Tag: pubmed

Biomarkers. 2024 Oct 30:1-15. doi: 10.1080/1354750X.2024.2421884. Online ahead of print.

ABSTRACT

OBJECTIVE: The objective of this study was to compare the levels of cathepsin B and pentraxin 3 in maternal serum of pregnant women with preeclampsia in the second trimester, to ascertain the impact of these levels on maternal and fetal outcomes, and to present a comprehensive analysis of the combined effects of cathepsin B and pentraxin 3 levels.

METHODS: This prospective case-control study was conducted at Bursa Yuksek Ihtisas Training and Research Hospital between 1 January 2022 and 31 December 2022. The study included 78 pregnant women diagnosed with preeclampsia and 78 healthy pregnant women in the second trimester, between the ages of 18 and 45. Once a diagnosis of preeclampsia was established, maternal serum samples were obtained from the pregnant women prior to the initiation of any therapeutic intervention. Once all samples had been collected, the values for cathepsin B and pentraxin 3 were determined using the ELISA method.

RESULTS: The results demonstrated a statistically significant elevation in the levels of pentraxin 3 (p = 0.008) and cathepsin B (p = 0.005) in pregnancies affected by preeclampsia when compared to those deemed healthy. Moreover, pentraxin-3 (p = 0.007) and cathepsin B (p = 0.002) were found to be significantly elevated in severe preeclampsia compared to mild preeclampsia. A comparison of the groups with and without HELLP syndrome revealed no statistically significant difference between the two groups. The ROC analysis revealed that the Cathepsin B 7.04 cut-off value was statistically significantly associated with the prediction of preeclampsia in all cases, with a sensitivity of 78.2% and a specificity of 47.4% (p = 0.005, AUC = 0.631).

CONCLUSION: The levels of CB and PTX3 may be employed as biomarkers to facilitate the early diagnosis of PE during the second trimester. Furthermore, these biomarkers may prove to be promising for the prediction of PE severity.

PMID:39475373 | DOI:10.1080/1354750X.2024.2421884

Eur Stroke J. 2024 Oct 30:23969873241293566. doi: 10.1177/23969873241293566. Online ahead of print.

ABSTRACT

PURPOSE: Secondhand smoke significantly increases the risk of cerebrovascular diseases, prompting recent public smoking bans. We aimed to ascertain the effects of smoke-free legislation on stroke incidence and mortality.

METHODS: We systematically searched Medline, Embase, Cochrane Library, and Scopus up to August 13, 2023, for studies reporting changes in stroke incidence following partial or comprehensive smoking bans. A random-effects meta-analysis was conducted on hospital admissions and mortality for stroke, stratified based on comprehensiveness of the ban ((i) workplaces-only, (ii) workplaces and restaurants, (iii) workplaces, restaurants and bars). The effect of post-ban follow-up duration was assessed visually by a forest plot, while meta-regression was employed to evaluate for any dose-response relationship between ban comprehensiveness and stroke risk.

FINDINGS: Of 3987 records identified, 15 studies analysing bans across a median follow-up time of 24 months (range: 3-67) were included. WRB bans were associated with reductions in the rates of hospital admissions for stroke (nine studies; RR, 0.918; 95% CI, 0.872-0.967) and stroke mortality (three studies; RR, 0.987; 95% CI, 0.952-1.022), although the latter did not reach statistical significance. There was no significant difference in the risk of stroke admissions for studies with increased ban comprehensiveness and no minimum duration for significant post-ban effects to be observed.

DISCUSSION AND CONCLUSION: Legislative smoking bans were associated with significant reductions in stroke-related hospital admissions, providing evidence for its utility as a public health intervention.

PMID:39475361 | DOI:10.1177/23969873241293566

Med Phys. 2024 Oct 30. doi: 10.1002/mp.17498. Online ahead of print.

ABSTRACT

BACKGROUND: Accurate preoperative prediction of cervical lymph node metastasis (LNM) for papillary thyroid carcinoma (PTC) patients is essential for disease staging and individualized treatment planning, which can improve prognosis and facilitate better management.

PURPOSE: To establish a fully automated deep learning-enabled model (FADLM) for automated tumor segmentation and cervical LNM prediction in PTC using ultrasound (US) video keyframes.

METHODS: The bicentral study retrospective enrolled 518 PTC patients, who were then randomly divided into the training (Hospital 1, n = 340), internal test (Hospital 1, n = 83), and external test cohorts (Hospital 2, n = 95). The FADLM integrated mask region-based convolutional neural network (Mask R-CNN) for automatic thyroid primary tumor segmentation and ResNet34 with Bayes strategy for cervical LNM diagnosis. A radiomics model (RM) using the same automated segmentation method, a traditional radiomics model (TRM) using manual segmentation, and a clinical-semantic model (CSM) were developed for comparison. The dice similarity coefficient (DSC) was used to evaluate segmentation performance. The prediction performance of the models was validated in terms of discrimination and clinical utility with the area under the receiver operator characteristic curve (AUC), heatmap analysis, and decision curve analysis (DCA). The comparison of the predictive performance among different models was conducted by DeLong test. The performances of two radiologists compared with FADLM and the diagnostic augmentation with FADLM’s assistance were analyzed in terms of accuracy, sensitivity and specificity using McNemar’s x² test. The p-value less than 0.05 was defined as a statistically significant difference. The Benjamini-Hochberg procedure was applied for multiple comparisons to deal with Type I error.

RESULTS: The FADLM yielded promising segmentation results in training (DSC: 0.88 ± 0.23), internal test (DSC: 0.88 ± 0.23), and external test cohorts (DSC: 0.85 ± 0.24). The AUCs of FADLM for cervical LNM prediction were 0.78 (95% CI: 0.73, 0.83), 0.83 (95% CI: 0.74, 0.92), and 0.83 (95% CI: 0.75, 0.92), respectively. It all significantly outperformed the RM (AUCs: 0.78 vs. 0.72; 0.83 vs. 0.65; 0.83 vs. 0.68, all adjusted p-values < 0.05) and CSM (AUCs: 0.78 vs. 0.71; 0.83 vs. 0.62; 0.83 vs. 0.68, all adjusted p-values < 0.05) across the three cohorts. The RM offered similar performance to that of TRM (AUCs: 0.61 vs. 0.63, adjusted p-value = 0.60) while significantly reducing the segmentation time (3.3 ± 3.8 vs. 14.1 ± 4.2 s, p-value < 0.001). Under the assistance of FADLM, the accuracies of junior and senior radiologists were improved by 18% and 15% (all adjusted p-values < 0.05) and the sensitivities by 25% and 21% (all adjusted p-values < 0.05) in the external test cohort.

CONCLUSION: The FADLM with elaborately designed automated strategy using US video keyframes holds good potential to provide an efficient and consistent prediction of cervical LNM in PTC. The FADLM displays superior performance to RM, CSM, and radiologists with promising efficacy.

PMID:39475358 | DOI:10.1002/mp.17498

Am J Speech Lang Pathol. 2024 Oct 30:1-19. doi: 10.1044/2024_AJSLP-23-00346. Online ahead of print.

ABSTRACT

PURPOSE: In this study, we evaluated the feasibility and efficacy of language plus goal management training program for individuals with aphasia. The intervention targeted expressive language, while concurrently integrating tasks designed to improve executive function and error awareness.

METHOD: A single-subject repeated-measures design was utilized to determine whether a combined treatment (Multi-Modal Aphasia Therapy PLUS Goal Management Training [M-MAT Meta]) would be efficacious for individuals with aphasia. This article reports on two participants with severe Wernicke’s aphasia, who comprised one of the four dyads of the study. Treatment was administered in a small group setting (N = 2) for 2 hr per day, 3 days per week for 4 weeks. Individual video feedback sessions were conducted once a week. Analysis of outcomes included visual inspection and calculation of Tau-U effect sizes of probed treatment data as well as statistical analysis of standardized language and executive function assessments.

RESULTS: Visual inspection indicated improvements in naming and discourse skills, which were maintained at the 1-month follow-up. Both participants’ standardized scores indicated a significant decrease in aphasia severity, which was maintained 1 month posttreatment. Error awareness improved for one of the two participants, but this improvement was not maintained. Participants demonstrated increased inhibition of unwanted responses and took longer on the planning and problem-solving time required to complete the assessment, indicating a decrease in impulsivity.

CONCLUSION: The results of this preliminary study suggest that M-MAT Meta may be an effective way to increase self-awareness and communication in individuals with severe Wernicke’s aphasia.

PMID:39475344 | DOI:10.1044/2024_AJSLP-23-00346

Pediatr Emerg Care. 2024 Oct 30. doi: 10.1097/PEC.0000000000003293. Online ahead of print.

ABSTRACT

OBJECTIVE: Subconjunctival hemorrhages (SCHs) are uncommon injuries in young children beyond the neonatal period and have been associated with abuse. In otherwise well infants, they are sometimes attributed to commonly observed symptoms that invoke Valsalva maneuvers, such as cough, vomiting, and constipation. Our study aims to ascertain the prevalence of SCH among children presenting to emergency care with cough, vomiting, and constipation.

METHODS: We conducted a cross-sectional secondary analysis of a prospectively collected dataset of children aged 1 month to 3 years presenting to a tertiary pediatric emergency department (ED). Children with and without SCH were identified at the time of their examination by ED providers. Children were assigned to Valsalva symptom groups of cough, vomiting, and/or constipation based on review of the ICD-10 codes associated with the ED encounter. Descriptive statistics and prevalence were calculated for each group. Chi-square testing of proportions was used to compare the prevalence of SCH based on the presence or absence of the 3 symptoms of interest.

RESULTS: Four thousand seven hundred seventeen qualifying ED encounters were captured, with 2 total cases of SCH identified (0.4 per 1000). SCHs were uncommonly observed in patients with cough (0.5 per 1000), vomiting (0 per 1000), and constipation (0 per 1000). We found no significant differences in the prevalence of SCH based on the presence or absence of cough (P = 0.87), vomiting (P = 0.52), or constipation (P = 0.82).

CONCLUSION: SCH is an uncommon finding in children under 3 years and is similarly uncommon among children with cough, vomiting, or constipation. It should not be attributed to uncomplicated presentations of cough, vomiting, or constipation, and alternative diagnoses, including abuse, should be carefully considered in the differential diagnosis of SCH.

PMID:39475329 | DOI:10.1097/PEC.0000000000003293

Int J Methods Psychiatr Res. 2024 Dec;33(4):e70006. doi: 10.1002/mpr.70006.

ABSTRACT

OBJECTIVES: To develop a composite score for differential resilience to effects of combat-related stressors (CRS) on persistent DSM-IV post-traumatic stress disorder (PTSD) among US Army combat arms soldiers using survey data collected before deployment.

METHODS: A sample of n = 2542 US Army combat arms soldiers completed a survey shortly before deployment to Afghanistan and then again two to three and 8-9 months after redeployment. Retrospective self-reports were obtained about CRS. Precision treatment methods were used to determine whether differential resilience to persistent PTSD in the follow-up surveys could be developed from pre-deployment survey data in a 60% training sample and validated in a 40% test sample.

RESULTS: 40.8% of respondents experienced high CRS and 5.4% developed persistent PTSD. Significant test sample heterogeneity was found in resilience (t = 2.1, p = 0.032), with average treatment effect (ATE) of high CRS in the 20% least resilient soldiers of 17.1% (SE = 5.5%) compared to ATE = 3.8% (SE = 1.2%) in the remaining 80%. The most important predictors involved recent and lifetime pre-deployment distress disorders.

CONCLUSIONS: A reliable pre-deployment resilience score can be constructed to predict variation in the effects of high CRS on persistent PTSD among combat arms soldiers. Such a score could be used to target preventive interventions to reduce PTSD or other resilience-related outcomes.

PMID:39475323 | DOI:10.1002/mpr.70006

Pharm Stat. 2024 Oct 30. doi: 10.1002/pst.2446. Online ahead of print.

ABSTRACT

An informed estimate of subject-level variance is a key determinate for accurate estimation of the required sample size for clinical trials. Evaluating completed adult Type 2 diabetes studies submitted to the FDA for accuracy of the variance estimate at the planning stage provides insights to inform the sample size requirements for future studies. From the U.S. Food and Drug Administration (FDA) database of new drug applications containing 14,106 subjects from 26 phase 3 randomized studies submitted to the FDA in support of drug approvals in adult type 2 diabetes studies reviewed between 2013 and 2017, we obtained estimates of subject-level variance for the primary endpoint-change in glycated hemoglobin (HbA1c) from baseline to 6 months. In addition, we used nine additional studies to examine the impact of clinically meaningful covariates on residual standard deviation and sample size re-estimation. Our analyses show that reduced sample sizes can be used without interfering with the validity of efficacy results for adult type 2 diabetes drug trials. This finding has implications for future research involving the adult type 2 diabetes population, including the potential to reduce recruitment period length and improve the timeliness of results. Furthermore, our findings could be utilized in the design of future endocrinology clinical trials.

PMID:39475306 | DOI:10.1002/pst.2446

Disaster Med Public Health Prep. 2024 Oct 30;18:e115. doi: 10.1017/dmp.2024.88.

ABSTRACT

OBJECTIVE: While many medical practitioners value the interactive nature of in-person conferences, results of these interactions are often poorly documented. The objective of this study was to pilot the Delphi method for developing consensus following a national conference and to compare the results between experts who did and did not attend.

METHODS: A 3-round Delphi included experts attending the 2023 Society of Disaster Medicine and Health Preparedness Annual Meeting and experts who were members of the society but did not attend. Conference speakers provided statements related to their presentations. Experts rated the statements on a 1-7 scale for agreement using STAT59 software (STAT59 Services Ltd, Edmonton, Alberta, Canada). Consensus was defined as a standard deviation of ≤ 1.0.

RESULTS: Seventy-five statements were rated by 27 experts who attended and 10 who did not: 2634 ratings in total. There was no difference in the number of statements reaching consensus in the attending group (26/75) versus that of the nonattending group (27/75) (P = 0.89). However, which statements reached consensus differed between the groups.

CONCLUSION: The Delphi method is a viable method to document consensus from a conference. Advantages include the ability to involve large groups of experts, statistical measurement of the degree of consensus, and prioritization of the results.

PMID:39475298 | DOI:10.1017/dmp.2024.88

Biometrics. 2024 Oct 3;80(4):ujae124. doi: 10.1093/biomtc/ujae124.

ABSTRACT

Mouse-tracking data, which record computer mouse trajectories while participants perform an experimental task, provide valuable insights into subjects’ underlying cognitive processes. Neuroscientists are interested in clustering the subjects’ responses during computer mouse-tracking tasks to reveal patterns of individual decision-making behaviors and identify population subgroups with similar neurobehavioral responses. These data can be combined with neuroimaging data to provide additional information for personalized interventions. In this article, we develop a novel hierarchical shrinkage partition (HSP) prior for clustering summary statistics derived from the trajectories of mouse-tracking data. The HSP model defines a subjects’ cluster as a set of subjects that gives rise to more similar (rather than identical) nested partitions of the conditions. The proposed model can incorporate prior information about the partitioning of either subjects or conditions to facilitate clustering, and it allows for deviations of the nested partitions within each subject group. These features distinguish the HSP model from other bi-clustering methods that typically create identical nested partitions of conditions within a subject group. Furthermore, it differs from existing nested clustering methods, which define clusters based on common parameters in the sampling model and identify subject groups by different distributions. We illustrate the unique features of the HSP model on a mouse tracking dataset from a pilot study and in simulation studies. Our results show the ability and effectiveness of the proposed exploratory framework in clustering and revealing possible different behavioral patterns across subject groups.

PMID:39475297 | DOI:10.1093/biomtc/ujae124

Biometrics. 2024 Oct 3;80(4):ujae121. doi: 10.1093/biomtc/ujae121.

ABSTRACT

This paper introduces a model for longitudinal functional data analysis that accounts for pointwise skewness. The proposed procedure decouples the marginal pointwise variation from the complex longitudinal and functional dependence using copula methodology. Pointwise variation is described through parametric distribution functions that capture varying skewness and change smoothly both in time and over the functional argument. Joint dependence is quantified through a Gaussian copula with a low-rank approximation-based covariance. The introduced class of models provides a unifying platform for both pointwise quantile estimation and prediction of complete trajectories at new times. We investigate the methods numerically in simulations and discuss their application to a diffusion tensor imaging study of multiple sclerosis patients. This approach is implemented in the R package sLFDA that is publicly available on GitHub.

PMID:39475296 | DOI:10.1093/biomtc/ujae121