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

A systematic review of the quality and fit of local spirometry studies to the Global Lung Initiative (GLI) and global chronic respiratory disease burden

Early diagnosis and treatment are vital to combatting the global rise in chronic respiratory diseases (CRD). Spirometry can reliably support a CRD diagnosis when reference equations (RE) represent the target population. Multi-ethnic representation in Global Lung Initiative (GLI) RE has been a significant advance. However, the GLI lacks data from many global population groups, thus its diagnostic sensitivity may be reduced in local or ethnically diverse populations. We aimed to analyse global trends in PFT studies comparing the applicability (fit) of GLI RE to local populations and their geospatial relationships with CRD burden. A systematic search was conducted using PubMed® and Medline. In the resulting 46 studies, the fit of each local population’s normative PFT data (relative to GLI) was determined using standardized criterion (mean Z-score=0 & -1.64 & <+1.64) and article quality was evaluated using a modified GRADE criterion. Geospatial relationships were modelled in R statistics. Only 56% of reviewed studies met the applicability criterion and 60% rated low or very low in quality. Evidence of acculturation (post migration) was found in 18% and evidence of longitudinal changes in 31% of studies. A geospatial mismatch was found between CRD burden and the normative data used to construct the GLI RE. We demonstrate a compelling need for normative spirometry data targeted to populations which are both underrepresented in the GLI and have the highest CRD burden. Improved quality in future studies could be facilitated with the adoption of a standardised protocol for normative PFT data collection and analysis

Predicting opioid consumption after surgical discharge: a multinational derivation and validation study using a foundation model

Opioids are frequently overprescribed after surgery. We applied a tabular foundation model to predict the risk of post-discharge opioid consumption. The model was trained and internally validated on an 80:20 training/test split of the ‘Opioid PrEscRiptions and usage After Surgery’ (ACTRN12621001451897p) study cohort, including adult patients undergoing general, orthopaedic, gynaecological and urological operations (n = 4267), with external validation in a distinct cohort of patients discharged after general surgical procedures (n = 826). The area under the receiver operator curve was 0.84 (95% confidence interval [CI] 0.81–0.88) at internal testing and 0.77 (95% CI 0.74–0.80) at external validation. Brier scores were 0.13 (95% CI 0.12–0.14) and 0.19 (95% CI 0.17–0.2). Patients with a <50% predicted risk of opioid consumption consumed a median of 0 oral morphine equivalents in the first week after surgery. Applying this model would reduce opioid prescriptions by 4.5% globally, and counterfactual modelling suggests without increasing time in severe pain (−4.3%, 95% CI −17.7 to 8.6)