Tag: pubmed

Scand J Med Sci Sports. 2021 Oct 13. doi: 10.1111/sms.14081. Online ahead of print.

ABSTRACT

This study aimed to examine 1) adherence to 24-hour movement guidelines over a 2-year follow-up in children aged 6-8 years and 2) association of this adherence with cardiometabolic risk factors. Physical activity and sleep were assessed by a monitor combining heart rate and accelerometry measurements. Screen time was reported by the parents. Body fat percentage, waist circumference, blood glucose, serum insulin, plasma lipids and blood pressure were assessed, and a cardiometabolic risk score was calculated using z-scores. Children were classified as meeting the guidelines if they had on average ≥60min/day of moderate-to-vigorous physical activity during the valid days; ≤120min/day of screen time; and 9-11h/day of sleep. In total, 485 children had valid data at baseline or at 2-year follow-up. Analyses were conducted using adjusted logistic and linear regression models. Most children adhered to the 24-hour movement guidelines at baseline, but the adherence decreased over the 2-year follow-up. Meeting physical activity guidelines individually, or in combination with screen time and/or sleep, was longitudinally associated with a lower cardiometabolic risk score, insulin and waist circumference, and cross-sectionally additionally with lower diastolic blood pressure and higher high-density lipoprotein cholesterol. However, these associations became statistically non-significant after adjustment for body fat. In conclusion, meeting 24-hour movement guidelines at baseline increases the odds of meeting them at 2-year follow-up in school-aged children. Furthermore, meeting 24-hour movement guidelines is associated with lower levels of cardiometabolic risk factors, but these associations are partly explained by lower body fat. Thus, promoting movement behaviors, especially physical activity, and healthy weight in early childhood is important in supporting cardiometabolic health in children.

PMID:34644434 | DOI:10.1111/sms.14081

Radiat Res. 2021 Oct 13. doi: 10.1667/RADE-20-00244.1. Online ahead of print.

ABSTRACT

To investigate the optimal pre- and post-adaptive statistical iterative reconstruction-V (ASiR-V) levels in pediatric abdominal computed tomography (CT) to minimize radiation exposure and maintain image quality using an animal model. A total of 10 standard piglets were selected and scanned to obtain unenhanced and enhanced images under different pre-ASiR-V conditions. The corresponding images were obtained using ASiR-V algorithm at different post-ASiR-V levels. CT value, signal-to-noise ratio (SNR), contrast noise ratio (CNR) of abdominal tissues, subjective image score, and radiation dose of unenhanced and enhanced scans were analyzed. With the increase of pre-ASiR-V level, the radiation dose in piglets gradually decreased (P < 0.05). Within the same group of pre-ASiR-V, the image noise was decreased (P < 0.05) by increasing post-ASiR-V level. There was no statistical difference between SNR and CNR values. In unenhanced CT, the subjective score of the images with the combination of 40% pre- and 60% post-ASiR-V levels had no statistical difference compared to the combination of 0% pre- and 60% post-ASiR-V levels, while the radiation dose decreased by 31.6%. In the enhanced CT, the subjective image score with the 60% pre- and 60% post-ASiR-V combination had no statistical difference compared to the 0% pre- and 60% post-ASiR-V combination, while the radiation dose was reduced by 48.9%. The combined use of pre- and post-ASiR-V maintains image quality at the reduced radiation dose. The optimal level for unenhanced CT is 40% pre-combined with 60% post-ASiR-V, while that for enhanced CT is 60% pre- combined with 60% post-ASiR-V in pediatric abdominal CT.

PMID:34644380 | DOI:10.1667/RADE-20-00244.1

Fam Pract. 2021 Oct 13:cmab129. doi: 10.1093/fampra/cmab129. Online ahead of print.

ABSTRACT

BACKGROUND: Cardiometabolic multimorbidity (CM) is the diagnosis of 2 or more cardiometabolic conditions. Multimorbidity and individual cardiometabolic conditions have been associated with activity limitation, a common form of disability, but few studies have investigated the association between CM and activity limitation.

OBJECTIVES: To estimate the prevalence of activity limitation among Canadians with CM and to quantify the association between CM and activity limitation.

METHODS: Using data from the Canadian Longitudinal Study on Aging, we conducted a cross-sectional analysis of activity limitation among Canadians aged 45-85 (n = 50,777; weighted n = 13,118,474). CM was defined as the diagnosis of 2 or more of diabetes/prediabetes, myocardial infarction, and stroke, and activity limitation was evaluated using the Older Americans Resources and Services scale. Descriptive statistics and logistic and multinomial logistic regression analyses were conducted to determine the association between CM and activity limitation.

RESULTS: The estimated prevalence of activity limitation among participants living with CM was 27.4% compared with 7.5% with no cardiometabolic conditions. Activity limitation increased in prevalence and severity with the number of cardiometabolic conditions. People with CM had increased odds of activity limitation compared with those without any cardiometabolic conditions (adjusted relative risk ratio = 3.99, 95% confidence interval [3.35-4.75]), and the odds increased with each additional condition. Stroke survivors had greater odds of activity limitation than those without a history of stroke and the same number of cardiometabolic conditions.

CONCLUSION: Activity limitation is common among Canadians living with CM. Odds of activity limitation increase with each additional cardiometabolic condition, especially for stroke survivors.

PMID:34644392 | DOI:10.1093/fampra/cmab129

PLoS One. 2021 Oct 13;16(10):e0258509. doi: 10.1371/journal.pone.0258509. eCollection 2021.

ABSTRACT

BACKGROUND: Variable, and typically inadequate, delivery of skills training following manual wheelchair (MWC) provision has a detrimental impact on user mobility and participation. Traditional in-person delivery of training by rehabilitation therapists has diminished due to cost, travel time, and most recently social distancing restrictions due to COVID-19. Effective alternative training approaches include eHealth home training applications and interactive peer-led training using experienced and proficient MWC users. An innovative TEAM Wheels program integrates app-based self-training and teleconference peer-led training using a computer tablet platform.

OBJECTIVE: This protocol outlines implementation and evaluation of the TEAM Wheels training program in a randomized control trial using a wait-list control group.

SETTING: The study will be implemented in a community setting in three Canadian cities.

PARTICIPANTS: Individuals ≥ 18 years of age within one year of transitioning to use of a MWC.

INTERVENTION: Using a computer tablet, participants engage in three peer-led teleconference training sessions and 75-150 minutes of weekly practice using a video-based training application over 4 weeks. Peer trainers individualize the participants’ training plans and monitor their tablet-based training activity online. Control group participants also receive the intervention following a 1-month wait-list period and data collection.

MEASUREMENTS: Outcomes assessing participation; skill capacity and performance; self-efficacy; mobility; and quality of life will be measured at baseline and post-treatment, and at 6-month follow-up for the treatment group.

IMPACT STATEMENT: We anticipate that TEAM Wheels will be successfully carried out at all sites and participants will demonstrate statistically significant improvement in the outcome measures compared with the control group.

PMID:34644350 | DOI:10.1371/journal.pone.0258509

PLoS One. 2021 Oct 13;16(10):e0258446. doi: 10.1371/journal.pone.0258446. eCollection 2021.

ABSTRACT

OBJECTIVE: Surge capacity refers to preparedness of health systems to face sudden patient inflows, such as mass-casualty incidents (MCI). To strengthen surge capacity, it is essential to understand MCI epidemiology, which is poorly studied in low- and middle-income countries lacking trauma databases. We propose a novel approach, the “systematic media review”, to analyze mass-trauma epidemiology; here piloted in Rwanda.

METHODS: A systematic media review of non-academic publications of MCIs in Rwanda between January 1st, 2010, and September 1st, 2020 was conducted using NexisUni, an academic database for news, business, and legal sources previously used in sociolegal research. All articles identified by the search strategy were screened using eligibility criteria. Data were extracted in a RedCap form and analyzed using descriptive statistics.

FINDINGS: Of 3187 articles identified, 247 met inclusion criteria. In total, 117 MCIs were described, of which 73 (62.4%) were road-traffic accidents, 23 (19.7%) natural hazards, 20 (17.1%) acts of violence/terrorism, and 1 (0.09%) boat collision. Of Rwanda’s 30 Districts, 29 were affected by mass-trauma, with the rural Western province most frequently affected. Road-traffic accidents was the leading MCI until 2017 when natural hazards became most common. The median number of injured persons per event was 11 (IQR 5-18), and median on-site deaths was 2 (IQR 1-6); with natural hazards having the highest median deaths (6 [IQR 2-18]).

CONCLUSION: In Rwanda, MCIs have decreased, although landslides/floods are increasing, preventing a decrease in trauma-related mortality. By training journalists in “mass-casualty reporting”, the potential of the “systematic media review” could be further enhanced, as a way to collect MCI data in settings without databases.

PMID:34644363 | DOI:10.1371/journal.pone.0258446

PLoS One. 2021 Oct 13;16(10):e0258556. doi: 10.1371/journal.pone.0258556. eCollection 2021.

ABSTRACT

BACKGROUND: Trichomonas vaginalis infection is underreported due to nonspecific clinical presentation and the nonavailability of sensitive laboratory diagnostic tests at the clinical setup. Hence, this study was designed to compare the sensitivity and specificity of microscopy and culture methods with polymerase chain reaction (PCR). The socio-demographic factors associated with the infection were explored.

METHODS: The study was carried out at the National Sexually Transmitted Diseases and Acquired Immuno Deficiency Syndrome Control Programme in Colombo and Sexually Transmitted Diseases and Acquired Immuno Deficiency Syndrome Control Programme in Kandy. Samples were collected from a total of 385 patients including, 272 females (70.7%) and 113 males (29.3%), and tested using microscopy (wet mount and Giemsa staining), culture, and PCR. Genus-specific primer set (TFR1/TFR2) that amplifies 5.8S rRNA and species-specific primer sets (TV16Sf-2/TV16Sr-2 and TVK3/7) that amplifies 18S rRNA and repetitive DNA, respectively, were used. Patient’s socio-demographic and sexual behaviour data were obtained using a standard interviewer-administered questionnaire. Data were analyzed with R statistical software Version 3.6.3.

RESULTS: The overall prevalence of trichomoniasis was 4.4% (17/385). Of these, six (1.6%) were positive for microscopic examination, 7 (1.8%) were positive for culture, and 13 (3.4%) for TVK3/7, 15 (3.9%) for TV16Sf/r, and TFR1/2 17 (4.4%) were positive for PCR. Sensitivities of PCR using TFR1/2, TV16Sf/r, and TVK3/7 primer sets were 100%, 88.20%, and 76.50%, respectively, against the expanded gold standard. Trichomoniasis was associated with age above 36 (p = 0.033), not using condoms in last three months (p = 0.016), multiple sex partners (p = 0.001), reason for attendance (p = 0.027), symptomatic nature (p = 0.015), and the presence of other sexually transmitted diseases (p = 0.001).

CONCLUSIONS: The study highlighted that age over 36 years, multiple sex partners, not using condoms, reason for attendance, symptomatic nature, and having other sexually transmitted diseases can increase the risk of acquiring trichomoniasis. Furthermore, this study confirmed PCR as highly sensitive and specific diagnostic test for the diagnosis of trichomoniasis in comparison to microscopy and culture methods.

PMID:34644344 | DOI:10.1371/journal.pone.0258556

PLoS One. 2021 Oct 13;16(10):e0258399. doi: 10.1371/journal.pone.0258399. eCollection 2021.

ABSTRACT

This study analysed the business sustainability of remanufacturing waste steel sheet from the shells of end-of-life vehicles into mesh steel sheet for manufacturing sheet-metal products. Hybrid statistical, fuzzy, and overall sustainability-index curve-fitting models were used to analyse the technical, economic, environmental, management, and social feasibility of remanufacturing, where the sales price, eco-cost savings, and CO2 emission reductions were used as typical statistical indicators. The remanufacturing process was optimised to allocate hardware for a plant recovering 480 m2/shift of waste sheet steel and producing 2851-5520 m2/shift of mesh sheet steel. Six scenarios were used to model the sustainability parameters to normalise the sustainability index values. The sustainability index of each parameter was calculated by multiplying its weight of importance by its weight of satisfaction. The highest sustainability index of 0.95 was calculated for the economic feasibility index, while the lowest sustainability index of 0.4 was calculated for the management feasibility. Remanufacturing of waste sheet steel into mesh sheet steel can be applied with an estimated overall sustainability index of 0.88.

PMID:34644340 | DOI:10.1371/journal.pone.0258399

PLoS One. 2021 Oct 13;16(10):e0258537. doi: 10.1371/journal.pone.0258537. eCollection 2021.

ABSTRACT

BACKGROUND: Real-world big data studies using health insurance claims databases require extraction algorithms to accurately identify target population and outcome. However, no algorithm for Crohn’s disease (CD) has yet been validated. In this study we aim to develop an algorithm for identifying CD using the claims data of the insurance system.

METHODS: A single-center retrospective study to develop a CD extraction algorithm from insurance claims data was conducted. Patients visiting the Kitasato University Kitasato Institute Hospital between January 2015-February 2019 were enrolled, and data were extracted according to inclusion criteria combining the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) diagnosis codes with or without prescription or surgical codes. Hundred cases that met each inclusion criterion were randomly sampled and positive predictive values (PPVs) were calculated according to the diagnosis in the medical chart. Of all cases, 20% were reviewed in duplicate, and the inter-observer agreement (Kappa) was also calculated.

RESULTS: From the 82,898 enrolled, 255 cases were extracted by diagnosis code alone, 197 by the combination of diagnosis and prescription codes, and 197 by the combination of diagnosis codes and prescription or surgical codes. The PPV for confirmed CD cases was 83% by diagnosis codes alone, but improved to 97% by combining with prescription codes. The inter-observer agreement was 0.9903.

CONCLUSIONS: Single ICD-code alone was insufficient to define CD; however, the algorithm that combined diagnosis codes with prescription codes indicated a sufficiently high PPV and will enable outcome-based research on CD using the Japanese claims database.

PMID:34644342 | DOI:10.1371/journal.pone.0258537

PLoS One. 2021 Oct 13;16(10):e0258326. doi: 10.1371/journal.pone.0258326. eCollection 2021.

ABSTRACT

Gene expression data has the characteristics of high dimensionality and a small sample size and contains a large number of redundant genes unrelated to a disease. The direct application of machine learning to classify this type of data will not only incur a great time cost but will also sometimes fail to improved classification performance. To counter this problem, this paper proposes a dimension-reduction algorithm based on weighted kernel principal component analysis (WKPCA), constructs kernel function weights according to kernel matrix eigenvalues, and combines multiple kernel functions to reduce the feature dimensions. To further improve the dimensional reduction efficiency of WKPCA, t-class kernel functions are constructed, and corresponding theoretical proofs are given. Moreover, the cumulative optimal performance rate is constructed to measure the overall performance of WKPCA combined with machine learning algorithms. Naive Bayes, K-nearest neighbour, random forest, iterative random forest and support vector machine approaches are used in classifiers to analyse 6 real gene expression dataset. Compared with the all-variable model, linear principal component dimension reduction and single kernel function dimension reduction, the results show that the classification performance of the 5 machine learning methods mentioned above can be improved effectively by WKPCA dimension reduction.

PMID:34644329 | DOI:10.1371/journal.pone.0258326

PLoS One. 2021 Oct 13;16(10):e0257421. doi: 10.1371/journal.pone.0257421. eCollection 2021.

ABSTRACT

Coronavirus Disease-2019 (COVID-19) quickly surged the whole world and affected people’s physical, mental, and social health thereby upsetting their quality of life. Therefore, we aimed to investigate the quality of life (QoL) of COVID-19 positive patients after recovery in Bangladesh. This was a study of adult (aged ≥18 years) COVID-19 individuals from eight divisions of Bangladesh diagnosed and confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) from June 2020 to November 2020. Given a response rate of 60% in a pilot study, a random list of 6400 COVID-19 patients was generated to recruit approximately 3200 patients from eight divisions of Bangladesh and finally a total of 3244 participants could be recruited for the current study. The validated Bangla version of the World Health Organization Quality of Life Brief (WHOQOL-BREF) questionnaire was used to assess the QoL. Data were analyzed by STATA (Version 16.1) and R (Version 4.0.0). All the procedures were conducted following ethical approval and in accordance with the Declaration of Helsinki. The mean scores of QoL were highest for the physical domain (68.25±14.45) followed by social (65.10±15.78), psychological (63.28±15.48), and environmental domain (62.77±13.07). Psychological and physical domain scores among females were significantly lower than the males (p<0.001). The overall quality of life was lower in persons having a chronic disease. Participants over 45 years of age were 52% less likely to enjoy good physical health than the participants aged below 26 years (AOR: 0.48, CI: 0.28-0.82). The quality of life of employed participants was found 1.8 times higher than the unemployed (AOR: 1.80, CI: 1.11-2.91). Those who were admitted to hospitals during infection had a low QoL score in physical, psychological, and socials domains. However, QoL improved in all aspect except the psychological domain for each day passed after the diagnosis. These findings call for a focus on the quality of life of the COVID-19 affected population, with special emphasis given to females, older adults, unemployed, and people with comorbidities.

PMID:34644332 | DOI:10.1371/journal.pone.0257421