Tag: pubmed

Proc Inst Mech Eng H. 2023 Nov 20:9544119231212269. doi: 10.1177/09544119231212269. Online ahead of print.

ABSTRACT

Electrogastrography (EGG) is a novel diagnostic modality for assessing the gastrointestinal tract (GI) that generates spontaneous electrical activity and monitors gastric motility. The aim of this study was to compare patients with functional dyspepsia (FD) and diabetic gastroparesis (D-GP) with healthy controls (CT) to use established findings on abnormalities of gastric motility based on EGG characteristics. In this study, 50 patients with FD, 50 D-GP patients, and 50 CT subjects were studied to compare EGG with discrete wavelet transform models (DWT) to extract signal characteristics using a variety of different qualitative and quantitative metrics from pre-prandial and postprandial states. As a result, higher statistically significant (p < 0.05*) were found in the DWT models based on power spectral density (PSD) analysis in both states. We also present that the correlations between EGG metrics and the presence of FD, D-GP, and CT symptoms were inconsistent. This paper represents that EGG assessments of FD and D-GP patients differ from healthy controls in terms of abnormalities of gastric motility. Additionally, we demonstrate that diverse datasets showed adequate gastric motility responses to a meal. We anticipate that our method will provide a comprehensive understanding of gastric motility disorders for better treatment and monitoring in both clinical and research settings. In conclusion, we present potential future opportunities for precise gastrointestinal electrophysiological disorders.

PMID:37982194 | DOI:10.1177/09544119231212269

Eur Heart J Cardiovasc Imaging. 2023 Nov 20:jead285. doi: 10.1093/ehjci/jead285. Online ahead of print.

ABSTRACT

Cardiac disease affects the heart non-uniformly. Examples include focal septal or apical hypertrophy with reduced strain in hypertrophic cardiomyopathy (HCM), replacement fibrosis with akinesia in an infarct-related coronary artery territory and pattern of scarring in dilated cardiomyopathy. The detail and versatility of cardiovascular magnetic resonance imaging (CMR) mean it contains a wealth of information imperceptible to the naked eye and not captured by standard global measures. CMR-derived heterogeneity biomarkers could facilitate earlier diagnosis, better risk stratification and more comprehensive prediction of treatment response. Small cohort and case-control studies demonstrate feasibility of proof-of-concept structural and functional heterogeneity measures. Detailed radiomic analyses of different CMR sequences using open source software delineate unique voxel patterns as hallmarks of histopathological changes. Meanwhile measures of dispersion applied to emerging CMR strain sequences describe variable longitudinal, circumferential and radial function across the myocardium. Two of the most promising heterogeneity measures are mean absolute deviation of regional standard deviations (madSD) on native T1 and T2 and the SD of time to maximum regional radial wall motion, termed tissue synchronisation index (TSI) in a 16-segment LV model. Real world limitations include the non-standardisation of CMR imaging protocols across different centres and the testing of large numbers of radiomic features in small inadequately powered patient samples. We therefore propose a 3-step roadmap to benchmark novel heterogeneity biomarkers, including defining normal reference ranges, statistical modelling against diagnosis and outcomes in large epidemiological studies and finally, comprehensive internal and external validation.

PMID:37982176 | DOI:10.1093/ehjci/jead285

J Comput Graph Stat. 2023;32(3):1097-1108. doi: 10.1080/10618600.2022.2146697. Epub 2022 Dec 13.

ABSTRACT

Many problems in classification involve huge numbers of irrelevant features. Variable selection reveals the crucial features, reduces the dimensionality of feature space, and improves model interpretation. In the support vector machine literature, variable selection is achieved by ${\ell }_1$ penalties. These convex relaxations seriously bias parameter estimates toward 0 and tend to admit too many irrelevant features. The current paper presents an alternative that replaces penalties by sparse-set constraints. Penalties still appear, but serve a different purpose. The proximal distance principle takes a loss function $L\left(\beta \right)$ and adds the penalty $\frac{\rho }{2}\text{dist}{\left(\beta ,S_k\right)}^2$ capturing the squared Euclidean distance of the parameter vector $\beta$ to the sparsity set $S_k$ where at most k components of $\beta$ are nonzero. If ${\beta }_{\rho }$ represents the minimum of the objective $f_{\rho }\left(\beta \right)=L\left(\beta \right)+\frac{\rho }{2}\text{dist}{\left(\beta ,S_k\right)}^2$, then ${\beta }_{\rho }$ tends to the constrained minimum of $L\left(\beta \right)$ over $S_k$ as $\rho$ tends to $\infty$. We derive two closely related algorithms to carry out this strategy. Our simulated and real examples vividly demonstrate how the algorithms achieve better sparsity without loss of classification power.

PMID:37982129 | PMC:PMC10656054 | DOI:10.1080/10618600.2022.2146697

Nucl Med Mol Imaging. 2023 Dec;57(6):275-286. doi: 10.1007/s13139-023-00818-1. Epub 2023 Aug 18.

ABSTRACT

OBJECTIVE: This study aimed to investigate the risk of second primary malignancy after radioiodine (RAI) therapy in patients with thyroid cancer, using the National Health Insurance Service (NHIS) database.

METHODS: We extracted data from the NHIS database of South Korea, which covers the entire population of the nation. Risk of second primary malignancy in the thyroid cancer patients who received RAI therapy were compared with the thyroid cancer patients who received surgery only.

RESULTS: Between January 1, 2004, and December 31, 2018, we identified 363,155 patients who underwent thyroid surgery due to thyroid cancer for analysis. The surgery only cohort was 215,481, and the RAI cohort was 147,674 patients. A total of 19,385 patients developed second primary malignancy (solid cancer, 18,285; hematologic cancer, 1,100). There was no significant increase in the risk of second primary malignancy in patients who received a total cumulative dose of 100 mCi or less (hazard ratio [HR], 1.013; 95% confidence interval [CI], 0.979-1.049). However, a statistically significant increase in the risk of second primary malignancy was observed in patients who received 101-200 mCi (HR, 1.214; 95% CI, 1.167-1.264), 201-300 mCi (HR, 1.422; 95% CI, 1.258-1.607), and > 300 mCi (HR, 1.693; 95% CI, 1.545-1.854).

CONCLUSION: Total cumulative doses of 100 mCi or less of RAI can be safely administered without concerns about second primary malignancy. However, the risk of second primary malignancy increases in a dose-dependent manner, and the risk-benefit needs to be considered for doses over 100 mCi of RAI therapy.

PMID:37982105 | PMC:PMC10654320 | DOI:10.1007/s13139-023-00818-1

Nucl Med Mol Imaging. 2023 Dec;57(6):257-264. doi: 10.1007/s13139-023-00811-8. Epub 2023 Jul 3.

ABSTRACT

PURPOSE: The growing incidence of differentiated thyroid cancer (DTC) demands dependable prognostic factors to guide follow-up and treatment plans. This study investigated the prognostic value of response to therapy (RTT) assessment using TSH stimulated-thyroglobulin (sti-Tg) and nonstimulated-thyroglobulin (nonsti-Tg) and evaluates whether RTT using nonsti-Tg (nonstiRTT) can replace RTT using sti-Tg (stiRTT) in clinical practice to improve patients’ quality of life during assessment.

METHODS: We enrolled 419 DTC patients who underwent total thyroidectomy, radioactive iodine (RAI) therapy, and Tg assessment. Patients with structural incomplete responses were excluded. Initial RTT assessments based on the 2015 American Thyroid Association guidelines (excellent response; ER, indeterminate response, biochemical incomplete response) were performed 6-24 months after RAI therapy. The second RTT assessments were performed 6-24 months after the first assessment. Statistical analysis for recurrence-free survival (RFS) was done with the log-rank test for stiRTT and nonstiRTT.

RESULTS: Although initial stiRTT and nonstiRTT were significant predictors for RFS (p < 0.0001), stiRTT provided better RFS prediction than nonstiRTT. The RFS analysis of the second RTT assessment demonstrated statistical significance only for stiRTT (p < 0.0001). In 116 patients classified as ER on initial stiRTT, there was no RFS difference between patients classified as ER on either second stiRTT or nonstiRTT.

CONCLUSION: The prognostic power of stiRTT surpasses that of nonstiRTT in both the initial and second RTT assessment. Nevertheless, among patients classified as ER on initial stiRTT, a second stiRTT may not be required for those classified as ER on the second nonstiRTT.

SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13139-023-00811-8.

PMID:37982102 | PMC:PMC10654278 | DOI:10.1007/s13139-023-00811-8

J Am Stat Assoc. 2019;114(528):1854-1864. doi: 10.1080/01621459.2018.1527226. Epub 2019 Mar 18.

ABSTRACT

In comparing two treatments via a randomized clinical trial, the analysis of covariance (ANCOVA) technique is often utilized to estimate an overall treatment effect. The ANCOVA is generally perceived as a more efficient procedure than its simple two sample estimation counterpart. Unfortunately, when the ANCOVA model is nonlinear, the resulting estimator is generally not consistent. Recently, various nonparametric alternatives to the ANCOVA, such as the augmentation methods, have been proposed to estimate the treatment effect by adjusting the covariates. However, the properties of these alternatives have not been studied in the presence of treatment allocation imbalance. In this article, we take a different approach to explore how to improve the precision of the naive two-sample estimate even when the observed distributions of baseline covariates between two groups are dissimilar. Specifically, we derive a bias-adjusted estimation procedure constructed from a conditional inference principle via relevant ancillary statistics from the observed covariates. This estimator is shown to be asymptotically equivalent to an augmentation estimator under the unconditional setting. We utilize the data from a clinical trial for evaluating a combination treatment of cardiovascular diseases to illustrate our findings.

PMID:37982094 | PMC:PMC10655936 | DOI:10.1080/01621459.2018.1527226

Child Abuse Rev. 2020 May-Jun;29(3):253-268. doi: 10.1002/car.2627. Epub 2020 Jun 23.

ABSTRACT

Although confessions related to abusive head trauma (AHT) are reported, no detailed analysis exists. Therefore, we systematically reviewed studies of AHT confessions and examined the details, including country of origin, mechanisms and perpetrators’ characteristics [PUBLISHER – THE PRECEDING UNDERLINED TEXT IS FOR THE MARGIN]. Employing 36 search terms across three search engines, we searched Medline and CINAHL from 1963 to 2018. All relevant studies underwent two independent reviews and data extraction. Descriptive statistics were used to characterise the sample; chi square and Fisher’s exact tests were used to assess differences in demographic and clinical characteristics. Of 6759 identified studies, 157 full texts were reviewed and 55 articles from 15 countries spanning four continents were included. Included articles contained 434 confessions. The mechanisms of abuse included shaking alone (64.1%), impact alone (17.1%), shaking plus impact (18.0%) and other (0.9%). There was no statistically significant difference in the percentage of confessions reporting shaking alone when comparing continents: North America (64.0%), Europe (64.2%) and Oceania (60.0%; P=.92), or when comparing circumstances in which the confession was obtained: medical evaluation (74.6%) vs police or judicial investigations (63.4%; P=.11). Of 119 cases with identified perpetrators, 67.2 per cent were cases with males alone. Confessions reveal striking similarities in the mechanism of AHT (predominantly shaking) and occur across the globe.

PMID:37982093 | PMC:PMC10655946 | DOI:10.1002/car.2627

Stoch Anal Appl. 2023;41(3):474-508. doi: 10.1080/07362994.2022.2033126. Epub 2022 Feb 25.

ABSTRACT

As COVID-19 is spreading, national agencies need to monitor and track several metrics. Since we do not have perfect testing programs on the hand, one needs to develop an advanced sampling strategies for prevalence study, control and management. Here we introduce REDACS: Regional emergency-driven adaptive cluster sampling for effective COVID-19 management and control and justify its usage for COVID-19. We show its advantages over classical massive individual testing sampling plans. We also point out how regional and spatial heterogeneity underlines proper sampling. Fundamental importance of adaptive control parameters from emergency health stations and medical frontline is outlined. Since the Northern hemisphere entered Autumn and Winter season (this paper was originally submitted in November 2020), practical illustration from spatial heterogeneity of Chile (Southern hemisphere, which already experienced COVID-19 winter outbreak peak) is underlying the importance of proper regional heterogeneity of sampling plan. We explain the regional heterogeneity by microbiological backgrounds and link it to behavior of Lyapunov exponents. We also discuss screening by antigen tests from the perspective of “on the fly” biomarker validation, i.e., during the screening.

PMID:37982071 | PMC:PMC10655945 | DOI:10.1080/07362994.2022.2033126

IEEE Trans Artif Intell. 2020 Sep 2;1(1):85-103. doi: 10.1109/TAI.2020.3020521. eCollection 2020 Aug.

ABSTRACT

COVID-19, an infectious disease caused by the SARS-CoV-2 virus, was declared a pandemic by the World Health Organisation (WHO) in March 2020. By mid-August 2020, more than 21 million people have tested positive worldwide. Infections have been growing rapidly and tremendous efforts are being made to fight the disease. In this paper, we attempt to systematise the various COVID-19 research activities leveraging data science, where we define data science broadly to encompass the various methods and tools-including those from artificial intelligence (AI), machine learning (ML), statistics, modeling, simulation, and data visualization-that can be used to store, process, and extract insights from data. In addition to reviewing the rapidly growing body of recent research, we survey public datasets and repositories that can be used for further work to track COVID-19 spread and mitigation strategies. As part of this, we present a bibliometric analysis of the papers produced in this short span of time. Finally, building on these insights, we highlight common challenges and pitfalls observed across the surveyed works. We also created a live resource repository at https://github.com/Data-Science-and-COVID-19/Leveraging-Data-Science-To-Combat-COVID-19-A-Comprehensive-Review that we intend to keep updated with the latest resources including new papers and datasets.

PMID:37982070 | PMC:PMC8545032 | DOI:10.1109/TAI.2020.3020521

Transl Stroke Res. 2023 Nov 20. doi: 10.1007/s12975-023-01205-w. Online ahead of print.

ABSTRACT

Few certainties exist regarding the optimal type, timing, or dosage of rehabilitation after stroke. Despite differing injury mechanisms and recovery patterns following ischemic and hemorrhagic stroke, most translational stroke research is conducted after ischemia. As we enter the era of personalized medicine, exploring subtype-specific treatment efficacy is essential to optimizing recovery. Our objective was to characterize common rehabilitation interventions used after in vivo preclinical intracerebral hemorrhage (ICH) and assess the impact of post-ICH rehabilitation (vs. no-rehabilitation) on recovery of motor function. Following PRISMA guidelines, a systematic review (Academic Search Complete, CINAHL, EMBASE, Medline, PubMed Central) identified eligible articles published up to December 2022. Risk of bias (SYRCLE) and study quality (CAMARADES) were evaluated, and random-effects meta-analysis was used to assess treatment efficacy in recovery of forelimb and locomotor functions. Thirty articles met inclusion criteria, and 48 rehabilitation intervention groups were identified. Most used collagenase to model striatal ICH in young, male rodents. Aerobic exercise, enriched rehabilitation, and constraint-induced movement therapy represented ~ 70% of interventions. Study quality was low (median 4/10, range 2-8), and risk of bias was unclear. Rehabilitation provided modest benefits in skilled reaching, spontaneous impaired forelimb use, and locomotor function; however, effects varied substantially by endpoint, treatment type, and study quality. Rehabilitation statistically improves motor function after preclinical ICH, but whether these effects are functionally meaningful is unclear. Incomplete reporting and variable research quality hinder our capacity to analyze and interpret how treatment factors influence rehabilitation efficacy and recovery after ICH.

PMID:37981635 | DOI:10.1007/s12975-023-01205-w