Random Cohort Research Articles

Beauty is in the eye of your cohort: Structured individual differences allow predictions of individualized aesthetic ratings of images.

In the last few years, there has been an increasing interest in computational models that are capable of predicting the aesthetic ratings of images based on objective image features. Given that aesthetic ratings vary across individuals, models that predict the average aesthetic ratings ignore the unique taste of an individual. In this paper, our goal is to better understand the individual differences in aesthetic ratings by investigating if individual differences follow structural rules or if taste is due to a random component of an individual's ratings. We address this question by using a collaborative filtering model that uses the similarities in ratings of a cohort of observers to predict individuals' ratings on a new set of images. Using Amazon Mechanical Turk, 299 online participants were instructed to rate how much they like a set of 50 art images. Using a subset of the images (40), we formed cohorts of individuals with similar ratings and used these cohorts to predict how each person would rate the remaining 10 images not included in the training set. The selected cohorts predicted individual ratings significantly better than random cohorts and outperformed predictions based on the mean image ratings. We also found that the optimal size was approximately 12% of the sample size. These results imply that individual differences in fact have an underlying structure that is consistent across the cohort and are not random. Using personality scores and subject backgrounds, we also looked at the subject characteristics of the cohorts and found that the participants' art background was the only significant factor. Finally, we explored whether the cohorts used particular visual features in a consistent way. For our small set of features, we didn't find any evidence for this. These results provide important insights into the sources of individual differences in aesthetic preferences and highlight the potential for computational models to improve predictions of individual preferences by leveraging structured individual differences rather than relying solely on population averages.

Random cohort effects and smooth structures for mortality modelling and forecasting: A mixed-effects Gaussian process time series approach

The issue of population ageing has become a critical challenge for many developed nations in recent decades, and urgent action is needed to address this concern. Despite numerous efforts have been made to tackle the risks associated with increased longevity, the problem remains unresolved. The Cairns-Blake-Dowd (CBD) model, widely recognised as a leading approach for mortality modelling at older ages, incorporates cohort effects parameters into its parsimonious design. This article proposes a new mixed-effects Gaussian process time series approach that not only considers random cohort effects but also ensures smoothness across age ranges. By adopting Gaussian process, this novelty allows the proposed method naturally accounts for all uncertainties of the estimated parameters without requiring any pre-specified constraints and provides more accurate results. Through two empirical applications using male and female mortality data, we demonstrate the exceptional capabilities of our approach, which outperforms the CBD models with cohorts in short-, mid-, and long-term forecasting of mortality rates from various developed countries. Our proposed approach offers a significant improvement in forecast accuracy and shows a valuable contribution to the field of cohort mortality modelling.

Influences of cerium oxide nanoparticles and salinity on common bean (Phaseolus vulgaris) growth, physiology, and root system architectural and anatomical traits

Engineered nanoparticles (ENPs) have emerged as global pollutants due to their extensive use across various industries, raising particular concerns in agricultural settings. This study addresses the understudied interactions between ENPs, specifically cerium oxide nanoparticles (CeO₂NPs), and sodium chloride (NaCl) in agricultural crops, within the context of widespread soil salinization. ‘Pinto’ common bean seedlings were cultivated in sand-filled pots under greenhouse conditions, following a completely randomized experimental design for one month. Four treatments were administered: (1) control with no NaCl and no CeO₂NPs, (2) 50 mM NaCl without CeO₂NPs, (3) 200 mg kg−1 CeO₂NPs without NaCl, and (4) a combination of 50 mM NaCl and 200 mg kg−1 CeO₂NPs. Weekly measurements were conducted, and a random cohort of 20 plants, including 5 from each treatment, was destructively sampled. At the experiment's conclusion, the final cohort was dissected into above- and below-ground organs to determine the concentrations of Ce and Na, and root scans were performed to analyze root system architectural traits. The results revealed significant differences in growth including root system architecture (including length, surface area, and volume), anatomical traits, biomass (fresh and dry), and vine length. Similarly, significant differences were observed in fluorescence; Ce and Na concentrations; electrolyte leakage, with the CeO2NPs + NaCl treatment having 3.3-fold more leakage than the control; and chlorophyll contents, with the CeO2NPs treatment having 3.3-fold more chlorophyll a than the NaCl treatment. Additionally, notable interactions between NaCl and CeO₂NPs were observed in root apoplastic barrier formation, vine length, Ce uptake, and chlorophyll content and fluorescence.

Technical note: An automated document verification tool in radiation oncology EMR: Application for LDR prostate brachytherapy.

This study aims to illustrate how a script-based automated tool can efficiently verify documentation for LDR prostate brachytherapy. An in-house Python-scripts-based tool was developed to automatically verify the specific checklists, aligned with our institutional practice guidelines for prostate seed implants (PSI). The scripts, compatible with our radiation oncology information system, could be executed with an optional web-based middleware to access and evaluate Aria documents. Optimized based on data from the previous 400 patients, the automated tool was applied to a random cohort of 50 LDR patients. It evaluated the adequacy of specific EMR documents by performing checks for data completeness, consistency, and allowable value range. We analyzed the efficiency of using this tool against conventional manual checks in two LDR processes: seed ordering and monthly audits for our PSI programs. The automated tool effectively performed chart checks on the involved PSI documents. Human errors, such as typos and inconsistent information, were identified in 7 out of 50 patients during the seed ordering process and in 2 out of 50 patients during the monthly audit. Meanwhile, this automation reduced the majority of manual chart-checking time by an average of 5 and 10 min per patient for these processes, respectively. The anticipated efficiency gains will continue to accrue as more check items are digitalized and assessable to the scripts. The implementation of an automated tool tailored for LDR prostate brachytherapy has demonstrated its efficiency benefits. Such an approach can help other clinics substantially enhance routine chart checks, periodic audits, and other applications in similar clinical settings.

The impact of heterogeneity on the analysis of platform trials with normally distributed outcomes

BackgroundA platform trial approach allows adding arms to on-going trials to speed up intervention discovery programs. A control arm remains open for recruitment in a platform trial while intervention arms may be added after the onset of the study and could be terminated early for efficacy and/or futility when early stopping is allowed. The topic of utilising non-concurrent control data in the analysis of platform trials has been explored and discussed extensively. A less familiar issue is the presence of heterogeneity, which may exist for example due to modification of enrolment criteria and recruitment strategy.MethodWe conduct a simulation study to explore the impact of heterogeneity on the analysis of a two-stage platform trial design. We consider heterogeneity in treatment effects and heteroscedasticity in outcome data across stages for a normally distributed endpoint. We examine the performance of some hypothesis testing procedures and modelling strategies. The use of non-concurrent control data is also considered accordingly. Alongside standard regression analysis, we examine the performance of a novel method that was known as the pairwise trials analysis. It is similar to a network meta-analysis approach but adjusts for treatment comparisons instead of individual studies using fixed effects.ResultsSeveral testing strategies with concurrent control data seem to control the type I error rate at the required level when there is heteroscedasticity in outcome data across stages and/or a random cohort effect. The main parameter of treatment effects in some analysis models correspond to overall treatment effects weighted by stage wise sample sizes; while others correspond to the effect observed within a single stage. The characteristics of the estimates are not affected significantly by the presence of a random cohort effect and/ or heteroscedasticity.ConclusionIn view of heterogeneity in treatment effect across stages, the specification of null hypotheses in platform trials may need to be more subtle. We suggest employing testing procedure of adaptive design as opposed to testing the statistics from regression models; comparing the estimates from the pairwise trials analysis method and the regression model with interaction terms may indicate if heterogeneity is negligible.

Social inequalities in medical appointment cancellations and reschedulings at the onset of the COVID-19 epidemic in France.

Inconsistent results are found regarding social inequalities related to healthcare appointment cancellations during the COVID-19 crisis. Whether rescheduling was associated with social status is unknown. By studying both cancellations and rescheduling, we comprehensively describe which social groups were affected by care disruption. First follow-up of a random population-based cohort was used, including 95118 people aged 18 or older at baseline and who live in France. Poisson and multinomial regressions were used to study social factors associated with experiencing both medical appointment cancellation by health professionals during the first COVID-19 lockdown, and rescheduling within six months. Among all individuals (including those without scheduled appointment), 21.1% reported cancellations initiated by healthcare professionals. Women, the richest, and those with a chronic disease were the most affected by these cancellations. Although 78.1% who had their appointment cancelled obtained a new appointment within six months, 6.6% failed to reschedule and 15.2% did not want to reschedule. While the oldest were more likely to reschedule, regardless of their health status, the poorest and those with multiple chronic diseases were less likely to do so. Difficulties in rescheduling revealed certain social groups were ultimately more penalized by the restriction of access to care during the first wave of the COVID-19 pandemic. Given that the poorest people, a social group that is in poorer health condition compared to other groups, were the most affected, our results raise questions about the ability of the healthcare system to reduce social health inequalities during a major health crisis.

Ultrasound screening of thyroid pathology in primary medical care in Bulgaria

Thyroid diseases are common and, in most cases, can be safely and effectively detected and treated in primary medical care. This article aimed to analyze and evaluate the rate of thyroid ultrasonographic abnormalities in a primary medical care practice in Bulgaria. The research was conducted from 2016 to 2021. A random cohort of patients undergone annual preventive screening was included. Demographic information (age and sex) was collected. The descriptions of the ultrasonographic findings were standardized based on the following parameters: deviations in shape, size, position of the thyroid gland, deviations from normal parenchymal echogenicity (hyper-, hypo-, and heteroechogenic parenchyma), presence and size of detectable formations, and presence of calcifications. The total number of participants in this study was 3 178. Of these, 60% (1 907/3 178) were women and 40% (1 271/3 178) were men. The average age of participants was 40.1 ± 11.3 years, and there was no significant difference between the males and females. Deviations from normal ultrasonographic findings were observed in 36.2% (1 151/3 178), with a frequency increasing with age. Detectable formations were seen in 19.7% (625/3 178) of the patients, and those larger than 1 cm accounted for 4.4% (139/3 178) of all cases and 22.2% of all formations (139/625). Calcifications were found in 0.5% (15/3 163). Over 1/3 of the performed thyroid ultrasounds revealed abnormalities. Thyroid ultrasonographic abnormalities were significantly more common in women compared to men, and their frequency increased with age.

Retention of En Route Cricothyroidotomy Skills in Novice Providers Following a Simulation-Based Mastery Learning Curriculum.

Surgical cricothyroidotomy (SC) is a vital skill that combat first responders must master as airway obstruction is the third most preventable cause of death on the battlefield. Degradation of skills over time is a known problem, and there is inadequate knowledge regarding the rate of SC skill retention. Our prior study showed that simulation-based mastery learning was effective in training 89 novices how to reliably perform an en route SC to mastery performance standards. This study aims to assess the durability of this skill by bringing participants back in 3 separate cohorts at 6, 12, or 24 months following the initial training to perform SC in the same test environment. This was a randomized prospective trial. Random cohorts of equal subjects who previously underwent SC simulation-based mastery learning training were selected to return at 6, 12, and 24 months to retest in the same en route medical evacuation (MEDEVAC) helicopter scenario. A total of 22, 14, and 10 subjects returned at 6, 12, and 24 months, respectively, due to Coronavirus-19 impacts and travel limitations. Participants in the 24-month cohort received a refresher training prior to retesting. All attempts were recorded and blindly graded using the same 10 item standardized SC checklist used in initial training. Our previous work found that mastery criteria for performing a SC were ≤40 seconds and completion of 9/10 items on the checklist. Outcome measures in this study were time to complete the procedure and percent of subjects who completed at least 9/10 items on the SC checklist. There was an increase in time required to complete the procedure compared to initial training in all three retesting cohorts (initial: median 27.50, interquartile range 25.38-31.07 seconds; 6 months: median 36.33, interquartile range 31.59-55.22 seconds; 12 months: median 49.50, interquartile range 41.75-60.75 seconds; 24 months: median 38.79, interquartile range 30.20-53.08 seconds; P < .0001, P < .0001, P = .0039). There was a decline in median value checklist scores compared to initial training in the 6- and 12-month retesting cohorts (initial: median 10.00/10, interquartile range 9.50-10.00; 6 months: median 8.00/10, interquartile range 6.75-9.00; 12 months: median 8.00/10, interquartile range 6.75-9.25; P < .0001, P < .001). There was no difference in median checklist scores between the initial and 24-month retesting scenario (initial: median 10.00/10, interquartile range 9.50-10.00; 24 months: 10.00/10, interquartile range 9.00-10.00; P= .125). There was a decrease in retention of skills as only 31.82% of subjects at 6 months and 14.29% at 12 months met the defined passing criteria of time to completion of ≤40 seconds and checklist score of ≥9/10. A brief refresher course several months prior to the 24-month cohort retesting greatly increased the retention of SC procedural skills, with 60% of subjects meeting the time and checklist criteria. This study showed that the skill required to perform a SC after initial mastery training does decay significantly. A brief refresher course can help increase retention of skills. Based on our findings SC skills should be refreshed at a minimum of every 6 months to assure optimal proficiency.

System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning

The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular clockwork. Nevertheless, how system-level SCN signals encode time of the day remains enigmatic. Here we show that population-level Ca2+ signals predict hourly time, via a group decision-making mechanism coupled with a spatially modular time feature representation in the SCN. Specifically, we developed a high-speed dual-view two-photon microscope for volumetric Ca2+ imaging of up to 9000 GABAergic neurons in adult SCN slices, and leveraged machine learning methods to capture emergent properties from multiscale Ca2+ signals as a whole. We achieved hourly time prediction by polling random cohorts of SCN neurons, reaching 99.0% accuracy at a cohort size of 900. Further, we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space, giving rise to bilaterally symmetrical ripple-like modular patterns. Individual modules represent distinctive time features, such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same module. These findings open a new paradigm in deciphering the design principle of the biological clock at the system level.

Prognosis and immunotherapy efficacy in dMMR&MSS colorectal cancer patients and an MSI status predicting model.

The inconsistency between mismatch repair (MMR) protein immunohistochemistry (IHC) and microsatellite instability PCR (MSI-PCR) methods has been widely reported. We aim to investigate the prognosis and the effect of immunotherapy in dMMR by IHC but MSS by MSI-PCR (dMMR&MSS) colorectal cancer (CRC) patients. A microsatellite instability (MSI) predicting model was established to help find dMMR&MSS patients. MMR and MSI states were detected by the IHC and MSI-PCR in 1622 CRC patients (ZS6Y-1 cohort). Logistic regression analysis was used to screen clinical features to construct an MSI-predicting nomogram. We propose a new nomogram-based assay to find patients with dMMR&MSS, in which the MSI-PCR assay only detects dMMR patients with MSS predictive results. We applied the new strategy to a random cohort of 248 CRC patients (ZS6Y-2 cohort). The consistency of MMR IHC and MSI-PCR in the ZS6Y-1 cohort was 95.7% (1553/1622). Both pMMR&MSS and dMMR&MSS groups experienced significantly shorter overall survival (OS) than those in dMMR by IHC and MSI-H by MSI-PCR (dMMR&MSI-H) group (hazard ratio [HR] = 2.429, 95% confidence interval [CI]: 1.89-3.116, p < .01; HR = 21.96, 95% CI: 7.24-66.61, p < .01). The dMMR&MSS group experienced shorter OS than the pMMR&MSS group, but the difference did not reach significance (log rank test, p = .0686). In the immunotherapy group, the progression-free survival of dMMR&MSS patients was significantly shorter than that of dMMR&MSI-H patients (HR = 13.83, 95% CI: 1.508-126.8, p < .05). The ZS6Y-MSI-Pre nomogram (C-index = 0.816, 95% CI: 0.792-0.841, already online) found 66% (2/3) dMMR&MSS patients in the ZS6Y-2 cohort. There are significant differences in OS and immunotherapy effect between dMMR&MSI-H and dMMR&MSS patients. Our prediction model provides an economical way to screen dMMR&MSS patients.

Plasma Metabolites and Life's Simple 7 in REGARDS.

The American Heart Association's Life's Simple 7 (LS7) is a health metric that captures important factors associated with cardiovascular and cerebrovascular health. Previous studies highlight the potential of plasma metabolites to serve as a marker for lifestyle and health behavior that could be a target for stroke prevention. The objectives of this study were to identify metabolites that were associated with LS7 and incident ischemic stroke and mediate the relationship between the two. Targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry was used to identify candidate metabolites in a stroke case-cohort nested within the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Weighted linear regression and weighted Cox proportional hazard models were used to identify metabolites that were associated with LS7 and incident ischemic stroke, respectively. Effect measures were based on a 1-SD change in metabolite level. Metabolite mediators were examined using inverse odds ratio weighting mediation analysis. The study comprised 1075 ischemic stroke cases and 968 participants in the random cohort sample. Three out of 162 metabolites were associated with the overall LS7 score including guanosine (β, -0.46 [95% CI, -0.65 to -0.27]; P=2.87×10-6), cotinine (β, -0.49 [95% CI, -0.70 to -0.28]; P=7.74×10-6), and acetylneuraminic acid (β, -0.59 [95% CI, -0.77 to -0.42]; P=4.29×10-11). Guanosine (hazard ratio, 1.47 [95% CI, 1.31-1.65]; P=6.97×10-11), cotinine (hazard ratio, 1.30 [95% CI, 1.16-1.44]; P=2.09×10-6), and acetylneuraminic acid (hazard ratio, 1.29 [95% CI, 1.15-1.45]; P=9.24×10-6) were associated with incident ischemic stroke. The mediation analysis identified guanosine (27% mediation, indirect effect; P=0.002), cotinine (30% mediation, indirect effect; P=0.004), and acetylneurminic acid (22% mediation, indirect effect; P=0.041) partially mediated the relationship between LS7 and ischemic stroke. We identified guanosine, cotinine, and acetylneuraminic acid that were associated with LS7, incident ischemic stroke, and mediated the relationship between LS7 and ischemic stroke.

Pioneering Arterial Hypertension Phenotyping on Nationally Aggregated Electronic Health Records

Background: Hypertension is frequently studied in epidemiological studies that have been conducted using retrospective observational data, either as an outcome or a variable. However, there are few validation studies investigating the accuracy of hypertension phenotyping algorithms in aggregated electronic health record (EHR) data. Methods: Utilizing a centralized repository of inpatient EHR data from Singapore for the period of 2019–2020, a new algorithm that incorporates both diagnostic codes and medication details (Diag+Med) was devised. This algorithm was intended to supplement and improve the diagnostic code-only model (Diag-Only) for the classification of hypertension. We computed various metrics (sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV)) to assess the algorithm’s effectiveness in identifying hypertension on 2813 chart-reviewed records. This pool was composed of two patient cohorts: a random sampling of all inpatient admissions (Random Cohort) and a targeted group with atrial fibrillation diagnoses (AF Cohort). Results: The Diag+Med algorithm was more sensitive at detecting hypertension patients in both cohorts compared to the Diag-Only algorithm (83.8 and 87.6% vs. 68.2 and 66.5% in the Random and AF Cohorts, respectively). These improvements in sensitivity came at minimal costs in terms of PPV reductions (88.2 and 90.3% vs. 91.4 and 94.2%, respectively). Conclusion: The combined use of diagnosis codes and specific antihypertension medication exposure patterns facilitates a more accurate capture of patients with hypertension in a database of aggregated EHRs from diverse healthcare institutions in Singapore. The results presented here allow for the bias correction of risk estimates derived from observational studies involving hypertension.

Exploring the presence of a sex-specific phenotype of autism spectrum disorder in a random cohort of males and females: a retrospective case note service audit

Purpose Recent research has proposed a specific female phenotype within autism spectrum disorder (ASD). It suggests females exhibit differences in social communication styles with higher levels of camouflaging and compensatory strategies, as well as variance in restrictive repetitive behaviours (RRBs); however, many existing studies have been based on either small, disproportionate or child and adolescent samples, leaving questions about the specific phenotype. This study aims to explore the sex difference and phenotype in a clinic sample of individuals diagnosed with autism. Design/methodology/approach A service evaluation of sex/ gender differences on 150 historical ASD assessment reports (75 males, 75 females) using a 103-item questionnaire developed from a quantitative review of existing literature was undertaken. Findings Females camouflaged more significantly than males in five different areas (thinking how to act next, preparing conversation in advance, making lists of prompts/social responses, wearing a mask/acting, less monotone voice); however, these were not maintained in post-analysis correction. Originality/value This study points the evidence towards a different phenotype of Autism that is more common in women than men rather than a unique female phenotype.

The External Carotid Artery and the Styloid Process.

The external carotid artery (ECA) is typically regarded as coursing between the styloid muscles to continue into the parotid space. The anatomical possibility of an ECA with an ascending parapharyngeal trajectory continuing posteriorly to an elongated styloid process (ESP), thus retrostyloid, to the parotid space is overlooked. It was, therefore, aimed to document the prevalence of this retrostyloid variant of the ECA's course. We investigated a retrospective random cohort of 160 archived CT angiograms of 97 males and 63 females aged between 47 and 76. The presence of an ESP and the retrostyloid course of the ECA were bilaterally documented. An ESP was identified in 99/320 sides (30.94%), regardless of the ECA course. In the overall group, we obtained 35% null cases for the two variables on the right and 34.06% for the left. ESPs were identified in 8.75% on the right side and 10.31% on the left. The ECAs had retrostyloid courses in 6.25% on the right side and 5.63% on the left. Thus, of the 320 ECAs documented on both sides, 221 (69.06%) had no retrostyloid courses, and we did not identify any ESP in those cases. ESPs were detected in 19.06% of the sides but without retrostyloid ECAs, and retrostyloid courses of the ECAs were detected in 11.88%. The possibility of a retrostyloid course of the ECA should not be ignored. An ESP may misinform the surgeon about the main carotid artery located immediately deep to it.

Place of care in the last three years of life for Medicare beneficiaries

BackgroundMost older adults prefer aging in place; however, patients with advanced illness often need institutional care. Understanding place of care trajectory patterns may inform patient-centered care planning and health policy decisions. The purpose of this study was to characterize place of care trajectories during the last three years of life.MethodsLinked administrative, claims, and assessment data were analyzed for a 10% random sample cohort of US Medicare beneficiaries who died in 2018, aged fifty or older, and continuously enrolled in Medicare during their last five years of life. A group-based trajectory modeling approach was used to classify beneficiaries based on the proportion of days of institutional care (hospital inpatient or skilled nursing facility) and skilled home care (home health care and home hospice) used in each quarter of the last three years of life. Associations between group membership and sociodemographic and clinical predictors were evaluated.ResultsThe analytic cohort included 199,828 Medicare beneficiaries. Nine place of care trajectory groups were identified, which were categorized into three clusters: home, skilled home care, and institutional care. Over half (59%) of the beneficiaries were in the home cluster, spending their last three years mostly at home, with skilled home care and institutional care use concentrated in the final quarter of life. One-quarter (27%) of beneficiaries were in the skilled home care cluster, with heavy use of skilled home health care and home hospice; the remaining 14% were in the institutional cluster, with heavy use of nursing home and inpatient care. Factors associated with both the skilled home care and institutional care clusters were female sex, Black race, a diagnosis of dementia, and Medicaid insurance. Extended use of skilled home care was more prevalent in southern states, and extended institutional care was more prevalent in midwestern states.ConclusionsThis study identified distinct patterns of place of care trajectories that varied in the timing and duration of institutional and skilled home care use during the last three years of life. Clinical, socioregional, and health policy factors influenced where patients received care. Our findings can help to inform personal and societal care planning.

E-GLR Score Predicts Early Graft Loss in Adult Live-Donor Liver Transplantation.

This study aimed to analyze risk factors and develop a predictive model for early allograft loss due to early graft dysfunction (EGD) in adult live-donor liver transplantation (LDLT). Data of patients who underwent LDLT from 2011 to 2019 were reviewed for EGD, associated factors, and outcomes. A homogeneous group of 387 patients was analyzed: random cohort A (n = 274) for primary analysis and random cohort B (n = 113) for validation. Of 274 recipients, 92 (33.6%) developed EGD. The risk of graft loss within 90 days was 29.3% and 7.1% in those with and without EGD, respectively (P < 0.001). Multivariate logistic regression analysis determined donor age (P = 0.045), estimated (e) graft weight (P = 0.001), and the model for end-stage liver disease (MELD) score (0.001) as independent predictors of early graft loss due to EGD. Regression coefficients of these factors were employed to formulate the risk model: Predicted (P) early graft loss risk (e-GLR) score = 10 × [(donor age × 0.052) + (e-Graft weight × 1.681) + (MELD × 0.145)] - 8.606 (e-Graft weight = 0, if e-Graft weight ≥640 g and e-Graft weight = 1, and if e-Graft weight < 640 g). Internal cross-validation revealed a high predictive value (C-statistic = 0.858). Our novel risk score can efficiently predict early allograft loss following graft dysfunction, which enables donor-recipient matching, evaluation, and prognostication simply and reliably in adult LDLT.

Genome‐wide identification of modifiers of age‐at‐onset for Alzheimer’s disease in African American populations

AbstractBackgroundSeveral studies have attempted to identify genes for age‐at‐onset (AAO) of Alzheimer’s disease (AD) through genome‐wide linkage and genome‐wide association studies (GWAS). While these efforts have thus far focused predominantly on non‐Hispanic white (NHW) populations, we present here the first GWAS to identify genetic contributors to AAO in African Americans (AA) using AA genotype and phenotype data from the Alzheimer’s Disease Genetics Consortium (ADGC).MethodWe combined data from 13 AA prospective and case‐control ADGC datasets, excluding family‐based datasets. Genotype data underwent standard quality control and were imputed to the TOPMed R5 reference panel using the Michigan Imputation Server. Data were merged across cohorts using QCTOOL and GTOOL, filtering out variants with MAF≤0.005). We performed two analyses: case‐only linear mixed‐model regression with AAO as outcome (LMM); and survival analysis using Cox proportional‐hazards frailty modeling (COXPHF) with time‐to‐AD‐onset (AAO in cases and censoring of controls at age‐at‐last‐exam). Both models were adjusted for sex, principal components capturing population substructure, and APOE‐ε4 dosage with a random cohort effect.ResultWe examined 2,262 AA AD cases, including 1,561 females (69%) with mean (SD) AAO of 77.7 (8.1) years. The APOE‐adjusted COXPHF analyses identified twelve genome‐wide significant regions (P&lt;5×10−8), the most significant in ABCA7 (P = 3.57×10−10), known to be associated with AD risk in AAs. In the LMM analysis, we observed strong novel associations with variants in CCDC141 on chr2q31.2 (Pmin = 2.93×10−9). In silico analyses of LD structure and functional potential suggest SESTD1, a gene involved in synaptic regulation, as driving the CCDC141 locus signal. Nine of 12 COXPHF loci were driven by African‐specific variants (MAF&lt;0.0002 in gnomAD Non‐Finish Europeans). These significant loci identified in the AA COXPHF or LMM analyses were not significant (P&gt;0.05) in equivalent analyses in NHW ADGC cohorts (9,220 AD cases/10,350 controls; Li et al. Alz Dement 2023), except for the ABCA7 locus (NHW P&lt;0.0002).ConclusionIn a large ADGC African American dataset, we confirmed AAO associations in the APOE region and ABCA7 and observed evidence for potential novel AD AAO loci including SESTD1; many of which might be African‐ancestry specific.

Glasgow Coma Scale on admission as predictor of neurological sequelae at discharge and acute respiratory failure in patients with heatstroke.

Transient neuronal dysfunction may occur in most brain regions with heatstroke (HS). This study aimed to explore the prognostic significance of initial Glasgow Coma Scale (GCS) scores in HS. Retrospective data regarding HS were obtained from six hospitals. The primary outcome was neurological sequelae at discharge. Secondary outcomes included acute respiratory failure (ARF) and intensive care unit (ICU) admission. Logistic regression models and random forest imputation were used to assess the independent association between GCS score and outcomes. Interaction and stratified analyses of body temperature (BT) at 0.5hours were also conducted. Receiver operating characteristic curves and decision curve analysis were used to estimate prognostic values. Of 206 patients, 44 (21.36%) had neurological sequelae at discharge. The mean ± standard deviation initial GCS score was 8.17 ± 4.05. After adjustment for confounders, GCS, as a continuous variable, was significantly related to neurological sequelae at discharge [odds ratio (OR): 0.65; 95% confidence interval (CI): 0.50-0.85; P = 0.002], ARF (OR: 0.76; 95% CI: 0.66-0.87; P = 0.001), and ICU admission (OR: 0.68; 95% CI: 0.53-0.87; P = 0.003). These relationships were consistent in the random forest imputation cohort. The OR between GCS and neurological sequelae at discharge was much lower (P = 0.048) in participants with BT at 0.5hours ≤39°C than in those with BT at 0.5hours >39°C. The GCS and National Early Warning Score (NEWS) had similar prognostic ability for all outcomes, whereas the net benefits were greater with the GCS compared with the NEWS. Initial GCS score was an independent prognostic factor for neurological sequelae at discharge in HS. Rapid cooling played a positive role in this relationship. Key messages What is already known on this topic Brain damage caused by heatstroke (HS) can be transient or result in irreversible injury. Early recognition of those at risk of death or developing neurological complications is very important for improving the outcomes of HS. What this study adds Initial Glasgow Coma Scale (GCS) score was an independent prognostic factor for neurological sequelae at discharge, acute respiratory failure, and intensive care unit (ICU) admission in HS. Rapid cooling played a positive role in this relationship. How this study might affect research, practice, or policy The GCS upon emergency department admission can be a useful predictor of prognosis in patients with HS.

Acetylglutamine Differentially Associated with First-Time Versus Recurrent Stroke.

Approximately one-quarter of strokes occur in individuals with prior stroke. Despite the advancement in secondary stroke prevention, the long-term risk of recurrent stroke has remained unchanged. The objective of this study was to identify metabolite risk markers that are associated with recurrent stroke. We performed targeted metabolomic profiling of 162 metabolites by liquid chromatography-tandem mass spectrometry in baseline plasma in a stroke case-cohort study nested within the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, an observational cohort study of 30,239 individuals aged 45 and older enrolled in 2003-2007. Weighted Cox proportional hazard models were used to identify metabolites that had a differential effect on first-time versus recurrent stroke using an interaction term between metabolite and prior stroke at baseline (yes or no). The study included 1391 incident stroke cases identified during 7.1 ± 4.5 years of follow-up and 1050 participants in the random cohort sample. Among 162 metabolites, 13 candidates had a metabolite-by-prior stroke interaction at a p-value <0.05, with one metabolite, acetylglutamine, surpassing the Bonferroni adjusted p-value threshold (p for interaction = 5.78 × 10-5). In an adjusted model that included traditional stroke risk factors, acetylglutamine was associated with recurrent stroke (HR = 2.27 per SD increment, 95% CI = 1.60-3.20, p = 3.52 × 10-6) but not with first-time stroke (HR = 0.96 per SD increment, 95% CI = 0.87-1.06, p = 0.44). Acetylglutamine was associated with recurrent stroke but not first-time stroke, independent of traditional stroke risk factors. Future studies are warranted to elucidate the pathogenesis of acetylglutamine and recurrent stroke risk.

Insulin resistance probability score and incident cardiovascular disease.

Insulin resistance (IR) is associated with cardiovascular disease (CVD). However, insulin immunoassay variability and scarce research of the elderly have hindered the adoption of IR assessment for CVD prevention. We asked whether the probability of having IR [p(IR)]-derived from insulin and C-peptide mass-spectrometry assays-was associated with CVD in the elderly. A random cohort was drawn from MPP, a population-based study of the elderly. After excluding those with missing data, CVD, or diabetes, 3645 participants (median age=68) remained. During follow-up (13.3 years), 794 incident CVD events were observed. p(IR)>80% (n=152) compared with p(IR)≤80% was associated with incident CVD (HR=1.51, 95% CI 1.12-2.05, p=0.007) and CVD or all-cause mortality (HR=1.43, 95% CI 1.16-1.77, p=0.0009) after adjusting for age, sex, hypertension, smoking, HDL-cholesterol, total cholesterol, triglycerides, BMI, and prediabetes. High p(IR) was associated with >50% greater risk of incident CVD. IR assessment in the elderly may be warranted.