Nevin Manimala

Genomics Inform. 2022 Jun;20(2):e22. doi: 10.5808/gi.22025. Epub 2022 Jun 22.

ABSTRACT

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant’s effect was contemplated as a weighted sum of the delta and omicron variants’ transmission rate and tuned using a hyperparameter k. Our models’ performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don’t see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.

PMID:35794702 | DOI:10.5808/gi.22025

Genomics Inform. 2022 Jun;20(2):e17. doi: 10.5808/gi.22033. Epub 2022 Jun 30.

ABSTRACT

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

PMID:35794697 | DOI:10.5808/gi.22033

Genomics Inform. 2022 Jun;20(2):e16. doi: 10.5808/gi.22022. Epub 2022 Jun 30.

ABSTRACT

Various methodologies for the genetic analysis of longitudinal data have been proposed and applied to data from large-scale genome-wide association studies (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with traits of interest and to detect SNP-time interactions. We recently proposed a grid-based Bayesian mixed model for longitudinal genetic data and showed that our Bayesian method increased the statistical power compared to the corresponding univariate method and well detected SNP-time interactions. In this paper, we further analyze longitudinal obesity-related traits such as body mass index, hip circumference, waist circumference, and waist-hip ratio from Korea Association Resource data to evaluate the proposed Bayesian method. We first conducted GWAS analyses of cross-sectional traits and combined the results of GWAS analyses through a meta-analysis based on a trajectory model and a random-effects model. We then applied our Bayesian method to a subset of SNPs selected by meta-analysis to further discover SNPs associated with traits of interest and SNP-time interactions. The proposed Bayesian method identified several novel SNPs associated with longitudinal obesity-related traits, and almost 25% of the identified SNPs had significant p-values for SNP-time interactions.

PMID:35794696 | DOI:10.5808/gi.22022

Genomics Inform. 2022 Jun;20(2):e15. doi: 10.5808/gi.20.2.e1. Epub 2022 Jun 30.

NO ABSTRACT

PMID:35794695 | DOI:10.5808/gi.20.2.e1

J Orthop Surg Res. 2022 Jul 6;17(1):337. doi: 10.1186/s13018-022-03227-w.

ABSTRACT

BACKGROUND: Recovery from knee surgery or injury can be hindered by knee arthrofibrosis, which can lead to motion limitations, pain and delayed recovery. Surgery or prolonged physical therapy are often treatment options for arthrofibrosis, but they can result in increased costs and decreased quality of life. A treatment option that can regain lost motion without surgery would help minimize risks and costs for the patient. The purpose of this study was to determine treatment efficacy of high-intensity home mechanical stretch therapy in patients with knee arthrofibrosis.

METHODS: Records were reviewed for 11,000+ patients who were prescribed a high-intensity stretch device to regain knee flexion. Initial and last recorded knee flexion and days between measurements were available for 9842 patients (Dataset 1). Dataset 2 was a subset of 966 patients from Dataset 1. These 966 patients had separate more rigorous measurements available from physical therapy notes (Dataset 3) in addition to data from the internal database (Dataset 2). Within and between dataset statistics were calculated using t tests for comparison of means and Cohen’s d for determination of effect size.

RESULTS: All dataset showed significant gains in flexion (p < 0.01). Mean initial flexion, last recorded flexion and flexion gain were 79.5°, 108.4°, and 29.9°, respectively in Dataset 1. Differences between Datasets 2 and 3 had small effect sizes (Cohen’s d < 0.17). The were no significant differences when comparing workers’ compensation and non-workers’ compensation patients. The average last recorded flexion for all datasets was above the level required to perform activities of daily living. Motion gains were recorded in under 60 days from device delivery.

CONCLUSIONS: High-intensity home mechanical stretch therapy was effective in restoring knee flexion, generally in 2 months or less, and in avoiding additional surgery in severe motion loss patients regardless of sex, age, or workers’ compensation status. We believe high-intensity stretching should be considered in any patient who is at risk for a secondary motion loss surgery, because in over 90% of these patients, the complications and costs associated with surgery can be avoided.

PMID:35794671 | DOI:10.1186/s13018-022-03227-w

Diagn Progn Res. 2022 Jul 7;6(1):13. doi: 10.1186/s41512-022-00126-w.

ABSTRACT

BACKGROUND: Prognostic models are used widely in the oncology domain to guide medical decision-making. Little is known about the risk of bias of prognostic models developed using machine learning and the barriers to their clinical uptake in the oncology domain.

METHODS: We conducted a systematic review and searched MEDLINE and EMBASE databases for oncology-related studies developing a prognostic model using machine learning methods published between 01/01/2019 and 05/09/2019. The primary outcome was risk of bias, judged using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). We described risk of bias overall and for each domain, by development and validation analyses separately.

RESULTS: We included 62 publications (48 development-only; 14 development with validation). 152 models were developed across all publications and 37 models were validated. 84% (95% CI: 77 to 89) of developed models and 51% (95% CI: 35 to 67) of validated models were at overall high risk of bias. Bias introduced in the analysis was the largest contributor to the overall risk of bias judgement for model development and validation. 123 (81%, 95% CI: 73.8 to 86.4) developed models and 19 (51%, 95% CI: 35.1 to 67.3) validated models were at high risk of bias due to their analysis, mostly due to shortcomings in the analysis including insufficient sample size and split-sample internal validation.

CONCLUSIONS: The quality of machine learning based prognostic models in the oncology domain is poor and most models have a high risk of bias, contraindicating their use in clinical practice. Adherence to better standards is urgently needed, with a focus on sample size estimation and analysis methods, to improve the quality of these models.

PMID:35794668 | DOI:10.1186/s41512-022-00126-w

Eye Vis (Lond). 2022 Jul 5;9(1):27. doi: 10.1186/s40662-022-00294-2.

ABSTRACT

BACKGROUND: Glaucoma is the leading cause of irreversible blindness. Normal tension glaucoma (NTG) is a subset of open-angle glaucoma, demonstrating glaucomatous optic nerve damage in the absence of raised intraocular pressure (IOP). NTG is more prevalent in Asian populations. While generally slow-progressing, NTG may be associated with significant central visual field loss. In recent years, minimally invasive glaucoma surgery has been added to the armamentarium of glaucoma surgery. This prospective study aims to evaluate 12-month surgical outcomes of combined iStent inject (Glaukos Corporation, Laguna Hills, CA) implantation and phacoemulsification in Asian eyes with NTG.

METHODS: This is a prospective, single-centre case series of 30 eyes followed up until 12 months after surgery. Outcome measures included IOP, number of glaucoma medications, best-corrected visual acuity (BCVA) and intra and postoperative complications.

RESULTS: Mean age of subjects was 73.1 ± 6.3 years. Majority were ethnic Chinese (n = 27, 90%). Baseline medicated mean IOP was 13.8 ± 2.4 mmHg and mean number of glaucoma medications was 1.3 ± 0.7. Mean Humphrey visual field mean deviation was – 13.7 ± 7.6. The mean IOP reduction at all timepoints from postoperative month (POM) 3 onwards was statistically significant (all P < 0.05), with mean reduction of 1.2 mmHg (95% CI: 0.1-2.2, P = 0.037) by POM12. There was statistically significant reduction in mean number of medications from postoperative day (POD) 1 onwards (all P < 0.05), with mean decrease of 1.0 medication (95% CI: 0.9-1.1, P < 0.001) by POM12. By POM12, 25 (83.3%) eyes were medication-free. Three (10%) eyes had stent occlusion by iris requiring laser iridoplasty. One eye had gross hyphema which resolved on conservative management before POM1. Mean BCVA improved from the baseline 0.3 ± 0.3 logMAR to 0.1 ± 0.1 logMAR postoperatively (P < 0.001). There were no major adverse or sight-threatening events. No eyes required further glaucoma surgery during the 12-month follow-up period.

CONCLUSION: Asian eyes with NTG which underwent combined iStent inject implantation and phacoemulsification demonstrated a significant and sustained reduction in IOP and glaucoma medications, up to 12 months postoperatively.

PMID:35794666 | DOI:10.1186/s40662-022-00294-2

Pilot Feasibility Stud. 2022 Jul 6;8(1):141. doi: 10.1186/s40814-022-01101-4.

ABSTRACT

BACKGROUND: Musculoskeletal disorders are a costly burden for health care and social care services. Patients with musculoskeletal disorders are often treated by physiotherapists in primary health care. Psychosocial variables can be a significant obstacle to recovering from musculoskeletal injuries. The primary aim of this pilot study was to assess the feasibility of performing a prospective study investigating whether self-efficacy, fear of movement, empowerment, or enablement has any relation to the number of visits to physiotherapists among patients with a musculoskeletal disorder in primary health care.

METHODS: Prospective study with a consecutive selection including eleven female and eight male patients age ranged between 22 and 82 years old seeking physiotherapist for the first time for a musculoskeletal disorder in primary health care. Primary outcome measures included operational and practical feasibility regarding recruitment of participants, use of questionnaires, and key variables to be collected as part of the study. Secondary outcomes included the correlation between self-efficacy (Exercise Self-Efficacy Scale (ESES-S)), fear of movement (Tampa Scale for Kinesiophobia (TSK-SV)), empowerment (Making Decisions Scale), enablement (Patient Enablement Instrument (PEI)), and the number of visits to physiotherapists. Statistical analysis was done using IBM SPSS statistics version 28 with analysis of correlation using Spearman’s rank correlation coefficient.

RESULTS: Nineteen patients accepted to participate in the study and were included in the final analysis. Between 14 and 18 completed questionnaires were included. There was a statistically significant correlation between the number of visits to the physiotherapist and self-efficacy, rho=0.692 and p=0.006.

CONCLUSION: The results of the study showed that the design is feasible in terms of recruitment of participants and use of questionnaires. New variables to collect in a large-scale study were identified. In a large-scale study, attention needs to be focused on the improvement of the number of completed questionnaires. The results of this study indicate that the present care of patients with a low level of self-efficacy is not optimal.

PMID:35794659 | DOI:10.1186/s40814-022-01101-4

Confl Health. 2022 Jul 6;16(1):38. doi: 10.1186/s13031-022-00470-0.

ABSTRACT

BACKGROUND: Conflict reduces availability of production input and income, increases the number of days households had to rely on less preferred foods, and limits the variety of foods eaten and the portion size of meals consumed. While existing studies examine the impact of conflict on different food security measures (e.g., Food Consumption Score, Food Insecurity Experience Scale), the relationship between these measures as well as their relationship with political, economic, and agricultural factors remain under explored. Food insecurity may not only be an externality of conflict but also food deprivation may be utilized as a weapon to discourage residency in contested territories or to incentivize rebellions.

METHODOLOGY: This paper examines the association between political factors (e.g., violence, policies that require permit for passage in one’s own hometown), economic factors (e.g., loss of assets, unemployment), agricultural factors (e.g., shortage of water, poor weather conditions), and food insecurity experience and dietary diversity in a conflict setting-that of the occupied Palestinian territory (oPt). The study employs generalized structural equation models to analyze the ‘Survey on socio-economic conditions for Palestinian households 2014’ dataset compiled by the Palestinian Central Bureau of Statistics-which contains a representative sample of the population in the oPt at governorate and locality levels.

RESULTS: We find that in the West Bank, residence in Area C-administered by Israel in both civil and security issues and contains illegal Israeli settlements and outposts-is associated with a higher level of agricultural hardship (p < 0.01) but lower economic hardship (p < 0.01) and a higher dietary diversity (p < 0.001), as compared to those living outside of Area C. In the Gaza Strip, living within one kilometer to a buffer zone is associated with lower dietary diversity (p < 0.01), higher level of political hardship (p < 0.01), and higher level food insecurity experience (p < 0.01) compared to not living in close proximity to a buffer zone. Concomitantly, in the Gaza Strip, food insecurity experience is associated with approximately a one-point reduction in dietary diversity as measured by the food consumption score (p < 0.01).

CONCLUSIONS: The results suggest that broader socio-political conditions in the oPt impact different aspects of food security through augmenting the economic and agricultural hardships that are experienced by the residents. As such, it is important to address these broader political and economic structures in order to have more sustainable interventions in reducing food insecurity.

PMID:35794657 | DOI:10.1186/s13031-022-00470-0

Implement Sci Commun. 2022 Jul 6;3(1):72. doi: 10.1186/s43058-022-00306-1.

ABSTRACT

BACKGROUND: To combat the opioid epidemic in the USA, unprecedented federal funding has been directed to states and territories to expand access to prevention, overdose rescue, and medications for opioid use disorder (MOUD). Similar to other states, California rapidly allocated these funds to increase reach and adoption of MOUD in safety-net, primary care settings such as Federally Qualified Health Centers. Typical of current real-world implementation endeavors, a package of four implementation strategies was offered to all clinics. The present study examines (i) the pre-post effect of the package of strategies, (ii) whether/how this effect differed between new (start-up) versus more established (scale-up) MOUD practices, and (iii) the effect of clinic engagement with each of the four implementation strategies.

METHODS: Forty-one primary care clinics were offered access to four implementation strategies: (1) Enhanced Monitoring and Feedback, (2) Learning Collaboratives, (3) External Facilitation, and (4) Didactic Webinars. Using linear mixed effects models, RE-AIM guided outcomes of reach, adoption, and implementation quality were assessed at baseline and at 9 months follow-up.

RESULTS: Of the 41 clinics, 25 (61%) were at MOUD start-up and 16 (39%) were at scale-up phases. Pre-post difference was observed for the primary outcome of percent of patient prescribed MOUD (reach) (β_time = 3.99; 0.73 to 7.26; p = 0.02). The largest magnitude of change occurred in implementation quality (ES = 0.68; 95% CI = 0.66 to 0.70). Baseline MOUD capability moderated the change in reach (start-ups 22.60%, 95% CI = 16.05 to 29.15; scale-ups -4.63%, 95% CI = -7.87 to -1.38). Improvement in adoption and implementation quality were moderately associated with early prescriber engagement in Learning Collaboratives (adoption: ES = 0.61; 95% CI = 0.25 to 0.96; implementation quality: ES = 0.55; 95% CI = 0.41 to 0.69). Improvement in adoption was also associated with early prescriber engagement in Didactic Webinars (adoption: ES = 0.61; 95% CI = 0.20 to 1.05).

CONCLUSIONS: Rather than providing an all-clinics-get-all-components package of implementation strategies, these data suggest that it may be more efficient and effective to tailor the provision of implementation strategies based on the needs of clinic. Future implementation endeavors could benefit from (i) greater precision in the provision of implementation strategies based on contextual determinants, and (ii) the inclusion of strategies targeting engagement.

PMID:35794653 | DOI:10.1186/s43058-022-00306-1