). Results: Frailty was significantly associated with higher intraoperative complication rates (FRAIL scale: p = 0.01; mFI-11: p = 0.046). Patients considered frail using the mFI-11 were more likely to have unplanned intensive care unit admissions (p < 0.001). Those classified as frail by the FRAIL scale and mFI-11 had significantly higher rates of vasopressor/inotrope use (p = 0.001 and p = 0.005, respectively) and mechanical ventilation (p = 0.033 and p = 0.007, respectively). In the univariate analysis, frailty measured using the FRAIL scale was significantly associated with intraoperative complications (odds ratio [OR], 2.41; 95% confidence interval [CI]: 1.33-4.38; p = 0.004); this association was not significant in the multivariate analysis (adjusted OR, 1.69; 95% CI: 0.83-3.43; p = 0.148; AUC = 0.550). Atrial fibrillation, hemoglobin levels, anesthesia type, and surgical subspecialty were stronger predictors of intraoperative complications. Conclusions: Frailty assessments demonstrate the limited predictive ability for intraoperative complications. Specific comorbidities, surgical techniques, and anesthesia types play more critical roles. Comprehensive preoperative evaluations integrating frailty with broader risk stratification methods are necessary to enhance patient outcomes and ensure safety.

Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.

Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (RA), and Sjögren's syndrome. Traditional evaluations often underestimate the associated cardiovascular disease (CVD) and stroke risk in women having AD. Vitamin D deficiency increases susceptibility to these conditions. CVD risk prediction in AD can benefit from surrogate biomarker for coronary artery disease (CAD), such as carotid ultrasound. Due to non-linearity in the CVD risk stratification, we use artificial intelligence-based system using AD biomarkers and carotid ultrasound. Investigate the relationship between AD and CVD/stroke markers including autoantibody-influenced plaque load. Second, to study the surrogate biomarkers for the CAD and gather radiomics-based features such as carotid intima-media thickness (cIMT), and plaque area (PA). Third and final, explore the automated CVD/stroke risk identification using advanced machine learning (ML) and deep learning (DL) paradigms. Analysed biomarker data from women with AD, including carotid ultrasonography imaging, clinical parameters, autoantibody profiles, and vitamin D levels. Proposed artificial intelligence (AI) models to predict CVD/stroke risk accurately in AD for women. There is a strong association between AD duration and elevated cIMT/PA, with increased CVD risk linked to higher rheumatoid factor (RF) and anti-citrullinated peptide antibodies (ACPAs) levels. AI models outperformed conventional methods by integrating imaging data and disorder-specific factors. Interdisciplinary collaboration is crucial for managing CVD/stroke in women with chronic autoimmune diseases. AI-based assisted risk stratification methods may improve treatment decision-making and cardiovascular outcomes.

Heart or Grace Score for Diagnostic and Risk Stratification in Acute Coronary Syndrome Patients

Some studies found that HEART score is better than GRACE score either as a rule-in method for myocardial infarction or as a risk stratification. However, GRACE score was also found to have better discriminatory ability as a prognostic model for patients with myocardial infarction. This study aims to evaluate whether the HEART and GRACE scores have equal capabilities either as a diagnostic method for myocardial infarction or risk stratification to predict inhospital Major Adverse Cardiovascular Events (MACE) in Acute Coronary Syndrome (ACS) patients at Adam Malik Hospital. This research is a retrospective and prospective observational study. Retrospective data was collected from all medical records of ACS patients from January to December 2022. Prospective data was collected by consecutive sampling until 46 samples were fulfilled from October 2023 at Adam Malik Hospital. Samples included in the research analysis were those who met the inclusion criteria. To compare each score, we use the area under the receiver-operating characteristics (AUC) method. As a conclusion, we found that HEART score is superior to GRACE score as a diagnostic method with an AUC of 0.903, a cutoff of 6.5, sensitivity of 86%, and specificity of 80%. The GRACE score is superior to the HEART score as a risk stratification with an AUC of 0.719, a cutoff of 128.5, a sensitivity of 66%, and a specificity of 65%.

Breast Arterial Calcification on a Screening Mammogram: A Potential Cardiovascular Risk Stratification Tool in Women.

Breast arterial calcification (BAC) is a common benign finding on a screening mammogram. Additionally, BAC is a type of medial calcification known as Mönckeberg medial calcific sclerosis, which differs from the intimal calcification seen in patients with coronary artery disease (CAD). Recently, BAC has appeared as a new cardiovascular risk stratification method. Studies have indicated a potential link between BAC and cardiovascular risk factors, particularly coronary artery calcification (CAC), as observed in coronary computed tomography. However, the association between BAC and myocardial ischemia and angiographic-proven CAD remains controversial. The usefulness of BAC during mammography as a potential screening tool for CAD has been the subject of uncertainty and debate for many years. This article reviews the current literature on BAC and its association with CAC, myocardial ischemia, and angiographic-proven CAD on both invasive and coronary computed tomography. Cardiovascular outcomes, current limitations, and future investigation and recommendations are also explored and discussed.

Baseline Tumor Burden Assessed With AI‐Guided PET/CT Total Metabolic Tumor Volume (TMTV) and LDH Levels Predict Efficacy of CAR‐T in Aggressive B‐Cell Lymphoma

ABSTRACTDisease burden is a critical determinant of outcomes in CAR‐T therapy for B‐cell lymphomas, and one of the most widely used techniques for its assessment is Total Metabolic Tumor Volume (TMTV) measured via [18F]FDG PET/CT. Biological parameters may further refine the risk profile. We analyzed baseline [18F]FDG PET/CT scans from 40 patients treated with CAR‐T, using an AI‐based automated segmentation algorithm to determine TMTV. Our analysis identified that a baseline TMTV greater than 48.4 cm³ and elevated LDH independently predicted progression‐free survival (PFS) after CAR‐T therapy (HR 4.28, p = 0.007, and HR 8.20, p &lt; 0.001, respectively). We then proposed a 0‐to‐2 risk score, assigning one point each for elevated TMTV and elevated LDH. All patients with a score of two experienced a PFS of less than 90 days following CAR‐T infusion. Among the remaining patients, those with 0 points versus 1 point demonstrated a 3‐month PFS of 100% versus 85%, a 6‐month PFS of 92% versus 53%, and a 12‐month PFS of 83% versus 53%, respectively. Importantly, patients with high baseline TMTV who achieved a TMTV reduction to less than 1.99 cm³ by day 30 had a PFS of 66%, significantly better compared to those who did not achieve this reduction. AI‐guided TMTV assessment, combined with LDH levels, provides a rapid and sensitive method for risk stratification at the bedside, which could help optimize patient management prior to CAR‐T therapy.

An inflammatory prognostic scoring system to predict the risk for adults with acute coronary syndrome undergoing percutaneous coronary intervention

BackgroundThis study aimed to investigate the value of the inflammatory prognostic score (IPS) system for predicting the risk of all-cause major adverse cardiovascular events (MACEs) and cardiac-related MACEs in patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention (PCI).MethodsOverall, 1384 patients with ACS who underwent PCI between January 2016 and December 2018 were consecutively enrolled. Demographic characteristics and related laboratory results for 11 inflammatory markers were collected. Least absolute shrinkage and selection operator (LASSO)-COX regression, Kaplan– Meier, restricted cubic spline (RCS), receiver operator characteristic curve (ROC), time-dependent ROC, and Cox hazard proportional regression were applied to explore the values of individual and IPS parameters.ResultsBased on the LASSO analysis, albumin (ALB) and monocyte-to-lymphocyte ratio (MLR) were included in the construction of the IPS system. A higher IPS was associated with a significantly worse long-term prognosis in the Kaplan–Meier analysis (log-rank p < 0.001). The Cox proportional hazards model demonstrated that the IPS was an independent risk factor for patients with ACS undergoing PCI. In addition, the IPS remained an independent prognosticator compared to the lowest tertiles. The time-dependent ROC showed satisfactory values for the long-term prognosis of different MACEs. Additionally, RCS showed a linear association with IPS, all-cause MACEs, and cardiac-related MACEs.ConclusionsA higher IPS level was associated with an increased risk in patients with ACS undergoing PCI, suggesting that the IPS may be a useful method for risk stratification in the assessment of the long-term prognosis of ACS.

Comparison of cardiovascular risk prediction in type 1 diabetes: an Australian viewpoint.

Cardiovascular disease (CVD) is a significant burden in individuals with type 1 diabetes mellitus (T1DM). Yet the optimal method of CVD risk stratification remains uncertain. We found that the new Australian CVD risk calculator could overestimate risk category compared with the Steno Type 1 Risk Engine and underestimate risk category compared with the new Swedish/Scottish prediction tool, both of which were validated for T1DM. More research is needed to derive a CVD risk assessment pathway for individuals with T1DM in Australia.

Advancements in MELD Score and Its Impact on Hepatology.

There continues to be an ongoing need for fair and equitable organ allocation. The Model for End-Stage Liver Disease (MELD) score has evolved as a calculated framework to evaluate and allocate patients for liver transplantation objectively. The original MELD score has undergone multiple modifications as it is continuously scrutinized for its accuracy in objectively representing the clinical context of patients with liver disease. Several refinements and iterations of the score have been developed, including the widely accepted MELD-Na score. In addition, the most recent updated iteration, MELD 3.0, has been created. The MELD 3.0 calculator incorporates new variables such as patient sex and serum albumin levels and assigns new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is anticipated that the use of MELD 3.0 scores will reduce overall waitlist mortality and enhance access for female liver transplant candidates. However, despite the emergence of the MELD score as one of the most objective measures for fair organ allocation, various countries and healthcare systems employ alternative methods for stratification and organ allocation. This review article will highlight the origins of the MELD score, its iterations, the current MELD 3.0, and future directions for managing liver transplantation organ allocation. LAY SUMMARY: Organ donation is crucial for the management of patients unwell with liver disease, but organs must be allocated fairly and equitably. One method used for this is the Model for End-Stage Liver Disease (MELD) score, which helps objectively decide which patient is a candidate for liver transplant. Over time, the MELD score has been refined to better reflect patients' needs. For example, the latest version, MELD 3.0, now considers factors like nutrition and gender. This should ensure that more patients, especially females, are candidates and receive appropriate access to liver transplantation. However, not every country uses the MELD score. Some countries have created their own scoring systems based on local research. This review will explain where the MELD score came from, how it has changed, the current characteristics of the MELD 3.0 score, and what the future might hold for organ allocation in liver transplants.

Evaluating the interchangeability of blood‐based biomarkers and amyloid‐PET for identifying patients with Alzheimer’s pathology

AbstractBackgroundPresence of amyloid pathology is used to identify patients who would benefit from novel amyloid‐targeting therapies for Alzheimer’s disease (AD). Whilst PET tracers are considered the gold standard for establishing the presence of amyloid pathology, they are costly and not widely accessible. Blood‐based biomarkers, if interchangeable with PET, could help negate such an inequitable barrier to treatment. This study assesses the agreement and interchangeability between blood‐based biomarkers and amyloid‐PET.MethodBioHermes participants with MCI or AD‐dementia and available amyloid‐PET evaluations as well as blood‐based biomarker results for PrecivityAD (C2N) and/or P‐tau217 (research use MSD, Lilly) were included. Agreement (PPA, NPA, OPA, PPV, NPV) between amyloid‐PET and blood‐based biomarker stratification as well as the non‐inferiority (Figure 1) of blood‐based biomarkers to amyloid‐PET for patient identification were evaluated. All thresholds and methods for stratification were pre‐specified. Two‐threshold stratification for the blood‐based biomarkers were implemented.Result537 participants with PrecivityAD and amyloid‐PET (mean‐age 73.2 years, 54.0% Female, 85.3% White, 47.3% amyloid‐PET positive) and 531 participants with P‐tau217 and amyloid‐PET (74.0 years, 53.9% Female, 85.3% White, 46.5% amyloid‐PET positive) were included. There was moderate to high agreement between the blood‐based biomarkers and amyloid‐PET visual read, Table 1. Higher agreement with amyloid‐PET visual read was achieved when participants between two‐thresholds were removed (and would require confirmatory CSF or PET evaluations). Generally, the P‐tau217 (MSD, Lilly) blood‐based biomarker demonstrated higher agreement with amyloid‐PET visual read in comparison to the Aβ blood‐based PrecivityAD test. Both blood‐based biomarkers, removing participants between the two‐thresholds, met criteria for non‐inferiority to amyloid‐PET clinical trial criteria for selecting patients with amyloid‐pathology, Table 2.ConclusionA clinically available plasma test (PrecivityAD, C2N) as well as a research use P‐tau‐217 assay (MSD, Lilly) were both able to rule in patients that would also be selected by amyloid PET (PPV 86% and 88%, respectively). New plasma diagnostics that incorporate P‐tau217 or other more sensitive markers may be more accurate than Aβ blood‐based tests for identifying amyloid pathology. Results support the hypothesis that blood‐biomarkers may be interchangeable with amyloid‐PET criteria for selecting patients who are suitable for and would benefit from treatment with amyloid‐targeting therapies.

Unsupervised online reaction time test improves estimation of cognitive function in a large sample of cognitively‐asymptomatic older adults

AbstractBackgroundFinding low‐cost, accessible methods to detect people at risk of preclinical Alzheimer’s disease (AD) is a research priority for neuroprotective drug development and clinical trials. Sub‐clinical asymptomatic decline in episodic memory is a proxy measure of preclinical AD and there is emerging evidence that analysis of motor patterns using laboratory apparatus may detect this stage. There has been little investigation of whether self‐administrated simple hand motor tests using personal computers in an unsupervised environment can detect preclinical AD. This study evaluated how home‐based reaction time tests predict cognitive performance in a sample of cognitively asymptomatic older adults.Method894 community participants (66.2 +/‐ 7.46 years old, 71.0 % female) who self‐reported an absence of cognitive symptoms were recruited from the ISLAND cohort study. In an unsupervised environment such as their home, they completed a simple reaction time test and a five‐choice reaction time test from the TAS Test website, and validated online cognitive tests (CANTAB) of episodic memory, working memory and executive function. Reaction time was measured in milliseconds. Test failure was defined as a delay of &gt; 2000 milliseconds. We fitted hurdle linear mixed models to examine associations between reaction time, and test failure, with cognitive performance, adjusted for choice (simple or 5‐choice).ResultHigher episodic and working memory errors, and worse executive function scores were associated with test failure (episodic memory log‐odds = 0.135, p &lt; 0.001, working memory log‐odds = 0.130, p = 0.002, and executive function log‐odds= 0.132, p &lt; 0.001). There was no significant association between cognitive test scores and reaction time on successful trials (episodic memory p = 0.438, working memory and executive function models would not converge).ConclusionTest failure in brief self‐administered online reaction time tests were associated with cognitive test performance across three domains, in a cognitively asymptomatic older cohort. This provides a potential low‐cost and brief home‐based method for risk stratification of enriched cohorts for further assessment.

Unveiling rhabdomyosarcoma: A rare cause of ischialgia

Abstract Rhabdomyosarcoma (RMS) represents a rare subset of mesodermal malignancies characterized by skeletal muscle differentiation, exhibiting a notably low incidence among adults and demonstrating inferior prognosis compared to pediatric counterparts. The 5- and 10-year overall survival rates were determined to be 30% and 18%, respectively, with a median age of onset at 46.5 years and median overall survival duration of 2.3 years. Current challenges in RMS research encompass optimizing local control, managing systemic disease, refining risk stratification methods, and elucidating disease progression patterns. While aggressive therapeutic interventions remain imperative, novel and individualized treatment modalities are imperative to enhance long-term outcomes. This research reported an elderly female patient presenting persistent lower back pain, persisting over several months, despite seeking medical consultation from multiple sources. Subsequent diagnostic investigations confirmed the diagnosis of rhabdomyosarcoma, denoting the relatively rare etiology of said initial symptoms. Hence, it is imperative to reconsider many differential diagnoses in the case of ischialgia.

Integrating Ward’s Clustering Stratification and Spatially Correlated Poisson Disk Sampling to Enhance the Accuracy of Forest Aboveground Carbon Stock Estimation

In forest resource surveys, using sampling methods to estimate aboveground carbon stock (ACS) can significantly reduce survey costs. This study improves the accuracy of ACS estimation by optimizing the stratified sampling design. The sampling process was divided into two stages: stratification and intra-stratum sampling. For stratification, remote sensing features were used as stratification variables, and a spatial clustering stratification method was introduced. For intra-stratum sampling, a composite method, Spatially Correlated Poisson Disk Sampling (SCPDS), was proposed. Using Random Forest (RF) and the sample points selected by SCPDS, the ACS was estimated and compared with traditional sampling methods for Pinus densata in Shangri-La, Yunnan, China. The results showed that (1) by selecting effective stratification variables (e.g., texture features), the required sample size was reduced by up to 19.35% compared to that of simple random sampling; (2) the Ward clustering method greatly improved stratification heterogeneity; (3) for intra-stratum sampling, the SCPDS method ensured spatial independence within strata, particularly at low sampling rates (1%–5%), where its error was significantly lower than that of other methods, indicating greater stability and improved accuracy; (4) the SCPDS-based model achieved the best fitting accuracy, with R2 = 0.886. The total carbon stock of Pinus densata using RF was 7,872,787.5 t, closely matching forest management inventory (FMI) data. Through sampling, even with a relatively small sample size, the representative plots can still accurately reflect ACS estimates that are consistent with those derived from large-scale plot surveys. Thus, the optimized stratified sampling method effectively reduced sampling costs while significantly enhancing the stability and accuracy of the results.