Knee osteoarthritis prognostic tools often target structural progression or surgery and require imaging or biomarker inputs that are not routinely available. Using Osteoarthritis Initiative data, we developed a fully clinical nomogram to estimate both the probability of long-term pain non-resilience (clinically important worsening) and, by complement, maintenance of acceptable pain in radiographic knee osteoarthritis. We included participants with radiographic knee osteoarthritis and complete worst-knee WOMAC pain scores at baseline, 24 and 48 months; non-resilience was defined as a ≥9-point increase on the 0–100 WOMAC pain scale over 4 years. A six-predictor Firth logistic regression model (age, body mass index, Kellgren–Lawrence grade, baseline pain, 0–24-month pain change and Center for Epidemiologic Studies Depression Scale score) was fitted and translated into a point-based nomogram. Among 2365 eligible participants, 527 (22.3%) were non-resilient. The model showed good performance, with optimism-corrected AUC 0.74 and Brier score 0.15, and decision-curve analysis indicated positive net benefit versus treat-none across 1–15% thresholds and small gains versus treat-all. Early pain worsening and higher depressive symptoms were the strongest predictors of non-resilience. This six-variable, clinic-ready nomogram provides a simple, well-calibrated tool for prognostic counseling and risk stratification in radiographic knee osteoarthritis and requires external validation before wider clinical use.

Introduction: Knee osteoarthritis is heterogeneous in radiographic severity, pain, and multimorbidity, and racial disparities in pain and knee replacement are documented. We derived knee osteoarthritis phenotypes from electronic health record and radiograph data and assessed their associations with race and incident total knee arthroplasty. Methods: We conducted a retrospective cohort study in the Emory Knee Radiograph dataset of adults aged ≥40 years with knee osteoarthritis (n = 33,553). Among participants with pain scores within ±90 days of the index radiograph (n = 20,030), we applied k-means clustering to features including age, radiographic severity, pain measures, and comorbidity indicators to define phenotypes. Among participants without pre-index strict total knee arthroplasty, we used Cox proportional hazards models to evaluate time to incident post-index strict total knee arthroplasty, with follow-up censored at last observed contact and capped at the procedure-code ascertainment horizon. Results: Clustering identified three phenotypes: structural/metabolic disease characterized by radiographic severity and multimorbidity; younger trauma-associated mild disease; and pain-dominant disease with pain disproportionate to radiographic severity. Black individuals were overrepresented in the pain-dominant phenotype and underrepresented in the structural/metabolic phenotype, whereas White individuals showed the opposite pattern. In time-to-event models, higher radiographic severity and male sex were associated with faster time to total knee arthroplasty, whereas the younger trauma-associated and pain-dominant phenotypes were associated with lower hazard of total knee arthroplasty than the structural/metabolic phenotype. These findings were preserved in known-race-only and categorical Kellgren–Lawrence grade sensitivity analyses. Discussion: Routinely available electronic health record and radiographic data can identify clinically meaningful knee osteoarthritis phenotypes that differ by race and are independently associated with subsequent total knee arthroplasty. These findings support further validation of phenotype-aware approaches to studying disparities and guiding osteoarthritis care.

Background: Knee osteoarthritis (OA) is a major cause of pain and disability, yet baseline radiographic severity grading provides only modest prediction of structural progression. We evaluated whether structured MRI-derived MOAKS features improve prediction of full-grade medial joint space narrowing (JSN) progression, and whether deep multimodal fusion adds value beyond structured feature models. Methods: We performed a patient-independent internal-validation study using the Osteoarthritis Initiative. Full-grade medial joint-space-narrowing (JSN) progression was defined as an increase of at least one grade between baseline and fixed 48-month central radiographic readings from the same longitudinal reading project. The final analytic cohort included 2,899 knees from 2,392 participants, partitioned at the participant level into training, validation, and held-out test sets of 2,050, 421, and 428 knees. We compared a radiographic baseline model (RBM), raw-MOAKS model (RMO), structured MRI/radiographic model (SMR), and radiograph-plus-MOAKS ResNet50 fusion model (XMF). AUPRC was primary; uncertainty was estimated with 2,000 patient-cluster bootstrap replicates. Results: Progression prevalence was 10.0%. On the held-out test set (40 progressor knees), AUPRC/AUROC were 0.220 (95% CI 0.142–0.331)/0.748 (0.663–0.827) for RBM, 0.412 (0.260–0.576)/0.805 (0.726–0.878) for RMO, 0.345 (0.219–0.507)/0.801 (0.725–0.871) for SMR, and 0.301 (0.191–0.464)/0.768 (0.679–0.852) for XMF. Compared with RBM, AUPRC increased by 0.192 (0.087–0.313) for RMO and 0.125 (0.042–0.233) for SMR; the corresponding AUROC differences were 0.057 (−0.012 to 0.123) and 0.053 (0.004–0.105). XMF did not improve on SMR in AUPRC or AUROC (differences −0.044 [−0.135 to 0.060] and −0.033 [−0.092 to 0.018], respectively). A stronger clinical-radiographic comparator achieved AUPRC/AUROC 0.251/0.759, increasing to 0.355/0.813 after adding MOAKS. Conclusion: Baseline MOAKS features provided prognostic information beyond radiographic or clinical-radiographic severity for fixed 48-month medial JSN progression. In this selected MOAKS-scored cohort, adding a baseline-radiograph ResNet50 encoder did not improve discrimination over the structured models. The finite number of test events, selected MOAKS availability, calibration requirements, and lack of external validation preclude claims of clinical readiness.

Purpura fulminans (PF) is a rare, life-threatening emergency characterized by rapidly progressive purpura evolving into hemorrhagic bullae and skin necrosis due to dermal microvascular thrombosis, typically accompanied by shock and disseminated intravascular coagulation (DIC). We report two fatal adult cases of infection-associated PF caused by Streptococcus pyogenes (group A streptococcus). Both patients presented with early gastrointestinal symptoms and rapidly developed septic shock, severe coagulopathy compatible with overt DIC, and extensive lower-limb purpura with bullae and necrosis. Pathogen identification was supported by next-generation sequencing from blood and/or tissue specimens. Management required immediate resuscitation, organ support, targeted anti–group A streptococcal therapy, and surgical source control; nevertheless, both patients deteriorated with refractory multiorgan failure. These cases highlight that gastrointestinal symptoms may precede fulminant invasive S. pyogenes infection with PF and streptococcal toxic shock syndrome overlap. Early recognition of the clinical pattern (shock + rapidly progressive purpura/bullae + DIC) and aggressive multidisciplinary management are essential.