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Nevin Manimala Statistics

Variation in global treatment for subaxial cervical spine isolated unilateral facet fractures

Eur Spine J. 2021 Apr 2. doi: 10.1007/s00586-021-06818-z. Online ahead of print.

ABSTRACT

PURPOSE: To determine the variation in the global treatment practices for subaxial unilateral cervical spine facet fractures based on surgeon experience, practice setting, and surgical subspecialty.

METHODS: A survey was sent to 272 members of the AO Spine Subaxial Injury Classification System Validation Group worldwide. Questions surveyed surgeon preferences with regard to diagnostic work-up and treatment of fracture types F1-F3, according to the AO Spine Subaxial Cervical Spine Injury Classification System, with various associated neurologic injuries.

RESULTS: A total of 161 responses were received. Academic surgeons use the facet portion of the AO Spine classification system less frequently (61.6%) compared to hospital-employed and private practice surgeons (81.1% and 81.8%, respectively) (p = 0.029). The overall consensus was in favor of operative treatment for any facet fracture with radicular symptoms (N2) and for any fractures categorized as F2N2 and above. For F3N0 fractures, significantly less surgeons from Africa/Asia/Middle East (49%) and Europe (59.2%) chose operative treatment than from North/Latin/South America (74.1%) (p = 0.025). For F3N1 fractures, significantly less surgeons from Africa/Asia/Middle East (52%) and Europe (63.3%) recommended operative treatment than from North/Latin/South America (84.5%) (p = 0.001). More than 95% of surgeons included CT in their work-up of facet fractures, regardless of the type. No statistically significant differences were seen in the need for MRI to decide treatment.

CONCLUSION: Considerable agreement exists between surgeon preferences with regard to unilateral facet fracture management with few exceptions. F2N2 fracture subtypes and subtypes with radiculopathy (N2) appear to be the threshold for operative treatment.

PMID:33797624 | DOI:10.1007/s00586-021-06818-z

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Nevin Manimala Statistics

Beyond magnification and illumination: preliminary clinical experience with the 4K 3D ORBEYE exoscope and a literature review

Acta Neurochir (Wien). 2021 Apr 2. doi: 10.1007/s00701-021-04838-8. Online ahead of print.

ABSTRACT

BACKGROUND: The operating microscope (OM) is an invaluable tool in neurosurgery but is not without its flaws. The ORBEYE (Olympus, Tokyo, Japan) is a 4K 3D exoscope aspiring to offer similar visual fidelity but with superior ergonomics. 2D visualisation was a major limitation of previous models which newer 3D exoscopes attempt to overcome. Here, we present our initial experience using a 4K 3D exoscope for neurosurgical procedures.

OBJECTIVE: To evaluate the feasibility of the ORBEYE exoscope in performing neurosurgery and review of the literature.

METHODS: All patients undergoing neurosurgery performed by a single surgeon, using the ORBEYE, were assessed. Descriptive statistics and data relating to complications and operative time were recorded and analysed. An anecdotal literature review was performed for the experience of other authors using 4K 3D exoscopes in neurosurgery and compared to our subjective experience with the ORBEYE.

RESULTS: 18 patients underwent surgery using the ORBEYE. There were no 30-day post-operative complications observed. Our experience and that of other authors suggests that the ORBEYE offers comparable visualisation to the traditional OM, with superior ergonomics and an enhanced experience for assistants and observers.

CONCLUSION: Neurosurgery can be performed safely and effectively with the ORBEYE, with improved ergonomics and educational benefit. There appears to be a short learning curve provided one has experience with endoscopic surgery and the use of a foot pedal.

PMID:33797629 | DOI:10.1007/s00701-021-04838-8

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Nevin Manimala Statistics

A thermoluminescent method for the evaluation of the 131I effective half-life in the thyroid when treating Graves’ disease

Radiat Environ Biophys. 2021 Apr 2. doi: 10.1007/s00411-021-00907-9. Online ahead of print.

ABSTRACT

When planning treatment for Graves’ disease with 131I, the effective half-life (Teff) should be estimated individually as it depends on biological characteristics such as iodine uptake and excretion, which differ from an individual to another (Berg et al. 1996). All the methods to quantify Teff described in the literature are quite complex and are difficult to be used in clinical routine. With the aim of optimizing this process, a simplified method is proposed here to evaluate Teff of 131I during treatment of Graves’ disease. The present study suggests improving the method of determining Teff based on thermoluminescence dosimetry. This involves implementing a new method and includes reduction of TLD (Thermoluminescent Dosimeter) measurements. The proposed method was validated on patients with Graves’ disease. The radiation dose delivered to the patients was determined using the MIRD (Medical Internal Radiation Dosimetry) formalism. The relative difference between Teff obtained based on seven measurement intervals at [0-24 h, 24-48 h, 48-72 h, 72-96 h, 96-120 h, 120-144 h, 144-168 h] and based on three measurement intervals at [0-24 h, 72-96 h, 144-168 h] and [0-24 h, 120-144 h, 144-168 h] was 1.9% and 3.81%, respectively. Comparison of doses obtained based on a general Teff and on a personalized Teff gave a statistically significant difference with a correlation coefficient R2of 0.44. The Teff obtained from just three measurements was found to be sufficiently accurate and easily applicable. The results obtained demonstrate the need to determine and use personalized Teff values instead of using a fixed value of 7 days.

PMID:33797646 | DOI:10.1007/s00411-021-00907-9

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Nevin Manimala Statistics

Association of pre- and early-pregnancy factors with the risk for gestational diabetes mellitus in a large Chinese population

Sci Rep. 2021 Apr 1;11(1):7335. doi: 10.1038/s41598-021-86818-7.

ABSTRACT

Gestational diabetes mellitus (GDM) has aroused wide public concern, as it affects approximately 1.8-25.1% of pregnancies worldwide. This study aimed to examine the association of pre-pregnancy demographic parameters and early-pregnancy laboratory biomarkers with later GDM risk, and further to establish a nomogram prediction model. This study is based on the big obstetric data from 10 “AAA” hospitals in Xiamen. GDM was diagnosed according to the International Association of Diabetes and Pregnancy Study Group (IADPSG) criteria. Data are analyzed using Stata (v14.1) and R (v3.5.2). Total 187,432 gestational women free of pre-pregnancy diabetes mellitus were eligible for analysis, including 49,611 women with GDM and 137,821 women without GDM. Irrespective of confounding adjustment, eight independent factors were consistently and significantly associated with GDM, including pre-pregnancy body mass index (BMI), pre-pregnancy intake of folic acid, white cell count, platelet count, alanine transaminase, albumin, direct bilirubin, and creatinine (p < 0.001). Notably, per 3 kg/m2 increment in pre-pregnancy BMI was associated with 22% increased risk [adjusted odds ratio (OR) 1.22, 95% confidence interval (CI) 1.21-1.24, p < 0.001], and pre-pregnancy intake of folic acid can reduce GDM risk by 27% (adjusted OR 0.73, 95% CI 0.69-0.79, p < 0.001). The eight significant factors exhibited decent prediction performance as reflected by calibration and discrimination statistics and decision curve analysis. To enhance clinical application, a nomogram model was established by incorporating age and above eight factors, and importantly this model had a prediction accuracy of 87%. Taken together, eight independent pre-/early-pregnancy predictors were identified in significant association with later GDM risk, and importantly a nomogram modeling these predictors has over 85% accuracy in early detecting pregnant women who will progress to GDM later.

PMID:33795771 | DOI:10.1038/s41598-021-86818-7

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Nevin Manimala Statistics

Incomplete footprint coverage under tension in repair of isolated supraspinatus full-thickness tear

Sci Rep. 2021 Apr 1;11(1):7425. doi: 10.1038/s41598-021-86800-3.

ABSTRACT

Although it is well known that repairing large or massive tears under tension may have an adverse effect on healing of the repaired tendons, only few studies have addressed this issue in medium-sized isolated supraspinatus full-thickness tear. The purpose of this study was to compare the clinical outcomes and structural integrity of arthroscopic rotator cuff repair with tension versus without it. This study retrospectively investigated 90 patients who underwent arthroscopic repair in a single-row for medium-sized isolated supraspinatus full-thickness tear. The patients were assigned to either repaired under tension (Group A, n = 38) or repaired without tension (Group B, n = 52) groups. Functional outcomes were assessed using the patient reported subjective values and the active range of motion (ROM). Postoperative radiographic evaluation was performed 6 months after the surgery to assess the structural integrity of the repaired tendons. Changes in the subjective shoulder scores from initial to 2 years after surgery showed no statistical significance between the two groups. The ROMs measured at initial and 2 years after surgery also showed no statistical difference between the two groups. Postoperative radiological evaluations found a significantly higher re-tear rate in Group A (28.9%, 11/38) than in Group B (9.6%, 5/52). The torn cuff tendons that were repaired under tension as retraction with limited mobility had significantly higher re-tear rate despite having immobilized for 6 weeks after surgery, but their clinical outcomes showed no significant difference from the outcomes of repaired tendons without tension.

PMID:33795780 | DOI:10.1038/s41598-021-86800-3

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Nevin Manimala Statistics

Neurodevelopment correlates with gut microbiota in a cross-sectional analysis of children at 3 years of age in rural China

Sci Rep. 2021 Apr 1;11(1):7384. doi: 10.1038/s41598-021-86761-7.

ABSTRACT

We investigated cross-sectional associations between children’s neurodevelopment and their gut microbiota composition. Study children (36 months of age) lived in rural China (n = 46). Neurodevelopment was assessed using the Bayley Scales of Infant Development, 2nd Edition, yielding the Mental Developmental Index (MDI) and Psychomotor Developmental Index (PDI). Children’s gut microbiota was assessed using 16S rRNA gene profiling. Microbial diversity was characterized using alpha diversity patterns. Additionally, 3 coabundance factors were determined for the 25 most abundant taxa. Multivariable linear regression models were constructed to examine the relationships between Bayley scores (MDI and PDI) and children’s gut microbiota. In adjusted models, MDI and PDI scores were not associated with alpha diversity indices. However, in adjusted models, MDI and PDI scores were positively associated with the first coabundance factor, which captured positive loadings for the genera Faecalibacterium, Sutterella, and Clostridium cluster XIVa. For an interquartile range increase in the first coabundance factor, MDI scores increased by 3.9 points [95% confidence interval (CI): 0, 7.7], while PDI scores increased by 8.6 points (95% CI 3.1, 14). Our results highlight the potential for gut microbial compositional characteristics to be important correlates of children’s Bayley Scales performance at 36 months of age.

PMID:33795717 | DOI:10.1038/s41598-021-86761-7

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Nevin Manimala Statistics

Modeling the first wave of Covid-19 pandemic in the Republic of Cyprus

Sci Rep. 2021 Apr 1;11(1):7342. doi: 10.1038/s41598-021-86606-3.

ABSTRACT

We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that have been taken by the government. Change point detection has been used in order to estimate the number and locations of changes in the behaviour of the collected data. Count time series methods have been employed to provide short term projections and a number of various compartmental models have been fitted to the data providing with long term projections on the pandemic’s evolution and allowing for the estimation of the effective reproduction number.

PMID:33795723 | DOI:10.1038/s41598-021-86606-3

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Nevin Manimala Statistics

Statistical shape modeling of the talocrural joint using a hybrid multi-articulation joint approach

Sci Rep. 2021 Apr 1;11(1):7314. doi: 10.1038/s41598-021-86567-7.

ABSTRACT

Historically, conventional radiographs have been the primary tool to morphometrically evaluate the talocrural joint, which is comprised of the distal tibia, distal fibula, and proximal talus. More recently, high-resolution volumetric imaging, including computed tomography (CT), has enabled the generation of three-dimensional (3D) reconstructions of the talocrural joint. Weightbearing cone-beam CT (WBCT) technology provides additional benefit to assess 3D spatial relationships and joint congruency while the patient is load bearing. In this study we applied statistical shape modeling, a computational morphometrics technique, to objectively quantify anatomical variation, joint level coverage, joint space distance, and congruency at the talocrural joint. Shape models were developed from segmented WBCT images and included the distal tibia, distal fibula, and full talus. Key anatomical variation across subjects included the fibular notch on the tibia, talar trochlea sagittal plane rate of curvature, tibial plafond curvature with medial malleolus prominence, and changes in the fibular shaft diameter. The shape analysis also revealed a highly congruent talocrural joint with minimal inter-individual morphometric differences at the articular regions. These data are helpful to improve understanding of ankle joint pathologies and to guide refinement of operative treatments.

PMID:33795729 | DOI:10.1038/s41598-021-86567-7

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Nevin Manimala Statistics

Phenotypically independent profiles relevant to mental health are genetically correlated

Transl Psychiatry. 2021 Apr 1;11(1):202. doi: 10.1038/s41398-021-01313-x.

ABSTRACT

Genome-wide association studies (GWAS) and family-based studies have revealed partly overlapping genetic architectures between various psychiatric disorders. Given clinical overlap between disorders, our knowledge of the genetic architectures underlying specific symptom profiles and risk factors is limited. Here, we aimed to derive distinct profiles relevant to mental health in healthy individuals and to study how these genetically relate to each other and to common psychiatric disorders. Using independent component analysis, we decomposed self-report mental health questionnaires from 136,678 healthy individuals of the UK Biobank, excluding data from individuals with a diagnosed neurological or psychiatric disorder, into 13 distinct profiles relevant to mental health, capturing different symptoms as well as social and risk factors underlying reduced mental health. Utilizing genotypes from 117,611 of those individuals with White British ancestry, we performed GWAS for each mental health profile and assessed genetic correlations between these profiles, and between the profiles and common psychiatric disorders and cognitive traits. We found that mental health profiles were genetically correlated with a wide range of psychiatric disorders and cognitive traits, with strongest effects typically observed between a given mental health profile and a disorder for which the profile is common (e.g. depression symptoms and major depressive disorder, or psychosis and schizophrenia). Strikingly, although the profiles were phenotypically uncorrelated, many of them were genetically correlated with each other. This study provides evidence that statistically independent mental health profiles partly share genetic underpinnings and show genetic overlap with psychiatric disorders, suggesting that shared genetics across psychiatric disorders cannot be exclusively attributed to the known overlapping symptomatology between the disorders.

PMID:33795632 | DOI:10.1038/s41398-021-01313-x

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Nevin Manimala Statistics

Detecting local genetic correlations with scan statistics

Nat Commun. 2021 Apr 1;12(1):2033. doi: 10.1038/s41467-021-22334-6.

ABSTRACT

Genetic correlation analysis has quickly gained popularity in the past few years and provided insights into the genetic etiology of numerous complex diseases. However, existing approaches oversimplify the shared genetic architecture between different phenotypes and cannot effectively identify precise genetic regions contributing to the genetic correlation. In this work, we introduce LOGODetect, a powerful and efficient statistical method to identify small genome segments harboring local genetic correlation signals. LOGODetect automatically identifies genetic regions showing consistent associations with multiple phenotypes through a scan statistic approach. It uses summary association statistics from genome-wide association studies (GWAS) as input and is robust to sample overlap between studies. Applied to seven phenotypically distinct but genetically correlated neuropsychiatric traits, we identify 227 non-overlapping genome regions associated with multiple traits, including multiple hub regions showing concordant effects on five or more traits. Our method addresses critical limitations in existing analytic strategies and may have wide applications in post-GWAS analysis.

PMID:33795679 | DOI:10.1038/s41467-021-22334-6