Infrapatellar fat pad size and subcutaneous fat in knee osteoarthritis radiographic progression: data from the osteoarthritis initiative.

OBJECTIVES: Adipose tissue has been associated with knee osteoarthritis (KOA) pathogenesis, but the longitudinal changes in adipose tissue with KOA progression have not been carefully evaluated. This study aimed to determine if longitudinal changes of systemic and local adipose tissue is associated with radiographic progression of KOA. METHODS: This case-control study used data from the Osteoarthritis Initiative (OAI) and included 315 cases (all the right knees with a minimum of Kellgren-Lawrence score (KL) of 0 and an increase of ≥ 1 KL from baseline to 48 months) and 315 controls matched by age, sex, race, and baseline KL. Cross sectional area of IPFP (IPFP CSA) and subcutaneous adipose tissue around the distal thigh (SCATthigh) were measured using MRI images at baseline and 24 months. Conditional logistic regression models were fitted to estimate associations of obesity markers, IPFP CSA, and SCATthigh with radiographic KOA progression. Mediation analysis was used to assess whether IPFP CSA or SCATthigh mediates the relationships between baseline BMI and radiographic KOA progression. RESULTS: 24-month changes of IPFP CSA (ΔIPFP CSA) and SCATthigh (ΔSCATthigh) were significantly greater in cases compared to controls, whereas Δ BMI and Δ abdominal circumference were similar in both groups during follow-up. Adjusted ORs for radiographic KOA progression were 9.299, 95% CI (5.357-16.141) per 1 SD increase of Δ IPFP CSA and 1.646, 95% CI (1.288-2.103) per 1 SD increase of Δ SCATthigh. ΔIPFP CSA mediated the association between baseline BMI and radiographic KOA progression (87%). CONCLUSIONS: Subjects with radiographic progression of KOA, had significant increases in IPFP CSA and subcutaneous adipose tissue while BMI and abdominal circumference remained stable. Additional studies are needed to confirm these associations.

Leaf and Flower Extracts from the Dwarf Elder (Sambucus ebulus): Toxicity and Repellence against Cosmopolitan Mosquito-Borne Diseases Vectors.

As there has been no scientific evidence of the bioactivity of Sambucus ebulus (Adoxaceae) extracts against insects, we chemically characterized S. ebulus leaves and flowers extracted in methanol and water. The crude extracts, phenolic compounds, and amino acids isolated were tested as larvicides against the fourth-instar larvae of Aedes albopictus and Culex pipiens (Diptera: Culicidae). To understand their mode of action, we evaluated the in vitro acetylcholinesterase (AChE) inhibitor effect of the crude extracts on the two mosquito larvae through a colorimetric method. Furthermore, the deterrent effect of the crude extracts against ovipositing Ae. albopictus females was assessed in the open field. Twelve phenylpropanoids and fourteen amino acids were detected in the extracts, with a prevalence of hydroxycinnamic acids and nonaromatic amino acids. The most toxic compound to Ae. albopictus larvae after 24 h was gallic acid, followed by the crude S. ebulus leaf extract; on Cx. pipiens, it was the crude flower extract. The AChE test showed higher inhibition on both mosquito species exerted by the leaf extract if compared to the flower extract, and it also deterred oviposition by Ae. albopictus females starting from the third day. The results indicated that vegetal extracts could effectively help in the integrated vector management of mosquitoes.

Predicting cervical cancer risk probabilities using advanced H20 AutoML and local interpretable model-agnostic explanation techniques.

Background: Cancer is positioned as a major disease, particularly for middle-aged people, which remains a global concern that can develop in the form of abnormal growth of body cells at any place in the human body. Cervical cancer, often known as cervix cancer, is cancer present in the female cervix. In the area where the endocervix (upper two-thirds of the cervix) and ectocervix (lower third of the cervix) meet, the majority of cervical cancers begin. Despite an influx of people entering the healthcare industry, the demand for machine learning (ML) specialists has recently outpaced the supply. To close the gap, user-friendly applications, such as H2O, have made significant progress these days. However, traditional ML techniques handle each stage of the process separately; whereas H2O AutoML can automate a major portion of the ML workflow, such as automatic training and tuning of multiple models within a user-defined timeframe. Methods: Thus, novel H2O AutoML with local interpretable model-agnostic explanations (LIME) techniques have been proposed in this research work that enhance the predictability of an ML model in a user-defined timeframe. We herein collected the cervical cancer dataset from the freely available Kaggle repository for our research work. The Stacked Ensembles approach, on the other hand, will automatically train H2O models to create a highly predictive ensemble model that will outperform the AutoML Leaderboard in most instances. The novelty of this research is aimed at training the best model using the AutoML technique that helps in reducing the human effort over traditional ML techniques in less amount of time. Additionally, LIME has been implemented over the H2O AutoML model, to uncover black boxes and to explain every individual prediction in our model. We have evaluated our model performance using the findprediction() function on three different idx values (i.e., 100, 120, and 150) to find the prediction probabilities of two classes for each feature. These experiments have been done in Lenovo core i7 NVidia GeForce 860M GPU laptop in Windows 10 operating system using Python 3.8.3 software on Jupyter 6.4.3 platform. Results: The proposed model resulted in the prediction probabilities depending on the features as 87%, 95%, and 87% for class '0' and 13%, 5%, and 13% for class '1' when idx_value=100, 120, and 150 for the first case; 100% for class '0' and 0% for class '1', when idx_value= 10, 12, and 15 respectively. Additionally, a comparative analysis has been drawn where our proposed model outperforms previous results found in cervical cancer research.

MedKnee: A New Deep Learning-Based Software for Automated Prediction of Radiographic Knee Osteoarthritis.

In computer-aided medical diagnosis, deep learning techniques have shown that it is possible to offer performance similar to that of experienced medical specialists in the diagnosis of knee osteoarthritis. In this study, a new deep learning (DL) software, called "MedKnee" is developed to assist physicians in the diagnosis process of knee osteoarthritis according to the Kellgren and Lawrence (KL) score. To accomplish this task, 5000 knee X-ray images obtained from the Osteoarthritis Initiative public dataset (OAI) were divided into train, valid, and test datasets in a ratio of 7:1:2 with a balanced distribution across each KL grade. The pre-trained Xception model is used for transfer learning and then deployed in a Graphical User Interface (GUI) developed with Tkinter and Python. The suggested software was validated on an external public database, Medical Expert, and compared with a rheumatologist's diagnosis on a local database, with the involvement of a radiologist for arbitration. The MedKnee achieved an accuracy of 95.36% when tested on Medical Expert-I and 94.94% on Medical Expert-II. In the local dataset, the developed tool and the rheumatologist agreed on 23 images out of 30 images (74%). The MedKnee's satisfactory performance makes it an effective assistant for doctors in the assessment of knee osteoarthritis.

Identification of Severe Grading in Knee OsteoArthritis from MRI using Ensemble Deep Learning.

BACKGROUND: Accurate finding of Knee Osteoarthritis (KOA) from structural Magnetic Resonance Imaging (MRI) is a difficult task and is greatly subject to user variation. Furthermore, the identification of knee osteoarthritis (KOA) from MRI scans presents a challenge due to the limited information available. A novel methodology using an ensemble Deep Learning algorithm, combining EfficientNet-B3 and ResNext-101 architectures, aims to forecast KOA advancement, bridging the identified gap in clinical trials. OBJECTIVES: The study aims to develop a precise predictive model for knee osteoarthritis using advanced deep-learning architectures and structural MRI scan data. By utilizing an ensemble technique, the model's accuracy in predicting disease development is enhanced, surpassing the limitations of traditional biomarkers. METHODS: The study used the Osteoarthritis Initiative dataset to develop an ensemble Deep Learning model that combined EfficientNet-B3 and ResNext-101 architectures. Techniques like cropping, gamma correction, and in-slice rotation were used to expand the dataset and improve the model's generalization capacity. RESULTS: The Deep Learning model demonstrated 93% validation accuracy on the OAI dataset, accurately capturing subtle patterns of knee osteoarthritis progression. Augmentation approaches enhanced its resilience. CONCLUSION: Our ensemble Deep Learning approach, using ResNext-101 and EfficientNet-B3 architectures, accurately predicts knee osteoarthritis courses using structural MRI data, demonstrating the importance of data augmentation for improved predictive tools.

Synergistic Effect of Precursor and Interface Engineering Enables High Efficiencies in FAPbI3 Perovskite Solar Cells.

Formamidinium lead iodide (FAPbI3)-based perovskite solar cells have gained immense popularity over the last few years within the perovskite research community due to their incredible opto-electronic properties and the record power conversion efficiencies (PCEs) achieved by the solar cells. However, FAPbI3 is vulnerable to phase transitions even at room temperature, which cause structural instability and eventual device failure during operation. We performed post-treatment of the FAPbI3 surface with octyl ammonium iodide (OAI) in order to stabilize the active phase and preserve the crystal structure of FAPbI3. The formation of a 2D perovskite at the interface depends on the stoichiometry of the precursor. By optimizing the precursor stoichiometry and the concentration of OAI, we observe a synergistic effect, which results in improved power conversion efficiencies, reaching the best values of 22% on a glass substrate. Using physical and detailed optical analysis, we verify the presence of the 2D layer on the top of the 3D surface of the perovskite film.

IJES-OA Net: A residual neural network to classify knee osteoarthritis from radiographic images based on the edges of the intra-joint spaces.

Among the musculoskeletal disorders in the world, osteoarthritis is the most common, affecting most of the body joints, especially the knee. Clinical radiographic imaging methods are commonly used to diagnose osteoarthritis thanks to their cheapness and availability. Due to the low quality and indiscernibility of these images, however, accurate osteoarthritis diagnosis has always faced inaccuracies, such as the wrong diagnosis. One of the osteoarthritis hallmarks is joint space narrowing. Thus, its degree and severity can be determined relatively by assessing the space between the bones in the joint. Therefore, in this research, a deep residual neural network, termed IJES-OA Net, is presented to automatically grade (classify) the severity of knee osteoarthritis via radiographs. This is achieved by tuning it in a way to have it focused on the distance of the edges of the bones inside the knee joint. Experimental results which are conducted on MOST (for training) and OAI (for validation and testing) datasets show that the IJES-OA Net achieves high average accuracy as well as average precision (80.23% and 0.802, respectively) while having less complexity compared to other methods. Additionally, the resulting attention maps from IJES-OA Net are accurate enough that increase experts' reliance on the provided results.

Radiographically detectable intra-articular mineralization: Predictor of knee osteoarthritis outcomes or only an indicator of aging? A brief report from the osteoarthritis initiative.

Objective: To determine the association between Intra-articular mineralization (IAM) and knee osteoarthritis (OA) outcomes stratified according to participants' age. Methods: Participants from the Osteoarthritis Initiative (OAI) with baseline radiographic OA (i.e., Kellgren-Lawrence grade ≥2 with Osteoarthritis Research Society International (OARSI) atlas joint space narrowing (JSN)) in either knee were identified. Both knees and dominant hand baseline radiographs were evaluated for the presence of IAM. Whole-grade OARSI-JSN radiographic progression and increased Western Ontario and McMaster universities osteoarthritis index scores of the knees with baseline radiographic OA (assessed annually) were defined as radiographic and symptomatic progression, respectively. Cox proportional-hazards and longitudinal multilevel regression models investigated radiographic and symptomatic progression, respectively. Results: 2010 participants with baseline radiographic OA in either one or both knees (N â€‹= â€‹2976) were identified. 178 participants had baseline IAM (hand radiographs â€‹= â€‹46, knee radiographs â€‹= â€‹166, both â€‹= â€‹34). An adjusted logistic regression model suggests an association between age and IAM (Odds Ratio: 1.06, 95% Confidence Interval (CI): 1.04-1.08). Presence of any IAM was not associated with whole-grade OARSI-JSN (Hazard Ratio (HR): 1.00, 95% CI: 0.73-1.37) or symptomatic progression (Estimated difference: 1.24, p-value: 0.13) in all participants. Using stratification analysis, in younger participants <60 years old, presence of any IAM was associated with radiographic progression (HR: 1.90, 95% CI: 1.01-3.60). Conclusion: Although the presence of any radiographic IAM increases with higher age and does not predict knee OA outcomes across the entire sample of OAI participants, it is associated with knee OA radiographic progression in participants aged <60.

Effusion-synovitis worsening mediates the association between body mass index and Kellgren-Lawrence progression in obese individuals: data from the Osteoarthritis Initiative.

OBJECTIVE: Both obesity and synovitis are independently associated with knee osteoarthritis (KOA) progression. We examined whether synovitis mediates the relationship between body mass index (BMI) and KOA radiographic progression in the Osteoarthritis Initiative (OAI) cohort. DESIGN: We conducted a case-control study within the OAI. Cases (n = 315) were right knees with an increase of ≥1 Kellgren-Lawrence from baseline to 48 months of follow-up. Controls (n = 315) were right knees with no KL change. Cases and controls were matched by age, sex, race, and baseline KL. MRI Osteoarthritis Knee Score (MOAKS) at baseline and at 2 years was used for a semi-quantitative scoring (0-3) of effusion-synovitis and Hoffa-synovitis. Conditional logistic regression estimated associations between BMI and synovitis with KOA progression. Mediation analysis was used to assess the mediating effects of synovitis. RESULTS: The mean age of participants was 61 years, 70.8% were women, and 87% were White. KOA progression was associated with higher BMI (adjusted OR 1.05; 95%CI 1.01-1.09) and effusion-synovitis relative to no effusion-synovitis (adjusted OR 2.2; 95%CI 1.6-3.1). Associations between effusion-synovitis worsening and KOA progression were more pronounced among obese individuals (OR 34.1; 95%CI 4.2-274.8; P = 0.001) compared to normal weight (OR 3.2; 95%CI 0.8-12.8, P=0.096) individuals. Effusion-synovitis at 2 years, but not at baseline, mediated the relationship between BMI and KOA progression over a 4-year period. CONCLUSIONS: We found that effusion-synovitis worsening mediated the association between BMI and KOA progression and was associated with increased risk of KOA progression, particularly among obese individuals.

Microbiological Diagnosis of Osteoarticular Infections: Comparison between BacT/Alert Bottles and Schaedler Broth.

Microbiological diagnosis of osteoarticular infections (OAIs) is based on culture on several media. Experts recommend the use of liquid media, such as Schaedler broth, but many laboratories use blood culture media with automated detection instead for convenience. We aimed to evaluate the performance of culturing in BacT/Alert (bioMérieux) bottles for the microbiological diagnosis of OAI versus culturing in Schaedler broth. This prospective study was conducted on all osteoarticular specimens sent to the microbiology laboratories of the Versailles and Diaconesses Croix Saint-Simon hospitals between October 2016 and February 2017. Each sample was inoculated onto solid agar, into BacT/Alert bottles incubated for 14 days, and into a Schaedler broth incubated for 14 days with daily reading. The gold standard was defined as follow: OAI was diagnosed for a patient if at least two samples were positive for a nonskin microorganism and at least three for a cutaneous species. The times to detection were compared. A total of 1,616 specimens from 349 patients were collected. BacT/Alert bottles were significantly more sensitive than the Schaedler process for OAI diagnosis (114/135 OAI detected by BacT/Alert bottles; 91/135 OAI detected by Schaedler broth; +17.0% [95% confidence interval {CI}, 6.8%, 27.3%]; P = 0.0004). The time to detection was significantly shorter using BacT/Alert bottles (2.0 ± 2.2 days) than using Schaedler broth (4.6 ± 3.6 days, P < 0.0001). The culture of osteoarticular specimens in BacT/Alert bottles allows bacterial enrichment with an automated detection of positivity. Their use decreased detection time and increased sensitivity, making it a useful tool for the diagnosis of OAI that should be included among the recommended media. IMPORTANCE Microbiological diagnosis of OAI is based on culture on several media. French experts recommend the use of liquid media such as Schaedler broth, but many laboratories use blood culture media with automated detection in substitution because it is more convenient. We report here a prospective multicentric study evaluating the performance of culture in BacT/Alert (bioMérieux) bottles for microbiological diagnosis of OAI in comparison with culture in Schaedler broth. A total of 1,616 osteoarticular specimens from 349 patients were collected and inoculated onto agar, into BacT/Alert aerobic and anaerobic bottles, and into a Schaedler broth. BacT/Alert bottles were significantly more sensitive than the Schaedler process for OAI diagnosis (+17.0% [95% CI, 6.8%, 27.3%], P = 0.0004). The time to detection was significantly shorter for the BacT/Alert bottles (2.0 ± 2.2 days) than for Schaedler broth (4.6 ± 3.6 days, P < 0.0001). This study suggests that the use of BacT/Alert bottles should be recommended in microbiological diagnosis of OAI.

Implementing a Registry Federation for Materials Science Data Discovery.

As a result of a number of national initiatives, we are seeing rapid growth in the data important to materials science that are available over the web. Consequently, it is becoming increasingly difficult for researchers to learn what data are available and how to access them. To address this problem, the Research Data Alliance (RDA) Working Group for International Materials Science Registries (IMRR) was established to bring together materials science and information technology experts to develop an international federation of registries that can be used for global discovery of data resources for materials science. A resource registry collects high-level metadata descriptions of resources such as data repositories, archives, websites, and services that are useful for data-driven research. By making the collection searchable, it aids scientists in industry, universities, and government laboratories to discover data relevant to their research and work interests. We present the results of our successful piloting of a registry federation for materials science data discovery. In particular, we out a blueprint for creating such a federation that is capable of amassing a global view of all available materials science data, and we enumerate the requirements for the standards that make the registries interoperable within the federation. These standards include a protocol for exchanging resource descriptions and a standard metadata schema for encoding those descriptions. We summarize how we leveraged an existing standard (OAI-PMH) for metadata exchange. Finally, we review the registry software developed to realize the federation and describe the user experience.

ADL Outcome of Stroke by Stroke Type and Time from Onset to Admission to a Comprehensive Inpatient Rehabilitation Ward.

OBJECTIVE: To examine the effect of onset to admission interval (OAI) and stroke type on activities of daily living (ADL) outcome. MATERIALS AND METHODS: Stroke patients (n=3112) admitted to and discharged from comprehensive inpatient rehabilitation wards at Nanakuri Memorial Hospital were classified into 8 OAI segments and by stroke type [intracerebral hemorrhage (ICH) and cerebral infarction (CI)]. Motor subscore of the Functional Independence Measure (FIM-M) on admission, FIM-M at discharge, FIM-M gain, length of stay (LOS), and FIM-M efficiency in the ICH and CI group matched by OAI segment were compared using the Wilcoxon test. Multiple comparisons using the Steel-Dwass test of FIM-M on admission, FIM-M at discharge, FIM-M gain, LOS, and FIM-M efficiency by OAI segments were performed. RESULTS: FIM-M on admission was lower in the ICH group than the CI group in matched OAI segments. However, FIM-M improvement was greater in the ICH group than the CI group, resulting in no difference in FIM-M between groups at discharge. In both groups, the longer the OAI, the lower the FIM-M on admission and at discharge. The distribution pattern of significant differences among OAI segments differed between the groups. LOS tended to be longer and FIM-M efficiency tended to be higher in the ICH group than in the CI group. CONCLUSIONS: The brain mass effect at the time of admission was larger and took longer to decrease in the ICH group than in the CI group. These results may improve prediction of outcomes in comprehensive inpatient rehabilitation wards.

Hoffa's fat pad thickness: a measurement method with sagittal MRI sequences.

BACKGROUND: Hoffa's fat pad is a structure located within the fibrous joint capsule of the knee joint, but outside the synovial cavity. It plays an important biomechanical and metabolic role in knee joint, reducing the impact of forces generated by loading and producing cytokines. Changes in its size can induce modifications in the knee homeostasis. However, a great variability exists regarding its measurements. This work aims to evaluate the reliability of a measurement method of Hoffa's fat pad dimensions through MRI. METHODS: 3T sagittal IW 2D TSE fat-suppressed MRI sequences, taken from the OAI (Osteoarthritis initiative) database, of 191 male and female patients, aged between 40 and 80 years, were analysed; a manual measurement of the thickness of Hoffa's fat pad of each subject was then performed by two different readers. The interobserver reliability and intraobserver reliability of the measurements were described by coefficient of variation (CV), Pearson correlation and Bland-Altman plots. RESULTS: All statistical analyses have shown that not significant intra- or interobservers differences were evident (intraobserver CV % for the first observer was 2.17% for the right knee and 2.24% for the left knee, while for the second observer 2.31% for the right knee and 2.24% for the left knee; linear correlation was for the first observer r = 0.96 for the right knee and r = 0.96 for the left knee, while for the second observer r = 0.97 for the right knee and r = 0.96 for the left knee; in addition, the interobserver CV % was 1.25% for the right knee and 1.21% for the left knee and a high interobserver linear correlation was found: r = 0.97 for the right knee and r = 0.96 for the left knee). All results suggest that this manual measurement method of Hoffa's fat pad thickness can be performed with satisfactory intra- and interobserver reliability. CONCLUSIONS: Hoffa's fat pad thickness can be measured, using sagittal MRI images, with this manual method that represents, for his high reliability, an effective means for the study of this anatomical structure.

Towards classification criteria for early-stage knee osteoarthritis: A population-based study to enrich for progressors.

OBJECTIVE: To facilitate a greater likelihood of favorable response to new disease-modifying therapies, recruitment of patients at an earlier stage of their disease into clinical trials may be an attractive strategy. Hence, there is a need to develop widely accepted classification criteria for early-stage knee osteoarthritis (OA). We have proposed a set of classification criteria for early-stage knee OA (2018 classification criteria) now being further refined. Here, we test the draft criteria for enrichment for clinical and structural progression. DESIGN: Performance of the 2018 classification criteria for early stage knee OA was tested using data from the Osteoarthritis Initiative (OAI). The OAI comprises data of 4796 men and women aged 45-79 years with or at risk for knee OA at baseline. Based on the 2018 classification criteria, a knee with Kellgren & Lawrence (K&L) grade of 0-I, two out of four Knee Injury and Osteoarthritis Outcome Score (KOOS) subscales equal or less than 85, and presence of at least one of joint line tenderness or crepitus, was considered as early-stage knee OA. Knees with K&L grade 0-I that did not fulfill the 2018 criteria, were considered as controls. Logistic regression analysis was used to evaluate the predictive performance of the criteria set for structural as well as clinical progression. We further explored the discriminatory capability of criteria by including the average KOOS4 score, and relevant clinical examination findings such as the presence of effusion and/or Heberden's nodes. RESULTS: We identified 1315 (27%) knees from OAI fulfilling the 2018 early-stage knee OA classification criteria. The female to male ratio was higher in the early knee OA group compared to controls. The early-stage knee OA group were on average slightly younger and had higher body mass index vs controls (mean [SD] age: 59.2 [8.9] years vs. 60.2 [9.1] and mean [SD] BMI 28.3 [7.0] vs. 26.8 [6.0]). By applying the 2018 criteria, there was a substantial enrichment compared to controls at 48 and 96 months for both structural (OR=1.1-1.4, and AUC=0.72-0.74) and clinical progressors (OR=2.1-2.5, 95% and AUC=0.66). Expanding the clinical examination findings by including joint effusion and/or Heberden's nodes improved the enrichment for both structural and clinical progressors (OR=4.2, 95% confidence interval=3.2-5.5 and OR=3.3, 95% confidence interval=2.8-3.5, respectively). Replacing scoring of the 4 separate KOOS domains by a KOOS4 score performed comparably. CONCLUSIONS: The proposed 2018 early-stage knee OA classification criteria showed encouraging performance characteristics with regard to an enrichment for structural and clinical progression using longitudinal OAI data. Our results indicate that the addition of clinical findings improves the performance of previous criteria to define early-stage disease and risk for progression.

Diagnostic accuracy of 99mTc-antigranulocyte SPECT/CT in patients with osteomyelitis and orthopaedic device-related infections: A retrospective analysis.

OBJECTIVES: Conventional imaging techniques are routinely used in the diagnostic work-up of patients with suspected osteomyelitis or orthopaedic implant-associated infections. Hybrid nuclear medicine imaging techniques are a suitable alternative to routine imaging modalities as they provide anatomical and functional information within one procedure. Our study investigated the performance of anti-granulocyte SPECT/CT using 99mTc-labelled monoclonal antibodies in the diagnosis of osteomyelitis and orthopaedic implant-associated infections. METHODS: In this retrospective analysis, we included patients with 99mTc-antigranulocyte SPECT/CT acquired in the context of a suspected bone and joint infection. All patients underwent routine diagnostics and/or had a clinical follow-up of at least 12months. RESULTS: 26 episodes were included. Fifteen exams were performed for suspected osteomyelitis, and 11 for suspected orthopaedic implant-associated infection. SPECT/CT was ordered most often if standard diagnostic tests or conventional imaging modalities remained inconclusive. The overall sensitivity and specificity for the diagnosis of an infection were 77.8% and 94.1%, respectively. The positive predictive value was 87.5% and the negative predictive value 88.9%. Diagnostic accuracy was 88.5%. CONCLUSIONS: 99mTc-antigranulocyte SPECT/CT imaging has a high accuracy in the diagnosis of osteomyelitis and orthopaedic implant-associated infections and is a suitable non-invasive diagnostic tool if standard diagnostic examinations are inconclusive or not applicable.

Stage-specific meniscal features predict progression of osteoarthritis of the knee: a retrospective cohort study using data from the osteoarthritis initiative.

BACKGROUND: In the progression of osteoarthritis (OA) of the knee, a correlation between meniscal posterior segment injuries and medial meniscal extrusion has been reported, but there have been few reports on the relationship with the meniscal shape. The purpose of this study was to clarify the features of the meniscal shape involved in the progression of knee OA. METHODS: Data were obtained from the Osteoarthritis Initiative (OAI) database. We defined two sets of subjects. One set included 455 knees of subjects whose OA grade on the Kellgren Lawrence (KL) scale progressed in 24 months from baseline and the other set consisted of 455 knees with no progression. The OA progressed subjects were divided to three groups: the "OA change group", KL0 and KL1 knees that progressed to KL2 and KL3; the "mild change group", KL2 knees that progressed to KL3; and the "severe change group", KL2 and KL3 knees that progressed to KL4. The no progression set was divided into three groups whose OA grade remained unchanged. We used magnetic resonance imaging data and manually measured seven items (longitudinal diameter [LD], anterior wedge thickness, anterior wedge width, posterior wedge width, posterior wedge thickness, anterior wedge angle, posterior wedge angle) from the sagittal slice and the extrusion from the coronal slice. These measurements were compared between knees with and without OA progression. RESULTS: In the "OA change group" and "mild change group", the anterior and posterior wedge widths and the extrusion were significantly larger, but the anterior and the posterior wedge angles were significantly smaller. In the "severe change group," the LD and the extrusion were significantly larger. In each group, there was no uniform tendency for the correlation coefficient of the parameters evaluated. CONCLUSIONS: Our findings suggested (1) a larger meniscal LD at the baseline predicted progression of knee OA after 24 months and (2) a larger meniscal width and smaller meniscal angle predicted progression of knee OA after 24 months.

Dietary magnesium intake and fracture risk: data from a large prospective study.

Research considering the relationship between dietary Mg and osteoporosis as well as fractures are sparse and conflicting. We therefore aimed to investigate Mg intake and the onset of fractures in a large cohort of American men and women involved in the Osteoarthritis Initiative over a follow-up period of 8 years. Dietary Mg intake (including that derived from supplementation) was evaluated through a FFQ at baseline and categorised using sex-specific quintiles (Q); osteoporotic fractures were evaluated through self-reported history. Overall, 3765 participants (1577 men; 2071 women) with a mean age of 60·6 (sd 9·1) years were included. During follow-up, 560 individuals (198 men and 368 women) developed a new fracture. After adjusting for fourteen potential confounders at baseline and taking those with lower Mg intake as reference (Q1), men (hazard ratio (HR) 0·47; 95 % CI 0·21, 1·00, P=0·05) and women (HR 0·38; 95 % CI 0·17, 0·82, P=0·01) in the highest quintile reported a significantly lower risk for fracture. Women meeting the recommended Mg intake were at a 27 % decreased risk for future fractures. In conclusion, higher dietary Mg intake has a protective effect on future osteoporotic fractures, especially in women with a high risk for knee osteoarthritis. Those women meeting the recommended Mg intake appear to be at a lower risk for fractures.

Predictive values of WOMAC, KOOS, and SF-12 score for knee arthroplasty: data from the OAI.

PURPOSE: A number of validated scores are available to monitor clinical outcome after knee arthroplasty. The current study examines whether WOMAC, KOOS, or SF-12 scores have a predictive value to identify patients that require total knee arthroplasty within 1 year. METHODS: The Osteoarthritis Initiative includes 4684 patients in two groups: incidence subcohort (Group A, n = 3284) and progression subcohort (Group B, n = 1400). A total of 278 patients reached the endpoint "unilateral knee replacement" (Group A = 96; Group B = 182). WOMAC, KOOS, and SF-12 scores at the maximum of 12 months prior to surgery were used to analyse predictive values. ROC analysis and the diagnostic accuracy for these scores were reported. RESULTS: Group A: WOMAC and KOOS score as well as the "physical component summary" of SF-12 showed an area under the curve (AUC) between 0.8 and 0.9 (high diagnostic evidence) to predict total knee replacement. The KOOS "symptoms" (0.67) and SF12 "function" (0.79) showed lower values. The KOOS QoL score showed the highest predictive value with an AUC of 0.84 (CI 95% 0.77-0.91, p < 0.001) resulting in a sensitivity of 0.88 and a specificity of 0.72. Similar numbers were achieved by the total WOMAC score with an AUC of 0.85 (CI 95% 0.82-0.88, p < 0.001) resulting in a sensitivity of 0.77 and a specificity of 0.82. The SF-12 physical component score had an AUC of 0.83 (CI 95% 0.79-0.87, p < 0.001) resulting in a sensitivity of 0.87 and a specificity of 0.68. Different combinations of scores increase the positive likelihood ratio (up to 18) and specificity (up to 0.97). Group B scores showed lower AUCs, sensitivities and specificities. CONCLUSIONS: Combinations of WOMAC, KOOS, or SF-12 scores accurately predict patients that require knee arthroplasty within 1 year. In addition to other clinical parameters (physical examination, radiographs), they can guide patient and surgeon during the treatment of arthritis of the knee. LEVEL OF EVIDENCE: II.

Limitaciones en la distribución de contenidos entre repositorios de acceso abierto en América Latina y el Caribe / Limitations in the distribution of contents among Latin American and Caribbean open access repositories

El presente trabajo muestra un estudio de 58 fuentes de acceso abierto correspondientes a 14 países de América Latina y el Caribe. Se busca identificar algunos problemas relacionados con la estandarización del protocolo OAI-PMH en los repositorios de acceso abierto en América Latina y el Caribe y cómo estos afectan la distribución de contenidos. El objetivo que el trabajo persigue es identificar las limitantes que afectan el intercambio de contenidos entre fuentes de acceso abierto en América Latina y el Caribe mediante el estudio de repositorios institucionales y de revistas de corte científico que hacen función de proveedores de datos. Las fuentes seleccionadas responden a revistas de corte científico y a repositorios de universidades. El estudio fue realizado con el empleo del software OHS (Open Harvester System) y tiene en cuenta aspectos como la tecnología empleada, los estándares de metadatos y la forma de representación de la información, además del uso de los verbos que establece el protocolo OAI-PMH. Se hizo una observación del funcionamiento de algunos repositorios de acceso abierto y se probaron las respuestas de estos ante las peticiones de los verbos. Los resultados obtenidos muestran diversidad, tanto tecnológica como en la forma de aplicar los estándares, y reflejan algunas de las problemáticas a las que se enfrenta el movimiento de acceso abierto en el área de estudio y cómo esto afecta la interoperabilidad necesaria para automatizar el intercambio de contenidos.

A review was conducted of 58 open access sources from 14 Latin American and Caribbean countries, with the purpose of identifying problems related to the standardization of the OAI-PMH protocol in Latin American and Caribbean open access repositories, as well as the way in which these problems affect the distribution of contents. The study was aimed at identifying the limitations affecting the exchange of contents between Latin American and Caribbean open access sources through the study of institutional repositories and scientific journals which perform the function of data providers. The sources selected were scientific journals and university repositories. The study was based on the software OHS (Open Harvester System) and considered aspects such as the technology used, metadata standards and the manner in which information was represented, besides the verbs established by the OAI-PMH protocol. The functioning of some open access repositories was observed and tests were conducted of their response to the requests of verbs. Results show diversity both in the technology and in the way standards are applied, as well as some of the problems faced by the open access movement in the study area and their impact on the interoperability required to automate the exchange of contents.