Publications by authors named "S S Koenders"

Objectives: Evidence on the optimal frequency of laboratory testing during outpatient parenteral antimicrobial therapy (OPAT) is lacking. Therefore, we investigated how often and when laboratory abnormalities occur during OPAT and which factors are associated with these abnormalities.

Methods: We performed a multicenter cohort study in four Dutch hospitals among adult patients receiving OPAT and collected routinely obtained laboratory test results.

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While the epidemiological literature recognizes associations between chronic non-cancer pain (CNCP), opioid use disorder (OUD), and interpersonal trauma stemming from physical, emotional, sexual abuse or neglect, the complex etiologies and interplay between interpersonal and structural traumas in CNCP populations are underexamined. Research has documented the relationship between experiencing multiple adverse childhood experiences (ACEs) and the likelihood of developing an OUD as an adult. However, the ACEs framework is criticized for failing to name the social and structural contexts that shape ACE vulnerabilities in families.

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Background: Clinicians' bias related to patients' race and substance use history play a role in pain management. However, patients' or clinicians' understandings about discriminatory practices and the structural factors that contribute to and exacerbate these practices are underexamined. We report on perceptions of discrimination from the perspectives of patients with chronic non-cancer pain (CNCP) and a history of substance use and their clinicians within the structural landscape of reductions in opioid prescribing in the United States.

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Introduction: Our aim was to estimate the probability of obstructive CAD (oCAD) for an individual patient as a function of the myocardial flow reserve (MFR) measured with Rubidium-82 (Rb-82) PET in patients with a visually normal or abnormal scan.

Materials And Methods: We included 1519 consecutive patients without a prior history of CAD referred for rest-stress Rb-82 PET/CT. All images were visually assessed by two experts and classified as normal or abnormal.

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Introduction: Accurate risk stratification in patients with suspected stable coronary artery disease is essential for choosing an appropriate treatment strategy. Our aim was to develop and validate a machine learning (ML) based model to diagnose obstructive CAD (oCAD).

Method: We retrospectively have included 1007 patients without a prior history of CAD who underwent CT-based calcium scoring (CACS) and a Rubidium-82 PET scan.

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