Tag: pubmed

Pediatr Blood Cancer. 2022 Nov 2:e30046. doi: 10.1002/pbc.30046. Online ahead of print.

ABSTRACT

INTRODUCTION: There is limited understanding of pain, patient-reported outcomes (PROs) of health-related quality of life (HRQoL), psychological factors, and experimental pain sensitivity before and following hematopoietic cell transplant (HCT) in children with sickle cell disease (SCD).

METHODS: Individuals aged 8 years and older, English speaking, and scheduled for a HCT were invited to participate in an observational study where they completed assessments of pain, PROs, psychological factors, and qualitative interviews before and around 3 months, 6 months, 1 year, and 2 years post-HCT. An optional substudy of experimental pain sensitivity before and around 6 month, 1 year, and 2 years post-HCT was also offered.

RESULTS: Data from eight participants (median age 13.5 years, 25% female) with sickle cell anemia (SCA) or similarly severe genotype, and successful donor-derived erythropoiesis post-HCT are reported. We found that collection of pain, PROs, psychological factors, and qualitative data were feasible in the context of HCT. We found moderate to large differences in pain and some PROs between baseline to 1 year and baseline to 2 year post-HCT based on effect sizes, but only some differences were statistically significant. We found moderate to large differences in pressure pain threshold and moderate differences in cold pain threshold between baseline to 1 year and baseline to 2 year post-HCT based on effect sizes, but these differences were not statistically significant. Qualitative data indicated an improvement in pain and HRQoL post-HCT.

CONCLUSION: This study provides a framework for the conduct of multimodal pain assessments before and after HCT, which is feasible but faced with unique barriers.

PMID:36322607 | DOI:10.1002/pbc.30046

PLoS One. 2022 Nov 2;17(11):e0276860. doi: 10.1371/journal.pone.0276860. eCollection 2022.

ABSTRACT

Providing access to non-confidential government data to the public is one of the initiatives adopted by many governments today to embrace government transparency practices. The initiative of publishing non-confidential government data for the public to use and re-use without restrictions is known as Open Government Data (OGD). Nevertheless, after several years after its inception, the direction of OGD implementation remains uncertain. The extant literature on OGD adoption concentrates primarily on identifying factors influencing adoption decisions. Yet, studies on the underlying factors influencing OGD after the adoption phase are scarce. Based on these issues, this study investigated the post-adoption of OGD in the public sector, particularly the data provider agencies. The OGD post-adoption framework is crafted by anchoring the Technology-Organization-Environment (TOE) framework and the innovation adoption process theory. The data was collected from 266 government agencies in the Malaysian public sector. This study employed the partial least square-structural equation modeling as the statistical technique for factor analysis. The results indicate that two factors from the organizational context (top management support, organizational culture) and two from the technological context (complexity, relative advantage) have a significant contribution to the post-adoption of OGD in the public sector. The contribution of this study is threefold: theoretical, conceptual, and practical. This study contributed theoretically by introducing the post-adoption framework of OGD that comprises the acceptance, routinization, and infusion stages. As the majority of OGD adoption studies conclude their analysis at the adoption (decisions) phase, this study gives novel insight to extend the analysis into unexplored territory, specifically the post-adoption phase. Conceptually, this study presents two new factors in the environmental context to be explored in the OGD adoption study, namely, the data demand and incentives. The fact that data providers are not influenced by data requests from the agency’s external environment and incentive offerings is something that needs further investigation. In practicality, the findings of this study are anticipated to assist policymakers in strategizing for long-term OGD implementation from the data provider’s perspective. This effort is crucial to ensure that the OGD initiatives will be incorporated into the public sector’s service thrust and become one of the digital government services provided to the citizen.

PMID:36322601 | DOI:10.1371/journal.pone.0276860

PLoS One. 2022 Nov 2;17(11):e0276944. doi: 10.1371/journal.pone.0276944. eCollection 2022.

ABSTRACT

Long-term exposure to low polycyclic aromatic hydrocarbon (PAH) concentration may ave detrimental effects, including changing platelet indices. Effects of chronic exposure to low PAH concentrations have been evaluated in cross-sectional, but not in longitudinal studies, to date. We aimed to assess the effects of long-term exposure to the low-concentration PAHs on alterations in platelet indices in the Chinese population. During 2014-2017, we enrolled 222 participants who had lived in a village in northern China, 1-2 km downwind from a coal plant, for more than 25 years, but who were not employed by the plant or related businesses. During three follow-ups, annually in June, demographic information and urine and blood samples were collected. Eight PAHs were tested: namely 2-hydroxynaphthalene, 1-hydroxynaphthalene, 2-hydroxyfluorene, 9-hydroxyfluorene (9-OHFlu), 2-hydroxyphenanthrene (2-OHPh), 1-hydroxyphenanthrene (1-OHPh), 1-hydroxypyrene (1-OHP), and 3-hydroxybenzo [a] pyrene. Five platelet indices were measured: platelet count (PLT), platelet distribution width (PDW), mean platelet volume (MPV), platelet crit, and the platelet-large cell ratio. Generalized mixed and generalized linear mixed models were used to estimate correlations between eight urinary PAH metabolites and platelet indices. Model 1 assessed whether these correlations varied over time. Models 2 and 3 adjusted for additional personal information and personal habits. We found the following significant correlations: 2-OHPh (Model1 β1 = 18.06, Model2 β2 = 18.54, Model β3 = 18.54), 1-OHPh (β1 = 16.43, β2 = 17.42, β3 = 17.42), 1-OHP(β1 = 13.93, β2 = 14.03, β3 = 14.03) with PLT, as well as 9-OHFlu with PDW and MPV (odds ratio or Model3 ORPDW[95%CI] = 1.64[1.3-2.06], ORMPV[95%CI] = 1.33[1.19-1.48]). Long-term exposure to low concentrations of PAHs, indicated by2-OHPh, 1-OHPh, 1-OHP, and 9-OHFlu, as urinary biomarkers, affects PLT, PDW, and MPV. 9-OHFlu increased both PDW and MPV after elimination of the effects of other PAH exposure modes.

PMID:36322595 | DOI:10.1371/journal.pone.0276944

PLoS One. 2022 Nov 2;17(11):e0275346. doi: 10.1371/journal.pone.0275346. eCollection 2022.

ABSTRACT

This paper proposes an improvement to the dwarf mongoose optimization (DMO) algorithm called the advanced dwarf mongoose optimization (ADMO) algorithm. The improvement goal is to solve the low convergence rate limitation of the DMO. This situation arises when the initial solutions are close to the optimal global solution; the subsequent value of the alpha must be small for the DMO to converge towards a better solution. The proposed improvement incorporates other social behavior of the dwarf mongoose, namely, the predation and mound protection and the reproductive and group splitting behavior to enhance the exploration and exploitation ability of the DMO. The ADMO also modifies the lifestyle of the alpha and subordinate group and the foraging and seminomadic behavior of the DMO. The proposed ADMO was used to solve the congress on evolutionary computation (CEC) 2011 and 2017 benchmark functions, consisting of 30 classical and hybrid composite problems and 22 real-world optimization problems. The performance of the ADMO, using different performance metrics and statistical analysis, is compared with the DMO and seven other existing algorithms. In most cases, the results show that solutions achieved by the ADMO are better than the solution obtained by the existing algorithms.

PMID:36322574 | DOI:10.1371/journal.pone.0275346

PLoS One. 2022 Nov 2;17(11):e0275967. doi: 10.1371/journal.pone.0275967. eCollection 2022.

ABSTRACT

Accurately counting the human cost of the COVID-19 at both the national and regional level is a policy priority. The Russian Federation currently reports one of the higher COVID-19 mortality rates in the world; but estimates of mortality differ significantly. Using a statistical method accounting for changes in the population age structure, we present the first national and regional estimates of excess mortality for 2021; calculations of excess mortality by age, gender, and urban/rural status for 2020; and mean remaining years of life expectancy lost at the regional level. We estimate that there were 351,158 excess deaths in 2020 and 678,022 in 2021 in the Russian Federation; and, in 2020, around 2.0 years of life expectancy lost. While the Russian Federation exhibits very high levels of excess mortality compared to other countries, there is a wide degree of regional variation: in 2021, excess deaths expressed as a percentage of expected deaths at the regional level range from 27% to 52%. Life expectancy loss is generally greater for males; while excess mortality is greater in urban areas. For Russia as whole, an average person who died due to the pandemic in 2020 would have otherwise lived for a further 14 more years (and as high as 18 years in some regions), disproving the widely held view that excess mortality during the pandemic period was concentrated among those with few years of life remaining-especially for females. At a regional level, less densely populated, more remote regions, rural regions appear to have fared better regarding excess mortality and life expectancy loss-however, a part of this differential could be owing to measurement issues. The calculations demonstrate more clearly the true degree of the human cost of the pandemic in the Russian Federation.

PMID:36322565 | DOI:10.1371/journal.pone.0275967

PLoS One. 2022 Nov 2;17(11):e0275397. doi: 10.1371/journal.pone.0275397. eCollection 2022.

ABSTRACT

BACKGROUND: Very few previous studies have involved school students or their parents in the evaluation of virtual learning environment (VLE). Thus, this survey was performed to evaluate the satisfaction of both school students and their parents with the VLE in the Kingdom of Saudi Arabia during the COVID-19 pandemic.

METHODS: A cross-sectional questionnaire-based survey was distributed online for VLE evaluation. The questionnaire was based on previous studies and expert opinions from validated instruments for assessing distance education, integrative and literature reviews of VLE environment. A median value >3 indicated participant satisfaction in each of the 5 domains of the questionnaire as well as overall VLE satisfaction. The used questionnaire was checked after its implementation by all possible statistical means and it was found to be of acceptable validity and reliability.

RESULTS: Six hundred and ninety-three participants including 571 Saudi citizens and 122 non-Saudi residents participated in this survey. The number of school students who agreed or strongly agreed were significantly lower than the number of students who disagreed or strongly disagreed with preferring the VLE over traditional education (p<0.001). The participants evaluated the VLE experience as unsatisfactory with a median value ≤3 for 4 out of 5 questionnaire domains with an overall satisfaction value of 2.8. Among the 117 participants who gave further written opinions/comments, 42(35.9%) participants supported the VLE as an alternative to traditional classrooms, if equipment and internet are made available and for the safety of their children.

CONCLUSIONS: This is one of few available adequate population-based studies for exploring the VLE satisfaction of both Saudi citizens and non-Saudi residents school students and their parents. This study showed the participants’ unsatisfactory VLE experience. The VLE is accepted as an alternative to traditional classrooms to keep up with learning and to maintain the safety of children and it can be a supplementary learning method but many measures are still needed to develop the VLE.

PMID:36322559 | DOI:10.1371/journal.pone.0275397

JMIR Res Protoc. 2022 Nov 2;11(11):e37420. doi: 10.2196/37420.

ABSTRACT

BACKGROUND: The incidence of eating disorders (EDs) among adolescents has significantly increased since the beginning of the COVID-19 pandemic. Hybrid care, which combines web-based and in-person modalities, is a promising approach for adolescents with EDs but remains understudied in this population.

OBJECTIVE: We aimed to implement a novel hybrid (web-based and in-person) intensive ambulatory care program for youth and evaluate its feasibility, acceptability, and preliminary effectiveness.

METHODS: We will use a naturalistic pretest-posttest design to evaluate our proposed pilot Intensive Ambulatory Care Program (IACP). This novel type of day hospital care follows evidence-based principles and uses a family-centered, educational, and motivational approach. It will be tailored to the psychological needs of each participant and will be delivered in a hybrid format. A total of 100 participants meeting the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) criteria for EDs, aged 12-18 years, will be recruited over the 2-year trial period. We will examine recruitment, retention, and adhesion-to-protocol rates; participant and family satisfaction; and preliminary effectiveness using quantitative self-report questionnaires.

RESULTS: Rolling recruitment will take place from winter 2022 to fall 2023, during which time we expect to recruit approximately 80% (100/120) of eligible participants, retain at least 75% (75/100) of enrolled participants and have at least 70% (70/100) of enrolled participants complete at least one therapeutic session per week and all pre- and postintervention questionnaires. Data collection will occur concurrently. We base our recruitment and retention estimates on previous literature and consider that the highly flexible design of the IACP and the fact that no extra work will be required of individuals in the program to participate in the study, will lead to high levels of feasibility. We anticipate that participants and their families will be satisfied with both the program and hybrid delivery format. We expect that participation in the IACP will be associated with a medium effect size reduction in ED psychopathology from baseline to end of treatment. The data analysis and manuscript writing are expected to be completed by the summer of 2024.

CONCLUSIONS: Given the high clinical burden associated with EDs, this study has the potential to fill an important research gap by testing the implementation of a novel hybrid mode of intervention. If feasible, acceptable, and effective, the IACP could lead to important improvements in health care services for adolescents with EDs.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/37420.

PMID:36322118 | DOI:10.2196/37420

Environ Technol. 2022 Nov 2:1-35. doi: 10.1080/09593330.2022.2143284. Online ahead of print.

ABSTRACT

Drones are revolutionizing earth system observations, and are increasingly used for high resolution monitoring of water quality. The objective of this research was to test whether drone-based multispectral imagery could predict important water quality parameters in an ICOLL (intermittently closed and opened lake or lagoon). Three water quality sampling campaigns were undertaken, measuring temperature, salinity, pH, dissolved oxygen (DO), chlorophyll (CHL), turbidity, total suspended sediments (TSS), coloured dissolved organic matter (CDOM), green algae, crytophyta, diatoms, bluegreen algae and total algal concentrations. DistilM statistical analyses were conducted to reveal the bands accounting for the most variation across all water quality data, then linear correlations between specific band/band ratios and individual water quality parameters were performed. DistilM analyses revealed the NIR band accounted for most variation in March, the Green band in April and the RE band in May, and showed that the most important contributors varied significantly among campaigns and variables. Significant linear correlations with R² > 0.4 were obtained for eleven of the water quality parameters tested, with the strongest correlation obtained for CHL and the green band (R² 0.72). The relative importance of predictor bands and observed water quality parameters varied temporally. We conclude that drones with a multispectral sensor can produce useful “snapshot” prediction maps for a range of water quality parameters, such as chlorophyll, bluegreen algae and dissolved oxygen. However, a single model was insufficient to reproduce the temporal variation of water parameters in dynamic estuarine systems.

PMID:36322116 | DOI:10.1080/09593330.2022.2143284

JMIR Med Inform. 2022 Nov 2;10(11):e40878. doi: 10.2196/40878.

ABSTRACT

BACKGROUND: In recent years, the progress and generalization surrounding portable ultrasonic probes has made ultrasound (US) a useful tool for physicians when making a diagnosis. With the advent of machine learning and deep learning, the development of a computer-aided diagnostic system for screening renal US abnormalities can assist general practitioners in the early detection of pediatric kidney diseases.

OBJECTIVE: In this paper, we sought to evaluate the diagnostic performance of deep learning techniques to classify kidney images as normal and abnormal.

METHODS: We chose 330 normal and 1269 abnormal pediatric renal US images for establishing a model for artificial intelligence. The abnormal images involved stones, cysts, hyperechogenicity, space-occupying lesions, and hydronephrosis. We performed preprocessing of the original images for subsequent deep learning. We redefined the final connecting layers for classification of the extracted features as abnormal or normal from the ResNet-50 pretrained model. The performances of the model were tested by a validation data set using area under the receiver operating characteristic curve, accuracy, specificity, and sensitivity.

RESULTS: The deep learning model, 94 MB parameters in size, based on ResNet-50, was built for classifying normal and abnormal images. The accuracy, (%)/area under curve, of the validated images of stone, cyst, hyperechogenicity, space-occupying lesions, and hydronephrosis were 93.2/0.973, 91.6/0.940, 89.9/0.940, 91.3/0.934, and 94.1/0.996, respectively. The accuracy of normal image classification in the validation data set was 90.1%. Overall accuracy of (%)/area under curve was 92.9/0.959..

CONCLUSIONS: We established a useful, computer-aided model for automatic classification of pediatric renal US images in terms of normal and abnormal categories.

PMID:36322109 | DOI:10.2196/40878

J Med Internet Res. 2022 Nov 2;24(11):e40364. doi: 10.2196/40364.

ABSTRACT

BACKGROUND: Chronic diseases are putting huge pressure on health care systems. Nurses are widely recognized as one of the competent health care providers who offer comprehensive care to patients during rehabilitation after hospitalization. In recent years, telerehabilitation has opened a new pathway for nurses to manage chronic diseases at a distance; however, it remains unclear which chronic disease patients benefit the most from this innovative delivery mode.

OBJECTIVE: This study aims to summarize current components of community-based, nurse-led telerehabilitation programs using the chronic care model; evaluate the effectiveness of nurse-led telerehabilitation programs compared with traditional face-to-face rehabilitation programs; and compare the effects of telerehabilitation on patients with different chronic diseases.

METHODS: A systematic review and meta-analysis were performed using 6 databases for articles published from 2015 to 2021. Studies comparing the effectiveness of telehealth rehabilitation with face-to-face rehabilitation for people with hypertension, cardiac diseases, chronic respiratory diseases, diabetes, cancer, or stroke were included. Quality of life was the primary outcome. Secondary outcomes included physical indicators, self-care, psychological impacts, and health-resource use. The revised Cochrane risk of bias tool for randomized trials was employed to assess the methodological quality of the included studies. A meta-analysis was conducted using a random-effects model and illustrated with forest plots.

RESULTS: A total of 26 studies were included in the meta-analysis. Telephone follow-ups were the most commonly used telerehabilitation delivery approach. Chronic care model components, such as nurses-patient communication, self-management support, and regular follow-up, were involved in all telerehabilitation programs. Compared with traditional face-to-face rehabilitation groups, statistically significant improvements in quality of life (cardiac diseases: standard mean difference [SMD] 0.45; 95% CI 0.09 to 0.81; P=.01; heterogeneity: X²₁=1.9; I²=48%; P=.16; chronic respiratory diseases: SMD 0.18; 95% CI 0.05 to 0.31; P=.007; heterogeneity: X²₂=1.7; I²=0%; P=.43) and self-care (cardiac diseases: MD 5.49; 95% CI 2.95 to 8.03; P<.001; heterogeneity: X²₅=6.5; I²=23%; P=.26; diabetes: SMD 1.20; 95% CI 0.55 to 1.84; P<.001; heterogeneity: X²₄=46.3; I²=91%; P<.001) were observed in the groups that used telerehabilitation. For patients with any of the 6 targeted chronic diseases, those with hypertension and diabetes experienced significant improvements in their blood pressure (systolic blood pressure: MD 10.48; 95% CI 2.68 to 18.28; P=.008; heterogeneity: X²₁=2.2; I²=54%; P=0.14; diastolic blood pressure: MD 1.52; 95% CI -10.08 to 13.11, P=.80; heterogeneity: X²1=11.5; I²=91%; P<.001), and hemoglobin A1c (MD 0.19; 95% CI -0.19 to 0.57 P=.32; heterogeneity: X²₄=12.4; I²=68%; P=.01) levels. Despite these positive findings, telerehabilitation was found to have no statistically significant effect on improving patients’ anxiety level, depression level, or hospital admission rate.

CONCLUSIONS: This review showed that telerehabilitation programs could be beneficial to patients with chronic disease in the community. However, better designed nurse-led telerehabilitation programs are needed, such as those involving the transfer of nurse-patient clinical data. The heterogeneity between studies was moderate to high. Future research could integrate the chronic care model with telerehabilitation to maximize its benefits for community-dwelling patients with chronic diseases.

TRIAL REGISTRATION: International Prospective Register of Systematic Reviews CRD42022324676; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=324676.

PMID:36322107 | DOI:10.2196/40364