Tag: statistics

Med Phys. 2022 Nov 6. doi: 10.1002/mp.16087. Online ahead of print.

ABSTRACT

BACKGROUND: The growing adoption of MRI-guided radiation therapy (RT) platforms and a focus on MRI-only RT workflows has brought the technical challenge of synthetic CT (sCT) reconstruction to the forefront. Unpaired-data deep learning-based approaches to the problem offer the attractive characteristic of not requiring paired training data, but the gap between paired- and unpaired-data results can be limiting.

PURPOSE: We present two distinct approaches aimed at improving unpaired-data sCT reconstruction results: a cascade ensemble that combines multiple models and a personalized training strategy originally designed for the paired-data setting.

METHODS: Comparisons are made between the following models: 1) the paired-data fully convolutional DenseNet (FCDN), 2) the FCDN with the Intentional Deep Overfit Learning (IDOL) personalized training strategy, 3) the unpaired-data CycleGAN, 4) the CycleGAN with the IDOL training strategy, and 5) the CycleGAN as an intermediate model in a cascade ensemble approach. Evaluation of the various models over 25 total patients is carried out using a five-fold cross validation scheme, with the patient-specific IDOL models being trained for the five patients of fold 3, chosen at random.

RESULTS: In both the paired- and unpaired-data settings, adopting the IDOL training strategy led to improvements in the mean absolute error (MAE) between true CT images and sCT outputs within the body contour (mean improvement, paired- and unpaired-data approaches, respectively: 38%, 9%) and in regions of bone (52%, 5%), the peak signal to noise ratio (PSNR; 15%, 7%), and the structural similarity index (SSIM; 6%, <1%). The ensemble approach offered additional benefits over the IDOL approach in all three metrics (mean improvement over unpaired-data approach in fold 3; MAE: 20% bone MAE: 16% PSNR: 10% SSIM: 2%), and differences in body MAE between the ensemble approach and the paired-data approach are statistically insignificant.

CONCLUSIONS: We have demonstrated that both a cascade ensemble approach and a personalized training strategy designed initially for the paired-data setting offer significant improvements in image quality metrics for the unpaired-data sCT reconstruction task. Closing the gap between paired- and unpaired-data approaches is a step towards fully enabling these powerful and attractive unpaired-data frameworks. This article is protected by copyright. All rights reserved.

PMID:36336718 | DOI:10.1002/mp.16087

Eur J Hum Genet. 2022 Nov 7. doi: 10.1038/s41431-022-01201-y. Online ahead of print.

ABSTRACT

Genetic prediction of male pattern baldness (MPB) is important in science and society. Previous genetic MPB prediction models were limited by sparse marker coverage, small sample size, and/or data dependency in the different analytical steps. Here, we present novel models for genetic prediction of MPB based on a large set of markers and large independent subsample sets drawn among 187,435 European subjects. We selected 117 SNP predictors within 85 distinct loci from a list of 270 previously MPB-associated SNPs in 55,573 males of the UK Biobank Study (UKBB). Based on these 117 SNPs with and without age as additional predictor, we trained, by use of different methods, prediction models in a non-overlapping subset of 104,694 UKBB males and tested them in a non-overlapping subset of 26,177 UKBB males. Estimates of prediction accuracy were similar between methods with AUC ranges of 0.725-0.728 for severe, 0.631-0.635 for moderate, 0.598-0.602 for slight, and 0.708-0.711 for no hair loss with age, and slightly lower without, while prediction of any versus no hair loss gave 0.690-0.711 with age and slightly lower without. External validation in an early-onset enriched MPB dataset from the Bonn Study (N = 991) showed improved prediction accuracy without considering age such as AUC of 0.830 for no vs. any hair loss. Because of the large number of markers and the large independent datasets used for the different analytical steps, the newly presented genetic prediction models are the most reliable ones currently available for MPB or any other human appearance trait.

PMID:36336714 | DOI:10.1038/s41431-022-01201-y

Malar J. 2022 Nov 6;21(1):319. doi: 10.1186/s12936-022-04323-2.

ABSTRACT

BACKGROUND: Detection of malaria parasitaemia in samples that are negative by rapid diagnostic tests (RDTs) requires resource-intensive molecular tools. While pooled testing using a two-step strategy provides a cost-saving alternative to the gold standard of individual sample testing, statistical adjustments are needed to improve accuracy of prevalence estimates for a single step pooled testing strategy.

METHODS: A random sample of 4670 malaria RDT negative dried blood spot samples were selected from a mass testing and treatment trial in Asembo, Gem, and Karemo, western Kenya. Samples were tested for malaria individually and in pools of five, 934 pools, by one-step quantitative polymerase chain reaction (qPCR). Maximum likelihood approaches were used to estimate subpatent parasitaemia (RDT-negative, qPCR-positive) prevalence by pooling, assuming poolwise sensitivity and specificity was either 100% (strategy A) or imperfect (strategy B). To improve and illustrate the practicality of this estimation approach, a validation study was constructed from pools allocated at random into main (734 pools) and validation (200 pools) subsets. Prevalence was estimated using strategies A and B and an inverse-variance weighted estimator and estimates were weighted to account for differential sampling rates by area.

RESULTS: The prevalence of subpatent parasitaemia was 14.5% (95% CI 13.6-15.3%) by individual qPCR, 9.5% (95% CI (8.5-10.5%) by strategy A, and 13.9% (95% CI 12.6-15.2%) by strategy B. In the validation study, the prevalence by individual qPCR was 13.5% (95% CI 12.4-14.7%) in the main subset, 8.9% (95% CI 7.9-9.9%) by strategy A, 11.4% (95% CI 9.9-12.9%) by strategy B, and 12.8% (95% CI 11.2-14.3%) using inverse-variance weighted estimator from poolwise validation. Pooling, including a 20% validation subset, reduced costs by 52% compared to individual testing.

CONCLUSIONS: Compared to individual testing, a one-step pooled testing strategy with an internal validation subset can provide accurate prevalence estimates of PCR-positivity among RDT-negatives at a lower cost.

PMID:36336700 | DOI:10.1186/s12936-022-04323-2

BMC Med. 2022 Nov 7;20(1):385. doi: 10.1186/s12916-022-02583-y.

ABSTRACT

BACKGROUND: The value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. METHODS: An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold.

RESULTS: In the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and – 0.023 (95% CI, – 0.025 to – 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category.

CONCLUSIONS: Addition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.

PMID:36336692 | DOI:10.1186/s12916-022-02583-y

BMC Geriatr. 2022 Nov 7;22(1):838. doi: 10.1186/s12877-022-03529-y.

ABSTRACT

BACKGROUND: The oldest-old (aged 80 or older) are the most rapidly growing age group, and they are more likely to suffer from cognitive impairment, leading to severe medical and economic burdens. The influence of intergenerational relationships on cognition among Chinese oldest-old adults is not clear. We aim to examine the association of intergenerational relationships with cognitive impairment among Chinese adults aged 80 or older.

METHODS: This was a prospective cohort study, and data were obtained from the Chinese Longitudinal Healthy Longevity Survey, 14,180 participants aged 80 or older with at least one follow-up survey from 1998 to 2018. Cognitive impairment was assessed by the Chinese version of Mini Mental State Examination, and intergenerational relationships were assessed by getting main financial support from children, living with children or often being visited by children, and doing housework or childcare. We used time-varying Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of associations between intergenerational relationships and cognitive impairment.

RESULTS: We identified 5443 incident cognitive impairments in the 24-cut-off MMSE cohort and 4778 in the 18-cut-off MMSE cohort between 1998 and 2018. After adjusting for a wide range of confounders, the HR was 2.50 (95% CI: 2.31, 2.72) in the old who received main financial support from children, compared with those who did not. The HR was 0.89 (95% CI: 0.83, 0.95) in the oldest-old who did housework or childcare, compared with those who did not. However, there were no significant associations between older adults’ cognitive impairments and whether they were living with or often visited by their children. Our findings were consistent in two different MMSE cut-off values (24 vs. 18) for cognitive impairment.

CONCLUSIONS: Sharing housework or childcare for children showed a protective effect on older adults’ cognitive function, whereas having children provide primary financial support could increase the risk for cognitive impairments. Our findings suggest that governments and children should pay more attention to older adults whose main financial sources from their children. Children can arrange some easy tasks for adults 80 years of age or older to prevent cognitive impairments.

PMID:36336683 | DOI:10.1186/s12877-022-03529-y

J Cardiovasc Magn Reson. 2022 Nov 7;24(1):57. doi: 10.1186/s12968-022-00891-z.

ABSTRACT

BACKGROUND: Computational fluid dynamics (CFD) is increasingly used for the assessment of blood flow conditions in patients with congenital heart disease (CHD). This requires patient-specific anatomy, typically obtained from segmented 3D cardiovascular magnetic resonance (CMR) images. However, segmentation is time-consuming and requires expert input. This study aims to develop and validate a machine learning (ML) method for segmentation of the aorta and pulmonary arteries for CFD studies.

METHODS: 90 CHD patients were retrospectively selected for this study. 3D CMR images were manually segmented to obtain ground-truth (GT) background, aorta and pulmonary artery labels. These were used to train and optimize a U-Net model, using a 70-10-10 train-validation-test split. Segmentation performance was primarily evaluated using Dice score. CFD simulations were set up from GT and ML segmentations using a semi-automatic meshing and simulation pipeline. Mean pressure and velocity fields across 99 planes along the vessel centrelines were extracted, and a mean average percentage error (MAPE) was calculated for each vessel pair (ML vs GT). A second observer (SO) segmented the test dataset for assessment of inter-observer variability. Friedman tests were used to compare ML vs GT, SO vs GT and ML vs SO metrics, and pressure/velocity field errors.

RESULTS: The network’s Dice score (ML vs GT) was 0.945 (interquartile range: 0.929-0.955) for the aorta and 0.885 (0.851-0.899) for the pulmonary arteries. Differences with the inter-observer Dice score (SO vs GT) and ML vs SO Dice scores were not statistically significant for either aorta or pulmonary arteries (p = 0.741, p = 0.061). The ML vs GT MAPEs for pressure and velocity in the aorta were 10.1% (8.5-15.7%) and 4.1% (3.1-6.9%), respectively, and for the pulmonary arteries 14.6% (11.5-23.2%) and 6.3% (4.3-7.9%), respectively. Inter-observer (SO vs GT) and ML vs SO pressure and velocity MAPEs were of a similar magnitude to ML vs GT (p > 0.2).

CONCLUSIONS: ML can successfully segment the great vessels for CFD, with errors similar to inter-observer variability. This fast, automatic method reduces the time and effort needed for CFD analysis, making it more attractive for routine clinical use.

PMID:36336682 | DOI:10.1186/s12968-022-00891-z

J Adolesc. 2022 Nov 6. doi: 10.1002/jad.12115. Online ahead of print.

ABSTRACT

INTRODUCTION: Given the growing scientific evidence on the detrimental effects of bullying, several prevention programs have been implemented internationally to prevent this behavior among students. Brazil’s Educational Program for Drug and Violence Resistance (PROERD) is an adaptation of US’ DARE/Keepin’ it REAL program, being the most widespread school-based prevention program in the country. However, it has been offered without any effectiveness evaluation. As such, this study evaluates the effectiveness of PROERD in reducing bullying perpetration and victimization among students.

METHODS: Two cluster randomized controlled trials were carried out with 4030 students (1727 5th graders and 2303 7th graders) in 30 public schools in São Paulo, Brazil. The intervention group attended 10 PROERD classes taught by trained police officers whereas the control group underwent no intervention. Data were collected by self-administered questionnaires using smartphones at two moments (baseline preintervention and 9-month follow-up). Multilevel analysis included two paradigms, complete cases (CC) and intention-to-treat (ITT), using Full Information Maximum Likelihood (FIML) and Multiple Imputation (MI). RESULTS AND CONCLUSION: Results show no statistical difference between groups, indicating lack of evidence on PROERD’s effectiveness in preventing bullying behaviors. The insufficient number of classes on bullying prevention and the lack of cultural adaptation may explain these unexpected results. New in-depth evaluation studies concerning the program’s components and process are needed.

PMID:36336666 | DOI:10.1002/jad.12115

Prim Care Diabetes. 2022 Nov 3:S1751-9918(22)00175-9. doi: 10.1016/j.pcd.2022.10.009. Online ahead of print.

ABSTRACT

BACKGROUND: Visual analogue scale (VAS) is one of the simplest to measure medication adherence. It has neither been widely used for Non communicable diseases (NCD) nor validated for in the Indian setting. We examined the validity of self-reported medication adherence measures in relation to HbA1C in a rural population with diabetes mellitus (DM).

METHODS: Participants with DM was administered VAS, Diabetes Self-Management Questionnaire (DMSQ) and assessed for missed pills. Descriptive statistics and logistic regression analysis were done.

RESULTS: We recruited 1347 participants and 84% of them reported being 100% adherent as per VAS and 83.8% stated that they did not miss any pills. However, 58.2% of participants who reported having 100% adherence had poor glycaemic control, as did 58.1% of those who did not miss any pills. None of the diabetic self-care measures was significantly associated with glycaemic control.

CONCLUSION: We found a lack of association between self-reported adherence measures and glycaemic control in participants with DM suggesting that self-reported adherence scales may not be valid in this population.

PMID:36336604 | DOI:10.1016/j.pcd.2022.10.009

Cardiovasc Revasc Med. 2022 Oct 8:S1553-8389(22)00819-3. doi: 10.1016/j.carrev.2022.10.002. Online ahead of print.

ABSTRACT

BACKGROUND: Atrial fibrillation (AF) is among the most common arrhythmias associated with an increased risk of cardioembolic phenomena, including stroke. Percutaneous left atrial appendage occlusion (LAAO) has proven beneficial in reducing stroke and mortality in patients with atrial fibrillation who have contraindications to anticoagulation. However, the sex differences in outcomes following LAAO have not been studied systematically.

METHODS: Electronic databases PUBMED, Embase, and Web of Science were systematically searched until March 2022 for studies evaluating patient outcomes following LAAO for AF. The primary outcomes of interest were the risks of periprocedural stroke, major bleeding, pericardial complications, and all-cause mortality. Secondary outcomes included stroke risks, major bleeding, device-related thrombus, cardiovascular and all-cause mortality on long-term follow-up. A random-effects model meta-analysis was conducted, and heterogeneity was assessed using the I-squared test.

RESULTS: Sixteen studies were included in the final analysis encompassing 111,775 patients, out of which 45,441 (40.7 %) were women. Women had a significantly higher risk of peri-procedural complications including all-cause mortality [relative risk (RR), 95 % confidence intervals (CI); RR 1.94, 95 % CI 1.40-2.69], stroke [RR 1.85, 95 % CI 1.29-2.67], major bleeding [RR 1.63, 95 % CI 1.08-2.44], and pericardial events [RR 1.80, 95 % CI 1.58-2.05]. However, there were no statistically significant differences between sexes in terms of risk of stroke, major bleeding, device-related thrombus, cardiovascular and all-cause mortality on long-term follow-up.

CONCLUSION: Among patients undergoing LAAO implantation, women were at higher risk of periprocedural complications than men. This risk was not significant on long-term follow-up.

PMID:36336589 | DOI:10.1016/j.carrev.2022.10.002

Arab J Gastroenterol. 2022 Nov 3:S1687-1979(22)00061-2. doi: 10.1016/j.ajg.2022.06.009. Online ahead of print.

ABSTRACT

BACKGROUND AND STUDY AIMS: Celiac disease (CD) management is based on a lifelong gluten-free diet (GFD) that affects the quality of life (QoL) of patients with CD. Specific instruments have been used to evaluate this QoL, such as the CD-Questionnaire (CD-Q). This study aimed to translate, validate, and cross-culturally adapt the CD-Q in an Arabic version and then apply it to evaluate the QoL of Moroccan adult patients with CD.

PATIENTS AND METHODS: The Moroccan version of the CD-Q (M-CD-Q) was administered to 150 patients with CD, and 112 of them completed it. The reproducibility and reliability of the M-CD-Q were studied by the intraclass coefficient (ICC) and Cronbach’s α, respectively. Parametric and nonparametric tests, confirmatory factor analysis, and Spearman correlation were used for the statistical analysis performed by SPSS, and the goodness-of-fit test was determined using SPSS AMOS.

RESULTS: No difficulties were found during the translation and cultural adaptation of the CD-Q. Cronbach’s α showed good internal consistency. The retest showed excellent reproducibility (ICC > 0.4). The study of the psychometric properties of the M-CD-Q showed good acceptance, zero ceiling effect, and floor effect. The model fit was good [(root mean square error of approximation = 0.075 (<0.08) and χ2 = 509.04, p < 0.001]. The total scores showed a neutral QoL. This QoL was worse in the worries subscale, which is related to gluten-free products. The GFD did not improve the QoL of the examined samples.

CONCLUSION: The M-CD-Q is the first reliable and adapted instrument in an Arab country for the evaluation of QoL in patients with CD. CD negatively influences this QoL, especially items related to gluten-free products.

PMID:36336586 | DOI:10.1016/j.ajg.2022.06.009