A comprehensive 3D CT based classification of intertrochanteric fracture

IntroductionDespite advancements in surgical techniques complications like implant failure is very common after the fixation of intertrochanteric fractures. Classifying these complex fractures based on plain radiographs underestimates the complexity of these fractures which in turn leads to complications. We propose a comprehensive classification of the intertrochanteric fractures based on 3D Non Contrast Computed Tomography (3D NCCT) scan.Material and methodsA total of 102 patients (51 males and 51 females) with intertrochanteric fractures were included in this study conducted over a time period of 22 months in a Tertiary care center in North India. NCCT proximal femur of the intertrochanteric fracture patients was done to formulate a new CT classification system and classify all fractures. Intra and inter-observer reliability was tested using kappa variance.ResultsNew classification system was proposed which included 3 main and a total of 6 groups. All the fractures were classifiable into the new system. Kappa variance of the study showed a good intra and interobserver reliability (0.95 and 0.90) proving clinical agreement of the classification.ConclusionThis new 3D-CT based classification has the advantages of being easy, comprehensible with high intra and inter-observer reliability. This 3DCT based classification can prove to be useful to detect occult intertrochanteric fractures undetectable in plain radiographs as well as choosing the optimum treatment plan.     

Contemporary Epidemiology of and Risk Factors Associated with Removal of a Pathologically Normal Appendix in Children with Suspected Appendicitis

BackgroundThe goal of this study was to characterize contemporary performance benchmarks and risk factors associated with negative appendectomy (NA) in children with suspected appendicitis.MethodsA multicenter retrospective cohort analysis of children undergoing appendectomy for suspected appendicitis was performed using data from the 2016–2021 NSQIP-Pediatric Appendectomy Targeted Public Use Files. Multivariable regression was used to evaluate the influence of year, age, sex, and WBC count on NA rate, and to generate rate estimates for NA based on different combinations of demographic characteristics and WBC profiles.Results100,322 patients were included from 140 hospitals. The overall NA rate was 2.4%, and rates decreased significantly during the study period (2016: 3.1% vs. 2021: 2.3%, p < 0.001). In adjusted analyses, the highest risk for NA was associated with a normal WBC (<9000/mm³; OR 5.31 [95% CI: 4.87–5.80]), followed by female sex (OR 1.55 [95% CI: 1.42–1.68]) and age <5 years (OR 1.64 [95% CI 1.39, 1.94]). Model-estimated risk for NA varied significantly across demographic and WBC strata, with a 14.4-fold range in rates between subgroups with the lowest and highest predicted risk (males 13–17 years with elevated WBC [1.1%] vs. females 3–4 years with normal WBC [15.8%]).ConclusionsContemporary NA rates have decreased over time, however NA risk remains high in children without a leukocytosis, particularly for girls and children <5 years of age. These data provide contemporary performance benchmarks for NA in children with suspected appendicitis and identify high-risk populations where further efforts to mitigate NA risk should be targeted.Level of EvidenceIII.     

Modification of an extended total temporomandibular joint replacement (eTMJR) classification system

The aims of this paper were to validate a modification of an extended total temporomandibular joint replacement (eTMJR) classification system and develop a classification schematic for ease of reference. High-volume TMJ surgeons were asked to score 20 separate eTMJR devices using the updated classification system, and inter-rater variability was calculated. Using the modified classification system developed, a Conger’s kappa (κ) coefficient of 0.53 was returned, suggesting moderate to good levels of agreement. The final classification system was then developed in a series of standardised graphic illustrations as visual representations of the different subcategories of eTMJR devices.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

头颈区黏膜淋巴瘤的WHO分类更新及诊断方法

2017年1月与9月，《WHO头颈肿瘤分类》（第4版）与《WHO造血淋巴组织肿瘤分类》（修订第4版）两本蓝皮书相继面世，笔者也有幸受邀参与了《WHO头颈肿瘤分类》（第4版）一书中淋巴造血组织肿瘤有关章节的编写工作，分别对这两个新分类中关于头颈区黏膜淋巴组织增生性疾病的内容更新、头颈区黏膜淋巴瘤的诊断方法以及该区域常见淋巴瘤类型的诊断与鉴别诊断要点作一简介。     

Chronic inflammation and risk of lung cancer in older adults in the health,aging and body composition cohort study

Objectives

We examined the association between three inflammatory markers (Interleukin (IL)-6, C-reactive protein (CRP), tumor necrosis factor (TNF)-α) and incident lung cancer using baseline, updated, and averaged inflammatory measures in older adults.