Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

La Petite presse : journal quotidien... / [rédacteur en chef : Balathier Bragelonne]

30 septembre 18681868/09/30 (A3,N895)

A novel mechanism for variable phenotypic expressivity in Mendelian diseases uncovered by an AU-rich element (ARE)-creating mutation

Abstract Background Variable expressivity is a well-known phenomenon in which patients with mutations in one gene display varying degrees of clinical severity, potentially displaying only subsets of the clinical manifestations associated with the multisystem disorder linked to the gene. This remains an incompletely understood phenomenon with proposed mechanisms ranging from allele-specific to stochastic. Results We report three consanguineous families in which an isolated ocular phenotype is linked to a novel 3′ UTR mutation in SLC4A4, a gene known to be mutated in a syndromic form of intellectual disability with renal and ocular involvement. Although SLC4A4 is normally devoid of AU-rich elements (AREs), a 3′ UTR motif that mediates post-transcriptional control of a subset of genes, the mutation we describe creates a functional ARE. We observe a marked reduction in the transcript level of SLC4A4 in patient cells. Experimental confirmation of the ARE-creating mutation is shown using a post-transcriptional reporter system that reveals consistent reduction in the mRNA-half life and reporter activity. Moreover, the neo-ARE binds and responds to the zinc finger protein ZFP36/TTP, an ARE-mRNA decay-promoting protein. Conclusions This novel mutational mechanism for a Mendelian disease expands the potential mechanisms that underlie variable phenotypic expressivity in humans to also include 3′ UTR mutations with tissue-specific pathology

Understanding Managers’ Attitudes and Behavioral Intentions towards Using Artificial Intelligence for Organizational Decision-Making

While using artificial intelligence (AI) could improve organizational decision-making, it also creates challenges associated with the “dark side” of AI. However, there is a lack of research on managers’ attitudes and intentions to use AI for decision making. To address this gap, we develop an integrated AI acceptance-avoidance model (IAAAM) to consider both the positive and negative factors that collectively influence managers’ attitudes and behavioral intentions towards using AI. The research model is tested through a large-scale questionnaire survey of 269 UK business managers. Our findings suggest that IAAAM provides a more comprehensive model for explaining and predicting managers’ attitudes and behavioral intentions towards using AI. Our research contributes conceptually and empirically to the emerging literature on using AI for organizational decision-making. Further, regarding the practical implications of using AI for organizational decision-making, we highlight the importance of developing favorable facilitating conditions, having an effective mechanism to alleviate managers’ personal concerns, and having a balanced consideration of both the benefits and the dark side associated with using AI