Patient Heterogeneity and the J-Curve Relationship Between Time-to-Antibiotics and the Outcomes of Patients Admitted With Bacterial Infection.

Objectives: Sepsis remains a leading and preventable cause of hospital utilization and mortality in the United States. Despite updated guidelines, the optimal definition of sepsis as well as optimal timing of bundled treatment remain uncertain. Identifying patients with infection who benefit from early treatment is a necessary step for tailored interventions.

min-SIA: a Lightweight Algorithm to Predict the Risk of 6-Month Mortality at the Time of Hospital Admission.

Background: Predicting death in a cohort of clinically diverse, multi-condition hospitalized patients is difficult. This frequently hinders timely serious illness care conversations. Prognostic models that can determine 6-month death risk at the time of hospital admission can improve access to serious illness care conversations.

Diagnostic Discordance, Health Information Exchange, and Inter-Hospital Transfer Outcomes: a Population Study.

Background: Studying diagnostic error at the population level requires an understanding of how diagnoses change over time.

Objective: To use inter-hospital transfers to examine the frequency and impact of changes in diagnosis on patient risk, and whether health information exchange can improve patient safety by enhancing diagnostic accuracy.

Design: Diagnosis coding before and after hospital transfer was merged with responses from the American Hospital Association Annual Survey for a cohort of patients transferred between hospitals to identify predictors of mortality.

Can serum Procalcitonin aid in the diagnosis of blood stream infection in patients on immunosuppressive medications?

Background: Patients on immunosuppressive medications may not exhibit the systemic inflammatory response syndrome (SIRS) in the setting of bacterial infection. Our study examines the relationship between serum PCT levels and the odds of manifesting SIRS and BSI in patients on immunosuppressive medications and examines whether this relationship is altered from patients who are not on these medications. The diagnostic performance of Procalcitonin (PCT) detecting BSI in patients on immunosuppressive agents is compared to that in non-immunosuppressed patients.

Development and Validation of Machine Learning Models for Prediction of 1-Year Mortality Utilizing Electronic Medical Record Data Available at the End of Hospitalization in Multicondition Patients: a Proof-of-Concept Study.

Background: Predicting death in a cohort of clinically diverse, multicondition hospitalized patients is difficult. Prognostic models that use electronic medical record (EMR) data to determine 1-year death risk can improve end-of-life planning and risk adjustment for research.

Objective: Determine if the final set of demographic, vital sign, and laboratory data from a hospitalization can be used to accurately quantify 1-year mortality risk.

Clinical and Sociocultural Factors Associated With Failure to Escalate Care of Deteriorating Patients.

In-hospital medical emergencies occur frequently. Understanding how clinicians respond to deteriorating patients outside the intensive care unit (ICU) could improve "rescue" interventions and rapid response programs. This was a qualitative study with interviews with 40 clinicians caring for patients who had a "Code Blue" activation or an unplanned ICU admission at teaching hospitals over 7 months.

Does serum procalcitonin aid in the diagnosis of bloodstream infection regardless of whether patients exhibit the systemic inflammatory response syndrome?

Background: Physicians frequently rely on the systemic inflammatory response syndrome (SIRS) criteria to detect bloodstream infections (BSIs). We evaluated the diagnostic performance of procalcitonin (PCT) in detecting BSI in patients with and without SIRS.

Methods: We tested the association between BSI, serum PCT levels, contemporaneous SIRS scores and serum lactate using logistic regression in a dataset of 4279 patients.

Extreme Hyperferritinemia: Causes and Impact on Diagnostic Reasoning.

Objectives: Hyperferritinemia can be a result of inflammation, infection, chronic iron overload, or other uncommon pathologies including hemophagocytic lymphohistiocytosis (HLH). There is a historical association between extreme hyperferritinemia and HLH, but in reality HLH is associated with a minority of hyperferritinemic states.

Methods: We identified conditions most associated with hyperferritinemia by identifying 65,536 serum ferritin levels at the University of Minnesota Hospital over a five-year period, with 86 values higher than 10,000 ng/mL.