Background: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burden of morbidity and mortality. Existing rule-based systems for prevention of such errors are unsuccessful and associated with substantial burden of false alerts. Objective: In this prospective study, we evaluated the accuracy, validity, and clinical usefulness of medication error alerts generated by a novel system using outlier detection screening algorithms, used on top of a legacy standard system, in a real-life inpatient setting. Materials and Methods: We integrated a novel outlier system into an existing electronic medical record system, in a single medical ward in a tertiary medical center. The system monitored all drug prescriptions written during 16 months. The department’s staff assessed all alerts for accuracy, clinical validity, and usefulness. We recorded all physician’s real-time responses to alerts generated. Results: The alert burden generated by the system was low, with alerts generated for 0.4% of all medication orders. Sixty percent of the alerts were flagged after the medication was already dispensed following changes in patients’ status which necessitated medication changes (eg, changes in vital signs). Eighty-five percent of the alerts were confirmed clinically valid, and 80% were considered clinically useful. Forty-three percent of the alerts caused changes in subsequent medical orders. Conclusion: A clinical decision support system that used a probabilistic, machine-learning approach based on statistically derived outliers to detect medication errors generated clinically useful alerts. The system had high accuracy, low alert burden and low false-positive rate, and led to changes in subsequent orders.

Neutrophil-to-lymphocyte ratio (NLR) is an easy-to-use inflammatory biomarker. Baseline NLR is independently associated with incident cardiovascular events and all-cause mortality. However, whether this applies to acute myocarditis (AM) has not been evaluated. The present study aimed to investigate the prognostic value of NLR in patients with AM. A total of 1,150 consecutive patients with a diagnosis of AM admitted to 10 international tertiary referral cardiac centers were included in the study. The diagnosis was confirmed using cardiac magnetic resonance or endomyocardial biopsy. The primary outcome measure was a composite of all-cause mortality or heart transplantation. Patients were divided into 2 groups according to an NLR cutoff of 4 derived from spline regression analysis and 70:30 train-test split algorithm. Patients with an NLR <4 were younger and more likely to present with chest pain, and those with an NLR ≥4 were more likely to present with breathlessness and have other comorbidities. Over a median follow-up of 228 weeks, a NLR ≥4 was associated with a worse prognosis (P < 0.0001). After adjustment for prognostic variables, NLR emerged as an independent predictor of outcome (HR: 3.03 [95% CI: 1.30-7.04]; P = 0.010). Elevated NLR remained associated with worse outcomes among patients with preserved ejection fraction at baseline, who are conventionally considered to be at lower risk of adverse events (P < 0.0001). In patients with AM, elevated NLR is associated with worse prognosis and may be valuable for stratifying patients, even those conventionally considered at low risk.

Sarcopenia and frailty are causes for morbidity and mortality amongst heart failure (HF) patients. Low alanine transaminase (ALT) is a marker for these syndromes and, therefore, could serve as a biomarker for the prognostication of HF patients. We performed a retrospective analysis of all consecutive hospitalized HF patients in our institute in order to find out whether low ALT values would be a biomarker for poor outcomes. Our cohort included 11,102 patients, 35.6% categorized as heart failure with reduced ejection fraction. We excluded patients with ALT > 40 IU/L and cirrhosis. 8700 patients were followed for a median duration of 22 months and included in a univariate analysis. Patients with ALT < 10 IU/L were older (mean age 78.6 vs. 81.8, p < 0.001), had past stroke (24.6% vs. 19.6%, p < 0.001), dementia (7.7% vs. 4.6%, p < 0.001), and malignancy (13.4% vs. 10.2%, p = 0.003). Hospitalization length was longer in the low-ALT group (4 vs. 3 days, p < 0.001), and the rate of acute kidney injury during hospitalization was higher (19.1% vs. 15.6%; p = 0.006). The in-hospital mortality rate was higher in the low-ALT group (6.5% vs. 3.9%; p < 0.001). Long-term mortality was also higher (73.3% vs. 61.5%; p < 0.001). In a multivariate regression analysis, ALT < 10 IU/L had a 1.22 hazard ratio for mortality throughout the follow-up period (CI = 1.09–1.36; p < 0.001). Low ALT plasma level, a biomarker for sarcopenia and frailty, can assist clinicians in prognostic stratification of heart failure patients.

Myocarditis is an inflammatory disease of the myocardium characterized by a great heterogeneity of presentation and evolution. Treatment of myocarditis is often supportive, and the evidence for immunosuppression is scarce and debated. Conventional treatment is based on clinical presentation, ranging from conservative to advanced mechanical assist devices. In this setting, immunosuppression and immunomodulation therapies are mostly reserved for patients presenting with major clinical syndromes. In this review, we will summarize the current evidence and strategies for conventional and immunosuppressive treatments for patients presenting with acute myocarditis.