Predictive models are indeed useful for causal inference.

The subject of investigating causation in ecology has been widely discussed in recent years, especially by advocates of a structural causal model (SCM) approach. Some of these advocates have criticized the use of predictive models and model selection for drawing inferences about causation. We argue that the comparison of model-based predictions with observations is a key step in hypothetico-deductive (H-D) science and remains a valid approach for assessing causation.

Integrating Patient-Generated Health Data from Mobile Devices into Electronic Health Records: Best Practice Recommendations by the IFCC Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MHBLM).

Background: An increasing number of wearable medical devices are being used for personal monitoring and professional health care purposes. These mobile health devices collect a variety of biometric and health data but do not routinely connect to a patient's electronic health record (EHR) or electronic medical record (EMR) for access by a patient's health care team.

Methods: The International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Committee on Mobile Health and Bioengineering in Laboratory Medicine (C-MHBLM) developed consensus recommendations for consideration when interfacing mobile health devices to an EHR/EMR.

Neurological Insights: Transient Unilateral Relative Afferent Pupillary Defect in the Context of Serotonin Syndrome.

The pupillary reflex is a complex physiological response involving both the eye and associated neural pathways. Relative afferent pupillary defects (RAPDs) can present due to various underlying pathologies, yet their occurrence in serotonin syndrome has been rarely documented. This report details the case of a 21-year-old non-binary individual with a history of bipolar disorder who presented to the emergency department following a polypharmacy overdose, including significant ingestion of sertraline, aripiprazole, and buspirone.

Investigating Older Adults' Perceptions of AI Tools for Medication Decisions: Vignette-Based Experimental Survey.

Background: Given the public release of large language models, research is needed to explore whether older adults would be receptive to personalized medication advice given by artificial intelligence (AI) tools.

Objective: This study aims to identify predictors of the likelihood of older adults stopping a medication and the influence of the source of the information.

Methods: We conducted a web-based experimental survey in which US participants aged ≥65 years were asked to report their likelihood of stopping a medication based on the source of information using a 6-point Likert scale (scale anchors: 1=not at all likely; 6=extremely likely).

Comparative study of two Rift Valley fever virus field strains originating from Mauritania.

Rift Valley fever (RVF) is one of the major viral arthropod-borne diseases in Africa. In recent decades, RVF virus (RVFV), the causative agent of RVF, has been responsible for multiple outbreaks in West Africa with important consequences on human and animal health. In particular, an outbreak occurred in 2010 after heavy rains in the desertic region of Adrar, Mauritania.