Matrix-induced autologous chondrocyte implantation (MACI) is an established technique used to treat osteochondral lesions in the knee. For larger osteochondral lesions (> 5 cm(2)) deeper than approximately 8 mm we have combined the use of two MACI membranes with impaction grafting of the subchondral bone. We report our results of 14 patients who underwent the 'bilayer collagen membrane' technique (BCMT) with a mean follow-up of 5.2 years (2 to 8). There were 12 men and two women with a mean age of 23.6 years (16 to 40). The mean size of the defect was 7.2 cm(2) (5.2 to 12 cm(2)) and were located on the medial (ten) or lateral (four) femoral condyles. The mean modified Cincinnati knee score improved from 45.1 (22 to 70) pre-operatively to 82.8 (34 to 98) at the most recent review (p < 0.05). The visual analogue pain score improved from 7.3 (4 to 10) to 1.7 (0 to 6) (p < 0.05). Twelve patients were considered to have a good or excellent clinical outcome. One graft failed at six years. The BCMT resulted in excellent functional results and durable repair of large and deep osteochondral lesions without a high incidence of graft-related complications.

COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed health services in the most affected countries. In response, governments initiated a series of non-pharmaceutical interventions (NPIs) that led to severe economic and social impacts. The effect of these intervention measures on the spread of the COVID-19 pandemic are not well investigated within developing country settings. This study simulated the trajectories of the COVID-19 pandemic curve in Jordan between February and May and assessed the effect of Jordan’s strict NPI measures on the spread of COVID-19. A modified susceptible, exposed, infected, and recovered (SEIR) epidemic model was utilized. The compartments in the proposed model categorized the Jordanian population into six deterministic compartments: suspected, exposed, infectious pre-symptomatic, infectious with mild symptoms, infectious with moderate to severe symptoms, and recovered. The GLEAMviz client simulator was used to run the simulation model. Epidemic curves were plotted for estimated COVID-19 cases in the simulation model, and compared against the reported cases. The simulation model estimated the highest number of total daily new COVID-19 cases, in the pre-symptomatic compartmental state, to be 65 cases, with an epidemic curve growing to its peak in 49 days and terminating in a duration of 83 days, and a total simulated cumulative case count of 1048 cases. The curve representing the number of actual reported cases in Jordan showed a good pattern compatibility to that in the mild and moderate to severe compartmental states. The reproduction number under the NPIs was reduced from 5.6 to less than one. NPIs in Jordan seem to be effective in controlling the COVID-19 epidemic and reducing the reproduction rate. Early strict intervention measures showed evidence of containing and suppressing the disease.

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This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare records (EHR). We have utilized supervised ML methods to predict lung cancer inpatients LOS during ICU hospitalization using the MIMIC-III dataset. Random Forest (RF) Model outperformed other models and achieved predicted results during the three framework phases. With clinical significance features selection, over-sampling methods (SMOTE and ADASYN) achieved the highest AUC results (98% with CI 95%: 95.3–100%, and 100% respectively). The combination of Over-sampling and under-sampling achieved the second-highest AUC results (98%, with CI 95%: 95.3–100%, and 97%, CI 95%: 93.7–100% SMOTE-Tomek, and SMOTE-ENN respectively). Under-sampling methods reported the least important AUC results (50%, with CI 95%: 40.2–59.8%) for both (ENN and Tomek- Links). Using ML explainable technique called SHAP, we explained the outcome of the predictive model (RF) with SMOTE class balancing technique to understand the most significant clinical features that contributed to predicting lung cancer LOS with the RF model. Our promising framework allows us to employ ML techniques in-hospital clinical information systems to predict lung cancer admissions into ICU.

Abstract Background: COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed the health services in most affected countries. In response, the governments initiated a series of non-pharmaceutical interventions (NPIs) that led to severe economic and social impacts. The effect of these intervention measures on the spread of the COVID-19 pandemic are not well investigated within developing countries settings. This study simulated the trajectories of COVID-19 epidemic curve Jordan and assessed the effect of Jordan’s strict NPI measures on the spread of COVID-19. Methods: A modified Susceptible, Exposed, Infected, and Recovered (SEIR) epidemic model was utilized. The compartments in the proposed model categorized Jordan population into six deterministic compartments; Suspected, Exposed, Infectious Pre-symptomatic, Infectious with Mild Symptoms, Infectious with Moderate to Severe Symptoms, and Recovered. GLEAMviz client simulator was used to run the simulation model. Epidemic curves were plotted for estimated COVID-19 cases in the simulation model, and compared against the reported cases. Results: The simulation model estimated the highest number of total daily new COVID-19 cases, in the pre-symptomatic compartmental state, to be 65 cases, with an epidemic curve growing to its peak in 49 days and terminating in a duration of 83 days, and a total number of simulated cumulative case count of 1,048 cases. The curve representing the number of actual reported cases in Jordan showed a good pattern compatibility to that in the mild and moderate to severe compartmental states. Reproduction number under the NPIs was reduced from 5.6 to less than one. Conclusion: NPIs in Jordan were effective in controlling the COVID-19 epidemic and reducing the reproduction rate. Early strict intervention measures showed evidence of containing and suppressing the disease.

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We describe an extremely rare case of an intra-articular extraskeletal myxoid chondrosarcoma causing devastating destruction to the ankle joint in a 71-year-old woman, which had been originally excised as a ganglion cyst. Histological analysis of the lesion revealed an extraskeletal myxoid chondrosarcoma. The patient proceeded to curative surgery with a below-the-knee amputation.