-
Lancet (London, England) Jun 2024After surgery for a broken ankle, patients are usually instructed to avoid walking for 6 weeks (delayed weight-bearing). Walking 2 weeks after surgery (early... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
After surgery for a broken ankle, patients are usually instructed to avoid walking for 6 weeks (delayed weight-bearing). Walking 2 weeks after surgery (early weight-bearing) might be a safe and preferable rehabilitation strategy. This study aimed to determine the clinical and cost effectiveness of an early weight-bearing strategy compared with a delayed weight-bearing strategy.
METHODS
This was a pragmatic, multicentre, randomised, non-inferiority trial including 561 participants (aged ≥18 years) who received acute surgery for an unstable ankle fracture in 23 UK National Health Service (NHS) hospitals who were assigned to either a delayed weight-bearing (n=280) or an early weight-bearing rehabilitation strategy (n=281). Patients treated with a hindfoot nail, those who did not have protective ankle sensation (eg, peripheral neuropathy), did not have the capacity to consent, or did not have the ability to adhere to trial procedures were excluded. Neither participants nor clinicians were masked to the treatment. The primary outcome was ankle function measured using the Olerud and Molander Ankle Score (OMAS) at 4 months after randomisation, in the per-protocol population. The pre-specified non-inferiority OMAS margin was -6 points and superiority testing was included in the intention-to-treat population in the event of non-inferiority. The trial was prospectively registered with ISRCTN Registry, ISRCTN12883981, and the trial is closed to new participants.
FINDINGS
Primary outcome data were collected from 480 (86%) of 561 participants. Recruitment was conducted between Jan 13, 2020, and Oct 29, 2021. At 4 months after randomisation, the mean OMAS score was 65·9 in the early weight-bearing and 61·2 in the delayed weight-bearing group and adjusted mean difference was 4·47 (95% CI 0·58 to 8·37, p=0·024; superiority testing adjusted difference 4·42, 95% CI 0·53 to 8·32, p=0·026) in favour of early weight-bearing. 46 (16%) participants in the early weight-bearing group and 39 (14%) in the delayed weight-bearing group had one or more complications (adjusted odds ratio 1·18, 95% CI 0·80 to 1·75, p=0·40). The mean costs from the perspective of the NHS and personal social services in the early and delayed weight-bearing groups were £725 and £785, respectively (mean difference -£60 [95% CI -342 to 232]). The probability that early weight-bearing is cost-effective exceeded 80%.
INTERPRETATION
An early weight-bearing strategy was found to be clinically non-inferior and highly likely to be cost-effective compared with the current standard of care (delayed weight-bearing).
FUNDING
National Institute for Health and Care Research (NIHR), NIHR Barts Biomedical Research Centre, and NIHR Applied Research Collaboration Oxford and Thames Valley.
Topics: Humans; Weight-Bearing; Female; Male; Ankle Fractures; Middle Aged; Adult; Cost-Benefit Analysis; Time Factors; Treatment Outcome; Walking; United Kingdom; Aged
PubMed: 38848738
DOI: 10.1016/S0140-6736(24)00710-4 -
Heliyon Jun 2024Cocoa beans are susceptible to fungal contamination during processing and storage. The knowledge of the use of pesticides and post-harvest handling of cocoa beans among...
Cocoa beans are susceptible to fungal contamination during processing and storage. The knowledge of the use of pesticides and post-harvest handling of cocoa beans among farmers is of great importance for safe consumption. The study evaluated common cocoa production and post-harvest practices of farmers in selected study locations in South Western Nigeria. Primary data were collected through the administration of structured questionnaires, and interviews. The collected data were analyzed using inferential descriptive statistics. The results of 394 farmers showed that 52.9 % in Osun and 47.3 % in Oyo were primarily farmers by occupation, the rest had other ventures. The majority of cocoa farmers were men:83.6 % in Oyo State, 88.2 % in Osun state and 87.9 % in Ondo state. 28.6 % and 32.7 % of farmers were aged 51-60 in the Ondo and Oyo communities, respectively. Osun farming communities are dominated by young adults (51 %) of 31-50 years, followed by Ondo 40 % and36 % of farmers in Oyo State. Most cocoa farmers were married with 4-6 children as the most common household size in Osun (51 %), Ondo (60.4 %) and 49.1 % in Oyo State. The literacy level of farmers in cocoa communities was the highest in Oyo state where 47.3 % had tertiary education. Farmers in Oyo State had better knowledge of the dangers of pesticides than Ondo and Osun. However, ignorance of dangers in agrochemicals was higher among Osun farmers than in Ondo State. The highest (18 %) pesticide use during storage was recorded among Oyo farmers, while the least (11.0 %) was recorded among farmers in Ondo State. Pesticide usage was more abundant in Osun (50 %) during cocoa production than in the other study areas. The majority of farmers were positively disposed to make use of nose masks during agrochemical application, meanwhile, 69 %, 62 %, and 61 % of farmers used them already in Oyo, Ondo, and Osun states, respectively. Educational qualification (χ = 9.176, p = 0.027) of cocoa farmers was significantly related to knowledge of best practices. Farmers with higher education have a greater ability to receive and process information relating to global best practices in production, postharvest, and pesticide handling in cocoa. In conclusion, cocoa farmers' knowledge of processing, use of pesticides, and storage practices differed from one location to another. Intensive orientation and more enlightenment by extension workers against indiscriminate use of pesticides in cocoa plantations and stores must be consistently and continuously done.
PubMed: 38846000
DOI: 10.1016/j.heliyon.2024.e31724 -
PloS One 2024This cross-sectional study aimed to determine 1) whether German citizens' adherence to health professionals' recommendations and mandates regarding protective masks...
This cross-sectional study aimed to determine 1) whether German citizens' adherence to health professionals' recommendations and mandates regarding protective masks during the COVID-19 pandemic varied according to their political party affiliations, and 2) how behavioral cues provided by members of shared social groups, such as family and friends, influenced individual mask-wearing behavior. A quota-based sample of German voters (n = 330) consisting of 55 citizens whose voting intentions aligned with each of the country's six main political parties responded to an online questionnaire consisting of multiple-choice and open-ended questions. Univariate descriptive statistical analyses of quantitative data were conducted, and multiple regressions were performed to determine log odds and significant variations among group-based responses. A pragmatic inductive coding process was used to conduct a thematic analysis of qualitative data. Results indicated that those participants who expressed an intention to vote for the populist radical right party were the least likely to follow health experts' recommendations and the most likely to express anger and dissatisfaction over mask mandates. Prospective Left Party voters were the most likely to adhere to the advice of their doctors, while those associated with the Green Party were the most likely to adhere to the advice of public health experts. Most survey participants reported aligning their mask-wearing behavior with that of family and friends, with prospective CDU/CSU voters particularly likely to consider the mask-wearing behavior of family members. The results indicate that public health officials should consider how group-related factors influence public health compliance in order to encourage protective mask-wearing in the future.
Topics: Humans; COVID-19; Germany; Masks; Male; Female; Adult; Middle Aged; Cross-Sectional Studies; Politics; Surveys and Questionnaires; Social Identification; Pandemics; SARS-CoV-2; Aged; Cues
PubMed: 38843142
DOI: 10.1371/journal.pone.0302399 -
EJNMMI Physics Jun 2024The purpose of our study is to validate the robustness and accuracy of consensus contour in 2-deoxy-2-[ F]fluoro-D-glucose ( F-FDG) PET radiomic features.
PURPOSE
The purpose of our study is to validate the robustness and accuracy of consensus contour in 2-deoxy-2-[ F]fluoro-D-glucose ( F-FDG) PET radiomic features.
METHODS
225 nasopharyngeal carcinoma (NPC) and 13 extended cardio-torso (XCAT) simulated data were enrolled. All segmentation were performed with four segmentation methods under two different initial masks, respectively. Consensus contour (ConSeg) was then developed using the majority vote rule. 107 radiomic features were extracted by Pyradiomics based on segmentation and the intraclass correlation coefficient (ICC) was calculated for each feature between masks or among segmentation, respectively. In XCAT ICC between segmentation and simulated ground truth were also calculated to access the accuracy.
RESULTS
ICC varied with the dataset, segmentation method, initial mask and feature type. ConSeg presented higher ICC for radiomic features in robustness tests and similar ICC in accuracy tests, compared with the average of four segmentation results. Higher ICC were also generally observed in irregular initial masks compared with rectangular masks in both robustness and accuracy tests. Furthermore, 19 features (17.76%) had ICC ≥ 0.75 in both robustness and accuracy tests for any of the segmentation methods or initial masks. The dataset was observed to have a large impact on the correlation relationships between radiomic features, but not the segmentation method or initial mask.
CONCLUSIONS
The consensus contour combined with irregular initial mask could improve the robustness and accuracy in radiomic analysis to some extent. The correlation relationships between radiomic features and feature clusters largely depended on the dataset, but not segmentation method or initial mask.
PubMed: 38839641
DOI: 10.1186/s40658-024-00652-0 -
Veterinary Medicine International 2024This review delves into the historical context, current epidemiological landscape, genomics, and pathobiology of monkeypox virus (MPXV). Furthermore, it elucidates the... (Review)
Review
This review delves into the historical context, current epidemiological landscape, genomics, and pathobiology of monkeypox virus (MPXV). Furthermore, it elucidates the present vaccination status and strategies to curb the spread of monkeypox. Monkeypox, caused by the known as MPXV, is a zoonotic ailment. MPXV can be transmitted from person to person through respiratory droplets during prolonged face-to-face interactions. While many cases of monkeypox are self-limiting, vulnerable groups such as young children, pregnant women, and immunocompromised individuals may experience severe manifestations. Diagnosis predominantly relies on clinical presentations, complemented by laboratory techniques like RT-PCR. Although treatment is often not required, severe cases necessitate antiviral medications like tecovirimat, cidofovir, and brincidofovir. Vaccination, particularly using the smallpox vaccine, has proven instrumental in outbreak control, exhibiting an efficacy of at least 85% against mpox as evidenced by data from Africa. Mitigating transmission requires measures like wearing surgical masks, adequately covering skin lesions, and avoiding handling wild animals.
PubMed: 38836166
DOI: 10.1155/2024/8839830 -
BMJ Global Health Jun 2024During the COVID-19 pandemic, governments and health authorities faced tough decisions about infection prevention and control measures such as social distancing, face...
BACKGROUND
During the COVID-19 pandemic, governments and health authorities faced tough decisions about infection prevention and control measures such as social distancing, face masks and travel. Judgements underlying those decisions require democratic input, as well as expert input. The aim of this review is to inform decisions about how best to achieve public participation in decisions about public health and social interventions in the context of a pandemic or other public health emergencies.
OBJECTIVES
To systematically review examples of public participation in decisions by governments and health authorities about how to control the COVID-19 pandemic.
DESIGN
We searched Participedia and relevant databases in August 2022. Two authors reviewed titles and abstracts and one author screened publications promoted to full text. One author extracted data from included reports using a standard data-extraction form. A second author checked 10% of the extraction forms. We conducted a structured synthesis using framework analysis.
RESULTS
We included 24 reports (18 from Participedia). Most took place in high-income countries (n=23), involved 'consulting' the public (n=17) and involved public meetings (usually online). Two initiatives reported explicit support for critical thinking. 11 initiatives were formally evaluated (only three reported impacts). Many initiatives did not contribute to a decision, and 17 initiatives did not include any explicit decision-making criteria.
CONCLUSIONS
Decisions about how to manage the COVID-19 pandemic affected nearly everyone. While public participation in those decisions had the potential to improve the quality of the judgements and decisions that were made, build trust, improve adherence and help ensure transparency and accountability, few examples of such initiatives have been reported and most of those have not been formally evaluated. Identified initiatives did point out potential good practices related to online engagement, crowdsourcing and addressing potential power imbalance. Future research should address improved reporting of initiatives, explicit decision-making criteria, support for critical thinking, engagement of marginalised groups and decision-makers and communication with the public.
PROSPERO REGISTRATION NUMBER
358991.
Topics: Humans; COVID-19; Community Participation; Decision Making; SARS-CoV-2; Pandemics; Public Health
PubMed: 38830748
DOI: 10.1136/bmjgh-2023-014404 -
Clinical Ophthalmology (Auckland, N.Z.) 2024To evaluate binocular intermediate visual acuity (IVA), depth of focus, and other visual outcomes achieved with a monofocal aspheric intraocular lens (IOL) using pooled...
PURPOSE
To evaluate binocular intermediate visual acuity (IVA), depth of focus, and other visual outcomes achieved with a monofocal aspheric intraocular lens (IOL) using pooled data from 2 randomized, double-masked, controlled trials.
PATIENTS AND METHODS
The studies conducted at 32 sites included patients aged ≥22 years with bilateral cataracts, preoperative corneal astigmatism 1.0 D, and lens power 18.0-25.0 D. Patients received bilateral AcrySof IQ IOLs (SN60WF). Primary endpoint data were collected at month 6. Binocular uncorrected and corrected distance visual acuity (UDVA and CDVA) at 4 m, binocular uncorrected and corrected IVA (UIVA and DCIVA) at 66 cm, manifest refraction spherical equivalent (MRSE), and binocular defocus curve at 4 m were assessed under photopic conditions. Validated questionnaires were used to assess spectacle use and quality of vision.
RESULTS
Of 233 patients who received SN60WF, 228 had visual acuity data at 6 months. Under photopic conditions, 51% of the eyes had pupils >4 mm, 40% had pupils 3-4 mm, and 9% had pupils <3 mm. Mean ± SD UDVA and CDVA were -0.019 ± 0.110 and -0.088 ± 0.082 logMAR, respectively. Mean ± SD UIVA and DCIVA were 0.125 ± 0.145 and 0.196 ± 0.139 logMAR, respectively. UIVA and DCIVA of 20/32 or better were achieved by 83% (188/228) and 71% (162/228) of patients, respectively. Mean ± SD MRSE was -0.007 ± 0.404 D for the first eye and 0.036 ± 0.371 for the second eye. The defocus curve demonstrated binocular vision of 0.24 logMAR or better from +1.2 to -1.5 D. Spectacle independence for distance and intermediate vision was reported by 86% and 41% of the patients, respectively. Based on questionnaires, 61%, 79%, and 65% of the patients did not experience starbursts, halos, or glare.
CONCLUSION
A monofocal aspheric IOL (SN60WF) assessed in a large, pooled study provided excellent distance vision and clinically functional intermediate vision.
PubMed: 38827774
DOI: 10.2147/OPTH.S458125 -
Ophthalmology Science 2024To gain an understanding of data labeling requirements to train deep learning models for measurement of geographic atrophy (GA) with fundus autofluorescence (FAF) images.
PURPOSE
To gain an understanding of data labeling requirements to train deep learning models for measurement of geographic atrophy (GA) with fundus autofluorescence (FAF) images.
DESIGN
Evaluation of artificial intelligence (AI) algorithms.
SUBJECTS
The Age-Related Eye Disease Study 2 (AREDS2) images were used for training and cross-validation, and GA clinical trial images were used for testing.
METHODS
Training data consisted of 2 sets of FAF images; 1 with area measurements only and no indication of GA location (Weakly labeled) and the second with GA segmentation masks (Strongly labeled).
MAIN OUTCOME MEASURES
Bland-Altman plots and scatter plots were used to compare GA area measurement between ground truth and AI measurements. The Dice coefficient was used to compare accuracy of segmentation of the Strong model.
RESULTS
In the cross-validation AREDS2 data set (n = 601), the mean (standard deviation [SD]) area of GA measured by human grader, Weakly labeled AI model, and Strongly labeled AI model was 6.65 (6.3) mm, 6.83 (6.29) mm, and 6.58 (6.24) mm, respectively. The mean difference between ground truth and AI was 0.18 mm (95% confidence interval, [CI], -7.57 to 7.92) for the Weakly labeled model and -0.07 mm (95% CI, -1.61 to 1.47) for the Strongly labeled model. With GlaxoSmithKline testing data (n = 156), the mean (SD) GA area was 9.79 (5.6) mm, 8.82 (4.61) mm, and 9.55 (5.66) mm for human grader, Strongly labeled AI model, and Weakly labeled AI model, respectively. The mean difference between ground truth and AI for the 2 models was -0.97 mm (95% CI, -4.36 to 2.41) and -0.24 mm (95% CI, -4.98 to 4.49), respectively. The Dice coefficient was 0.99 for intergrader agreement, 0.89 for the cross-validation data, and 0.92 for the testing data.
CONCLUSIONS
Deep learning models can achieve reasonable accuracy even with Weakly labeled data. Training methods that integrate large volumes of Weakly labeled images with small number of Strongly labeled images offer a promising solution to overcome the burden of cost and time for data labeling.
FINANCIAL DISCLOSURES
Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
PubMed: 38827491
DOI: 10.1016/j.xops.2024.100477 -
AMIA Joint Summits on Translational... 2024Relation Extraction (RE) is a natural language processing (NLP) task for extracting semantic relations between biomedical entities. Recent developments in pre-trained...
Relation Extraction (RE) is a natural language processing (NLP) task for extracting semantic relations between biomedical entities. Recent developments in pre-trained large language models (LLM) motivated NLP researchers to use them for various NLP tasks. We investigated GPT-3.5-turbo and GPT-4 on extracting the relations from three standard datasets, EU-ADR, Gene Associations Database (GAD), and ChemProt. Unlike the existing approaches using datasets with masked entities, we used three versions for each dataset for our experiment: a version with masked entities, a second version with the original entities (unmasked), and a third version with abbreviations replaced with the original terms. We developed the prompts for various versions and used the chat completion model from GPT API. Our approach achieved a F1-score of 0.498 to 0.809 for GPT-3.5-turbo, and a highest F1-score of 0.84 for GPT-4. For certain experiments, the performance of GPT, BioBERT, and PubMedBERT are almost the same.
PubMed: 38827097
DOI: No ID Found -
Research Square May 2024Traditional feature dimension reduction methods have been widely used to uncover biological patterns or structures within individual spatial transcriptomics data....
Traditional feature dimension reduction methods have been widely used to uncover biological patterns or structures within individual spatial transcriptomics data. However, these methods are designed to yield feature representations that emphasize patterns or structures with dominant high variance, such as the normal tissue spatial pattern in a precancer setting. Consequently, they may inadvertently overlook patterns of interest that are potentially masked by these high-variance structures. Herein we present our graph contrastive feature representation method called CoCo-ST (Comparing and Contrasting Spatial Transcriptomics) to overcome this limitation. By incorporating a background data set representing normal tissue, this approach enhances the identification of interesting patterns in a target data set representing precancerous tissue. Simultaneously, it mitigates the influence of dominant common patterns shared by the background and target data sets. This enables discerning biologically relevant features crucial for capturing tissue-specific patterns, a capability we showcased through the analysis of serial mouse precancerous lung tissue samples.
PubMed: 38826463
DOI: 10.21203/rs.3.rs-4359834/v1