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Nevin Manimala Statistics

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Nevin Manimala Statistics

MCMC with Gaussian Processes for fast parameter estimation and uncertainty quantification in a 1D fluid-dynamics model of the pulmonary circulation.

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MCMC with Gaussian Processes for fast parameter estimation and uncertainty quantification in a 1D fluid-dynamics model of the pulmonary circulation.

Int J Numer Method Biomed Eng. 2020 Nov 28;:e3421

Authors: Paun LM, Husmeier D

Abstract
The past few decades have witnessed an explosive synergy between physics and the life sciences. In particular, physical modelling in medicine and physiology is a topical research area. The present work focuses on parameter inference and uncertainty quantification in a 1D fluid-dynamics model for quantitative physiology: the pulmonary blood circulation. The practical challenge is the estimation of the patient-specific biophysical model parameters, which cannot be measured directly. In principle this can be achieved based on a comparison between measured and predicted data. However, predicting data requires solving a system of partial differential equations (PDEs), which usually have no closed-form solution, and repeated numerical integrations as part of an adaptive estimation procedure are computationally expensive. In the present article, we demonstrate how fast parameter estimation combined with sound uncertainty quantification can be achieved by a combination of statistical emulation and Markov chain Monte Carlo (MCMC) sampling. We compare a range of state-of-the-art MCMC algorithms and emulation strategies, and assess their performance in terms of their accuracy and computational efficiency. The long-term goal is to develop a method for reliable disease prognostication in real time, and our work is an important step towards an automatic clinical decision support system. This article is protected by copyright. All rights reserved.

PMID: 33249755 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

Derivation with Internal Validation of a Multivariable Predictive Model to Predict COVID-19 Test Results in Emergency Department Patients.

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Derivation with Internal Validation of a Multivariable Predictive Model to Predict COVID-19 Test Results in Emergency Department Patients.

Acad Emerg Med. 2020 Nov 28;:

Authors: McDonald SA, Medford RJ, Basit MA, Diercks DB, Courtney DM

Abstract
OBJECTIVES: The COVID-19 pandemic has placed acute care providers in demanding situations in predicting disease given the clinical variability, desire to cohort patients, and high variance in testing availability. An approach to stratify patients by likelihood of disease based on rapidly available emergency department (ED) clinical data would offer significant operational and clinical value. The purpose of this study was to develop and internally validate a predictive model to aid in the discrimination of patients undergoing investigation for COVID-19.
METHODS: All patients greater than 18 years presenting to a single academic ED who were tested for COVID-19 during this index ED evaluation were included. Outcome was defined as the result of COVID-19 PCR testing during the index visit or any positive result within the following 7 days. Variables included chest radiograph interpretation, disease specific screening questions, and laboratory data. Three models were developed with a split-sample approach to predict outcome of the PCR test utilizing logistic regression, random forest, and gradient boosted decision-tree methods. Model discrimination was evaluated comparing AUC and point statistics at a predefined threshold.
RESULTS: 1026 patients were included in the study collected between March and April 2020. Overall, there was disease prevalence of 9.6% in the population under study during this time frame. The logistic regression model was found to have an AUC of 0.89 (95% CI 0.84 – 0.94) when including four features: exposure history, temperature, WBC, and chest radiograph result. Random forest method resulted in AUC of 0.86 (95% CI 0.79 – 0.92) and gradient boosting had an AUC of 0.85 (95% CI 0.79-0.91). With a consistently held negative predictive value, the logistic regression model had a positive predictive value of 0.29 (0.2-0.39) compared to 0.2 (0.14-0.28) for random forest and 0.22 (0.15 – 0.3) for the gradient boosted method.
CONCLUSION: The derived predictive models offer good discriminating capacity for COVID-19 disease and provide interpretable and usable methods for those providers caring for these patients at the important crossroads of the community and the health system. We found utilization of the logistic regression model utilizing exposure history, temperature, WBC, and Chest XR result had the greatest discriminatory capacity with the most interpretable model. Integrating a predictive model-based approach to COVID-19 testing decisions and patient care pathways and locations could add efficiency and accuracy to decrease uncertainty.

PMID: 33249683 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

Full compliance with Respiratory syncytial virus prophylaxis was associated with fewer respiratory-related hospital admissions in preterm children: a cohort study.

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Full compliance with Respiratory syncytial virus prophylaxis was associated with fewer respiratory-related hospital admissions in preterm children: a cohort study.

Acta Paediatr. 2020 Nov 28;:

Authors: Torchin H, Charkaluk ML, Rousseau J, Marchand-Martin L, Treluyer L, Nuytten A, Truffert P, Jarreau PH, Ancel PY

Abstract
AIM: Although well documented in randomised trials, the efficacy of prophylaxis against respiratory syncytial virus (RSV) in real-word conditions is less studied. The objective was to assess the impact of partial versus full RSV prophylaxis for acute respiratory infections (ARIs) and ARI-related hospital admissions in preterm children.
METHODS: This study included children born preterm in 2011 in France who were eligible for RSV prophylaxis and received at least one palivizumab dose from October 2011 to March 2012. Full prophylaxis was defined as receiving at least one palivizumab dose for each month of RSV exposure in the community. Children with full and partial prophylaxis were matched, and odds of ARIs and ARI-related hospital admission were compared by logistic regression.
RESULTS: Full prophylaxis concerned 861/1083 (80%) children. As compared with full prophylaxis, partial prophylaxis was not associated with ARI occurrence (odds ratio OR 1.3, 95% confidence interval CI 0.9-1.9) but was significantly associated with ARI-related hospital admission during the RSV epidemic (OR 1.9, 95% CI 1.2-2.9).
CONCLUSION: During the 2011-2012 RSV epidemic, hospital admission rates were higher for preterm children with partial than full RSV prophylaxis. Improving compliance could help alleviate the burden of RSV on healthcare systems.

PMID: 33249609 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

Cost-effectiveness analysis of thoracoscopic versus open esophagectomy for esophageal cancer: a population-based study.

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Cost-effectiveness analysis of thoracoscopic versus open esophagectomy for esophageal cancer: a population-based study.

Dis Esophagus. 2020 Nov 30;:

Authors: Chao YK, Wen YW

Abstract
The question as to whether the clinical benefits of video-assisted thoracoscopic esophagectomy (VATE) do outweigh its increased costs remains unanswered. Here, we analyzed the cost-effectiveness of VATE versus open esophagectomy (OE) in a real-world setting. Using 2008-2015 Taiwanese Health Insurance claim data, we identified 3271 patients with esophageal cancer who underwent transthoracic esophagectomy. By taking into account nine confounding variables, we constructed a 1:1 propensity score-matched sample of patients who underwent VATE or OE (n = 629 each). Direct costs incurred within three years after surgery and survival were analyzed. There were no significant intergroup differences in terms of R0 resection rates, length of stay, as well as 30- and 90-day mortality and unplanned readmission rates. However, the number of dissected nodes was higher in the VATE group (median: 24 vs. 18, P < 0.001). While VATE had higher index hospitalization costs (median, 12331 USD vs. 10730 USD, P < 0.001), cost differences were reduced over time. The average accumulated cost person-month of VATE declined below that of OE at 14 months after hospital discharge. Overall survival (OS) figures were more favorable for patients treated with VATE (3-year OS: 47% vs. 41%; life expectancy: 4.04 life-years [LY] vs. 3.30 LY). The cost-effectiveness plane showed that only 0.3% of all VATE procedures were more costly and less effective than OE. The probabilities for VATE to be cost-effective at the willingness-to-pay (WTP) thresholds of 10000 and 50000 USD/LY were 63.5% and 92.4%, respectively. Using commonly accepted WTP thresholds, VATE was more cost-effective than OE for patients with esophageal cancer.

PMID: 33249485 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

Impact of preconception, pregnancy, and postpartum culinary nutrition education interventions: a systematic review.

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Impact of preconception, pregnancy, and postpartum culinary nutrition education interventions: a systematic review.

Nutr Rev. 2020 Nov 29;:

Authors: Taylor RM, Wolfson JA, Lavelle F, Dean M, Frawley J, Hutchesson MJ, Collins CE, Shrewsbury VA

Abstract
CONTEXT: Frequent consumption of home-prepared meals is associated with higher diet quality in children and adults. Therefore, increasing the culinary skills of women and couples during their childbearing years may be an effective strategy for the prevention of overweight and obesity.
OBJECTIVE: To determine the impact of culinary nutrition-education interventions for women with or without their partners during preconception, pregnancy, or postpartum (PPP) on parental cooking skills, nutrition knowledge, parent/child diet quality, or health outcomes.
DATA SOURCES: Eligibility criteria were defined using a PICOS framework. A systematic search strategy was developed to identify eligible studies and was implemented in 11 electronic databases. Reference lists of selected systematic reviews were manually searched for additional studies.
DATA EXTRACTION: Study characteristics and outcomes were extracted from eligible studies by 1 reviewer and checked by a second reviewer.
DATA ANALYSIS: A narrative synthesis of the findings of eligible studies was prepared including descriptive statistics. Reporting was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and Synthesis Without Meta-Analysis in systematic reviews reporting guideline.
RESULTS: A total of 6951 articles were identified from the search strategy and 31 studies during pregnancy or postpartum were included. By category, the number of studies with a favorable outcome per total number of studies measuring outcome were as follows: parental food/cooking skills (n = 5 of 5), nutrition knowledge (n = 6 of 11), parent/child diet quality (n = 10 of 19), infant feeding (n = 6 of 11), eating behavior (n = 2 of 5), maternal (n = 2 of 5) and child anthropometry (n = 6 of 10), mental health and development n = (2 of 3), and clinical indictors (n = 1 of 1).
CONCLUSIONS: Culinary nutrition-education interventions during pregnancy and the postpartum period show promise in improving cooking skills, diet quality, and a variety of health-related outcomes. The precise effect of these interventions during PPP is limited by the quality and heterogeneity of study designs to date.
SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration number: CRD42020154966.

PMID: 33249446 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

High-resolution population-specific recombination rates and their effect on phasing and genotype imputation.

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High-resolution population-specific recombination rates and their effect on phasing and genotype imputation.

Eur J Hum Genet. 2020 Nov 28;:

Authors: Hassan S, Surakka I, Taskinen MR, Salomaa V, Palotie A, Wessman M, Tukiainen T, Pirinen M, Palta P, Ripatti S

Abstract
Previous research has shown that using population-specific reference panels has a significant effect on downstream population genomic analyses like haplotype phasing, genotype imputation, and association, especially in the context of population isolates. Here, we developed a high-resolution recombination rate mapping at 10 and 50 kb scale using high-coverage (20-30×) whole-genome sequenced data of 55 family trios from Finland and compared it to recombination rates of non-Finnish Europeans (NFE). We tested the downstream effects of the population-specific recombination rates in statistical phasing and genotype imputation in Finns as compared to the same analyses performed by using the NFE-based recombination rates. We found that Finnish recombination rates have a moderately high correlation (Spearman’s ρ = 0.67-0.79) with NFE, although on average (across all autosomal chromosomes), Finnish rates (2.268 ± 0.4209 cM/Mb) are 12-14% lower than NFE (2.641 ± 0.5032 cM/Mb). Finnish recombination map was found to have no significant effect in haplotype phasing accuracy (switch error rates ~2%) and average imputation concordance rates (97-98% for common, 92-96% for low frequency and 78-90% for rare variants). Our results suggest that haplotype phasing and genotype imputation mostly depend on population-specific contexts like appropriate reference panels and their sample size, but not on population-specific recombination maps. Even though recombination rate estimates had some differences between the Finnish and NFE populations, haplotyping and imputation had not been noticeably affected by the recombination map used. Therefore, the currently available HapMap recombination maps seem robust for population-specific phasing and imputation pipelines, even in the context of relatively isolated populations like Finland.

PMID: 33249422 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

A new approach in analyzing the accident severity of pedestrian crashes using structural equation modeling.

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A new approach in analyzing the accident severity of pedestrian crashes using structural equation modeling.

J Inj Violence Res. 2020 Nov 22;13(1):

Authors: Tavakoli Kashani A, Jafari M, Azizi Bondarabadi M

Abstract
BACKGROUND: According to official statistics in Iran, there were 17000 fatalities in road traffic crashes in 2018 that 25% of all crash fatalities belong to pedestrians. In most of the researches related to pedestrians’ safety, one aspect of the traffic crash (e.g. the injury or crash severity) is almost considered for the investigation. In order to perform a complete study of the crash, accident size can be utilized which involves different aspects of the crash. Accident size is described in terms of the number of fatalities and injured individuals and the number of damaged and involved vehicles in a crash.
METHODS: According to the fact that accident size has multiple indicators and it is not measured directly, traditional methodologies cannot be applied. So, in the present study the effective factors on the accident size of pedestrian crashes are investigated through structural equation modeling. For the purpose of this study, 3718 pedestrian-involved crash data occurred in Isfahan province is used for the modeling. The independent variables are weather conditions, road surface conditions, time, horizontal and vertical alignments, road type and location, driver’s gender and age, vehicle type, pedestrian’s age, gender and clothing color.
RESULTS: The results indicated that highways, the pedestrians’ invisibility, female and old-aged pedestrians, heavy vehicles, old-aged and female drivers are related to the increase of the accident size in pedestrian crashes. These results denote that the mentioned variables are associated with the higher number of injuries, fatalities, the higher number of involved and damaged vehicles in a crash.
CONCLUSIONS: Present study shows the importance of considering safety improvement measures in highways, educating the people in the society about the traffic safety, the separation of pedestrian and motor vehicle traffic flow and considering the old people in policies and programs for mitigating the accident size.

PMID: 33249418 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

Grain analysis of atomic force microscopy images via persistent homology.

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Grain analysis of atomic force microscopy images via persistent homology.

Ultramicroscopy. 2020 Nov 21;220:113176

Authors: Duman AN

Abstract
Atomic force microscopy (AFM) is an established technique in nanoscale grain analysis due to its accuracy in producing 3-dimensional images. Even though height threshold and watershed algorithms are commonly used to determine the grain size and number of grains, they mostly require image processing that result in the change of topographical features of the surface that generates misleading conclusions. In this study, we use persistent homology, a method of representing topological features, to obtain more accurate information about the granular surfaces from unprocessed AFM images than the conventional methods. The method is also useful as a robust alternative to common parameters describing the topography of the AFM images. Most of these parameters such as arithmetic roughness and root-mean-squared roughness are represented by a single number which results in uncertainty in characterization of different surfaces. Persistent homology provides more precise summary about surface properties than a single parameter.

PMID: 33249346 [PubMed – as supplied by publisher]

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Nevin Manimala Statistics

The prognostic value of the tumor-stroma ratio in squamous cell lung cancer, a cohort study.

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The prognostic value of the tumor-stroma ratio in squamous cell lung cancer, a cohort study.

Cancer Treat Res Commun. 2020 Nov 21;25:100247

Authors: Smit MA, Philipsen MW, Postmus PE, Putter H, Tollenaar RA, Cohen D, Mesker WE

Abstract
OBJECTIVES: The tumor-stroma ratio (TSR) is based on the relative amount of stroma in the primary tumor and has proven to be an independent prognostic factor in various solid tumors. The prognosis of patients and adjuvant treatment decision making in lung squamous cell carcinomas (SqCC) is based on the TNM classification. Currently, no other prognostic biomarkers are available. In this study we evaluated the prognostic value of the TSR in lung SqCC.
MATERIAL AND METHODS: Patients undergoing lung surgery because of lung SqCC between 2000 and 2018 at the Leiden University Medical Center were included. The TSR was scored on hematoxylin & eosin stained tissue sections. Based on the amount of tumor-stroma, two groups were defined: ≤50% was classified as a stroma-low tumor and >50% as stroma-high. The prognostic value of the TSR was determined with survival analysis.
RESULTS: A total of 174 stage I-III patients were included. Of them, 79 (45%) were stroma-low and 95 (55%) stroma-high. Separately analyzed for tumor stages, the TSR showed to be an independent prognostic biomarker in stage II (n = 68) for 5-year overall survival (HR=3.0; 95% CI, 1.1-8.6; p = 0.035) and 5-year disease free survival (DFS) (HR=3.6; 95% CI, 1.3-9.9; p = 0.014). Patients with a stroma-high tumor had a worse 5-year DFS in the whole cohort (HR 1.6; 95% CI, 1.0-2.4; p = 0.048), but no independent prognostic value was found.
CONCLUSION: In stage II lung SqCC patients, stroma-low tumors have a better prognosis compared to stroma-high tumors. Moreover, adjuvant chemotherapy could be spared for these stroma-low patients.

PMID: 33249210 [PubMed – as supplied by publisher]