Impact of Arrhythmia in Hospital Mortality in Acute Ischemic Stroke Patients: A Retrospective Cohort Study in Northern Mexico.

BACKGROUND: Atrial fibrillation has been associated with higher morbidity and mortality rates in acute ischemic stroke patients (AIS). However, there is scarce information regarding the clinical outcomes and strokes' characteristics among AIS patients with other type of arrhythmias. OBJECTIVE: Our study aims to analyze the hospital mortality rate, stroke characteristics, and clinical and demographical data of patients with any post-stroke arrhythmia. METHODS: Retrospective cohort study of AIS patients with 24h-Holter monitoring during hospital admission recruited between 2015-2020, outcomes were measured using the modified Rankin scale. RESULTS: 597 patients (61.13±13.61 years; 352 men) were included. Arrhythmias were diagnosed in 33 (5.5%), with atrial fibrillation as the most common finding (82%). Age was related to a higher rate of arrhythmia (P = 0.014). A larger prevalence of cardioembolic strokes (69.7% vs 16.6%, P < 0.05) and AIS in the middle cerebral artery's vascular territory (78.8% vs 58.7%, P < 0.05) were found amongst patients with an arrhythmia. No significant association was found between NIHSS at admission with neither incidence of arrhythmia nor mortality. Within the arrhythmia group, three in-hospital deaths were reported: one AF, one ventricular arrhythmia and one second-degree atrioventricular block. In a logistic regression analysis, patients with any kind of arrhythmia had a higher mortality rate (9.1% vs 1.2%, P = 0.011; OR 6.766, 95% CI 1.552 - 29.500). CONCLUSION: Arrhythmia detection after an AIS was associated with increased in-hospital mortality. Risk factors related to arrhythmia detection were a higher mean age, cardioembolic strokes and AIS affecting the middle cerebral artery.

Scipion PKPD: an Open-Source Platform for Biopharmaceutics, Pharmacokinetics and Pharmacodynamics Data Analysis.

PURPOSE: Biopharmaceutics examines the interrelationship of the drug's physical/chemical properties, the dosage form (drug product) in which the drug is given, and the administration route on the rate and extent of sys- temic drug absorption. Pharmacokinetics is the study of the movement of drugs in the body. It uses mathematical models to evaluate the movement of absorption, distribution, metabolism, and excretion (ADME) within an organism. Finally, Pharmacodynamics is the analysis of how these drugs af- fect that organism. Pharmacokinetics data normally comes in samples over time of the drug concentration either in plasma or in some specific tissue. Similarly, pharmacodynamics data comes normally in samples over time of some quantity of interest (biophysical quantity like temperature, blood pres- sure, etc.). The data is submitted to a non-parametric analysis, in which a description of the observed data is reported (e.g., the Area Under the Curve), or to a parametric analysis by fitting a model (normally based on differential equations) so that prediction about future events can be made. This paper aims to introduce Scipion PKPD, an open-source platform for data analysis of this kind in the three domains (Biopharmaceutics, Pharmacokinetics, and Pharmacodynamics). The platform implements the most popular models and is open to new ones. The platform provides almost 100 different high-level operations that we call protocols. METHODS: We have developed a Python module integrated into the work- flow engine Scipion. The plugin implements the numerical analysis and meta- data handling tools to address multiple problems (see Suppl. Material for a detailed list of the tasks solved). RESULTS: We illustrate the use of this package with an integrative exam- ple that involves all these areas. CONCLUSIONS: We show that the package successfully addresses these kinds of analyses. Scipion PKPD is freely available at https://github. com/cossorzano/scipion-pkpd .