Acquired von Willebrand's Syndrome in a Patient with Concomitant Chronic Lymphocytic Lymphoma and Smoldering Multiple Myeloma.

An African-American female in her sixties presented to the hospital with intermittent gum bleeding for the past two years along with severe anemia. This case details the differential and workup that lead to the diagnosis of acquired von Willebrand's syndrome (AvWS). A thorough investigation in the possible etiologies of AvWS revealed that the patient had concomitant chronic lymphocytic lymphoma (CLL) and smoldering multiple myeloma (SMM). Due to the concomitant diagnosis of CLL and SMM, there was a dilemma regarding whether CLL, SMM, or both was driving this patient's AvWS. Decision was made to treat the underlying CLL initially with rituximab and later on at recurrence with obinutuzumab/venetoclax with complete resolution of patient's bleeding and normalization of her factor VIII activity, von Willebrand factor antigen levels, and vWF:ristocetin cofactor levels. We believe this is first case in the literature of a patient with AvWS with concurrent CLL and SMM.

A Simple Scoring Tool to Predict Medical Intensive Care Unit Readmissions Based on Both Patient and Process Factors.

BACKGROUND: Although many predictive models have been developed to risk assess medical intensive care unit (MICU) readmissions, they tend to be cumbersome with complex calculations that are not efficient for a clinician planning a MICU discharge. OBJECTIVE: To develop a simple scoring tool that comprehensively takes into account not only patient factors but also system and process factors in a single model to predict MICU readmissions. DESIGN: Retrospective chart review. PARTICIPANTS: We included all patients admitted to the MICU of Robert Wood Johnson University Hospital, a tertiary care center, between June 2016 and May 2017 except those who were < 18 years of age, pregnant, or planned for hospice care at discharge. MAIN MEASURES: Logistic regression models and a scoring tool for MICU readmissions were developed on a training set of 409 patients, and validated in an independent set of 474 patients. KEY RESULTS: Readmission rate in the training and validation sets were 8.8% and 9.1% respectively. The scoring tool derived from the training dataset included the following variables: MICU admission diagnosis of sepsis, intubation during MICU stay, duration of mechanical ventilation, tracheostomy during MICU stay, non-emergency department admission source to MICU, weekend MICU discharge, and length of stay in the MICU. The area under the curve of the scoring tool on the validation dataset was 0.76 (95% CI, 0.68-0.84), and the model fit the data well (Hosmer-Lemeshow p = 0.644). Readmission rate was 3.95% among cases in the lowest scoring range and 50% in the highest scoring range. CONCLUSION: We developed a simple seven-variable scoring tool that can be used by clinicians at MICU discharge to efficiently assess a patient's risk of MICU readmission. Additionally, this is one of the first studies to show an association between MICU admission diagnosis of sepsis and MICU readmissions.