Diagnosis of early stage knee osteoarthritis: probability stratification, internal and external validation; data from the check and oai cohorts

ObjectiveTo develop and validate a simple risk scores chart to estimate the probability of poor outcomes in patients with severe head injury (HI).DesignRetrospective.SettingLevel-1, government-funded trauma centre, India.ParticipantsPatients with severe HI admitted to the neurosurgery intensive care unit during 19 May 2010–31 December 2011 (n=946) for the model development and further, data from same centre with same inclusion criteria from 1 January 2012 to 31 July 2012 (n=284) for the external validation of the model.Outcome(s)In-hospital mortality and unfavourable outcome at 6 months.ResultsA total of 39.5% and 70.7% had in-hospital mortality and unfavourable outcome, respectively, in the development data set. The multivariable logistic regression analysis of routinely collected admission characteristics revealed that for in-hospital mortality, age (51–60, >60 years), motor score (1, 2, 4), pupillary reactivity (none), presence of hypotension, basal cistern effaced, traumatic subarachnoid haemorrhage/intraventricular haematoma and for unfavourable outcome, age (41–50, 51–60, >60 years), motor score (1–4), pupillary reactivity (none, one), unequal limb movement, presence of hypotension were the independent predictors as its 95% confidence interval (CI) of odds ratio (OR)_did not contain one. The discriminative ability (area under the receiver operating characteristic curve (95% CI)) of the score chart for in-hospital mortality and 6 months outcome was excellent in the development data set (0.890 (0.867 to 912) and 0.894 (0.869 to 0.918), respectively), internal validation data set using bootstrap resampling method (0.889 (0.867 to 909) and 0.893 (0.867 to 0.915), respectively) and external validation data set (0.871 (0.825 to 916) and 0.887 (0.842 to 0.932), respectively). Calibration showed good agreement between observed outcome rates and predicted risks in development and external validation data set (p>0.05).ConclusionFor clinical decision making, we can use of these score charts in predicting outcomes in new patients with severe HI in India and similar settings.

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DeepRePath: Identifying the Prognostic Features of Early-Stage Lung Adenocarcinoma Using Multi-Scale Pathology Images and Deep Convolutional Neural Networks

Cancers ◽

10.3390/cancers13133308 ◽

2021 ◽

Vol 13 (13) ◽

pp. 3308

Author(s):

Won Sang Shim ◽

Kwangil Yim ◽

Tae-Jung Kim ◽

Yeoun Eun Sung ◽

Gyeongyun Lee ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Early Stage ◽

External Validation ◽

Area Under The Curve ◽

The Cancer Genome Atlas ◽

Deep Convolutional Neural Networks ◽

Prognostic Features ◽

Multi Scale ◽

Model Based ◽

Number Of Patients

The prognosis of patients with lung adenocarcinoma (LUAD), especially early-stage LUAD, is dependent on clinicopathological features. However, its predictive utility is limited. In this study, we developed and trained a DeepRePath model based on a deep convolutional neural network (CNN) using multi-scale pathology images to predict the prognosis of patients with early-stage LUAD. DeepRePath was pre-trained with 1067 hematoxylin and eosin-stained whole-slide images of LUAD from the Cancer Genome Atlas. DeepRePath was further trained and validated using two separate CNNs and multi-scale pathology images of 393 resected lung cancer specimens from patients with stage I and II LUAD. Of the 393 patients, 95 patients developed recurrence after surgical resection. The DeepRePath model showed average area under the curve (AUC) scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Owing to low performance, DeepRePath cannot be used as an automated tool in a clinical setting. When gradient-weighted class activation mapping was used, DeepRePath indicated the association between atypical nuclei, discohesive tumor cells, and tumor necrosis in pathology images showing recurrence. Despite the limitations associated with a relatively small number of patients, the DeepRePath model based on CNNs with transfer learning could predict recurrence after the curative resection of early-stage LUAD using multi-scale pathology images.

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The development and external validation of an overall survival nomogram in medically inoperable centrally located early-stage non-small cell lung carcinoma

Radiotherapy and Oncology ◽

10.1016/j.radonc.2020.12.038 ◽

2021 ◽

Author(s):

M. Duijm ◽

E. Oomen-de Hoop ◽

N. van Voort van der Zyp ◽

P. van de Vaart ◽

H. Tekatli ◽

...

Keyword(s):

Overall Survival ◽

Lung Carcinoma ◽

Early Stage ◽

Small Cell Lung Carcinoma ◽

External Validation ◽

Small Cell ◽

Small Cell Lung ◽

Cell Lung Carcinoma

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Reanalysis and External Validation of a Decision Tree Model for Detecting Unrecognized Diabetes in Rural Chinese Individuals

International Journal of Endocrinology ◽

10.1155/2017/3894870 ◽

2017 ◽

Vol 2017 ◽

pp. 1-6 ◽

Cited By ~ 2

Author(s):

Zhong Xin ◽

Lin Hua ◽

Xu-Hong Wang ◽

Dong Zhao ◽

Cai-Guo Yu ◽

...

Keyword(s):

Decision Tree ◽

Predictive Value ◽

Early Stage ◽

Current Model ◽

External Validation ◽

Area Under The Curve ◽

Decision Tree Model ◽

Tree Model ◽

Chinese Adult ◽

Significant Difference

We reanalyzed previous data to develop a more simplified decision tree model as a screening tool for unrecognized diabetes, using basic information in Beijing community health records. Then, the model was validated in another rural town. Only three non-laboratory-based risk factors (age, BMI, and presence of hypertension) with fewer branches were used in the new model. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve (AUC) for detecting diabetes were calculated. The AUC values in internal and external validation groups were 0.708 and 0.629, respectively. Subjects with high risk of diabetes had significantly higher HOMA-IR, but no significant difference in HOMA-B was observed. This simple tool will help general practitioners and residents assess the risk of diabetes quickly and easily. This study also validates the strong associations of insulin resistance and early stage of diabetes, suggesting that more attention should be paid to the current model in rural Chinese adult populations.

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Lack of agreement in experts’ classification of patients with early-stage knee osteoarthritis

Osteoarthritis and Cartilage ◽

10.1016/j.joca.2021.02.393 ◽

2021 ◽

Vol 29 ◽

pp. S299-S300

Author(s):

A. Mahmoudian ◽

S. Lohmander ◽

M. Englund ◽

P. Hansen ◽

F. Luyten

Keyword(s):

Knee Osteoarthritis ◽

Early Stage

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Platelet-rich plasma as an effective biological therapy in early-stage knee osteoarthritis: One year follow up

SICOT-J ◽

10.1051/sicotj/2021003 ◽

2021 ◽

Vol 7 ◽

pp. 6

Author(s):

Deepak Rai ◽

Jyotsana Singh ◽

Thimmappa Somashekharappa ◽

Ajit Singh

Keyword(s):

Knee Osteoarthritis ◽

Early Stage ◽

Platelet Rich Plasma ◽

Symptomatic Relief ◽

Womac Questionnaire ◽

Significant Clinical Improvement ◽

Bioactive Agents ◽

One Year ◽

Early Oa

Objective: PRP is produced by centrifugation of whole blood containing highly concentrated platelets, associated growth factors, and other bioactive agents which has been shown to provide some symptomatic relief in early knee osteoarthritis (OA). The principal objective of our study was to evaluate the effectiveness and safety of standardized intra-articular injection of autologous PRP in early osteoarthritis knee. Methods: A total of 98 eligible symptomatic patients received two injections of standardized PRP 3 weeks apart. Clinical outcomes were evaluated using the VAS and Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire before treatment and at 6 weeks, 3 months, 6 months, and 1 year after treatment. Secondary objectives were safety (side effects), and the effect of PRP on the different grades of knee degeneration. Results: There was a statistically significant improvement in mean VAS and WOMAC scores at 6 weeks, 3 months, 6 months, and slight loss of improvement at 1 year follow-up. There was also a correlation between the degree of degeneration and improvement in the mean scores. The decrease in mean pain score is more in grades 1 and 2 (early OA) than in grade 3. The intraarticular injection is safe, with no major complications. Conclusion: PRP is a safe and effective biological regenerative therapy for early OA Knees. It provides a significant clinical improvement in patients with some loss of improvement with time. More studies will be needed to confirm our findings.

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INeo-Epp: A novel T-cell HLA class-I immunogenicity or neoantigenic epitope prediction method based on sequence related amino acid features

10.1101/697011 ◽

2019 ◽

Author(s):

Guangzhi Wang ◽

Huihui Wan ◽

Xingxing Jian ◽

Yuyu Li ◽

Jian Ouyang ◽

...

Keyword(s):

Amino Acid ◽

T Cell ◽

Antigen Processing ◽

External Validation ◽

Cell Epitope ◽

Epitope Prediction ◽

Validation Data ◽

Data Set ◽

Immunogenic Peptide ◽

Related Amino Acid

AbstractIn silico T-cell epitope prediction plays an important role in immunization experimental design and vaccine preparation. Currently, most epitope prediction research focuses on peptide processing and presentation, e.g. proteasomal cleavage, transporter associated with antigen processing (TAP) and major histocompatibility complex (MHC) combination. To date, however, the mechanism for immunogenicity of epitopes remains unclear. It is generally agreed upon that T-cell immunogenicity may be influenced by the foreignness, accessibility, molecular weight, molecular structure, molecular conformation, chemical properties and physical properties of target peptides to different degrees. In this work, we tried to combine these factors. Firstly, we collected significant experimental HLA-I T-cell immunogenic peptide data, as well as the potential immunogenic amino acid properties. Several characteristics were extracted, including amino acid physicochemical property of epitope sequence, peptide entropy, eluted ligand likelihood percentile rank (EL rank(%)) score and frequency score for immunogenic peptide. Subsequently, a random forest classifier for T cell immunogenic HLA-I presenting antigen epitopes and neoantigens was constructed. The classification results for the antigen epitopes outperformed the previous research (the optimal AUC=0.81, external validation data set AUC=0.77). As mutational epitopes generated by the coding region contain only the alterations of one or two amino acids, we assume that these characteristics might also be applied to the classification of the endogenic mutational neoepitopes also called ‘neoantigens’. Based on mutation information and sequence related amino acid characteristics, a prediction model of neoantigen was established as well (the optimal AUC=0.78). Further, an easy-to-use web-based tool ‘INeo-Epp’ was developed (available at http://www.biostatistics.online/INeo-Epp/neoantigen.php)for the prediction of human immunogenic antigen epitopes and neoantigen epitopes.

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Increase in Tibial Internal Rotation Due to Weight-bearing is a Key Feature to Diagnose Early-stage Knee Osteoarthritis: A Study with Upright Computed Tomography

10.21203/rs.3.rs-957182/v1 ◽

2021 ◽

Author(s):

Kazuya Kaneda ◽

Kengo Harato ◽

Satoshi Oki ◽

Yoshitake Yamada ◽

Masaya Nakamura ◽

...

Keyword(s):

Knee Osteoarthritis ◽

Internal Rotation ◽

Early Stage ◽

Weight Bearing ◽

Three Dimensional ◽

Surface Registration ◽

Lower Limbs ◽

Clinical Issue ◽

Osteoarthritic Change ◽

Tibial Internal Rotation

Abstract Background The classification of knee osteoarthritis is an essential clinical issue, particularly in terms of diagnosing early knee osteoarthritis. However, the evaluation of three-dimensional limb alignment on two-dimensional radiographs is limited. This study evaluated the three-dimensional changes induced by weight-bearing in the alignments of lower limbs at various stages of knee osteoarthritis.Methods 45 knees of 25 patients (69.9 ± 8.9 years) with knee OA were examined in the study. CT images of the entire leg were obtained in the supine and standing positions using conventional CT and 320 low-detector upright CT, respectively. Next, the differences in the three-dimensional alignment of the entire leg in the supine and standing positions were obtained using 3D-3D surface registration technique, and those were compared for each Kellgren–Lawrence grade. Results Increased flexion, adduction, and tibial internal rotation were observed in the standing position, as opposed to the supine position. Kellgren–Lawrence grades 1 and 4 showed significant differences in flexion, adduction, and tibial internal rotation between two postures. Grades 2 and 4 showed significant differences in adduction, while grades 1 and 2, and 1 and 3 showed significant differences in tibial internal rotation between standing and supine positions.Conclusions Weight-bearing increased the three-dimensional deformities in knees with osteoarthritis. Particularly, increased tibial internal rotation was observed in patients with grades 2 and 3 compared to those with grade 1. The increase in tibial internal rotation due to weight-bearing is a key pathologic feature to detect early osteoarthritic change in knees undergoing osteoarthritis.

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The Relationship Between Early-Stage Knee Osteoarthritis and Lower-Extremity Alignment, Joint Laxity, and Subjective Scores of Pain, Stiffness, and Function

Journal of Sport Rehabilitation ◽

10.1123/jsr.2014-0170 ◽

2016 ◽

Vol 25 (3) ◽

pp. 213-218

Author(s):

Charlie A. Hicks-Little ◽

Richard D. Peindl ◽

Tricia J. Hubbard-Turner ◽

Mitchell L. Cordova

Keyword(s):

Knee Joint ◽

Lower Extremity ◽

Knee Osteoarthritis ◽

Outcome Measures ◽

Early Stage ◽

Joint Laxity ◽

Knee Oa ◽

Lower Extremity Alignment ◽

Knee Joint Laxity ◽

And Function

Context:Knee osteoarthritis (OA) is a debilitating disease that affects an estimated 27 million Americans. Changes in lowerextremity alignment and joint laxity have been found to redistribute the medial and/or lateral loads at the joint. However, the effect that changes in anteroposterior knee-joint laxity have on lower-extremity alignment and function in individuals with knee OA remains unclear.Objective:To examine anteroposterior knee-joint laxity, lower-extremity alignment, and subjective pain, stiffness, and function scores in individuals with early-stage knee OA and matched controls and to determine if a relationship exists among these measures.Design:Case control.Setting:Sports-medicine research laboratory.Participants:18 participants with knee OA and 18 healthy matched controls.Intervention:Participants completed the Western Ontario McMaster (WOMAC) osteoarthritis questionnaire and were tested for total anteroposterior knee-joint laxity (A-P) and knee-joint alignment (ALIGN).Main Outcome Measures:WOMAC scores, A-P (mm), and ALIGN (°).Results:A significant multivariate main effect for group (Wilks’ Λ = 0.30, F7,26 = 8.58, P < .0001) was found. Knee-OA participants differed in WOMAC scores (P < .0001) but did not differ from healthy controls on ALIGN (P = .49) or total A-P (P = .66). No significant relationships were identified among main outcome measures.Conclusion:These data demonstrate that participants with early-stage knee OA had worse pain, stiffness, and functional outcome scores than the matched controls; however, ALIGN and A-P were no different. There was no association identified among participants’ subjective scores, ALIGN, or A-P measures in this study.

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