Machine learning models in predicting graft survival in kidney transplantation: meta-analysis.

BACKGROUND: The variations in outcome and frequent occurrence of kidney allograft failure continue to pose important clinical and research challenges despite recent advances in kidney transplantation. The aim of this systematic review was to examine the current application of machine learning models in kidney transplantation and perform a meta-analysis of these models in the prediction of graft survival. METHODS: This review was registered with the PROSPERO database (CRD42021247469) and all peer-reviewed original articles that reported machine learning model-based prediction of graft survival were included. Quality assessment was performed by the criteria defined by Qiao and risk-of-bias assessment was performed using the PROBAST tool. The diagnostic performance of the meta-analysis was assessed by a meta-analysis of the area under the receiver operating characteristic curve and a hierarchical summary receiver operating characteristic plot. RESULTS: A total of 31 studies met the inclusion criteria for the review and 27 studies were included in the meta-analysis. Twenty-nine different machine learning models were used to predict graft survival in the included studies. Nine studies compared the predictive performance of machine learning models with traditional regression methods. Five studies had a high risk of bias and three studies had an unclear risk of bias. The area under the hierarchical summary receiver operating characteristic curve was 0.82 and the summary sensitivity and specificity of machine learning-based models were 0.81 (95 per cent c.i. 0.76 to 0.86) and 0.81 (95 per cent c.i. 0.74 to 0.86) respectively for the overall model. The diagnostic odds ratio for the overall model was 18.24 (95 per cent c.i. 11.00 to 30.16) and 29.27 (95 per cent c.i. 13.22 to 44.46) based on the sensitivity analyses. CONCLUSION: Prediction models using machine learning methods may improve the prediction of outcomes after kidney transplantation by the integration of the vast amounts of non-linear data.

Comparison of the bite force and occlusal contact area of the deviated and non-deviated sides after intraoral vertical ramus osteotomy in skeletal Class III patients with mandibular asymmetry: Two-year follow-up.

Objective: The objectives of this study were to compare the time-dependent changes in occlusal contact area (OCA) and bite force (BF) of the deviated and non-deviated sides in mandibular prognathic patients with mandibular asymmetry before and after orthognathic surgery and investigate the factors associated with the changes in OCA and BF on each side. Methods: The sample consisted of 67 patients (33 men and 34 women; age range 15-36 years) with facial asymmetry who underwent 2-jaw orthognathic surgery. OCA and BF were taken before presurgical orthodontic treatment, within 1 month before surgery, and 1 month, 3 months, 6 months, 1 year, and 2 years after surgery. OCA and BF were measured using the Dental Prescale System. Results: The OCA and BF decreased gradually before surgery and increased after surgery on both sides. The OCA and BF were significantly greater on the deviated side than on the non-deviated side before surgery, and there was no difference after surgery. According to the linear mixed-effect model, only the changes in the mandibular plane angle had a significant effect on BF (p < 0.05). Conclusions: There was a difference in the amount of the OCA and BF between the deviated and non-deviated sides before surgery. The change in mandibular plane angle affects the change, especially on the non-deviated side, during the observation period.

Combination of ectopic pancreas and intestinal malrotation presenting as non-specific right iliac fossa pain in a SARS-CoV-2 positive patient.

We describe the case of a 31-year-old man who presented with a 3-day history of right iliac fossa pain with associated nausea and vomiting. He denied any previous incidents of abdominal pain and had no relevant medical history or family history to note. Given the typical history, examination findings of localised peritonism and infection risk, he was taken to theatre for laparoscopic appendicectomy without diagnostic imaging. Intraoperatively, we noted gut malrotation and an inflammatory jejunal mass which was resected after converting to a mini-laparotomy. The inflammatory mass was reported to be an ectopic pancreatic tissue from histology. Given that this patient had tested positive for SARS-CoV-2 on admission, we propose a possible case of SARS-CoV-2 infection triggering inflammation of the ectopic pancreatic tissue.