Split Sample Research Articles

Drivers of disaster planning among African-American households

PurposeThe paper seeks to explore the drivers of disaster planning in African-American households. While the paper is exploratory, the authors attempt to dialogue with substantial theoretical and applied research around vulnerability and disaster. Race, ethnicity and vulnerability are issues deeply entangled with American disaster preparedness and response. In this study, the authors hope to illuminate the threads which bind them together and contribute to a more nuanced understanding of the relationship between race, ethnicity, class and preparedness.Design/methodology/approachData for this project come from a disaster planning question placed on the 2020 Collaborative Multiracial Post-Election Survey (CMPS). The authors analyze a split sample of around 5,000 African-American households descriptively and with multinomial logistic regression.FindingsDisaster planning among African-American households is a product of past experiences, concern about other hazards, social trust and gender identity. These results are similar to other findings within the study of household preparedness and help to advance the understanding of predictors within the African-American community. Key drivers such as income, education level, gender identity, social trust and perceptions of other risks are consistent with previous studies.Originality/valueThis project is the first to examine issues of disaster planning utilizing a national sample of African-American households via the one-of-a-kind 2020 CMPS.

A Predictive Model Based on Machine Learning for Early Progression/Relapse of Follicular Lymphoma

Introduction:Management of follicular lymphoma (FL) improved dramatically in the last decade, and progression/relapse of disease within 24 months (POD24) is now established as a predictor for poor survival. Risk prediction of early POD (E-POD) prior to the start of therapy may enhance clinical management and research strategies. We aimed to establish a comprehensive model based on machine learning (ML) that could predict the E-POD of FL patients for earlier identify such patients earlier. Methods: In this study, patients with a diagnosis of FL at the Shandong Provincial Hospital between January 1, 2010, to May 1, 2023, were identified retrospectively. All patients met the following criteria: pathologically confirmed with grades 1-3A FL and no previous treatment for FL. Model building was performed on a 70% split sample based on ML algorithms, and with 30% held for internal testing. Model performance was evaluated using the ROC curve, accuracy, precision, and f1-score. Furthermore, we compared the features of FL patients with early (<2 years) and late POD (relapsing after 5 years of starting treatment, L-POD). This study was in accordance with the Declaration of Helsinki and it was approved by the Medical Ethical Committee of the Shandong Provincial Hospital. All patients were obtained for the collection of informed consent at their first visit. Results: Of the included 224 patients, 45 (20.1%) had at least one POD. E-POD occurred in of the 29 (64.4%) evaluable patients and 6 (13.3%) had late POD (relapsing after 5 years of starting treatment, L-POD), In our center, the median age at the time of the FL diagnosis was 49 years (range 19-82), and the median length of follow-up was 28 months (range 3-120). Most patients were diagnosed with advanced disease (80.8%) and had grade 1-2 disease (75.9%). 75 cases (33.9%) had bone marrow participation and 63 cases (28.1%) with Ki-67≥30%. To establish a scoring system for predicting E-POD, we selected 34 variables for served as the input candidate features, including sociodemographic, clinical, and immunohistochemistry data, and used lymphoma E-POD (yes or no) as the output variable. In 14 models based on ML algorithms, the best models were RF Classifier (AUC: 0.83, Accuracy: 89.5%). To improve the performance, it was optimized after the complete construction of the model. Finally, the RF Classifier demonstrated AUC and accuracy as follows: 0.96, and 92.3% and we calculated the recall, precision, and F1 scores based on the confusion matrix as follows: 84.1%, 97.4%, and 90.3%, respectively. We evaluated the performance of prediction models built with data in a validation cohort and found the performance of the model was similar in both cohorts. Based on this RF Classifier, we selected relative variables important out of the multiple clinical and laboratory blood markers to predict E-POD ( Fig. 1A). Meanwhile, we analyzed the Pearson correlation coefficients (r) between 20 statistically meaningful biomarkers to reduce the complexity of the model ( Fig. 1B). To further screen for prognostic biomarkers, the top ten risk factors from the three best-performing models were integrated. The five biomarkers were completely involved in these three modules, including adenosine deaminase (ADA), β2-macroglobulin (β2-MG), C-reactive protein (CRP), aspartate transaminase (AST), and D-dimer. Additionally, we also found a significant difference in OS between the clusters among FL patients (p<0.05). Among 224 patients with FL, 45 (20.1%) patients experienced recurrence and progression. Besides 23 (60.5%) cases with E-POD, there are 6 (15.8%) patients who had L-POD. In comparison with those who experienced E-POD, L-POD patients showed a trend toward a better outcome, and a more favorable risk profile at presentation: lower pathological grade (1-2), anemia, and no mutation of the CARD11. Conclusion: We established a prognostic model to identify a subgroup of patients at high risk of E-POD based on AI analysis. This model utilizes objective variables easily and reliably measured at diagnosis which makes it easier for clinicians to predict the E-POD risk of FL and dynamically monitor changes during treatment. Further validation will hopefully facilitate the incorporation of these simple biomarkers into clinical decision-making tools to prevent adverse outcomes and promote personalized treatment options.

Stated Preferences with Survey Consequentiality and Outcome Uncertainty: A Split Sample Discrete Choice Experiment

Stated Preferences with Survey Consequentiality and Outcome Uncertainty: A Split Sample Discrete Choice Experiment

Prediction of acute kidney injury following coronary artery bypass graft surgery in elderly Chinese population

BackgroundAcute kidney injury (AKI) is a common and serious complication following coronary artery bypass graft (CABG) surgery. Advanced age is an independent risk factor for the development of AKI, and the incidence of AKI in the elderly increases more rapidly than that in younger patients. This study aimed to develop and validate the risk prediction model for AKI after CABG in elderly patients.MethodsPatients were retrospectively recruited from January 2019 to December 2020. AKI after CABG was defined according to the criteria of Kidney Disease Improving Global Outcomes (KDIGO). The entire population was divided into the derivation set and the verification set using random split sampling (ratio: 7:3). Lasso regression method was applied to screen for the variables in the derivation set. Decision curve analysis (DCA) and receiver operating characteristic (ROC) curves were plotted to analyze the predictive ability of the model for AKI risk in the derivation set and the verification set.ResultsA total of 2155 patients were enrolled in this study. They were randomly divided into the derivation set (1509 cases) and the validation set (646 cases). Risk factors associated with AKI were selected by Lasso regression including T2DM, diabetes mellitus type intraoperative use of intra-aortic ballon pump (IABP), cardiopulmonary bypass (CPB), epinephrine, isoprenaline, and so on. The model was established by Lasso logistic regression. The area under the ROC curve (AUC) of the model for the derivation set was 0.754 (95% CI: 0.720 − 0.789), and that for the validation cohort was 0.718 (95% CI: 0.665 − 0.771).ConclusionIn this study, the model with significant preoperative and intraoperative variables showed good prediction performance for AKI following CABG in elderly patients to optimize postoperative treatment strategies and improve early prognosis.

A-370 High Rates of Potassium, Chloride and Hemoglobin Discordances in Split Samples Drawn within 1 minute and Analyzed on Point of Care GEM 5000 and Central Laboratory Roche Cobas 8000 and Sysmex Analyzers

Abstract Background Previously, we used serial intensive care unit patient data as well as split sample glucose comparisons to characterize the analytical performance of the GEM 4000 and its tendency to generate outliers in the early to late evening. In this work, we summarize the discordance rate of 2 years of split specimens (minimally 17 700 patient care samples) that were drawn within 1 minute of each other and analyzed on the GEM 5000, Roche Cobas 8000 and Sysmex analyzers. Methods Two years (2020 and 2021) of GEM-central laboratory Cobas 8000 and Sysmex comparisons were obtained for potassium, sodium, chloride, glucose and hemoglobin (Sysmex). We used the GEM's iQM2 control (drift) limits to define discordant differences between the GEM and Roche/Sysmex analyses. We graphed the differences vs time of day and applied Dahlberg's formula to derive the magnitude of the running variation of the differences. Results The Table summarizes the drift limits, the number of comparisons performed over the two-year period and the average incidence of discordances over the 24 hour period. What strikes the casual observer is the asymmetric distribution of the discordances. More subtle is the lower frequency of potassium and hemoglobin discordances in the early morning and the higher frequency in the late afternoon and evening. The Dahlberg running variation graphs readily demonstrate this diurnal pattern. Conclusion The GEM 5000 overcalls increases in potassium, decreases in chloride and increases in hemoglobin. We recommend that other laboratories verify these findings.

A-004 Analytical Assessment and Expanded Stability Studies of the Abbott Alinity i STAT High Sensitivity Troponin-I Assay

Abstract Background The Mount Sinai Health System has recently integrated the Abbott Alinity i STAT High Sensitivity Troponin-I Assay (HS-Trop) into its “Suspected Acute Coronary Syndrome Algorithm”. Prior to doing so, a comprehensive evaluation of the assay was performed. In particular, the manufacturer’s specifications state that HS-Trop samples (plasma) are stable for 8 h at room temperature (RT), and that plasma and red cells must be separated by centrifugation within 30 min of draw. This centrifugation time window and RT storage requirements are not practical for most large hospital laboratories. Sample delivery, accessioning, and centrifugation are often greater than 30 min, and in most laboratory automation systems, sample storage modules are refrigerated. RT storage would require the removal of the HS-Trop sample from the automation line, and storing the sample elsewhere. This adds additional work to laboratory staff, and makes add-on testing challenging. As such, refrigerated storage and a longer centrifugation time window would be ideal. In this study, we sought to assess the analytical performance of the HS-Trop assay, and validate expanded centrifugation and stability requirements. Methods Inter and Intraday precision was assessed through replicate measurements (n = 10) of low, mid, and high Technopath Quality Controls. Linearity was determined through triplicate analysis of Maine Standards linearity standards. Accuracy was assessed through split sample (n = 40) analysis on two distinct reagent lots. Stability was assessed in centrifuged samples at RT and 4 °C through analysis at 0, 4, and 8 h time points, with an additional 16 h time point assessed at 4 °C. Unspun sample stability was assessed at RT at 0, 2, 4, and 8 h time points. LoQ was assessed through a sensitivity profile, by performing a serial dilution spanning 1:2–1:128, measuring each dilution in triplicate on 10 different days. Reference range verification was performed through the assessment of 20 sex-stratified normal donor samples. Results Intraday precision afforded CVs of 5.1%, 5.6%, and 2.9% for the low, mid, and high controls, respectively, while Interday precision at low, mid, and high controls yielded CVs of 4.3%, 6.3%, and 3.3%. Accuracy assessment resulted in a slope of 0.928, y-intercept of 6.613, and R2 = 0.9943. Linearity was confirmed between 12.3 and 4216.5 ng/mL with a slope of 0.997, y-intercept of 0.261. Spun and Unspun sample stability was confirmed at RT and 4 °C for a maximum of 8 h, affording percent difference values with respect to the initial time point of <20%. Stability studies failed at the 16 h time point. The LoQ was determined to be 4.4 ng/L at 20% CV. The reference range was verified at: Males, <34, and Females, <18 ng/L. Conclusions Our study has shown the Abbott HS-Trop assay performs well analytically, with acceptable precision, accuracy, linearity, and analytical sensitivity for the assessment of HS-Trop. The manufacturer-specified reference range was confirmed. Our study has validated and confirmed an expanded stability and centrifugation window, which will allow for the easy integration of the assay into large hospital networks, and for its use in many laboratory automation systems.

B-041 Evaluation of a Nuclear Magnetic Resonance Spectroscopy-Based Method for Estimating Glomerular Filtration Rate Using Creatinine, Cystatin C, Myo-Inositol, and Valine

Abstract Background Timely and accurate monitoring of renal dysfunction is critical for patients with chronic kidney disease (CKD). Most equations currently used for estimating glomerular filtration rate (GFR) incorporate serum levels of creatinine and/or cystatin C. Here, we evaluate a recently introduced method for estimating GFR that uses nuclear magnetic resonance spectroscopy (NMR) to measure creatinine, myo-inositol, and valine in combination with cystatin C measured by immunoassay, and patient’s age and sex (eGFRNMR). Methods Serum creatinine, valine, and myo-inositol measurements were performed simultaneously by an NMR assay on a Bruker Avance III HD 600 MHz NMR instrument (Bruker Corporation, MA). Cystatin C testing was performed using an immunoturbidimetric assay (Diazyme Laboratories, CA) on a cobas 8000 analyzer (Roche Diagnostics, IN). Within-run and between-day precision studies were performed across 5 days. Method comparison was carried out by testing 86 split serum samples from adult individuals against the numares AG GFR (NMR) assay. Of the 86 samples, 20 were spiked with various concentrations of creatinine, myo-inositol, and valine to reach a wide range of GFR results. An additional method comparison study was performed against Mayo Clinic Laboratories (Rochester, MN) on 59 serum samples from adult patients that had already been tested using the same assay. Measured GFR (mGFR) was also performed on these patients by Mayo Clinic Laboratories using urinary iothalamate clearance. Results Within-run and between-day coefficients of variation (%CV) for eGFRNMR did not exceed 6%. The eGFRNMR measurement range was confirmed at 10 to 157 mL/min/1.73 m2 based on verified analytical measurement ranges of creatinine (0.28–9.8 mg/dL), myo-inositol (39–430 µmol/L), and valine (30–1250 µmol/L). Method comparison studies against both numares AG and Mayo Clinic Laboratories demonstrated excellent concordance (r2 = 0.95 and r2 = 0.97, respectively) and minimal bias (4.1% and −0.3%, respectively) with results ranging from 21 to 157 mL/min/1.73 m2. When the 59 patients who had their GFR measured were staged by their mGFR results according to the CKD classification ranges of <15, 15–29, 30–44, 45–59, 60–89, and ≥90 mL/min/1.73 m2, eGFRNMR showed higher classification concordance with mGFR (69%) than the CKD-EPI 2021 creatinine-cystatin C equation (63%). Conclusion Our evaluation confirms the excellent analytical and clinical performance of the recently introduced eGFRNMR assay, supporting its integration into clinical practice for improved estimation of GFR.

A-268 Evaluation of a Real-Time Multiplex PCR Assay for Simultaneous Detection of Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis in Urine Specimens

Abstract Background Infections with Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Trichomonas vaginalis (TV) are among the most prevalent and treatable sexually transmitted diseases in the US. Currently, most available testing methods require patient samples to be split between CT/NG and TV assays. Here, we evaluate performance characteristics of the Seegene Novaplex STI Essential Assay, a real-time multiplex polymerase chain reaction assay for concurrent amplification and detection of multiple pathogens including CT, NG, and TV. Methods To prepare urine samples for extraction, 1 mL of each sample was centrifuged at 13 000 rpm for 15 min. The supernatant was discarded and the pellet was rehydrated in 190 µL of saline. Nucleic acid extraction was performed on a CyBio® FeliX liquid handler (Analytik Jena, Germany) using MagMAX™ Viral/Pathogen Nucleic Acid Isolation Kit (Thermo Fisher Scientific, MA). PCR amplification and detection were performed using Seegene Novaplex STI assay (Seegene Inc, South Korea) on a CFX96™ System (Bio-Rad Laboratories, CA). The assay utilizes Seegene MuDT™ technology that allows detection of multiple targets in a single channel without melting curve analysis. For method validation, precision studies were performed within-run and over 5 days. Limits of detection were verified by spiking known negative urine samples with CT/NG standards from Exact Diagnostics (Bio-Rad Laboratories, CA) and TV standards from ZeptoMetrix® (Antylia Scientific, IL). Method comparison was carried out by extracting and analyzing split patient urine samples against cobas® CT/NG assay (Roche Diagnostics, IL) and Solana® Trichomonas assay (Quidel, CA) performed by a reference laboratory. Additional accuracy studies were performed by spiking 20 negative patient samples with variable concentrations of the three pathogens. Results Within-run and between-day precision studies demonstrated consistent and reproducible results for all pathogens. Limit of detection was established at 10 copies/mL for CT and NG and 10 cells/mL for TV. Results of the spike-and-recovery studies were consistent with expected results for all three targets across evaluated concentrations. Patient correlation studies demonstrated 100% agreement with results obtained by the reference laboratory for both NG (32 total samples, 11 positive) and TV (22 total samples, 4 positive), and 96% agreement for CT (29 total samples, 10 positive). Conclusion The Seegene Novaplex STI Essential Assay offers a rapid and reliable method for detecting CT, NG, and TV in urine samples. The capability of the assay to detect multiple targets in a single sample well improves efficiency and turnaround time.

A-374 Analytical Performance Assessment and Comparison of Point of Care Testing (POCT) Devices for Blood Lipids Measurements

Abstract Background Cardiovascular diseases (CVDs) are the leading cause of death in the U.S. and worldwide. According to the World Health Organization (WHO), worldwide, 85% of CVD deaths are due to heart disease and strokes, and over 75% occur in low- and middle-income countries (LMICs). Early detection and treatment are key to preventing the consequences of CVD. Point-of-care testing (POCT) devices offer alternatives to screening large populations for CVD risk. Although POCT are increasingly used for screening, only few information is available about their accuracy and reliability. Methods Eight POCT devices for blood lipids that previously successfully participated in the CDC CVD Biomarker Standardization Programs were used in this preliminary study. The analytical performance for all eight devices was assessed using split sample comparisons to the CDC reference measurement procedures for measurements performed in whole blood (WB) and serum. Specifically, the accuracy of total cholesterol (TC) was determined in WB and serum. The accuracy of high-density lipoprotein-cholesterol (HDL-c), and low-density lipoprotein-cholesterol (LDL-c) was determined in serum. The precision of TC, HDL-c, LDL-c, and triglycerides (TG) was determined in WB and serum. Results The reference values of the specimens from 20 donors ranged between 154–279 mg/dL, 36.9–109 mg/dL, and 71.1–182 mg/dL for TC, HDL-c, and LDL-c in serum, and between 145–210 mg/dL for TC in WB. Preliminary assessments found that the mean bias for each instrument ranged from -7.86%–13.82% and from -11.90%–3.24% for TC in WB and serum, respectively. For serum HDL-c samples, the mean bias ranged from −6.81%–15.43%. The mean bias for serum LDL-c samples ranged from −22.40% to 3.08%. For three devices, approximately 30% of the WB measurements and approximately 50% of the serum measurements were reported as outside of the measurement range. The mean imprecision for each instrument ranged from 2.2%–13.75% and from 1.88%–11.76% for TC in WB and serum, respectively. For HDL-c, the mean imprecision ranged from 5.36%–23.21% and from 2.30% to 26.69% in WB and serum, respectively. The mean imprecision ranged from 4.82%–20.34% and from 3.06%–20.54% for LDL-c in WB and serum, respectively. For TG, the mean imprecision ranged from 5.78%–23.91% and from 1.71%–11.02% in WB and serum, respectively. Conclusion These preliminary findings about the analytical performance of POCT devices indicate notable differences in accuracy and precision for lipids measured in WB and serum, with serum measurements being more likely within performance requirements than WB measurements. Some devices appear to be more likely to report values outside the measurement range even though reference values are within the measurement range of the device. Further studies to verify these preliminary findings with more individual donor samples are underway.

A-207 Analytical Validation of Helena SPIFE Touch to Determine ApoB-Containing Lipoproteins Lp(a)-P, LDL-P and VLDL-P

Abstract Background Elevated Lp(a) is an independent risk factor for atherosclerotic (ASCVD) events and associates with aortic stenosis. Accurate immunochemical measurement of Lp(a) is complicated by heterogeneity of Lp(a) molecular size. The objective of this study was to validate the analytical performance of an electrophoretic assay for measurement of ApoB-containing lipoprotein particles including Lp(a)-P, LDL-P, and VLDL-P and to compare results to other standard clinical methods. Method Lp(a)-P, LDL-P, and VLDL-P were quantified by electrophoretic serum separation followed by immuno-staining with an ApoB antibody using the SPIFE Touch (Helena Laboratories, Beaumont, TX). Stability was evaluated by comparison to results at time zero (n = 10). Precision was assessed by 5 measurements twice daily for five days. Limit of quantitation (LoQ) was determined by 20 replicate measurements. Linearity was assessed by mixing high and low concentrations at various ratios. Accuracy was assessed by split sample comparison (n = 126) with Helena Laboratories. Lp(a)-P and LDL-P results were compared to nuclear magnetic resonance (NMR) using a Bruker Ascend 600 NMR (Bruker, Billerica, MA) with AXINON software (numares, AG, Regensberg, Germany) (n = 114). Lp(a)-P is included with LDL-P by NMR. Therefore, the SPIFE Lp(a)-P + LDL-P was compared to NMR LDL-P. SPIFE Lp(a)-P was compared directly to Roche cobas c501 Lp(a) immunoassay calibrated to molar units (Roche Diagnostics, Indianapolis, IN) (n = 126). Results The analytical performance of Lp(a)-P, LDL-P, and VLDL-P measured on the SPIFE Touch met all acceptance criteria. Bias to the reference method was <20% with R2 > 0.98. All analytes were stable 14 days refrigerated and 14 days frozen. Lipoprotein particle measurements on SPIFE Touch correlated to those obtained by both NMR and Roche assays. Conclusion The analytical performance of the SPIFE Touch for measuring the concentration of ApoB-containing lipoproteins is acceptable. Further studies are needed to determine clinical implications and utility compared to NMR and Roche assays.

The representation of child-parent relation: validation of the Italian version of the child-parent relationship scale (CPRS-I).

This study proposes a psychometric validation of the Italian version of the Child-Parent Relationship Scale (CPRS) developed by Pianta in 1992. Based on attachment theory, the scale assesses parents' relationship perceptions with their own child and comprises three scales: Closeness, Conflict, and Dependency. A sample of 501 parents (188 fathers and 313 mothers) completed 30 items of the Italian version of the Child-Parent Relationship Scale (CPRS-I) online, but only 437 answered 85% of the entire protocol; hence, the analyses only focused on 437 participants. The first analysis of the original theoretical model revealed poor fit, item loadings, and internal consistency. Therefore, a follow-up analysis was conducted. Exploratory and confirmatory analyses with a split sample (EFA = 218; CFA = 219) confirmed the original three-factor structure of the Italian sample, although some items were eliminated. The validity and reliability of the Italian version of the CPRS-I were also verified by correlating the above three factors with measures of adult attachment styles and children's internalizing and externalizing behaviors. The CPRS-I showed significant correlations with all tested constructs, in line with those found by Driscoll and Pianta for the short form of the scale. Our results confirm that the CPRS-I has the same structure as the original scale; therefore, it can be a useful tool for assessing parents' perceptions of their relationship with their children. The implications for educational and clinical settings are also discussed.

Complementarity between product and process innovation in small and micro-enterprises in Johannesburg, South Africa

ABSTRACT Innovation is important to firms’ productivity, competitiveness, agility, resilience and growth. The success of a firm’s innovation strategy depends in part on how it combines and absorbs different innovation activities. Using the Crépon-Duguet-Mairesse (CDM) structural model, this paper analyses complementarity between product and process innovation for the case of small and micro manufacturing firms in Johannesburg, South Africa. The empirical analysis utilises rich new firm-level survey data that, unlike most firm surveys, includes micro-sized firms as well as informal enterprises. Our results show strong evidence of complementarity between product and process innovations in their effects on firm performance. The results suggest that firm size, capital intensity, firm age, innovation expenditure and financial constraints are key variables associated with complementarity. We extend the specifications used in previous studies to take account of the contextual setting, with split samples by firm formality, ownership and size. We find evidence of complementarity in formal firms only. Our results also show stronger effects of complementarity in micro-firms and foreign-owned firms. The findings have relevance for promoting innovation and for enhancing the effects of innovation on firm performance among micro- and small enterprises (MSEs) in a developing country context.

Related party lending and rural bank risk: Evidence during the Covid-19 period

This study aims to investigate bank lending behaviors during the Covid-19 period and further to examine the effect of related party lending (RPL) on the rural bank risk. We posit there is significant change on the lending growth and related party lending proportion during this period. We utilize 730 rural banks in Indonesia using panel data approach from 2019 to 2022. Utilizing panel data estimations to test the impact of RPL on risk and to further investigate its interaction with the COVID-19 using system GMM, we document that RPL is negatively associated with rural bank risk proxied by loan loss provision as ex-ante credit risk and positively associated with Z-Score as bank default risk. Moreover, the COVID-19 weaken the relationship between related party lending and rural bank risk. These results provide new insight into understanding risk management implementation for minimizing these risks. We also adopt several proxies and a split sample analysis to check for the robustness. Finally, we seek for lesson learned from the crisis and propose some implication for bank and relevant authorities.

Reevaluating the Binge Eating Scale cut-off using DSM-5 criteria: analysis and replication in preoperative metabolic and bariatric surgery samples.

Metabolic and bariatric surgery is effective for sustained weight loss, but binge eating disorder (BED) can be associated with poorer outcomes and lead to weight regain. A common measure used to screen for BED is the Binge Eating Scale (BES). A BES cut-off score of ≥17 previously identified patients who have a high likelihood of meeting criteria for BED. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), lowered the threshold for meeting criteria for BED, and the psychometrics of the BES need to be reevaluated. The objective of the current investigation is to evaluate whether alternative cut-scores on the BES result in better classification of BED based on the DSM-5 revision of the the BED diagnostic criteria. Academic medical hospital in the Midwestern United States. Patients (n =1133) seeking metabolic and bariatric surgery were randomly split into 2 samples for validation and replication. The validation sample consisted of 561 patients (30.1% men, 35% non-White). The replication sample consisted of 572 patients who were demographically similar to the first random split sample (e.g., 25.3% men, 34.4% non-White). Of these patients, 13.5% met DSM-5 criteria for BED in the validation sample and 13.8% met criteria for BED in the replication sample. Lowering the interpretative cut-off to ≥15 on the BES yielded sensitivity values of >.72, specificity values of >.67, and an accurate classification of BED in >.70 of patients across both samples. These classification values were as good as or better than the standard cut-off score of ≥17 in both samples. The BES is appropriate to screen for BED in patients who are seeking bariatric surgery. A 2-point decrease in the BES score for clinical interpretation is appropriate-lowering it from 17 to 15 given DSM-5 updates to diagnostic criteria.

Two neurosubtypes of ADHD different from the clinical phenotypes

Clinical and etiological variability of attention deficit hyperactivity disorder (ADHD) presents an obstacle to understand the disorder. The aim of this study was to disentangle the heterogeneity of ADHD using neuroimaging and a semi-supervised machine learning algorithm. We collected brain structural and functional magnetic resonance imaging (MRI) data and clinical profiles of 183 children with ADHD and 396 neurotypical controls from 7 independent sites. We also used an external validation set with 750 subjects. We adopted a semi-supervised clustering method to subtype ADHD by regional volumetric measures of gray matter, white matter, and fractional amplitude of low frequency fluctuation (fALFF). In addition, split sample test, leave-one-site-out test and external validation were applied to evaluate the reproducibility and stability of ADHD subtypes. Two stable and reproducible neurosubtypes of ADHD were disclosed, which were proved by the split-sample test and leave-one-site-out validation. The structural and functional patterns of ADHD subtypes were also stable in the external validation set. The current two neurosubtypes differed in clinical manifestations and volumetric gray matter, white matter volume and fALFF patterns. The current neurosubtypes of ADHD which were different from clinical phenotypes could facilitate understanding the underlying neuropathological and neurobiological mechanism of the disorder.

Psychometric Assessment of the Physicians' Job Demands and Resources Scale.

Job demands and resources have been consistently associated with the burnout syndrome in physicians, however the literature points to a lack of robust measures to assess these job characteristics across various medical specialties. This study aimed to develop a theoretically and empirically grounded physician-specific job demands and resources self-report measure - the Physicians' Job Demands and Resources Scale. Relevant dimensions of physicians' job demands and resources were identified, corresponding measurement items were generated and pre-tested, and the factor structure of the resulting 44 items was tested with a sample of 9,176 Portuguese physicians. The results of EFAs and CFAs with two random split samples provided consistent evidence of a nine-factor structure with 38 of the 44 items. Importantly, the nine-factor structure is consistent with the dimensions identified in the literature. The paper discusses the theoretical and practical impacts of the scale.

Assumption-light and computationally cheap inference on inequality measures by sample splitting: the Student t approach

Inference on inequality indices remains challenging, even in large samples. Heavy right tails in income and wealth distributions hinder the quality and threaten the validity of asymptotic approximations to finite sample distributions. Attempts to improve on asymptotic approximations by bootstrap techniques or permutation tests are only partial successes. We evaluate a different approach to robust inference, relying on Student t statistics obtained from split samples. This relatively simple ‘t-based’ approach requires no consistent variance estimators, no random sampling of populations, and only mild distributional assumptions. We compare its performance with that of refined bootstrap and permutation techniques. We find that the more complex bootstrap methods still have the edge in one-sample tests, where the t-approach suffers from a negative skew. In two-sample comparisons though, the t-approach offers advantages: it is undersized while bootstrap tests and permutation tests are often oversized. In certain circumstances it is less powerful than permutation tests and bootstrap tests, but for large samples, this difference dissipates. It is also more generally applicable than permutation tests and easily generates confidence intervals. These differences are illustrated with an empirical application using two different sources of household data from the Russian Federation.

Predictors of British Isles Lupus Assessment Group-based outcomes in patients with systemic lupus erythematosus: Analysis from the Systemic Lupus International Collaborating Clinics Inception Cohort.

We aimed to identify factors associated with a significant reduction in SLE disease activity over 12months assessed by the BILAG Index. In an international SLE cohort, we studied patients from their 'inception enrolment' visit. We also defined an 'active disease' cohort of patients who had active disease similar to that needed for enrolment into clinical trials. Outcomes at 12months were; Major Clinical Response (MCR: reduction to classic BILAG C in all domains, steroid dose of ≤7.5mg and SLEDAI ≤ 4) and 'Improvement' (reduction to ≤1B score in previously active organs; no new BILAG A/B; stable or reduced steroid dose; no increase in SLEDAI). Univariate and multivariate logistic regression with Least Absolute Shrinkage and Selection Operator (LASSO) and cross-validation in randomly split samples were used to build prediction models. 'Inception enrolment' (n = 1492) and 'active disease' (n = 924) patients were studied. Models for MCR performed well (ROC AUC = .777 and .732 in the inception enrolment and active disease cohorts, respectively). Models for Improvement performed poorly (ROC AUC = .574 in the active disease cohort). MCR in both cohorts was associated with anti-malarial use and inversely associated with active disease at baseline (BILAG or SLEDAI) scores, BILAG haematological A/B scores, higher steroid dose and immunosuppressive use. Baseline predictors of response in SLE can help identify patients in clinic who are less likely to respond to standard therapy. They are also important as stratification factors when designing clinical trials in order to better standardize overall usual care response rates.

The perceived impact of pandemic scale (PIPS): Initial development and examination among U.S. military veterans

The COVID-19 pandemic has had significant impacts, including increases in mental health problems, distress, interpersonal conflict, unemployment, loss of income, housing instability, and food insecurity. Veterans may be particularly vulnerable to such impacts given their burden of mental and physical health problems. Few existing measures assess pandemic impact, and none have been validated for use with Veterans. We developed such a measure (the Perceived Impact of the Pandemic Scale; PIPS) and examined its psychometric performance in a national sample of US Veterans. Survey data from 567 Veterans were collected between 12/2020 and 2/2021. To examine PIPS factor structure, split sample exploratory/confirmatory factor analyses (EFA/CFA) were conducted to identify and test the most plausible model among an initial set of 18 items. Based on tests of factor extraction and factor loadings, 15 items clearly loaded onto three distinct factors. Internal reliability of all factors was ω > 0.8 and CFA model fit was good (χ2(87) = 167.39, p < .001; SRMR = 0.068; RMSEA = 0.060 [95% CI: 0.05, 0.07], CFI = 0.92). Mean factor scores were significantly positively correlated with measures of depression and loneliness, and negatively correlated with perceived social support. Results suggest the PIPS assesses three internally reliable factors comprised of perceived impact of the pandemic on interpersonal relationships, financial impact, and personal health and well-being. Construct validity with US Veterans was supported. The PIPS may be useful for examining the potentially disparate impact of pandemics on different populations. Research is needed to validate the PIPS in non-Veteran populations.

Using high pressure solutions of polyfluoroacrylate and CO2 to Seal cement cracks for improved wellbore integrity

Polyfluoroacrylate (PFA) is a hydrophobic and oleophobic polymer that is soluble in high pressure carbon dioxide (CO2). In this study, the ability of PFA-CO2 solutions to greatly reduce the apparent permeability of split or cracked Portland cement cylindrical samples is assessed. The apparent permeability values of confined samples were determined before and after treatment with PFA-CO2 solutions. In four tests, PFA-CO2 solutions were continuously displacing pure CO2 from the cracked cement and the decrease in apparent permeability due to PFA adsorption and wettability alteration was monitored. The lowest apparent permeability cracked cement sample (81 nD) was completely sealed with a very small amount of solution. Samples with initial apparent permeabilities of 89 μD and 29.4 mD exhibited 92% and 99% reductions in permeability, respectively, before the experiments had to be stopped because of the excessively large increase in pressure drop. A 50% reduction in apparent permeability was observed with a 3.80 mD sample. Four other split cement samples (bound together with tape) with an initial apparent permeability in the 9.0–70 mD range were removed from the core holder and immersed in a PFA-CO2 solution for 24 h to allow for PFA adsorption. Then the PFA-CO2 solution was depressurized, allowing for the deposition of additional PFA from the solution within the crack as the pressure fell below the cloud point pressure of the PFA-CO2 solution. These four samples were then confined again in a core holder and apparent permeability reductions of 29–93% were observed. Results from these eight experiments indicates that the more substantial reductions in the nD – mD apparent permeability of the cracked cement correlated to lower initial crack permeability, higher PFA concentration, and slower injection rate of the PFA-CO2 solution into the crack.