Background: Public Health interventions to slow the spread of the Covid-19 pandemic focus on protecting individuals at risk for severe disease. Risk categorization is essential to effective pandemic response. However, existing risk models for severe Covid-19 lack needed integration of both socio-demographic and clinical risk factors, and geographic characteristics. Methods: We present an integrated multi-factor risk model for severe Covid-19 using de-identified Medicare claims from which we extracted demographic and clinical data for a cohort of 15 million Medicare beneficiaries with 770,000 Covid-19 cases, and socio-economic data at the county and zip code level from the CDC Social Vulnerability Index. The model and associated digital maps were developed as part of Project Salus of the Department of Defense Joint Artificial Intelligence Center, for use by the National Guard and other military personnel in their support mission to hospitals and local jurisdictions impacted by the pandemic. Results: The model affirms ethnicity (Black: OR 1.64; 95% CI 1.61-1.68, American Indian: OR 2.21; 95% CI 2.01-2.42), age over 85 (OR 1.75, 95% CI 1.69-1.81), the socio-economic factor of residing in a zip code in the lowest quartile of income (OR 1.23; 95% CI 1.21-1.26), ESRD (OR 2.35; 95% CI 2.25-2.45) and chronic lung disease (OR 1.95; 95% CI 1.90-2.00) as leading risk factors for Covid-19 hospitalizations, but reveals low risk for COPD (OR 1.15; 95% CI 1.13 -1.17) and minimal or no risk for diabetes (OR 1.03; CI 1.01-1.05), CHF (OR 1.10, 95% CI 1.08-1.12) or hypertension (OR 0.96; 95% CI 0.94-0.98), and demonstrates an association between prior herpes zoster immunization (OR 0.74; 95% CI 0.71-0.77), and to a lesser degree prior influenza and pneumococcal vaccines with less severe Covid-19. Conclusions: This multi-factor risk model and derived digital maps can be applied for use by national and local health authorities to augment existing tools for pandemic response, including monitoring of post Covid-19 sequelae, prioritization of Covid-19 vaccine, and vaccine monitoring for both safety and efficacy.

Background: Patellar instability is a common orthopedic condition in the pediatric population. Many factors contribute to patellar instability, including trochlear dysplasia. However, patellar instability and its treatments are not well documented in the literature for patients with osteogenesis imperfecta. Case Report: After medial patellofemoral ligament (MPFL) reconstruction, a 17-year-old male with osteogenesis imperfecta had a patellar dislocation that resulted in a patellar fracture. The patient subsequently had a revision of his MPFL reconstruction, and at 2½ years postoperation has had no episodes of recurrent patellar instability. Conclusion: The combination of bone fragility, trochlear dysplasia, and strength of the allograft used for MPFL reconstruction compared to the patient's bone strength led to dislocation and patellar fracture. Research into alternative methods for patellar fixation and postoperative physical therapy protocols for patients with osteogenesis imperfecta is needed. Special considerations must be made for this patient population.

Catfish have the ability to inflict stings on their victims through spines located on their dorsal and pectoral fins. The stings of catfish can release toxins that have dermonecrotic, edemogenic, and vasospastic factors. In this case, a 56-year-old man suffered a catfish sting to his right thumb, which resulted in acute hand compartment syndrome and resultant hand fasciotomies. His hospital course was complicated by multiple irrigation and debridements, finger amputations, hand fluid cultures positive for Vibrio damsela, and eventual wrist disarticulation. The combination of envenomation, infection, and delayed presentation for treatment ultimately led to a hand amputation.