A Monte Carlo Comparison of Tests for Multivariate Normality Based on Multivariate Skewness and Kurtosis.

The assumption of multivariate normality (MVN) underlies many common parametric multivariate statistical procedures, and numerous tests have been defined for testing the assumption. Among these tests, those based on concepts of multivariate skewness and multivariate kurtosis hold special interest since they appear to test for specific types of departures from MVN. This research uses Monte Carlo simulation to compare the performance of several MVN tests which are based on various definitions of multivariate skewness and kurtosis. Specifically, the tests are Mardia\u27s (1970) b\sb{\rm 1,p} and b\sb{\rm 2,p}, Small\u27s (1980) Q\sb1 and Q\sb2, and Srivastava\u27s (1984) b\sb{\rm 1p} and b\sb{\rm 2p}. Two main issues are addressed. First, Mardia\u27s tests are affine invariant, while those of Small and Srivastava are coordinate dependent. Conjectures are advanced regarding the conditions under which coordinate-dependent tests will perform better than affine-invariant tests and vice versa. A Monte Carlo experiment is constructed to evaluate these conjectures. It is concluded that neither coordinate-dependent nor affine-invariant tests can be eliminated from consideration, since each type is strongly superior to the other under certain circumstances. These circumstances pertain to whether or not those third- and fourth-order moments involving more than one variable in the coordinate system have normal or non-normal values. The second issue concerns the distributional dependency of skewness tests. It is conjectured, in particular, that skewness tests based on third-order moments (which includes all skewness tests considered here) are highly distributionally dependent, with this dependency being related to the same distributional characteristic that determines kurtosis. It is further conjectured that this dependency remains of importance asymptotically A Monte Carlo experiment is designed to evaluate these conjectures. Results confirm the dependency and that it is not simply a small sample problem. Based on this, it is concluded that skewness tests are not truly diagnostic; that is, they do not distinguish well between skewed and non-skewed distributions. In particular, skewness tests are likely to identify as skewed many non-skewed distributions with greater than MVN kurtosis; and they will fail to identify as skewed many skewed distributions with less than MVN kurtosis

Probability of Occult Ankle Fracture Based on Radiograph-Measured Swelling

INTRODUCTION: Pediatric ankle injuries are a common presentation in the emergency department (ED). A quarter of pediatric ankle fractures show no radiographic evidence of a fracture. Physicians often correlate non-weight bearing and tenderness with an occult fracture. We present this study to predict the probability of an occult fracture using radiographic soft-tissue swelling on initial ED radiographs. METHODS: This is a retrospective study at a Level 1 pediatric trauma center from 2021 to 22. Soft-tissue swelling between the lateral malleolus and skin was measured on radiographs, and weight-bearing status was documented. Statistical analysis was conducted using Stata software. DISCUSSION: The study period involved 32 patients with an occult fracture, with 8 (25%) diagnosed with a fracture on follow-up radiographs. The probability of an occult fracture was calculated as a function of the ankle swelling in millimeters (mm) using a computer-generated predictive model. False-negative and false-positive rates were plotted as a function of the degree of ankle swelling. CONCLUSION: Magnitude of ankle soft-tissue swelling as measured on initial ED radiographs is predictive of an occult fracture. Although weight-bearing status was not a sign of occult fracture, it improves the predictive accuracy of soft-tissue swelling

Antithrombin III (AT) and recombinant tissue plasminogen activator (R-TPA) used singly and in combination versus supportive care for treatment of endotoxin-induced disseminated intravascular coagulation (DIC) in the neonatal pig

BACKGROUND: Disseminated intravascular coagulation (DIC) is a pathological disturbance of the complex balance between coagulation and anticoagulation that is precipitated by vascular injury, acidosis, endotoxin release and/or sepsis and characterized by severe bleeding and excessive clotting. The innately low levels of coagulation factors found in newborn infants place them at extremely high risk for DIC. Anecdotal reports suggest that either anticoagulant or fibrinolytic therapy may alleviate some of the manifestations of DIC. To test the hypothesis that replacement of both anticoagulants and fibrinolytics may improve survival and outcome better than either single agent or supportive care alone, we utilized a neonatal piglet model of endotoxin-induced DIC. METHODS: DIC was induced in twenty-seven neonatal pigs (7 to 14 days of age) by intravenous administration of E. coli endotoxin (800 μg/kg over 30 min). The piglets were divided into 4 groups on the basis of treatment protocol [A: supportive care alone; B: Antithrombin III (AT, 50 μg/kg bolus, 25 μg/kg per hr continuous infusion) and supportive care; C: Recombinant Tissue Plasminogen Activator (R-TPA, 25 μg/kg per hr continuous infusion) and supportive care; D: AT, R-TPA and supportive care] and monitored for 3 primary outcome parameters (survival time, macroscopic and microscopic organ involvement) and 4 secondary outcome parameters (hematocrit; platelet count; fibrinogen level; and antithrombin III level). RESULTS: Compared with supportive care alone, combination therapy with AT and R-TPA resulted in a significant improvement of survival time, hematocrit, AT level, macroscopic and microscopic organ involvement, p < 0.05. Compared with supportive care alone, R-TPA alone significantly reduced macroscopic organ involvement and AT alone increased AT levels. CONCLUSION: The findings suggest that combining AT, R-TPA and supportive care may prove more advantageous in treating the clinical manifestations of DIC in this neonatal pig model than either single modality or supportive care alone

Intraclass correlation coefficients for weight loss cluster randomized trials in primary care: The PROPEL trial

The aim of this study was to compute intra-class correlations (ICCs) for weight-related and patient-reported outcomes in a cluster randomized clinical trial (cRCT) for weight loss. Baseline and follow-up data from the Promoting Successful Weight Loss in Primary Care in Louisiana (PROPEL) cRCT were used in this analysis. ICCs were computed for baseline and follow-up measures, and changes in body weight, cardiometabolic risk factors and health-related and weight-related quality of life at 6, 12, 18 and 24 months. Baseline ICCs ranged from 0 for PROMIS measures of anxiety and fatigue to 0.055 for total cholesterol (median = 0.019). The ICCs were higher for changes and decreased over time during follow-up. The ICCs for changes were highest in the pooled sample (intervention and usual care combined) followed by the intervention and usual care groups, respectively. The results demonstrated significant ICCs for several outcomes in a weight loss cRCT. The ICCs differed in magnitude depending on whether baseline versus longitudinal data were used, whether data were combined across treatment arms or were considered separately, and varied across the follow-up period. All these factors must be considered when choosing an ICC to inform sample size estimates for future weight loss cRCTs conducted in primary care settings

Four-year follow-up of weight loss maintenance using electronic medical record data: The PROPEL trial

Rationale: Short-term weight loss is possible in a variety of settings. However, long-term, free-living weight loss maintenance following structured weight loss interventions remains elusive. Objective: The purpose was to study body weight trajectories over 2 years of intensive lifestyle intervention (ILI) and up to 4 years of follow-up versus usual care (UC). Methods: Data were obtained from electronic medical records (EMRs) from participating clinics. Baseline (Day 0) was established as the EMR data point closest but prior to the baseline date of the trial. The sample included 111 ILI and 196 UC patients. The primary statistical analysis focused on differentiating weight loss trajectories between ILI and UC. Results: The ILI group experienced significantly greater weight loss compared with the UC group from Day 100 to Day 700, beyond which there were no significant differences. Intensive lifestyle intervention patients who maintained ≥5% and ≥10% weight loss at 24 months demonstrated significantly greater weight loss (p \u3c 0.001) across the active intervention and follow-up. Conclusions: Following 24 months of active intervention, patients with ILI regained weight toward their baseline to the point where ILI versus UC differences were no longer statistically or clinically significant. However, patients in the ILI who experienced ≥5% or ≥10% weight loss at the cessation of the active intervention maintained greater weight loss at the end of the follow-up phase. Clinical Trial Registration: ClinicalTrials.gov: NCT02561221

Comparison of weight loss data collected by research technicians versus electronic medical records: the PROPEL trial

Background/objectives: Pragmatic trials are increasingly used to study the implementation of weight loss interventions in real-world settings. This study compared researcher-measured body weights versus electronic medical record (EMR)-derived body weights from a pragmatic trial conducted in an underserved patient population. Subjects/methods: The PROPEL trial randomly allocated 18 clinics to usual care (UC) or to an intensive lifestyle intervention (ILI) designed to promote weight loss. Weight was measured by trained technicians at baseline and at 6, 12, 18, and 24 months. A total of 11 clinics (6 UC/5 ILI) with 577 enrolled patients also provided EMR data (n = 561), which included available body weights over the period of the trial. Results: The total number of assessments were 2638 and 2048 for the researcher-measured and EMR-derived body weight values, respectively. The correlation between researcher-measured and EMR-derived body weights was 0.988 (n = 1 939; p \u3c 0.0001). The mean difference between the EMR and researcher weights (EMR-researcher) was 0.63 (2.65 SD) kg, and a Bland-Altman graph showed good agreement between the two data collection methods; the upper and lower boundaries of the 95% limits of agreement are −4.65 kg and +5.91 kg, and 71 (3.7%) of the values were outside the limits of agreement. However, at 6 months, percent weight loss in the ILI compared to the UC group was 7.3% using researcher-measured data versus 5.5% using EMR-derived data. At 24 months, the weight loss maintenance was 4.6% using the technician-measured data versus 3.5% using EMR-derived data. Conclusion: At the group level, body weight data derived from researcher assessments and an EMR showed good agreement; however, the weight loss difference between ILI and UC was blunted when using EMR data. This suggests that weight loss studies that rely on EMR data may require larger sample sizes to detect significant effects. Clinical trial registration: ClinicalTrials.gov number NCT02561221

Associations between COVID-19 therapies and outcomes in rural and urban America: A multisite, temporal analysis from the Alpha to Omicron SARS-CoV-2 variants

Purpose: To investigate the enduring disparities in adverse COVID-19 events between urban and rural communities in the United States, focusing on the effects of SARS-CoV-2 vaccination and therapeutic advances on patient outcomes. Methods: Using National COVID Cohort Collaborative (N3C) data from 2021 to 2023, this retrospective cohort study examined COVID-19 hospitalization, inpatient death, and other adverse events. Populations were categorized into urban, urban-adjacent rural (UAR), and nonurban-adjacent rural (NAR). Adjustments included demographics, variant-dominant waves, comorbidities, region, and SARS-CoV-2 treatment and vaccination. Statistical methods included Kaplan-Meier survival estimates, multivariable logistic, and Cox regression. Findings: The study included 3,018,646 patients, with rural residents constituting 506,204. These rural dwellers were older, had more comorbidities, and were less vaccinated than their urban counterparts. Adjusted analyses revealed higher hospitalization odds in UAR and NAR (aOR 1.07 [1.05–1.08] and 1.06 [1.03–1.08]), greater inpatient death hazard (aHR 1.30 [1.26–1.35] UAR and 1.37 [1.30–1.45] NAR), and greater risk of other adverse events compared to urban dwellers. Delta increased, while Omicron decreased, inpatient adverse events relative to pre-Delta, with rural disparities persisting throughout. Treatment effectiveness and vaccination were similarly protective across all cohorts, but dexamethasone post-ventilation was effective only in urban areas. Nirmatrelvir/ritonavir and molnupiravir better protected rural residents against hospitalization. Conclusions: Despite advancements in treatment and vaccinations, disparities in adverse COVID-19 outcomes persist between urban and rural communities. The effectiveness of some therapeutic agents appears to vary based on rurality, suggesting a nuanced relationship between treatment and geographic location while highlighting the need for targeted rural health care strategies

Dietary intake during a pragmatic cluster-randomized weight loss trial in an underserved population in primary care

Background: Currently there are limited data as to whether dietary intake can be improved during pragmatic weight loss interventions in primary care in underserved individuals. Methods: Patients with obesity were recruited into the PROPEL trial, which randomized 18 clinics to either an intensive lifestyle intervention (ILI) or usual care (UC). At baseline and months 6, 12, and 24, fruit and vegetable (F/V) intake and fat intake was determined. Outcomes were analyzed by repeated-measures linear mixed-effects multilevel models and regression models, which included random cluster (clinic) effects. Secondary analyses examined the effects of race, sex, age, and food security status. Results: A total of 803 patients were recruited. 84.4% were female, 67.2% African American, 26.1% received Medicaid, and 65.5% made less than $40,000. No differences in F/V intake were seen between the ILI and UC groups at months 6, 12, or 24. The ILI group reduced percent fat at months 6, 12, and 24 compared to UC. Change in F/V intake was negatively correlated with weight change at month 6 whereas change in fat intake was positively associated with weight change at months 6, 12, and 24 for the ILI group. Conclusions: The pragmatic weight loss intervention in primary care did not increase F/V intake but did reduce fat intake in an underserved population with obesity. F/V intake was negatively associated with weight loss at month 6 whereas percent fat was positively correlated with weight loss throughout the intervention. Future efforts better targeting both increasing F/V intake and reducing fat intake may promote greater weight loss in similar populations. Trial registration: NCT Registration: NCT02561221

Association Of Obesity And Diabetes With The Incidence Of Breast Cancer In Louisiana

Introduction: Breast cancer is a heterogeneous disease, consisting of multiple molecular subtypes. Obesity has been associated with an increased risk for postmenopausal breast cancer, but few studies have examined breast cancer subtypes separately. Obesity is often complicated by type 2 diabetes, but the possible association of diabetes with specific breast cancer subtypes remains poorly understood. Methods: In this retrospective case-control study, Louisiana Tumor Registry records of primary invasive breast cancer diagnosed in 2010–2015 were linked to electronic health records in the Louisiana Public Health Institute\u27s Research Action for Health Network. Controls were selected from Research Action for Health Network and matched to cases by age and race. Conditional logistic regression was used to identify metabolic risk factors. Data analysis was conducted in 2020‒2021. Results: There was a significant association between diabetes and breast cancer for Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2‒positive subtypes. In multiple logistic regression, including both obesity status and diabetes as independent risk factors, Luminal A breast cancer was also associated with overweight status. Diabetes was associated with increased risk for Luminal A and Triple-Negative Breast Cancer in subgroup analyses, including women aged ≥50 years, Black women, and White women. Conclusions: Although research has identified obesity and diabetes as risk factors for breast cancer, these results underscore that comorbid risk is complex and may differ by molecular subtype. There was a significant association between diabetes and the incidence of Luminal A, Triple-Negative Breast Cancer, and human epidermal growth factor 2‒positive breast cancer in Louisiana