Category: Statistics

Int Dent J. 2023 Dec 2:S0020-6539(23)00964-4. doi: 10.1016/j.identj.2023.10.020. Online ahead of print.

ABSTRACT

BACKGROUND: Dental sleep medicine education (DSME) should be emphasised in postgraduate orthodontic training; however, there appears to be no clear guideline for its implementation into the curriculum.

OBJECTIVE: The aim was to investigate the current status of DSME as well as its feasibility and implementation in postgraduate orthodontic programmes.

METHODS: A structured interview with predetermined response options was chosen as a data collection method to gather relevant information from representatives of all accredited postgraduate orthodontic programmes in Thailand. These interviews were conducted online via the Cisco Webex Meeting platform. A combination of data analysis techniques was employed to achieve a thorough comprehension of the research findings, including descriptive statistics, quantitative content analysis, thematic analysis, and alignment analysis.

RESULTS: All participating programmes reported the inclusion of DSME in their curricula. A didactic approach was adopted by all programmes. However, only 2 out of 7 programmes offered clinical sessions for their students. Several challenges in implementing DSME within orthodontic programmes were identified, including a shortage of expertise and limited patient access. The participants also suggested that knowledge and resource sharing amongst institutions could serve as a potential solution to enhance the feasibility of DSME.

CONCLUSIONS: This research highlighted the significant disparities and inadequacy of DSME within postgraduate orthodontic programmes in Thailand due to various challenges. Consequently, there is a compelling need to place greater emphasis on DSME and establish a national-level standardisation within orthodontic programmes. This effort is essential for enhancing the awareness and competency of orthodontists in the field of DSME.

PMID:38044215 | DOI:10.1016/j.identj.2023.10.020

J Formos Med Assoc. 2023 Dec 2:S0929-6646(23)00439-4. doi: 10.1016/j.jfma.2023.10.021. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer’s disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated.

METHODS: A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics.

RESULTS: The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel).

CONCLUSIONS: The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.

PMID:38044212 | DOI:10.1016/j.jfma.2023.10.021

J Formos Med Assoc. 2023 Dec 2:S0929-6646(23)00476-X. doi: 10.1016/j.jfma.2023.11.010. Online ahead of print.

ABSTRACT

BACKGROUND/PURPOSE: Predictive modeling aids in identifying patients at high risk of adverse events. Using routinely collected data, we report a competing risk prediction model for kidney failure.

METHODS: A total of 5138 patients with CKD stages 3b-5 were included and randomized into the development and validation cohorts at a ratio of 7:3. The outcome was end-stage kidney disease, defined as the initiation of dialysis or kidney transplantation. All patients were followed-up until December 31, 2020. A Fine and Gray model was applied to estimate the sub-hazard ratio of kidney failure, with death as a competing event.

RESULTS: In the development cohort, the mean age was 67.6 ± 13.9 years and 60 % were male. The mean index eGFR and median urinary protein-creatinine ratio (UPCR) were 26.5 ± 12.8 mL/min/1.73 m² and 1051 mg/g, respectively. The median follow-up duration was 1051 days. The proportion of patients with kidney failure and death was 25.4 % and 14.1 %, respectively. Four models were applied, including eGFR, age, sex, UPCR, systolic and diastolic blood pressure, serum albumin, phosphate, uric acid, haemoglobin, and potassium levels had the best goodness of fit. All models had good discrimination with time-to-event c statistics of 0.89-0.95 in the development cohort and 0.86-0.95 in the validation cohort. The prediction models showed excellent and fairly good calibration at 2 and 5-year risk, respectively.

CONCLUSION: Using real-world data, our competing risk model can accurately predict progression to kidney failure over 2 years in patients with advanced CKD.

PMID:38044210 | DOI:10.1016/j.jfma.2023.11.010

Eur J Intern Med. 2023 Dec 2:S0953-6205(23)00415-6. doi: 10.1016/j.ejim.2023.11.018. Online ahead of print.

NO ABSTRACT

PMID:38044167 | DOI:10.1016/j.ejim.2023.11.018

Circ J. 2023 Dec 1. doi: 10.1253/circj.CJ-23-0409. Online ahead of print.

ABSTRACT

BACKGROUND: This study was performed to clarify the clinical findings of pediatric patients diagnosed with long QT syndrome (LQTS) through electrocardiographic screening programs and to predict their outcome using Holter electrocardiographic approaches.Methods and Results: This retrospective study included pediatric patients with a Schwartz score of ≥3.5 who visited the National Hospital Organization Kagoshima Medical Center between April 2005 and March 2019. Resting 12-lead and Holter electrocardiograms were recorded at every visit. The maximum resting QTc and maximum Holter QTc values among all recordings were used for statistical analyses. To test the prognostic value of QTc for the appearance of cardiac events after the first hospital visit, receiver operating characteristic curves were used to calculate the area under the curve (AUC). Among 207 patients, 181 (87%) were diagnosed through screening programs. The prevalence of cardiac events after the first hospital visit was 4% (8/207). Among QTc at diagnosis, maximum resting QTc, and maximum Holter QTc, only maximum Holter QTc value was a predictor (P=0.02) of cardiac events after the hospital visit in multivariate regression analysis. The AUC of the maximum Holter QTc was significantly superior to that of maximum resting QTc.

CONCLUSIONS: The maximum Holter QTc value can be used to predict the appearance of symptoms in pediatric patients with LQTS.

PMID:38044147 | DOI:10.1253/circj.CJ-23-0409

Curr Opin Psychol. 2023 Nov 17;55:101753. doi: 10.1016/j.copsyc.2023.101753. Online ahead of print.

ABSTRACT

Children have a reputation for credulity that is undeserved; even preschoolers have proven adept at identifying implausible claims and unreliable informants. Still, the strategies children use to identify and reject dubious information are often superficial, which leaves them vulnerable to accepting such information if conveyed through seemingly authoritative channels or formatted in seemingly authentic ways. Indeed, children of all ages have difficulty differentiating legitimate websites and news stories from illegitimate ones, as they are misled by the inclusion of outwardly professional features such as graphs, statistics, and journalistic layout. Children may not be inherently credulous, but their skepticism toward dubious information is often shallow enough to be overridden by the deceptive trappings of online misinformation.

PMID:38043147 | DOI:10.1016/j.copsyc.2023.101753

Injury. 2023 Nov 24;55(2):111231. doi: 10.1016/j.injury.2023.111231. Online ahead of print.

ABSTRACT

BACKGROUND: Our study examined if there were any limitations when using various measurement techniques in the literature to quantify osseous exposure. Additionally, we also examined if surface contour had any influence on obtained measurements, which no previous study has attempted.

MATERIALS AND METHODS: Three methods used to quantify osseous exposure area were identified, one in which involves manually applying mesh over exposure area. The other two use digital image capture software (ImageJ, Bethesda, MD). We simulated flat, convex, and mixed surface types using synthetic bone analogs. We assessed the degree of variability between mean values using an ANOVA or Kruskal-Wallis equality of populations rank test. Cronbach’s alpha test of internal reliability was used to assess the internal reliability of measurement technique.

RESULTS: ANOVA test for difference in measurement techniques on all three surface types was statistically significant (p < 0.05). Cronbach’s alpha test of internal reliability for each technique on the convex surface did not obtain adequate significance (alpha >0.70). Only the mesh method obtained adequate alpha value for significance when applied to the flat and mixed surface types.

DISCUSSION: Each of the three measurement techniques tested demonstrated poor internal reliability. We suggest taking care when comparing studies that use different quantification techniques when calculating osseous exposure for different surgical approaches. Future studies should explore alternative methods of osseous exposure quantification.

PMID:38043145 | DOI:10.1016/j.injury.2023.111231

ALTEX. 2023 Dec 1. doi: 10.14573/altex.2310041. Online ahead of print.

ABSTRACT

Historical data from control groups in animal toxicity studies is currently mainly used for comparative purposes to assess validity and robustness of study results. Due to the highly controlled environment in which the studies are performed and the homogeneity of the animal collectives it has been proposed to use the historical data for building so-called virtual control groups, which could replace partly or entirely the concurrent control. This would constitute a substantial contribution to the reduction of animal use in safety studies. Before the concept can be implemented, the prerequisites regarding data collection, curation and statistical evaluation together with a validation strategy need to be identified to avoid any impairment of the study outcome and subsequent consequences for human risk assessment. To further assess and develop the concept of virtual control groups the transatlantic think tank for toxicology (t⁴) sponsored a workshop with stakeholders from the pharmaceutical and chemical industry, academia, FDA, pharmaceutical, contract research organizations (CROs), and non-governmental organizations in Washington, which took place in March 2023. This report summarizes the current efforts of a European initiative to share, collect and curate animal control data in a centralized database and the first approaches to identify optimal matching criteria between virtual controls and the treatment arms of a study as well as first reflections about strategies for a qualification procedure and potential pitfalls of the concept.

PMID:38043132 | DOI:10.14573/altex.2310041

Eur Spine J. 2023 Dec 3. doi: 10.1007/s00586-023-08041-4. Online ahead of print.

ABSTRACT

PURPOSE: To compare the clinical effectiveness of reduction and fusion with in situ fusion in the management of patients with degenerative lumbar spondylolisthesis (DLS).

METHODS: The systematic review was conducted following the PRISMA guidelines. Relevant studies were identified from PubMed, Embase, Scopus, Cochrane Library, ClinicalTrials.gov, and Google Scholar. The inclusion criteria were: (1) comparative studies of reduction and fusion versus in situ fusion for DLS patients, (2) outcomes reported as VAS/NRS, ODI, JOA score, operating time, blood loss, complication rate, fusion rate, or reoperation rate, (3) randomized controlled trials and observational studies published in English from the inception of the databases to January 2023. The exclusion criteria included: (1) reviews, case series, case reports, letters, and conference reports, (2) in vitro biomechanical studies and computational modeling studies, (3) no report on study outcomes. The risk of bias 2 (RoB2) tool and the Newcastle-Ottawa scale was conducted to assess the risk of bias of RCTs and observational studies, respectively.

RESULTS: Five studies with a total of 704 patients were included (375 reduction and fusion, 329 in situ fusion). Operating time was significantly longer in the reduction and fusion group compared to in situ fusion group (weighted mean difference 7.20; 95% confidence interval 0.19, 14.21; P = 0.04). No additional significant intergroup differences were noted in terms of other outcomes analyzed.

CONCLUSION: While the reduction and fusion group demonstrated a statistically longer operating time compared to the in situ fusion group, the clinical significance of this difference was minimal. The findings suggest no substantial superiority of lumbar fusion with reduction over without reduction for the management of DLS.

PMID:38043128 | DOI:10.1007/s00586-023-08041-4

Med Phys. 2023 Dec 3. doi: 10.1002/mp.16861. Online ahead of print.

ABSTRACT

BACKGROUND: Acute stroke is the leading cause of death and disability globally, with an estimated 16 million cases each year. The progression of carotid stenosis reduces blood flow to the intracranial vasculature, causing stroke. Early recognition of ischemic stroke is crucial for disease treatment and management.

PURPOSE: A computer-aided diagnosis (CAD) system was proposed in this study to rapidly evaluate ischemic stroke in carotid color Doppler (CCD).

METHODS: Based on the ground truth from the clinical examination report, the vision transformer (ViT) features extracted from all CCD images (513 stroke and 458 normal images) were combined in machine learning classifiers to generate the likelihood of ischemic stroke for each image. The pretrained weights from ImageNet reduced the time-consuming training process. The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve were calculated to evaluate the stroke prediction model. The chi-square test, DeLong test, and Bonferroni correction for multiple comparisons were applied to deal with the type-I error. Only p values equal to or less than 0.00125 were considered to be statistically significant.

RESULTS: The proposed CAD system achieved an accuracy of 89%, a sensitivity of 94%, a specificity of 84%, and an area under the receiver operating characteristic curve of 0.95, outperforming the convolutional neural networks AlexNet (82%, p < 0.001), Inception-v3 (78%, p < 0.001), ResNet101 (84%, p < 0.001), and DenseNet201 (85%, p < 0.01). The computational time in model training was only 30 s, which would be efficient and practical in clinical use.

CONCLUSIONS: The experiment shows the promising use of CCD images in stroke estimation. Using the pretrained ViT architecture, the image features can be automatically and efficiently generated without human intervention. The proposed CAD system provides a rapid and reliable suggestion for diagnosing ischemic stroke.

PMID:38043124 | DOI:10.1002/mp.16861