Tag: nevin manimala

J Public Health (Oxf). 2023 Aug 8:fdad145. doi: 10.1093/pubmed/fdad145. Online ahead of print.

ABSTRACT

BACKGROUND: Long-term conditions (LTCs) are prevalent in socio-economically deprived populations. Self-management interventions can improve health outcomes, but socio-economically deprived groups have lower participation in them, with potentially lower effectiveness. This review explored whether self-management interventions delivered to people experiencing socio-economic deprivation improve outcomes.

METHODS: We searched databases up to November 2022 for randomized trials. We screened, extracted data and assessed the quality of these studies using Cochrane Risk of Bias 2 (RoB2). We narratively synthesized all studies and performed a meta-analysis on eligible articles. We assessed the certainty of evidence using GRADE for articles included in the meta-analysis.

RESULTS: The 51 studies included in this review had mixed findings. For the diabetes meta-analysis, there was a statistically significant pooled reduction in haemoglobin A1c (-0.29%). We had moderate certainty in the evidence. Thirty-eight of the study interventions had specific tailoring for socio-economically deprived populations, including adaptions for low literacy and financial incentives. Each intervention had an average of four self-management components.

CONCLUSIONS: Self-management interventions for socio-economically deprived populations show promise, though more evidence is needed. Our review suggests that the number of self-management components may not be important. With the increasing emphasis on self-management, to avoid exacerbating health inequalities, interventions should include tailoring for socio-economically deprived individuals.

PMID:37553102 | DOI:10.1093/pubmed/fdad145

Int J Hyg Environ Health. 2023 Aug 6;253:114235. doi: 10.1016/j.ijheh.2023.114235. Online ahead of print.

ABSTRACT

The purpose of this paper was to develop exposure estimates for repetitive sub-concussive head impacts (RSHI) for use in epidemiological analyses. We used a questionnaire to collect lifetime history of heading and other head contacts associated with training and playing football from 159 former footballers all members of the English professional football association. We used linear mixed effect regression with player as the random effect, to model the number of headers, blows to the head and head-to-head impacts as a function of potential exposure affecting factors, which were treated as the fixed effects. Exposure affecting factors included playing position, league, context of play (game vs training) and decade of play. Age at time of response to the questionnaire was also included in the models. In model results, playing position was important, with RSHIs being highest among defenders and lowest among goalkeepers. Players headed the ball more during games than in training, and when playing in amateur or youth leagues compared with semi-professional or professional leagues. The average number of reported head impacts declined linearly throughout the observation period (1949-2015). The derived final model for headers explained 43%, 9% and 36% of the between player, within player and total variance in exposure, respectively with good precision and predictive performance. These findings are generally in agreement with previously published results pointing towards the models forming a valid method for estimating exposure to RSHI among former footballers although some further external validation is still warranted.

PMID:37552911 | DOI:10.1016/j.ijheh.2023.114235

Eur J Orthod. 2023 Aug 8:cjad050. doi: 10.1093/ejo/cjad050. Online ahead of print.

ABSTRACT

BACKGROUND: There are a few hypotheses for the origin of palatally impacted canines (PIC). Nevertheless, the results of different studies are controversial.

OBJECTIVE: Considering the evidence available in the literature to determine the skeletal and dentoalveolar dimensions in patients with PIC using cone beam computed tomography (CBCT).

SEARCH METHODS: This systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement. The literature search with no publication date restriction in five databases and hand searching was performed until April 2023.

DATA COLLECTION AND ANALYSIS: Data assessing the skeletal and dentoalveolar characteristics of subjects with PIC evaluated with CBCT was extracted, and the studies’ quality was evaluated with the Newcastle-Ottawa Scale (NOS). Skeletal and dentoalveolar characteristics of subjects with PIC were compared with non-impacted subjects or non-impacted sides. MedCalc software was used to perform the meta-analysis. Statistical heterogeneity was assessed using the chi-square and I-square tests.

RESULTS: The initial database search identified a total of 1153 studies. After applying the selection criteria, nine articles were included in the systematic review and meta-analysis. According to the NOS, all included articles were graded as “Good” quality. The meta-analysis showed a non-significant difference in measuring dentoalveolar height, alveolar first molar width, and basal lateral width. Controversial results were observed when evaluating both basal and alveolar first premolar widths. A significant difference was found when assessing anterior alveolar crest height and basal maxillary width.

CONCLUSIONS: Studies demonstrated the reduction of both dentoalveolar and skeletal maxillary parameters of the patients with PIC. The meta-analysis indicated that PIC correlates to both vertical and transverse skeletal dimensions of the maxilla. However, the results remain controversial. The findings should be interpreted with caution due to different study designs and unbalanced groups in the included studies; therefore, further research is needed for more reliable conclusions.

REGISTRATION: This systematic review and meta-analysis were registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42022362124).

PMID:37552898 | DOI:10.1093/ejo/cjad050

Mol Biol Evol. 2023 Aug 8:msad175. doi: 10.1093/molbev/msad175. Online ahead of print.

ABSTRACT

The clade Pancrustacea, comprising crustaceans and hexapods, is the most diverse group of animals on earth, containing over 80% of animal species and half of animal biomass. It has been the subject of several recent phylogenomic analyses, yet relationships within Pancrustacea show a notable lack of stability. Here, the phylogeny is estimated with expanded taxon sampling, particularly of malacostracans. We show small changes in taxon sampling have large impacts on phylogenetic estimation. By analyzing identical orthologs between two slightly different taxon sets, we show that the differences in the resulting topologies are due primarily to the effects of taxon sampling on the phylogenetic reconstruction method. We compare trees resulting from our phylogenomic analyses with those from the literature to explore the large tree space of pancrustacean phylogenetic hypotheses and find that statistical topology tests reject the previously published trees in favor of the Maximum Likelihood trees produced here. Our results reject several clades including Caridoida, Eucarida, Multicrustacea, Vericrustacea, and Syncarida. Notably, we find Copepoda nested within Allotriocarida with high support and recover a novel relationship between decapods, euphausiids, and syncarids that we refer to as the Syneucarida. With denser taxon sampling, we find Stomatopoda sister to this latter clade, which we collectively name Stomatocarida, dividing Malacostraca into three clades: Leptostraca, Peracarida, and Stomatocarida. A new Bayesian divergence time estimation is conducted using 13 vetted fossils. We review our results in the context of other pancrustacean phylogenetic hypotheses and highlight 15 key taxa to sample in future studies.

PMID:37552897 | DOI:10.1093/molbev/msad175

J Chem Theory Comput. 2023 Aug 8. doi: 10.1021/acs.jctc.3c00383. Online ahead of print.

ABSTRACT

Explainable and interpretable unsupervised machine learning helps one to understand the underlying structure of data. We introduce an ensemble analysis of machine learning models to consolidate their interpretation. Its application shows that restricted Boltzmann machines compress consistently into a few bits the information stored in a sequence of five amino acids at the start or end of α-helices or β-sheets. The weights learned by the machines reveal unexpected properties of the amino acids and the secondary structure of proteins: (i) His and Thr have a negligible contribution to the amphiphilic pattern of α-helices; (ii) there is a class of α-helices particularly rich in Ala at their end; (iii) Pro occupies most often slots otherwise occupied by polar or charged amino acids, and its presence at the start of helices is relevant; (iv) Glu and especially Asp on one side and Val, Leu, Iso, and Phe on the other display the strongest tendency to mark amphiphilic patterns, i.e., extreme values of an effective hydrophobicity, though they are not the most powerful (non)hydrophobic amino acids.

PMID:37552831 | DOI:10.1021/acs.jctc.3c00383

JCO Clin Cancer Inform. 2023 Aug;7:e2300082. doi: 10.1200/CCI.23.00082.

ABSTRACT

PURPOSE: Altmetric Attention Scores (Altmetrics) are real-time measures of scientific impact and attention through various public outlets, including news, blogs, and social media. Herein, we aimed to describe and characterize the relationship between Altmetrics, conventional impact metrics, and features of published cancer clinical trials.

METHODS: We identified two-arm phase III cancer randomized clinical trials with a superiority end point and publication date between 2015 and 2020 from HemOnc and tabulated the following data: Altmetric, study positivity, US Food and Drug Administration (FDA) registration trial status, cancer site/category, treatment context (curative or palliative), trial design, primary end point type, experimental/control arm modality, and journal tier. We further collected conventional bibliometrics including the number of citations and relative citation ratio (RCR) for all published studies. Multiple linear regression modeling identified clinical trial factors predictive of Altmetrics, with alpha = .05 defining statistical significance.

RESULTS: Altmetrics were found for 681 (98%) of 698 publications, with a median score of 38.5 (IQR, 13-132.8). FDA registration studies (β [95% CI], 84.7 [48.8 to 120.6]; P < .001), studies reporting on curative (as opposed to palliative) interventions (-29 [-53.7 to -4.4]; P = .02), genitourinary trials (73.2 [28.1 to 118.2]; P = .001), studies published in tier 1 journals (P < .001), and those with an increased number of citations per year (0.81 [0.66 to 0.95]; P < .001) were significantly associated with increased engagement as measured by Altmetrics. Furthermore, there was a strong correlation between all collected bibliometrics and Altmetrics (R² = 0.63, 0.68, and 0.67; P < .001 for citation count, citations per year, and RCR, respectively).

CONCLUSION: FDA registration trials describing curative interventions, studies published in traditionally defined high-impact journals, and genitourinary trial publications tend to have the greatest Altmetrics. We observed a strong relationship between Altmetrics and conventional bibliometrics. The significance and consequences of these relationships warrant further investigation.

PMID:37552823 | DOI:10.1200/CCI.23.00082

Eur J Neurol. 2023 Aug 8. doi: 10.1111/ene.16025. Online ahead of print.

ABSTRACT

BACKGROUND: Existing data regarding the link between COVID-19 vaccine and myasthenia gravis (MG) are scarce. We aimed to assess the association between Pfizer-BioNTech vaccine with both new-onset MG and MG exacerbation.

METHODS: For the first aim, we conducted a nested case-control study in a cohort of 3,052,467 adults, without a diagnosis of MG, from the largest healthcare provider in Israel. Subjects were followed from January 1, 2021, until June 30, 2022, for the occurrence of MG. Ten randomly selected controls were matched to each case of new-onset MG on age, and sex. For the second aim, a nested case-control study was conducted in a cohort of 1,446 MG patients. Four randomly selected MG patients (controls) were matched to each case of MG exacerbation. Exposure to COVID-19 vaccine in the prior four weeks was assessed in cases and controls.

RESULTS: Overall, 332 patients had new-onset MG and were matched with 3,320 controls. Multivariable conditional logistic regression models showed that the OR for new-onset MG, associated with COVID-19 vaccine, was 1.14 (95% CI, 0.73-1.78). The results were consistent in sensitivity analysis that used more stringent criteria to define MG. Overall, 62 patients with MG exacerbation were matched to 248 MG controls. The multivariable OR for MG exacerbation, associated with COVID-19 vaccine, was 1.35 (0.37-4.89). All results were similar when the prior exposure to COVID-19 vaccine was extended to 8 weeks.

CONCLUSIONS: This study suggests that Pfizer-BioNTech vaccine is not associated with increased risk of new-onset nor exacerbation of myasthenia gravis.

PMID:37552795 | DOI:10.1111/ene.16025

Clin Infect Dis. 2023 Aug 8:ciad464. doi: 10.1093/cid/ciad464. Online ahead of print.

ABSTRACT

BACKGROUND: Scarce data are available comparing infective endocarditis (IE) following surgical aortic valve replacement (SAVR) and transcatheter aortic valve replacement (TAVR). This study aimed to compare the clinical presentation, microbiological profile, management, and outcomes of IE after SAVR vs. TAVR.

METHODS: Data were collected from the “Infectious Endocarditis after TAVR International” (enrollment from 2005 to 2020) and the “International Collaboration on Endocarditis” enrollment from 2000 to 2012) registries. Only patients with an IE affecting the aortic valve prosthesis were included. A 1:1 paired matching approach was used to compare patients with TAVR and SAVR.

RESULTS: A total of 1688 patients were included. Of them, 602 (35.7%) had a surgical bioprosthesis (SB), 666 (39.5%) a mechanical prosthesis, 70 (4.2%) a homograft, and 350 (20.7%) a transcatheter heart valve. In the SAVR vs. TAVR matched population, the rate of new moderate or severe aortic regurgitation was higher in the SB group (43.4% vs. 13.4%, p < 0.001), and fewer vegetations were diagnosed in the SB group (62.5% vs. 82%, p < 0.001). Patients with a SB had a higher rate of perivalvular extension (47.9% vs.27%, p < 0.001) and Staphylococcus Aureus was less common in this group (13.4% vs. 22%, p = 0.033). Despite a higher rate of surgery in patients with SB (44.4% vs. 26.8%, p < 0.001), 1-year mortality was similar (SB: 46.5%, TAVR: 44.8%, log-rank p = 0.697).

CONCLUSIONS: Clinical presentation, type of causative microorganism and treatment differed between patients with an IE located on SB compared to TAVR. Despite these differences, both groups exhibited high and similar mortality at 1-year follow-up.

PMID:37552784 | DOI:10.1093/cid/ciad464

ACS ES T Water. 2022 May 12:acsestwater.2c00060. doi: 10.1021/acsestwater.2c00060. Online ahead of print.

ABSTRACT

Because of the increased population density, high-risk behavior of young students, and lower vaccination rates, university campuses are considered hot spots for COVID-19 transmission. This study monitored the SARS-CoV-2 RNA levels in the wastewater of a Canadian university campus for a year to provide actionable information to safely manage COVID-19 on campus. Wastewater samples were collected from the campus sewer and residence buildings to identify changes, peaks, and hotspots and search for associations with campus events, social gatherings, long weekends, and holidays. Furthermore, the impact of wastewater parameters (total solids, volatile solids, temperature, pH, turbidity, and UV absorbance) on SARS-CoV-2 detection was investigated, and the efficiency of ultrafiltration and centrifugation concentration methods were compared. RT-qPCR was used for detecting SARS-CoV-2 RNA. Wastewater signals largely correlated positively with the clinically confirmed COVID-19 cases on campus. Long weekends and holidays were often followed by increased viral signals, and the implementation of lockdowns quickly decreased the case numbers. In spite of online teaching and restricted access to campus, the university represented a microcosm of the city and mirrored the same trends. Results indicated that the centrifugation concentration method was more sensitive for wastewater with high solids content and that the ultrafiltration concentration method was more sensitive for wastewater with low solids content. Wastewater characteristics collected from the buildings and the campus sewer were different. Statistical analysis was performed to manifest the observations. Overall, wastewater surveillance provided actionable information and was also able to bring high-risk factors and events to the attention of decision-makers, enabling timely corrective measures.

PMID:37552746 | PMC:PMC9128010 | DOI:10.1021/acsestwater.2c00060

ACS ES T Water. 2022 Jul 29:acsestwater.2c00053. doi: 10.1021/acsestwater.2c00053. Online ahead of print.

ABSTRACT

Wastewater-based epidemiology (WBE) is a useful complement to clinical testing for managing COVID-19. While community-scale wastewater and clinical data frequently correlate, less is known about subcommunity relationships between the two data types. Moreover, nondetects in qPCR wastewater data are typically handled through methods known to bias results, overlooking perhaps better alternatives. We address these knowledge gaps using data collected from September 2020-June 2021 in Davis, California (USA). We hypothesize that coupling the expectation maximization (EM) algorithm with the Markov Chain Monte Carlo (MCMC) method could improve estimation of “missing” values in wastewater qPCR data. We test this hypothesis by applying EM-MCMC to city wastewater treatment plant data and comparing output to more conventional nondetect handling methods. Dissimilarities in results (i) underscore the importance of specifying nondetect handling method in reporting and (ii) suggest that using EM-MCMC may yield better agreement between community-scale clinical and wastewater data. We also present a novel framework for spatially aligning clinical data with wastewater data collected upstream of a treatment plant (i.e., distributed across a sewershed). Applying the framework to data from Davis reveals reasonable agreement between wastewater and clinical data at highly granular spatial scales-further underscoring the public-health value of WBE.

PMID:37552742 | PMC:PMC9397567 | DOI:10.1021/acsestwater.2c00053