Novel approaches in the treatment of Hansen's disease (Leprosy): a case series of multidrug therapy of monthly rifampin, moxifloxacin, and minocycline (RMM) in the United States.

The World Health Organization (WHO) recommends multidrug therapy (MDT) for the treatment of paucibacillary and multibacillary forms of leprosy, also known as Hansen's disease (HD). MDT combinations of dapsone, rifampin, and clofazimine have reduced the prevalence of the disease but are not without adverse effects impacting regimen adherence. Hence, an urgent need exists to consider alternative MDT regimens with an improved safety profile that promotes treatment adherence. Herein, we described a case series of 10 patients with HD (nine patients with multibacillary leprosy and one with pure neural leprosy) treated with monthly rifampin, moxifloxacin, and minocycline (RMM). The United States National Hansen's Disease Program (NHDP) diagnosed and treated patients across US institutions. All patients received a regimen of 12-24 months of RMM. We reviewed the clinical outcomes, adherence, rate of completion, and adverse events of patients treated with monthly RMM from January 2019 to August 2022. Nine patients had multibacillary leprosy, with some having type-2 reactions. One patient had pure neural leprosy with a reversal reaction. In this case series, we identified that all patients completed the RMM regimen without treatment interruptions. None of the patients experienced any skin hyperpigmentation or any significant side effects. All patients tolerated the monthly RMM regimen with rapid improvement of skin lesions and without logistic hurdles. Based on previous clinical evidence and the results of this case series, the NHDP and other programs should consider the RMM regimen as first-line therapy.

Development and validation of a laboratory-based risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19.

BACKGROUND: Early identification of patients with COVID-19 who may develop critical illness is of great importance. METHODS: In this study a retrospective cohort of 264 COVID-19 cases admitted at Macarena University was used for development and internal validation of a risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. Backward stepwise logistic regression was used to derive the model, including clinical and laboratory variables predictive of critical illness. Internal validation of the final model used bootstrapped samples and the model scoring derived from the coefficients. External validation was performed in a cohort of 154 cases admitted at Valme and Virgen del Rocio University Hospital. RESULTS: A total of 62 (23.5%) patients developed a critical illness during their hospitalization stay, 21 (8.0%) patients needed invasive ventilation, 34 (12.9%) were admitted at the ICU and the overall mortality was of 14.8% (39 cases). 5 variables were included in the final model: age >59.5 years (OR: 3.11;95%CI 1.39-6.97), abnormal CRP results (OR: 5.76;95%CI 2.32-14.30), abnormal lymphocytes count (OR: 3.252;95%CI 1.56-6.77), abnormal CK results (OR: 3.38;95%CI 1.59-7.20) and abnormal creatinine (OR: 3.30;95%CI 1.42-7.68). The AUC of this model was 0.850 with sensitivity of 65% and specificity of 87% and the IDI and NRI were 0.1744 and 0.2785, respectively. The validation indicated a good discrimination for the external population. CONCLUSIONS: Biomarkers add prognostic information in COVID-19 patients. Our risk-score provides an easy to use tool to identify patients who are likely to develop critical illness during their hospital stay.