Nevin Manimala

Proteomics Clin Appl. 2021 Jul 30:e2000058. doi: 10.1002/prca.202000058. Online ahead of print.

ABSTRACT

PURPOSE: There are great demands for identifying biomarkers of major depressive disorder (MDD), a common mental illness with a prevalence of approximately 6%. Finding potential biomarkers to aid MDD diagnosis is in high demand.

EXPERIMENTAL DESIGN: In this study, a combination of pretreatment methods named salt-out assisted liquid-liquid extraction(SALLE) and nontargeted peptidomics based on nano-LC-Orbitrap/MS was primarily employed to discover the candidate peptide markers from the plasma of 238 subjects.

RESULTS: Many peptides were enriched and identified from the plasma, 42 of which showed significant differences between MDD patients and controls by univariate statistical analysis. A binary logistic regression(BLR) model combined four peptide markers (P1, P9, P17, P29) was established, yielding an overall prediction accuracy of 91.7% and 82.2% in the discovery and validation sets, respectively.

CONCLUSIONS AND CLINICAL RELEVANCE: In conclusion, the excellent performance of the BLR model in both discovery and validation sets demonstrates the robustness of the four peptide markers panel. It is very valuable for quantification of the absolute content of four peptides and further verification. This article is protected by copyright. All rights reserved.

PMID:34329527 | DOI:10.1002/prca.202000058

J Med Virol. 2021 Jul 30. doi: 10.1002/jmv.27248. Online ahead of print.

ABSTRACT

Understanding the regional lineages and sublineages of HPV 56 would be of great importance for further evolutionary, epidemiological, and biological investigations. To identify the distribution of lineages and sublineages of HPV 56 in Iran, the sequence variations of E6 gene were analyzed in normal, premalignant, and malignant samples obtained from the cervix. In total, 58 HPV 56-positive samples were investigated by nested-PCR and followed by bidirectional direct nucleotide sequencing analysis. Both lineages A and B were identified in studied samples. Lineage B was dominant as it was detected in 88.4% of all samples and the remaining of samples were belonged to lineages A (11.6%). Sublineages A1 and A2 were detected in 3.3 % and 8.3 % of all samples, respectively. Regard to the pathological stages of cervical specimens, no statistically significant differences was found in three studied groups (P > 0.05). In conclusion, our findings showed that lineage B of HPV 56 was prevalent in Iran. However, further studies with larger sample size are warranted to estimate the pathogenicity risk of HPV 56 lineages/sublineages to progress of cervical cancer among Iranian women. This article is protected by copyright. All rights reserved.

PMID:34329490 | DOI:10.1002/jmv.27248

J Med Virol. 2021 Jul 30. doi: 10.1002/jmv.27247. Online ahead of print.

ABSTRACT

In this study we show a 7-individual cluster belonging to the SARS-CoV-2 B.1.621 lineage, imported in Italy by traveler from abroad This article is protected by copyright. All rights reserved.

PMID:34329486 | DOI:10.1002/jmv.27247

J Athl Train. 2021 Jul 30. doi: 10.4085/1062-6050-0359.19. Online ahead of print.

ABSTRACT

CONTEXT: Where a person lives can have a significant impact on health. Limited access to health care, food insecurity, lack of affordable housing, and violence increases a person’s likelihood for poor health. Athletic trainers can have an impact on identifying and improving the determinants of health that affect student-athletes.

OBJECTIVE: To understand 1) What are the current perceptions athletic trainers have about the health behaviors (specifically mental health and substance use) of high school student-athletes? 2) What are the barriers that athletic trainers experience when providing health services to high school student-athletes? 3) How does the developed environment effect the health behaviors and barriers that athletic trainers observe?

DESIGN: Survey Setting: Online Participants: Certified National Athletic Training Association Members employed in the secondary school setting Main Outcome Measure(s): Demographics of athletic trainers, athletic trainers’ perceptions on the health of student-athletes across developed environments, prevalence of mental health issues, tobacco and substance use, barriers to health care services, and housing and food insecurities among student-athletes. Descriptive statistics for the outcome measures are reported.

RESULTS: 7,600 electronic surveys were distributed to athletic trainers, with 910 respondents. Respondents were 61% female; average age was 36 years old; and an average of 12.5 years of experience. 82% of athletic trainers identified their school setting as public, 43.7% of respondents identified their school as suburban, 30.1% rural, and 26.2% urban. Athletic trainers perceived a high average prevalence of mental health issues (32%), e-cigarette use (31.7%), and marijuana use (26.9%) in student athletes. There were significant perceived barriers to health including access to transportation, poverty, housing and food insecurities.

CONCLUSIONS: This study highlights health disparities and barriers athletic trainers observe when addressing health care needs of student-athletes. Understanding determinants of health to identify causes of health disparities may better prepare athletic trainers to manage the health needs of underserved student-athletes.

PMID:34329451 | DOI:10.4085/1062-6050-0359.19

Int J Qual Health Care. 2021 Jul 30:mzab109. doi: 10.1093/intqhc/mzab109. Online ahead of print.

ABSTRACT

BACKGROUND: The Turkish healthcare system has seen broad population-based improvements in expanded health insurance coverage and access to healthcare services. Hospital performance in this national system is understudied. We aimed to identify trends in hospital performance over time following implementation of the Health Transformation Program and describe how regional outcomes correlate with regional vital statistics.

METHODS: We conducted a retrospective cohort study of 674 public hospitals in Turkey using baseline data from 2013 and follow-up data from 2014-15 collected by the Turkish Statistical Institution (TSI) and the Public Hospital Agency (PHA). We report demographic and socioeconomic data across 12 geographic regions and analyze 29 hospital-level performance measures across four domains: (1) health services; (2) administrative services; (3) financial services; and (4) quality measures. We examine temporal variation, and study correlation between performance measures and regional vital statistics. We fit mixed-effects linear regression models to estimate linear trend over time accounting for within-hospital residual correlation. We prepared our manuscript in accordance with guidelines set by the STROBE statement for cohort studies.

RESULTS: During the three years of study period, 21 of 29 measures improved, and 8 measures worsened. All but 3 measures demonstrated significant differences across regions of the country. Several measures, including inpatient efficiency, patient satisfaction, and audit score, are associated with regional infant mortality and life expectancy.

CONCLUSIONS: Evidence for temporal improvement in hospital-level performance may suggest some positive changes within the Turkish national healthcare system. Correlation of some measures with regional level health outcomes suggests a quality measurement strategy to monitor performance changes in the future. Although hospital-level functions have improved performance, the results of our study may help achieve further improvement for the health of the country’s citizens.

PMID:34329442 | DOI:10.1093/intqhc/mzab109

J Athl Train. 2021 Jul 30. doi: 10.4085/1062-6050-0158.21. Online ahead of print.

ABSTRACT

CONTEXT: Previously, the most common treatment for a concussion was prolonged physical and cognitive rest. Recent research suggests that earlier physical activity (PA) may be better at promoting recovery. Research has not evaluated the relationship between free-living PA (e.g., walking) and symptom reporting or recovery duration.

OBJECTIVE: To assess the relationship between free-living physical activity (PA) participation and two recovery outcomes in college-aged adults with a concussion.

DESIGN: Prospective Cohort Setting: Division 1 & 3 Universities Participants: Thirty-two college-aged adults (68.8% female, age: 19.8±1.4) with a concussion.

MAIN OUTCOME MEASURES: Participants completed a post-concussion symptom evaluation at visits 1 (<72 hours from concussion) and 2 (8 days later). Between visits, participants’ PA was monitored using an Actigraph GT9X Link PA monitor and expressed as total PA (counts per minute) and percent time of PA spent in moderate-to-vigorous intensity (%MVPA). Recovery time was the number of days from injury occurrence to medical clearance. Separate hierarchical multiple regressions evaluated the relationship between total PA and each recovery variable (visit 2 symptom severity, recovery time). Additionally, separate exploratory hierarchical multiple regressions evaluated the relationship between %MVPA and each recovery variable. Statistical significance was set a priori at p ≤ .05.

RESULTS: Participants averaged 2446±441 counts per minute and spent 12.1±4.2% of their PA performing MVPA. Participants yielded median symptom severities of 28[24] and 2[8] for visit 1 and 2, respectively. Average recovery time was 14.7±7.5 days. Total PA did not significantly contribute to the model for visit 2 symptom severity (p=.122) or recovery time (p=.301). Similarly, %MVPA had little contribution to the model for visit 2 symptom severity (p=.358) or recovery time (p=.276).

CONCLUSION: Results suggest that free-living PA may not be enough to reduce symptoms or shorten recovery. Thus, clinicians may need to provide patients with more structured PA protocols mimicking previous research.

PMID:34329439 | DOI:10.4085/1062-6050-0158.21

Eur J Cardiothorac Surg. 2021 Jul 30:ezab349. doi: 10.1093/ejcts/ezab349. Online ahead of print.

ABSTRACT

OBJECTIVES: Our goal was to investigate the correlation of clinical and computed tomography (CT) features of thymic epithelial tumours (TET) with the World Health Organization classification and the Masaoka-Koga staging system.

METHODS: Clinical and CT imaging data from 159 patients surgically and pathologically diagnosed with TET (82 men, 77 women; mean [± standard deviation] age, 52.08 ± 11.76 years) were retrospectively collected and reviewed. CT features were evaluated by radiologists. Tumour size, morphology, margin, density, calcification, cystic necrosis, density of the fat layer around the tumour, invasion of surrounding tissues, mediastinal lymph node enlargement, pleural/pericardial effusion, metastasis, plain CT scans and enhanced CT values were analysed.

RESULTS: Of the 159 patients with TET, 76 had low-risk thymoma, 55 had high-risk thymoma and 28 had thymic carcinomas. Age, maximum tumour diameter, myasthenia gravis, morphology, edges, density, fat around the lesion, mediastinal vascular, pericardial and lung tissue invasion, pleural/pericardial effusion, metastasis and arterial phase CT values were statistically different among the 3 groups (P < 0.05). Multivariate regression analysis revealed that edges, fat around the lesion, mediastinal vascular invasion and pericardial effusion were most relevant to TET classification. The 159 patients with TET were categorized into the non-invasion group (stage I; n = 58); the invasion of surrounding fat (stage II; n = 46); and the invasion of surrounding structures and metastasis group (stages III and IV; n = 55). Tumour diameter, morphology, margins, density, cystic degeneration and necrosis, invasion of surrounding fat and structure, pleural and pericardial effusion and lymph node enlargement were statistically different among the 3 groups (P < 0.05). Multivariate regression analysis revealed that edges, fat around the lesion, mediastinal vascular invasion and pleura invasion were the most relevant CT signs in relation to TET staging.

CONCLUSIONS: Analysis of clinical and CT features before surgery may facilitate the preliminary classification and stage diagnosis of TET.

PMID:34329409 | DOI:10.1093/ejcts/ezab349

Eur J Public Health. 2021 Jul 30:ckab128. doi: 10.1093/eurpub/ckab128. Online ahead of print.

ABSTRACT

BACKGROUND: The aim of this analysis was to examine the prospective association between household availability of lard, butter, margarine and vegetable oil with all-cause mortality and cardiovascular disease (CVD) incidence in a general population sample in Russia.

METHODS: Data from the Russian Longitudinal Monitoring Survey were used. 6618 adult individuals with no previous CVD who were recruited for the study in 1994 and followed-up in subsequent years were included in the analysis. Household availability of lard, butter, margarine and vegetable oil were assessed at baseline with questions on whether these food items were purchased by the participants’ family. Self-reported information on heart attack or stroke (CVD) and death reported by another household member were used as outcome.

RESULTS: Over the median follow-up of 11 years, 1787 participants died or reported incident CVD. In the multivariable adjusted survival models, household availability of lard was significantly associated with the combined outcome of CVD incidence and/or death (OR in the high vs. no availability categories: 1.31; 95% CI: 1.05-1.62). The associations with butter (1.06; 0.93-1.20), margarine (1.18; 0.94-1.47) and vegetable oil (0.92; 0.80-1.06) were not statistically significant. When self-reported CVD and mortality were examined separately, the association regarding lard was particularly strong for CVD (1.52; 1.11-2.09).

CONCLUSION: Our results suggest that lard, a dietary fat of animal origin traditionally used in Eastern European cooking, is of a particular concern regarding CVD risk. Replacing it with plant-based oils in cooking practices is strongly recommended.

PMID:34329405 | DOI:10.1093/eurpub/ckab128

PLoS One. 2021 Jul 30;16(7):e0255271. doi: 10.1371/journal.pone.0255271. eCollection 2021.

ABSTRACT

BACKGROUND: The identification of high-risk heart failure (HF) patients makes it possible to intensify their treatment. Our aim was to determine the prognostic value of a newly developed, high-sensitivity troponin I assay (Atellica®, Siemens Healthcare Diagnostics) for patients with HF with reduced ejection fraction (HFrEF; LVEF < 40%) and HF with mid-range EF (HFmrEF) (LVEF 40%-49%).

METHODS AND RESULTS: A total of 520 patients with HFrEF and HFmrEF were enrolled in this study. Two-year all-cause mortality, heart transplantation, and/or left ventricular assist device implantation were defined as the primary endpoints (EP). A logistic regression analysis was used for the identification of predictors and development of multivariable models. The EP occurred in 14% of the patients, and these patients had higher NT-proBNP (1,950 vs. 518 ng/l; p < 0.001) and hs-cTnI (34 vs. 17 ng/l, p < 0.001) levels. C-statistics demonstrated that the optimal cut-off value for the hs-cTnI level was 17 ng/l (AUC 0.658, p < 0.001). Described by the AUC, the discriminatory power of the multivariable model (NYHA > II, NT-proBNP, hs-cTnI and urea) was 0.823 (p < 0.001). Including heart failure hospitalization as the component of the combined secondary endpoint leads to a diminished predictive power of increased hs-cTnI.

CONCLUSION: hs-cTnI levels ≥ 17 ng/l represent an independent increased risk of an adverse prognosis for patients with HFrEF and HFmrEF. Determining a patient’s hs-cTnI level adds prognostic value to NT-proBNP and clinical parameters.

PMID:34329368 | DOI:10.1371/journal.pone.0255271

PLoS One. 2021 Jul 30;16(7):e0255301. doi: 10.1371/journal.pone.0255301. eCollection 2021.

ABSTRACT

In the context of the current global pandemic and the limitations of the RT-PCR test, we propose a novel deep learning architecture, DFCN (Denoising Fully Connected Network). Since medical facilities around the world differ enormously in what laboratory tests or chest imaging may be available, DFCN is designed to be robust to missing input data. An ablation study extensively evaluates the performance benefits of the DFCN as well as its robustness to missing inputs. Data from 1088 patients with confirmed RT-PCR results are obtained from two independent medical facilities. The data includes results from 27 laboratory tests and a chest x-ray scored by a deep learning model. Training and test datasets are taken from different medical facilities. Data is made publicly available. The performance of DFCN in predicting the RT-PCR result is compared with 3 related architectures as well as a Random Forest baseline. All models are trained with varying levels of masked input data to encourage robustness to missing inputs. Missing data is simulated at test time by masking inputs randomly. DFCN outperforms all other models with statistical significance using random subsets of input data with 2-27 available inputs. When all 28 inputs are available DFCN obtains an AUC of 0.924, higher than any other model. Furthermore, with clinically meaningful subsets of parameters consisting of just 6 and 7 inputs respectively, DFCN achieves higher AUCs than any other model, with values of 0.909 and 0.919.

PMID:34329354 | DOI:10.1371/journal.pone.0255301