Interobserver Agreement and Performance of Concurrent AI Assistance for Radiographic Evaluation of Knee Osteoarthritis.

Background Due to conflicting findings in the literature, there are concerns about a lack of objectivity in grading knee osteoarthritis (KOA) on radiographs. Purpose To examine how artificial intelligence (AI) assistance affects the performance and interobserver agreement of radiologists and orthopedists of various experience levels when evaluating KOA on radiographs according to the established Kellgren-Lawrence (KL) grading system. Materials and Methods In this retrospective observer performance study, consecutive standing knee radiographs from patients with suspected KOA were collected from three participating European centers between April 2019 and May 2022. Each center recruited four readers across radiology and orthopedic surgery at in-training and board-certified experience levels. KL grading (KL-0 = no KOA, KL-4 = severe KOA) on the frontal view was assessed by readers with and without assistance from a commercial AI tool. The majority vote of three musculoskeletal radiology consultants established the reference standard. The ordinal receiver operating characteristic method was used to estimate grading performance. Light kappa was used to estimate interrater agreement, and bootstrapped t statistics were used to compare groups. Results Seventy-five studies were included from each center, totaling 225 studies (mean patient age, 55 years ± 15 [SD]; 113 female patients). The KL grades were KL-0, 24.0% (n = 54); KL-1, 28.0% (n = 63); KL-2, 21.8% (n = 49); KL-3, 18.7% (n = 42); and KL-4, 7.6% (n = 17). Eleven readers completed their readings. Three of the six junior readers showed higher KL grading performance with versus without AI assistance (area under the receiver operating characteristic curve, 0.81 ± 0.017 [SEM] vs 0.88 ± 0.011 [P < .001]; 0.76 ± 0.018 vs 0.86 ± 0.013 [P < .001]; and 0.89 ± 0.011 vs 0.91 ± 0.009 [P = .008]). Interobserver agreement for KL grading among all readers was higher with versus without AI assistance (κ = 0.77 ± 0.018 [SEM] vs 0.85 ± 0.013; P < .001). Board-certified radiologists achieved almost perfect agreement for KL grading when assisted by AI (κ = 0.90 ± 0.01), which was higher than that achieved by the reference readers independently (κ = 0.84 ± 0.017; P = .01). Conclusion AI assistance increased junior readers' radiographic KOA grading performance and increased interobserver agreement for osteoarthritis grading across all readers and experience levels. Published under a CC BY 4.0 license. Supplemental material is available for this article.

Does closed incision negative wound pressure therapy in non-traumatic major lower-extremity amputations improve survival rates?

Closed incision negative pressure wound therapy (CINPWT) has been shown to be clinically effective compared with the traditional gauze dressing, reducing surgical site infections and wound complications. We evaluated the effect of CINPWT compared with gauze dressing on the need for revision surgery and survival after non-traumatic major lower amputation. We included 309 patients undergoing 403 major lower amputations in a retrospective study from January 1, 2010 to November 23, 2017. A total of 139 patients received CINPWT, and 170 patients received stump bandage. There was no statistically significant difference between the two groups regarding the need for revision surgery (P = .45). Fourteen stump bandage patients and 15 CINPWT patients died in hospital (P = .57). One year after amputation, 55 CINPWT patients and 66 stump bandage patients had died (P = .82). Survival probabilities adjusted for age and gender 2 years after amputation were .52 (.43-.61) and .49 (.42-.58), respectively, and 3 years after amputation were .36 (.25-.50) and .39 (.32-.47), respectively. We also found no significant difference in the need for revision surgery in survival probabilities up till 3 years after amputation between patients treated with CINPWT and patients treated with gauze bandage postoperatively.