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Purpose: The incidence of both primary and revision total knee arthroplasty (TKA) is expected to rise, making early recognition of TKA failure crucial to prevent extensive revision surgeries. This study aims to develop a deep learning (DL) model to predict TKA failure using radiographic images., Methods: Two patient cohorts who underwent primary TKA were retrospectively collected: one was used for the model development and the other for the external validation. Each cohort encompassed failed and non-failed subjects, according to the need for TKA revision surgery. Moreover, for each patient, one anteroposterior and one lateral radiographic view obtained during routine TKA follow-up, were considered. A transfer learning fine-tuning approach was employed. After pre-processing, the images were analyzed using a convolutional neuronal network (CNN) that was originally developed for predicting hip prosthesis failure and was based on the Densenet169 pre-trained on Imagenet. The model was tested on 20% of the images of the first cohort and externally validated on the images of the second cohort. Metrics, such as accuracy, sensitivity, specificity and area under the receiving operating characteristic curve (AUC), were calculated for the final assessment., Results: The trained model correctly classified 108 out of 127 images in the test set, providing a classification accuracy of 0.85, sensitivity of 0.80, specificity of 0.89 and AUC of 0.86. Moreover, the model correctly classified 1547 out of 1937 in the external validation set, providing a balanced accuracy of 0.79, sensitivity of 0.80, specificity of 0.78 and AUC of 0.86., Conclusions: The present DL model predicts TKA failure with moderate accuracy, regardless of the cause of revision surgery. Additionally, the effectiveness of the transfer learning fine-tuning approach, leveraging a previously developed DL model for hip prosthesis failure, has been successfully demonstrated., Level of Evidence: Level III, diagnostic study., Competing Interests: Mattia Loppini declares Research grant as principal investigator (2022YME9N3) from the Italian Ministry of University and Research; Research grant as co‐principal investigator (GR‐2019‐12371158) from the Italian Ministry of Health; Research grants as principal investigator for postmarket study formedical devices from Zimmer Biomet; Financial support for attending symposia and educational programs from Zimmer Biomet; Scientific Director of Fondazione Livio‐Sciutto. Valentina Corino declares Research grant as a co‐prinvipal investigator (2022YME9N3) from the Italian Ministry of University and Research. The remaining authors declare no conflicts of interest., (© 2024 The Author(s). Journal of Experimental Orthopaedics published by John Wiley & Sons Ltd on behalf of European Society of Sports Traumatology, Knee Surgery and Arthroscopy.)

Chronic daily headaches (CDH) consist of episodes of head pain occurring daily; more than 15 days each month; often associated with a history of migraine, with or without aura; or with a history of tension-type headaches occurring alone or both occurring together. Chronic daily headaches are frequently associated with rebound headaches after ergotamine, barbiturate, caffeine, and analgesic abuse. We previously reported that migraineurs with typical intermittent headaches exhibited excessive cerebral cortical vasodilation after oral acetazolamide which usually precipitated and reproduced their typical headaches. In the present study, cerebral vasodilator responses were tested by measuring changes in local cerebral blood flow (Delta LCBF) utilizing xenon-contrasted CT scanning, before and after oral administration of 14.3 mg/kg of acetazolamide, in 11 patients with CDH. The results were compared with 12 age-matched typical migraineurs, with and without aura, who had a history of migraine attacks occurring at intervals of 1 month or longer. Global and subcortical gray and white matter Delta LCBFs were quantitated and compared between both groups. After acetazolamide, Delta LCBF increased in cortical gray matter by 11.8% among patients with CDH and by 16.7% among migraineurs, with no significant differences between groups. Typical migraine attacks were provoked by acetazolamide in 9 patients (82%) with CDH and in 11 (92%) migraineurs with intermittent headaches. These observations are taken as evidence that at least 82% of patients with CDH have transformed migraine as judged by the provocation by acetazolamide of typical migraine attacks associated with excessive Delta LCBF increases. Serotonin agonists should be considered in the treatment of CDH to avoid ergotamine, caffeine, barbiturate, and analgesic abuse.