Tag: pubmed

Magn Reson Med. 2022 Oct 5. doi: 10.1002/mrm.29462. Online ahead of print.

ABSTRACT

PURPOSE: Through-time spiral GRAPPA is a real-time imaging technique that enables ungated, free-breathing evaluation of the left ventricle. However, it requires a separate fully-sampled calibration scan to calculate GRAPPA weights. A self-calibrated through-time spiral GRAPPA method is proposed that uses a specially designed spiral trajectory with interleaved arm ordering such that consecutive undersampled frames can be merged to form calibration data, eliminating the separate fully-sampled acquisition.

THEORY AND METHODS: The proposed method considers the time needed to acquire data at all points in a GRAPPA calibration kernel when using interleaved arm ordering. Using this metric, simulations were performed to design a spiral trajectory for self-calibrated GRAPPA. Data were acquired in healthy volunteers using the proposed method and a comparison electrocardiogram-gated and breath-held cine scan. Left ventricular functional values and image quality are compared.

RESULTS: A 12-arm spiral trajectory was designed with a temporal resolution of 32.72 ms/cardiac phase with an acceleration factor of 3. Functional values calculated using the proposed method and the gold-standard method were not statistically significantly different (paired t-test, p < 0.05). Image quality ratings were lower for the proposed method, with statistically significantly different ratings (Wilcoxon signed rank test, p < 0.05) for two of five image quality aspects rated (level of artifact, blood-myocardium contrast).

CONCLUSIONS: A self-calibrated through-time spiral GRAPPA reconstruction can enable ungated, free-breathing evaluation of the left ventricle in 71 s. Functional values are equivalent to a gold-standard cine technique, although some aspects of image quality may be inferior due to the real-time nature of the data collection.

PMID:36198001 | DOI:10.1002/mrm.29462

Biomed Tech (Berl). 2022 Oct 6. doi: 10.1515/bmt-2022-0100. Online ahead of print.

ABSTRACT

Research shows that Attention Deficit Hyperactivity Disorder (ADHD) is related to a disorder in brain networks. The purpose of this study is to use an effective connectivity measure and graph theory to examine the impairments of brain connectivity in ADHD. Weighted directed graphs based on electroencephalography (EEG) signals of 61 children with ADHD and 60 healthy children were constructed. The edges between two nodes (electrodes) were calculated by Phase Transfer Entropy (PTE). PTE is calculated for five frequency bands: delta, theta, alpha, beta, and gamma. The graph theory measures were divided into two categories: global and local. Statistical analysis with global measures indicates that in children with ADHD, the segregation of brain connectivity increases while the integration of the brain connectivity decreases compared to healthy children. These brain network differences were identified in the delta and theta frequency bands. The classification accuracy of 89.4% is obtained for both in-degree and strength measures in the theta band. Our result indicated local graph measures classified ADHD and healthy subjects with accuracy of 91.2 and 90% in theta and delta bands, respectively. Our analysis may provide a new understanding of the differences in the EEG brain network of children with ADHD and healthy children.

PMID:36197950 | DOI:10.1515/bmt-2022-0100

PLoS One. 2022 Oct 5;17(10):e0275250. doi: 10.1371/journal.pone.0275250. eCollection 2022.

ABSTRACT

BACKGROUND: Measurement of care quality and safety mainly relies on abstracted administrative data. However, it is well studied that administrative data-based adverse event (AE) detection methods are suboptimal due to lack of clinical information. Electronic medical records (EMR) have been widely implemented and contain detailed and comprehensive information regarding all aspects of patient care, offering a valuable complement to administrative data. Harnessing the rich clinical data in EMRs offers a unique opportunity to improve detection, identify possible risk factors of AE and enhance surveillance. However, the methodological tools for detection of AEs within EMR need to be developed and validated. The objectives of this study are to develop EMR-based AE algorithms from hospital EMR data and assess AE algorithm’s validity in Canadian EMR data.

METHODS: Patient EMR structured and text data from acute care hospitals in Calgary, Alberta, Canada will be linked with discharge abstract data (DAD) between 2010 and 2020 (n~1.5 million). AE algorithms development. First, a comprehensive list of AEs will be generated through a systematic literature review and expert recommendations. Second, these AEs will be mapped to EMR free texts using Natural Language Processing (NLP) technologies. Finally, an expert panel will assess the clinical relevance of the developed NLP algorithms. AE algorithms validation: We will test the newly developed AE algorithms on 10,000 randomly selected EMRs between 2010 to 2020 from Calgary, Alberta. Trained reviewers will review the selected 10,000 EMR charts to identify AEs that had occurred during hospitalization. Performance indicators (e.g., sensitivity, specificity, positive predictive value, negative predictive value, F1 score, etc.) of the developed AE algorithms will be assessed using chart review data as the reference standard.

DISCUSSION: The results of this project can be widely implemented in EMR based healthcare system to accurately and timely detect in-hospital AEs.

PMID:36197944 | DOI:10.1371/journal.pone.0275250

PLoS One. 2022 Oct 5;17(10):e0275571. doi: 10.1371/journal.pone.0275571. eCollection 2022.

ABSTRACT

The key to maintaining a clay court with quality and lastingly is through water applications, carried out periodically and through systems with high distribution uniformity, developed specifically for this purpose. The objective in this study was to evaluate the performance of a sprinkler irrigation system with hose and shower, traditionally used in clay tennis court, and propose another low-cost system that is operational and technically feasible, which is the irrigating bar. For each irrigation system, three evaluations were performed. At the beginning of each test, the pressures and flow rates of the emitters were measured, and the water distribution profile method was used to determine the distribution uniformity of the systems. Distribution efficiency was obtained through the Christiansen’s (UC), distribution (UD), absolute (UA), statistical (US) and Hart’s (UH) uniformity coefficients, HSPA standard efficiency (UHSPA) and, coefficient of variation (CV). Subsequently, the application and irrigation efficiencies were calculated. It was found that the irrigation bar required lower operating pressure, as well as greater stability of pressure and flow in relation to the hose system. Water losses in the hose/shower system (22.0%) were higher than in the irrigation bar (0.6%). Regardless of the evaluated system, UC (68.4% and 86.5%) and UH (66.4% and 87.5%) values were similar and higher than those of the other coefficients (~51.8% and ~81.2%). The collected depths, applied by the hose/shower irrigation system, showed high spatial variability and, consequently, low values of uniformity, being classified as poor or unacceptable. The irrigating bar promoted higher values of uniformity coefficients, being classified as good. Irrigation efficiencies were 53.97 and 85.97% for hose/shower and irrigation bar systems, respectively. The hose/shower system has low performance in the irrigation of clay tennis courts. The irrigation bar system, for providing technical, operational, and economic benefits, and has the potential to be used in the irrigation of clay tennis courts.

PMID:36197943 | DOI:10.1371/journal.pone.0275571

PLoS Comput Biol. 2022 Oct 5;18(10):e1010278. doi: 10.1371/journal.pcbi.1010278. Online ahead of print.

ABSTRACT

Gene set analysis (GSA) remains a common step in genome-scale studies because it can reveal insights that are not apparent from results obtained for individual genes. Many different computational tools are applied for GSA, which may be sensitive to different types of signals; however, most methods implicitly test whether there are differences in the distribution of the effect of some experimental condition between genes in gene sets of interest. We have developed a unifying framework for GSA that first fits effect size distributions, and then tests for differences in these distributions between gene sets. These differences can be in the proportions of genes that are perturbed or in the sign or size of the effects. Inspired by statistical meta-analysis, we take into account the uncertainty in effect size estimates by reducing the influence of genes with greater uncertainty on the estimation of distribution parameters. We demonstrate, using simulation and by application to real data, that this approach provides significant gains in performance over existing methods. Furthermore, the statistical tests carried out are defined in terms of effect sizes, rather than the results of prior statistical tests measuring these changes, which leads to improved interpretability and greater robustness to variation in sample sizes.

PMID:36197939 | DOI:10.1371/journal.pcbi.1010278

PLoS Comput Biol. 2022 Oct 5;18(10):e1010495. doi: 10.1371/journal.pcbi.1010495. eCollection 2022 Oct.

ABSTRACT

COVID-19 patients display a wide range of disease severity, ranging from asymptomatic to critical symptoms with high mortality risk. Our ability to understand the interaction of SARS-CoV-2 infected cells within the lung, and of protective or dysfunctional immune responses to the virus, is critical to effectively treat these patients. Currently, our understanding of cell-cell interactions across different disease states, and how such interactions may drive pathogenic outcomes, is incomplete. Here, we developed a generalizable and scalable workflow for identifying cells that are differentially interacting across COVID-19 patients with distinct disease outcomes and use this to examine eight public single-cell RNA-seq datasets (six from peripheral blood mononuclear cells, one from bronchoalveolar lavage and one from nasopharyngeal), with a total of 211 individual samples. By characterizing the cell-cell interaction patterns across epithelial and immune cells in lung tissues for patients with varying disease severity, we illustrate diverse communication patterns across individuals, and discover heterogeneous communication patterns among moderate and severe patients. We further illustrate patterns derived from cell-cell interactions are potential signatures for discriminating between moderate and severe patients. Overall, this workflow can be generalized and scaled to combine multiple scRNA-seq datasets to uncover cell-cell interactions.

PMID:36197936 | DOI:10.1371/journal.pcbi.1010495

PLoS One. 2022 Oct 5;17(10):e0273991. doi: 10.1371/journal.pone.0273991. eCollection 2022.

ABSTRACT

BACKGROUND: Over 95% of childhood injury deaths occur in low- and middle-income countries (LMICs). Patients with severe traumatic brain injury (TBI) have twice the likelihood of dying in LMICs than in high-income countries (HICs). In Africa, TBI estimates are projected to increase to upwards of 14 million new cases in 2050; however, these estimates are based on sparse data, which underscores the need for robust injury surveillance systems. We aim to describe the clinical factors associated with morbidity and mortality in pediatric TBI at the Kilimanjaro Christian Medical Centre (KCMC) in Moshi, Tanzania to guide future prevention efforts.

METHODS: We conducted a secondary analysis of a TBI registry of all pediatric (0-18 years of age) TBI patients presenting to the KCMC emergency department (ED) between May 2013 and April 2014. The variables included demographics, acute treatment and diagnostics, Glasgow Coma Scores (GCSs, severe 3-8, moderate 9-13, and mild 14-15), morbidity at discharge as measured by the Glasgow Outcome Scale (GOS, worse functional status 1-3, better functional status 4-6), and mortality status at discharge. The analysis included descriptive statistics, bivariable analysis and multivariable logistic regression to report the predictors of mortality and morbidity. The variables used in the multivariable logistic regression were selected according to their clinical validity in predicting outcomes.

RESULTS: Of the total 419 pediatric TBI patients, 286 (69.3%) were male with an average age of 10.12 years (SD = 5.7). Road traffic injury (RTI) accounted for most TBIs (269, 64.4%), followed by falls (82, 19.62%). Of the 23 patients (5.58%) who had alcohol-involved injuries, most were male (3.6:1). Severe TBI occurred in 54 (13.0%) patients. In total, 90 (24.9%) patients underwent TBI surgery. Of the 21 (5.8%) patients who died, 11 (55.0%) had severe TBI, 6 (30.0%) had moderate TBI (GCS 9-13) and 3 (15.0%) presented with mild TBI (GCS>13). The variables most strongly associated with worse functional status included having severe TBI (OR = 9.45) and waiting on the surgery floor before being moved to the intensive care unit (ICU) (OR = 14.37).

CONCLUSIONS: Most pediatric TBI patients were males who suffered RTIs or falls. Even among children under 18 years of age, alcohol was consumed by at least 5% of patients who suffered injuries, and more commonly among boys. Patients becoming unstable and having to be transferred from the surgery floor to the ICU could reflect poor risk identification in the ED or progression of injury severity. The next steps include designing interventions to reduce RTI, mitigate irresponsible alcohol use, and improve risk identification and stratification in the ED.

PMID:36197935 | DOI:10.1371/journal.pone.0273991

JMIR Form Res. 2022 Oct 5;6(10):e36275. doi: 10.2196/36275.

ABSTRACT

BACKGROUND: Obesity is a global public health concern. Interventions rely predominantly on managing dietary intake and increasing physical activity; however, sustained adherence to behavioral regimens is often poor. The lack of sustained motivation, self-efficacy, and poor adherence to behavioral regimens are recognized barriers to successful weight loss. Avatar-based interventions achieve better patient outcomes in the management of chronic conditions by promoting more active engagement. Virtual representations of self can affect real-world behavior, acting as a catalyst for sustained weight loss behavior.

OBJECTIVE: We evaluated whether a personalized avatar, offered as an adjunct to an established weight loss program, can increase participant motivation, sustain engagement, optimize service delivery, and improve participant health outcomes.

METHODS: A feasibility randomized design was used to determine the case for future development and evaluation of avatar-based technology in a randomized controlled trial. Participants were recruited from general practitioner referrals to a 12-week National Health Service weight improvement program. The main outcome measure was weight loss. Secondary outcome measures were quality-of-life and self-efficacy. Quantitative data were subjected to descriptive statistical tests and exploratory comparison between intervention and control arms. Feasibility and acceptability were assessed through interviews and analyzed using framework approach. Health Research Authority ethics approval was granted.

RESULTS: Overall, 10 men (n=7, 70% for routine care and avatar and n=3, 30% for routine care) and 33 women (n=23, 70% for intervention and n=10, 30% for routine care) were recruited. Participants’ initial mean weight was greater in the intervention arm than in the routine care arm (126.3 kg vs 122.9 kg); pattern of weight loss was similar across both arms of the study in T0 to T1 period but accelerated in T1 to T2 period for intervention participants, suggesting that access to the self-resembling avatar may promote greater engagement with weight loss initiatives in the short-to-medium term. Mean change in participants’ weight from T0 to T2 was 4.5 kg (95% CI 2.7-6.3) in the routine care arm and 5.3 kg (95% CI 3.9-6.8) in the intervention arm. Quality-of-life and self-efficacy measures demonstrated greater improvement in the intervention arm at both T1 (105.5 for routine care arm and 99.7 for intervention arm) and T2 (100.1 for routine care arm and 81.2 for intervention arm). Overall, 13 participants (n=11, 85% women and n=2, 15% men) and two health care professionals were interviewed about their experience of using the avatar program.

CONCLUSIONS: Participants found using the personalized avatar acceptable, and feedback reiterated that seeing a future self helped to reinforce motivation to change behavior. This feasibility study demonstrated that avatar-based technology may successfully promote engagement and motivation in weight loss programs, enabling participants to achieve greater weight loss gains and build self-confidence.

TRIAL REGISTRATION: ISRCTN Registry 17953876; https://doi.org/10.1186/ISRCTN17953876.

PMID:36197703 | DOI:10.2196/36275

RMD Open. 2022 Sep;8(2):e002449. doi: 10.1136/rmdopen-2022-002449.

ABSTRACT

BACKGROUND: Nailfold videocapillaroscopy (NVC) non-specific abnormalities may be present in subjects with isolated Raynaud’s phenomenon (RP) before the potential transition to systemic sclerosis (SSc) specific microvascular alterations (‘scleroderma pattern’). This study aims to investigate NVC non-specific abnormalities, notably capillary dilations, in RP patients, as possible forerunners of the ‘scleroderma pattern’.

METHODS: A 10-year retrospective NVC-based investigation evaluated 55 RP patients sorted into 3 sex-matched and age-matched groups according to clinical evolution: 18 later developing SSc (cases), 19 later developing other connective tissue disease and 18 maintaining primary RP at long-term follow-up (controls). All patients had a basal NVC showing non-specific abnormalities, namely non-specific >30 µm dilated capillaries (30-50 μm diameter). Sequential NVCs were longitudinally evaluated using current standardised approach. Statistical analysis assessed the risk for developing a ‘scleroderma pattern’.

RESULTS: Significantly larger capillary diameters were observed in cases versus controls both at basal NVC and during follow-up NVC (p=<0.05 to <0.001). Interestingly, controls showed stable NVC non-specific abnormalities over the study follow-up. The number of >30 µm dilated capillaries/mm at basal NVC was the strongest single predictor of ‘scleroderma pattern’ evolution with 24% increased risk per each dilated capillary (OR 1.24, 95% CI 1.17,1.32). Additionally, a tree-based analysis suggested the efferent (venous) diameter of the most dilated capillary on basal NVCas a variable of interest to identify patients maintaining primary RP.

CONCLUSION: This is the first study to describe an NVC ‘prescleroderma signature’ to potentially identify RP patients later developing a ‘scleroderma pattern’.

PMID:36197673 | DOI:10.1136/rmdopen-2022-002449

JAMA Netw Open. 2022 Oct 3;5(10):e2234862. doi: 10.1001/jamanetworkopen.2022.34862.

ABSTRACT

IMPORTANCE: Childhood lipid levels have been associated with adult subclinical atherosclerosis; however, life-course lipid trajectories and their associations with cardiovascular disease risk are poorly characterized.

OBJECTIVES: To examine the associations of lipid levels at different ages and discrete lipid trajectory patterns from childhood to adulthood with subclinical atherosclerosis in midlife.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used data from the Bogalusa Heart Study, a prospective, population-based cohort study conducted in a semirural, biracial community in Bogalusa, Louisiana, with follow-up from 1973 to 2016 (median follow-up, 36.8 years). Participants had 4 to 16 repeated measurements of lipids, including total cholesterol (TC), non-high-density lipoprotein cholesterol (non-HDL-C), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG), from childhood to midlife and adult measurement of carotid intima-media thickness (IMT). Statistical analyses were conducted from July 1 to December 31, 2021.

EXPOSURES: Age-specific lipid levels were estimated, and lipid trajectory patterns were identified using latent mixture modeling.

MAIN OUTCOMES AND MEASURES: Subclinical atherosclerosis measured by carotid IMT.

RESULTS: The study evaluated 1201 adults (mean [SD] age, 45.7 [6.8] years; 691 [57.5%] women and 510 [42.5%] men; 392 Black [32.6%] and 809 White [67.4%] individuals). Levels of all lipids at each age from 5 to 45 years were significantly associated with adult IMT. The magnitude of associations generally increased with age, and non-HDL-C (age 5 y: β, 0.040; 95% CI, 0.025-0.055; age 45 y, β, 0.049; 95% CI, 0.026-0.072) and LDL-C (age 5 y: β, 0.039; 95% CI, 0.024-0.054; age 45 y, β, 0.043; 95% CI, 0.023-0.063) showed the strongest associations. After adjusting for race, sex, and other cardiovascular risk factors, mean IMT values were significantly higher in the low-slow increase, low-rapid increase, and high-stable trajectory groups for TC (eg, high-stable group: mean difference, 0.152 mm; 95% CI, 0.059-0.244 mm), the low-slow increase, low-rapid increase, moderate-stable, and high-stable trajectory groups for non-HDL-C (eg, low-slow increase group: mean difference, 0.048 mm; 95% CI, 0.012-0.085 mm) and LDL-C (eg, low-rapid increase group: mean difference, 0.104 mm; 95% CI, 0.056-0.151 mm) and the low-rapid increase and moderate-stable trajectory groups for TG (eg, moderate-stable group: mean difference, 0.071 mm; 95% CI, 0.019-0.122 mm) vs the corresponding low-stable trajectory groups. These associations were slightly attenuated after further adjustment for lipid levels at baseline or follow-up. There were no significant differences in mean IMT among HDL-C trajectory groups.

CONCLUSIONS AND RELEVANCE: In this cohort study, discrete life-course lipid trajectories were associated with the development of atherosclerosis in midlife. The findings emphasize the importance of maintaining optimal lipid levels across the lifespan.

PMID:36197664 | DOI:10.1001/jamanetworkopen.2022.34862