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Purpose: To determine the accuracy of nursing diagnoses at hospital admission and discharge for patients with heart failure (HF).

Methods: This comparative study examined the documentation in 155 medical records of patients with an admitting diagnosis of HF during August 2018 and July 2019. An audit tool was used to record the diagnoses made by nurses during routine care at the time of admission and discharge.

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Background Endoscopic dilatation is the cornerstone therapy for esophageal strictures. The primary indication for dilatation is to provide immediate and durable symptomatic relief from dysphagia. Following esophageal dilatation, the two most common major consequences are bleeding and perforation, both of which are quite rare.

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Background: Despite guideline recommendations, few institutions have implemented clinical pathways that incorporate frailty into routine decision-making for patients undergoing radical cystectomy (RC). This paper presents an integrated clinical pathway designed to address the needs of frail patients undergoing RC. The purpose of the study is to determine whether a multifaceted prevention programme that tailors interventions to the syndromic components of frailty can improve postoperative morbidity and recovery time for patients.

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Despite mounting evidence of a robust relation between discrimination and poor pain outcomes in people of color (POC) with chronic pain, little is known about everyday discrimination's role in increasing the risk of opioid misuse and its potential interactive effects. This study aimed to evaluate the potential moderating effect of everyday discrimination on the relationship between chronic pain severity and the risk of opioid misuse among POC with chronic pain. Everyday discrimination was assessed using the 9-item Everyday Discrimination Scale (EDS), while the risk of opioid misuse was measured with the 14-item Screener and Opioid Assessment for Patients with Pain (SOAPP).

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Mixture Markov Model (MMM) is a widely used tool to cluster sequences of events coming from a finite state-space. However, the MMM likelihood being multi-modal, the challenge remains in its maximization. Although Expectation-Maximization (EM) algorithm remains one of the most popular ways to estimate the MMM parameters, however, convergence of EM algorithm is not always guaranteed.

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