TRIM37 controls cancer-specific vulnerability to PLK4 inhibition.

Centrosomes catalyse the formation of microtubules needed to assemble the mitotic spindle apparatus1. Centrosomes themselves duplicate once per cell cycle, in a process that is controlled by the serine/threonine protein kinase PLK4 (refs. 2,3). When PLK4 is chemically inhibited, cell division proceeds without centrosome duplication, generating centrosome-less cells that exhibit delayed, acentrosomal spindle assembly4. Whether PLK4 inhibitors can be leveraged as a treatment for cancer is not yet clear. Here we show that acentrosomal spindle assembly following PLK4 inhibition depends on levels of the centrosomal ubiquitin ligase TRIM37. Low TRIM37 levels accelerate acentrosomal spindle assembly and improve proliferation following PLK4 inhibition, whereas high TRIM37 levels inhibit acentrosomal spindle assembly, leading to mitotic failure and cessation of proliferation. The Chr17q region containing the TRIM37 gene is frequently amplified in neuroblastoma and in breast cancer5-8, rendering these cancer types highly sensitive to PLK4 inhibition. We find that inactivating TRIM37 improves acentrosomal mitosis because TRIM37 prevents PLK4 from self-assembling into centrosome-independent condensates that serve as ectopic microtubule-organizing centres. By contrast, elevated TRIM37 expression inhibits acentrosomal spindle assembly through a distinct mechanism that involves degradation of the centrosomal component CEP192. Thus, TRIM37 is an essential determinant of mitotic vulnerability to PLK4 inhibition. Linkage of TRIM37 to prevalent cancer-associated genomic changes-including 17q gain in neuroblastoma and 17q23 amplification in breast cancer-may offer an opportunity to use PLK4 inhibition to trigger selective mitotic failure and provide new avenues to treatments for these cancers.

Sudden cardiac death after myocardial infarction: individual participant data from pooled cohorts.

BACKGROUND AND AIMS: Risk stratification of sudden cardiac death after myocardial infarction and prevention by defibrillator rely on left ventricular ejection fraction (LVEF). Improved risk stratification across the whole LVEF range is required for decision-making on defibrillator implantation. METHODS: The analysis pooled 20 data sets with 140 204 post-myocardial infarction patients containing information on demographics, medical history, clinical characteristics, biomarkers, electrocardiography, echocardiography, and cardiac magnetic resonance imaging. Separate analyses were performed in patients (i) carrying a primary prevention cardioverter-defibrillator with LVEF ≤ 35% [implantable cardioverter-defibrillator (ICD) patients], (ii) without cardioverter-defibrillator with LVEF ≤ 35% (non-ICD patients ≤ 35%), and (iii) without cardioverter-defibrillator with LVEF > 35% (non-ICD patients >35%). Primary outcome was sudden cardiac death or, in defibrillator carriers, appropriate defibrillator therapy. Using a competing risk framework and systematic internal-external cross-validation, a model using LVEF only, a multivariable flexible parametric survival model, and a multivariable random forest survival model were developed and externally validated. Predictive performance was assessed by random effect meta-analysis. RESULTS: There were 1326 primary outcomes in 7543 ICD patients, 1193 in 25 058 non-ICD patients ≤35%, and 1567 in 107 603 non-ICD patients >35% during mean follow-up of 30.0, 46.5, and 57.6 months, respectively. In these three subgroups, LVEF poorly predicted sudden cardiac death (c-statistics between 0.50 and 0.56). Considering additional parameters did not improve calibration and discrimination, and model generalizability was poor. CONCLUSIONS: More accurate risk stratification for sudden cardiac death and identification of low-risk individuals with severely reduced LVEF or of high-risk individuals with preserved LVEF was not feasible, neither using LVEF nor using other predictors.

Factors associated with long-term opioid use among patients with axial spondyloarthritis or psoriatic arthritis who initiated opioids.

OBJECTIVE: Up to one in five patients with axial spondyloarthritis (AxSpA) or psoriatic arthritis (PsA) newly initiated on opioids transition to long-term use within the first year. This study aimed to investigate individual factors associated with long-term opioid use among opioid new users with AxSpA/PsA. METHODS: Adult patients with AxSpA/PsA and without prior cancer who initiated opioids between 2006-2021 were included from Clinical Practice Research Datalink Gold, a national UK primary care database. Long-term opioid use was defined as having ≥3 opioid prescriptions issued within 90 days, or ≥ 90 days of opioid supply, in the first year of follow-up. Individual factors assessed included sociodemographic, lifestyle factors, medication use and comorbidities. A mixed-effects logistic regression model with patient-level random intercept was used to examine the association of individual characteristics with the odds of long-term opioid use. RESULTS: In total 10 300 opioid initiations were identified from 8,212 patients (3037 AxSpA; 5175 PsA). The following factors were associated with long-term opioid use: being a current smoker (OR : 1.62; 95%CI : 1.38,1.90), substance use disorder (OR : 2.34, 95%CI : 1.05,5.21), history of suicide/self-harm (OR : 1.84; 95%CI : 1.13,2.99), co-existing fibromyalgia (OR : 1.62; 95%CI : 1.11,2.37), higher Charlson Comorbidity Index (OR : 3.61; 95%CI : 1.69,7.71 for high scores), high MME/day at initiation (OR : 1.03; 95%CI : 1.02,1.03) and gabapentinoid (OR : 2.35; 95%CI : 1.75,3.16) and antidepressant use (OR : 1.69; 95%CI : 1.45,1.98). CONCLUSIONS: In AxSpA/PsA patients requiring pain relief, awareness of lifestyle, sociodemographic and prescribing characteristics associated with higher risk of long-term opioid use can prompt timely interventions such as structured medication reviews and smoking cessation to promote safer prescribing and better patient outcomes.

Trends for opioid prescribing and the impact of the COVID-19 pandemic in patients with rheumatic and musculoskeletal diseases between 2006 and 2021.

OBJECTIVE: To investigate opioid prescribing trends and assess the impact of the COVID-19 pandemic on opioid prescribing in rheumatic and musculoskeletal diseases (RMDs). METHODS: Adult patients with RA, PsA, axial spondyloarthritis (AxSpA), SLE, OA and FM with opioid prescriptions between 1 January 2006 and 31 August 2021 without cancer in UK primary care were included. Age- and gender-standardized yearly rates of new and prevalent opioid users were calculated between 2006 and 2021. For prevalent users, monthly measures of mean morphine milligram equivalents (MME)/day were calculated between 2006 and 2021. To assess the impact of the pandemic, we fitted regression models to the monthly number of prevalent opioid users between January 2015 and August 2021. The time coefficient reflects the trend pre-pandemic and the interaction term coefficient represents the change in the trend during the pandemic. RESULTS: The study included 1 313 519 RMD patients. New opioid users for RA, PsA and FM increased from 2.6, 1.0 and 3.4/10 000 persons in 2006 to 4.5, 1.8 and 8.7, respectively, in 2018 or 2019. This was followed by a fall to 2.4, 1.2 and 5.9, respectively, in 2021. Prevalent opioid users for all RMDs increased from 2006 but plateaued or dropped beyond 2018, with a 4.5-fold increase in FM between 2006 and 2021. In this period, MME/day increased for all RMDs, with the highest for FM (≥35). During COVID-19 lockdowns, RA, PsA and FM showed significant changes in the trend of prevalent opioid users. The trend for FM increased pre-pandemic and started decreasing during the pandemic. CONCLUSION: The plateauing or decreasing trend of opioid users for RMDs after 2018 may reflect the efforts to tackle rising opioid prescribing in the UK. The pandemic led to fewer people on opioids for most RMDs, providing reassurance that there was no sudden increase in opioid prescribing during the pandemic.

Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data.

BACKGROUND: Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data. METHODS: 2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups. RESULTS: Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF. CONCLUSIONS: Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

Dasatinib does not exacerbate dexamethasone-induced osteonecrosis in murine models of acute lymphoblastic leukemia therapy.

INTRODUCTION: There are clinical reports that the incorporation of dasatinib may increase the frequency of osteonecrosis in acute lymphoblastic leukemia (ALL) treatment regimens. No rigorous testing of this hypothesis is available to guide clinicians. METHODS: We tested whether oral dasatinib increased the frequency of dexamethasone-induced osteonecrosis in a murine model and tested its effects on dexamethasone's antileukemic efficacy in a murine BCR-ABL+ model of ALL. RESULTS: Dasatinib did not change the frequency of osteonecrosis (p = .99) nor of arteriopathy (p = .36) in dexamethasone-treated mice when given at dosages that achieved clinically relevant steady-state dasatinib plasma concentrations of 53.1 ng/ml (95% CI: 43.5-57.3 ng/ml). These dasatinib exposures were not associated with increased dexamethasone plasma exposure in nonleukemia-bearing mice. These same dosages were not associated with any decrement in antileukemic efficacy of dexamethasone in a responsive BCR-ABL+ model of ALL. CONCLUSIONS: Based on the results of our preclinical murine studies, we conclude that dasatinib is unlikely to increase the osteonecrotic effects of dexamethasone in ALL regimens.

Fenofibrate reduces osteonecrosis without affecting antileukemic efficacy in dexamethasone-treated mice.

Recent clinical trials in children with acute lymphoblastic leukemia (ALL) indicate that severe hypertriglyceridemia (> 1000 mg/dL) during therapy is associated with increased frequency of symptomatic osteonecrosis. Interventions to lower triglycerides have been considered, but there have been no pre-clinical studies investigating impact of lowering triglycerides on osteonecrosis risk, nor whether such interventions interfere with the antileukemic efficacy of ALL treatment. We utilized our clinically relevant mouse model of dexamethasone-induced osteonecrosis to determine if fenofibrate decreased osteonecrosis. To test whether fenofibrate affected the antileukemic efficacy of dexamethasone, we utilized a BCR-ABL+ model of ALL. Serum triglycerides were reduced with fenofibrate throughout treatment, with the most pronounced 4.5-fold decrease at week 3 (p<1x10-6). Both frequency (33% versus 74%, p=0.006) and severity (median necrosis score of 0 versus 75; p=6x10-5) of osteonecrosis were reduced with fenofibrate. Fenofibrate had no impact on BCR-ABL+ ALL survival (p=0.65) nor on the antileukemic properties of dexamethasone (p=0.49). These data suggest that lowering triglycerides with fenofibrate reduces dexamethasone-induced osteonecrosis while maintaining antileukemic efficacy, and thus may be considered for clinical trials.

Methods for the inclusion of real-world evidence in network meta-analysis.

BACKGROUND: Network Meta-Analysis (NMA) is a key component of submissions to reimbursement agencies world-wide, especially when there is limited direct head-to-head evidence for multiple technologies from randomised controlled trials (RCTs). Many NMAs include only data from RCTs. However, real-world evidence (RWE) is also becoming widely recognised as a valuable source of clinical data. This study aims to investigate methods for the inclusion of RWE in NMA and its impact on the level of uncertainty around the effectiveness estimates, with particular interest in effectiveness of fingolimod. METHODS: A range of methods for inclusion of RWE in evidence synthesis were investigated by applying them to an illustrative example in relapsing remitting multiple sclerosis (RRMS). A literature search to identify RCTs and RWE evaluating treatments in RRMS was conducted. To assess the impact of inclusion of RWE on the effectiveness estimates, Bayesian hierarchical and adapted power prior models were applied. The effect of the inclusion of RWE was investigated by varying the degree of down weighting of this part of evidence by the use of a power prior. RESULTS: Whilst the inclusion of the RWE led to an increase in the level of uncertainty surrounding effect estimates in this example, this depended on the method of inclusion adopted for the RWE. 'Power prior' NMA model resulted in stable effect estimates for fingolimod yet increasing the width of the credible intervals with increasing weight given to RWE data. The hierarchical NMA models were effective in allowing for heterogeneity between study designs, however, this also increased the level of uncertainty. CONCLUSION: The 'power prior' method for the inclusion of RWE in NMAs indicates that the degree to which RWE is taken into account can have a significant impact on the overall level of uncertainty. The hierarchical modelling approach further allowed for accommodating differences between study types. Consequently, further work investigating both empirical evidence for biases associated with individual RWE studies and methods of elicitation from experts on the extent of such biases is warranted.

Effects of zoledronic acid on osteonecrosis and acute lymphoblastic leukemia treatment efficacy in preclinical models.

BACKGROUND: Osteonecrosis is a devastating side effect of acute lymphoblastic leukemia (ALL) therapy. Associations between bone density loss and osteonecrosis have sparked interest in using bisphosphonates to reduce this complication. PROCEDURE: We assessed the impact of zoledronic acid (ZA) on the development of osteonecrosis in murine models when used either throughout therapy (continuous administration) or late in therapy after vascular lesions have developed but before osteonecrosis has occurred. Effects on bone density were measured using microcomputed tomography (µCT)-assessed tibial cortical thickness, while osteonecrosis was assessed histologically in the distal femur. Effects on antileukemic efficacy of chemotherapy were evaluated in both immunocompetent/syngeneic and patient-derived xenograft (PDX) models. RESULTS: Continuous administration of ZA with chemotherapy prevented chemotherapy-associated bone loss (p < .001) and reduced osteonecrosis (p = .048). Late initiation of ZA diminished bone loss (p < .001) but had no impact on the development of osteonecrosis (p = .93). In the immunocompetent murine ALL model, mice treated with ZA and chemotherapy succumbed to leukemia sooner than mice treated with chemotherapy alone (p = .046). Analysis using PDX showed a nonsignificant decrease in survival with ZA (p = .17). CONCLUSION: Our data indicate ZA may prevent osteonecrosis if begun with chemotherapy but showed no benefit when administered later in therapy. However, ZA may also reduce the antileukemic efficacy of chemotherapy.

Potential prognostic factors for delayed healing of common, non-traumatic skin ulcers: A scoping review.

Healing of non-traumatic skin ulcers is often suboptimal. Prognostic tools that identify people at high risk of delayed healing within the context of routine ulcer assessments may improve this, but robust evidence on which factors to include is lacking. Therefore, we scoped the literature to identify which potentially prognostic factors may warrant future systematic reviews and meta-analyses. We conducted electronic searches in MEDLINE and Embase to identify studies in English published between 1997 and 2017 that tested the association between healing of the three most common non-traumatic skin ulcers encountered by health care professionals (venous leg, diabetic foot, and pressure ulcers) and patient characteristics, ulcer characteristics, and results from clinical investigations. We included 42 studies that investigated factors which may be associated with the healing of venous leg ulcers (n = 17), diabetic foot ulcers (n = 15), and pressure ulcers (n = 10). Across ulcer types, ulcer characteristics were most commonly reported as potential prognostic factors for healing (n = 37), including the size of the ulcer area (n = 29) and ulcer duration at first assessment (n = 16). A total of 35 studies investigated the prognostic value of patient characteristics (n = 35), including age (n = 31), gender (n = 30), diabetes (n = 22), smoking status (n = 15), and history of deep vein thrombosis (DVT) (n = 13). Of these studies, 23 reported results from clinical investigations as potential prognostic factors, with the majority regarding vessel quality. Age, gender, diabetes, smoking status, history of DVT, ulcer area, and ulcer duration at time of first assessment warrant a systematic review and meta-analysis to quantify their prognostic value for delayed ulcer healing.

Transforming Students' Attitudes and Anxieties Toward Death and Loss: The Role of Prior Death Experiences.

This study examines the impact of a death and dying course on 39 undergraduate students' attitudes and anxieties about death. Authors outline key aspects of the curriculum used in the course and discuss how the approach lends itself to a transformative learning experience related to death and loss, preparing students who will face clients with a variety of needs in these areas across practice settings. The majority of students ( n = 34) experienced a decrease in death avoidance, fear of death, and overall death anxiety. Students with a history of multiple violent, traumatic, or unexpected deaths ( n = 5) did not experience any significant changes but demonstrated increased scores of death anxiety suggesting that they may be in need of greater support while engaging in death education.

Diaphorina citri (Hemiptera: Liviidae) Abundance in Puerto Rico Declines with Elevation.

Diaphorina citri Kuwayama is the primary vector of Huanglongbing, the most devastating disease of citrus. D. citri populations in Puerto Rico were monitored with yellow sticky traps on citrus trees or other psyllid host plants at different elevations, ranging from 10 to 880 m above sea level. Trapping was conducted in March through May of 2013 and 2014 when psyllid populations usually are highest. Population levels of D. citri, based on the trapping data, varied among the sites, and there was a strong trend in both years for decreasing psyllid abundance with increased elevation based on the number of psyllids captured on traps and the proportion of trees shown to be infested. No psyllids were collected at an elevation of >600 m. Reduced populations at higher elevations could be a consequence of differences in temperature, air pressure, oxygen levels, ultraviolet light, or other factors alone or in combination. We discuss our results as they pertain to management of D. citri and Huanglongbing.

Attraction of Pollinators to Atemoya (Annona squamosa × Annona cherimola) in Puerto Rico Using Commercial Lures and Food Attractants.

Atemoya is a hybrid between Annona squamosa L. and Annona cherimola Miller (Annonaceae) and has potential to be an important fruit crop in tropical and subtropical areas. A major impediment to fruit production is low fruit set due to inadequate pollinator visits, typically, by beetles in the family Nitidulidae. We used Universal moth traps to monitor the attractiveness of two commercially available Nitidulidae lures in combination with various food attractants, including raw bread dough, apple juice, and malta beverage, a soft drink by-product of the brewing process. The most commonly trapped beetles were, in order of decreasing frequency, Carpophilus dimidiatus (F.), Brachypeplus mutilatus Erichson, Urophorus humeralis (F.) (Coleoptera: Nitidulidae), and Europs fervidus Blatchley (Coleoptera: Monotomidae). All traps, except the unbaited control traps, caught beetles. In a previous study, we found that combining two commercial lures had a synergistic effect on the attraction of these beetle species. In this study, the addition of food attractants increased the number of beetles trapped compared with traps baited with only the commercial lures. Also, food attractants appear to be key in attracting U. humeralis; only one U. humeralis individual of the 206 caught during the experiment was trapped without a food attractant. The variation between the number of beetles caught in traps containing the same treatments was high and may explain the erratic results reported in other studies of pollination in Annona spp. The results are discussed with respect to the use of nitidulid lures and food attractants to increase fruit set in atemoya and other Annonaceae.

Development and internal validation of prehospital prediction models for identifying intracerebral haemorrhage in suspected stroke patients.

Introduction: Distinguishing patients with intracerebral haemorrhage (ICH) from other suspected stroke cases in the prehospital setting is crucial for determining the appropriate level of care and minimising the onset-to-treatment time, thereby potentially improving outcomes. Therefore, we developed prehospital prediction models to identify patients with ICH among suspected stroke cases. Methods: Data were obtained from the Field Administration of Stroke Therapy-Magnesium prehospital stroke trial, where paramedics evaluated multiple variables in suspected stroke cases within the first 2 hours from the last known well time. A total of 19 candidate predictors were included to minimise overfitting and were subsequently refined through the backward exclusion of non-significant predictors. We used logistic regression and eXtreme Gradient Boosting (XGBoost) models to evaluate the performance of the predictors. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), confusion matrix metrics and calibration measures. Additionally, models were internally validated and corrected for optimism through bootstrapping. Furthermore, a nomogram was built to facilitate paramedics in estimating the probability of ICH. Results: We analysed 1649 suspected stroke cases, of which 373 (23%) were finally diagnosed with ICH. From the 19 candidate predictors, 9 were identified as independently associated with ICH (p<0.05). Male sex, arm weakness, worsening neurological status and high systolic blood pressure were positively associated with ICH. Conversely, a history of hyperlipidaemia, atrial fibrillation, coronary artery disease, ischaemic stroke and improving neurological status were associated with other diagnoses. Both logistic regression and XGBoost demonstrated good calibration and predictive performance, with optimism-corrected sensitivities ranging from 47% to 49%, specificities from 89% to 90% and AUCs from 0.796 to 0.801. Conclusions: Our models demonstrate good predictive performance in distinguishing patients with ICH from other diagnoses, making them potentially useful tools for prehospital ICH management.

The prevalence of long COVID in people with diabetes mellitus-evidence from a UK cohort.

Background: It was apparent from the early phase of the SARS-CoV-2 virus (COVID-19) pandemic that a multi-system syndrome can develop in the weeks following a COVID-19 infection, now referred to as Long COVID. Given that people living with diabetes are at increased risk of hospital admission/poor outcomes following COVID-19 infection we hypothesised that they may also be more susceptible to developing Long COVID. We describe here the prevalence of Long COVID in people living with diabetes when compared to matched controls in a Northwest UK population. Methods: This was a retrospective cohort study of people who had a recorded diagnosis of type 1 diabetes (T1D) or type 2 diabetes (T2D) who were alive on 1st January 2020 and who had a proven COVID-19 infection. We used electronic health record data from the Greater Manchester Care Record collected from 1st January 2020 to 16th September 2023, we determined the prevalence of Long COVID in people with T1D and T2D vs matched individuals without diabetes (non-DM). Findings: There were 3087 T1D individuals with 14,077 non-diabetes controls and 3087 T2D individuals with 14,077 non-diabetes controls and 29,700 T2D individuals vs 119,951 controls. For T1D, there was a lower proportion of Long COVID diagnosis and/or referral to a Long COVID service at 0.33% vs 0.48% for matched controls. The prevalence of Long COVID In T2D individuals was 0.53% vs 1:3 matched controls 0.54%. For T2D, there were differences by sex in the prevalence of Long COVID in comparison with 1:3 matched controls. For Long COVID between males with T2D and their matched controls, the prevalence was lower in matched controls at 0.46%.vs 0.54% (0.008). When considering the prevalence of LC between females with T2D and their matched controls, the prevalence was higher in matched controls at 0.61% vs 0.53% (0.007). The prevalence of Long COVID in males with T2D vs females was not different. T2D patients at older vs younger age were at reduced risk of developing Long COVID (OR 0.994 [95% CI) [0.989, 0.999]). For females there was a minor increase of risk (OR 1.179, 95% CI [1.002, 1.387]). Presence of a higher body mass index (BMI) was also associated an increased risk of developing Long COVID (OR 1.013, 95% CI [1.001, 1.026]). The estimated general population prevalence of Long COVID based on general practice coding (not self-reported) of this diagnosis was 0.5% of people with a prior acute COVID-19 diagnosis. Interpretation: Recorded Long COVID was more prevalent in men with T2D than in matched non-T2D controls with the opposite seen for T2D women, with recorded Long COVID rates being similar for T2D men and women. Younger age, female sex and higher BMI were all associated with a greater likelihood of developing Long COVID when taken as individual variables. There remains an imperative for continuing awareness of Long COVID as a differential diagnosis for multi-system symptomatic presentation in the context of a previous acute COVID-19 infection. Funding: The time of co-author RW was supported by the NIHR Applied Research Collaboration Greater Manchester (NIHR200174) and the NIHR Manchester Biomedical Research Centre (NIHR203308).

Machine learning identifies risk factors associated with long-term opioid use in fibromyalgia patients newly initiated on an opioid.

OBJECTIVES: Fibromyalgia is frequently treated with opioids due to limited therapeutic options. Long-term opioid use is associated with several adverse outcomes. Identifying factors associated with long-term opioid use is the first step in developing targeted interventions. The aim of this study was to evaluate risk factors in fibromyalgia patients newly initiated on opioids using machine learning. METHODS: A retrospective cohort study was conducted using a nationally representative primary care dataset from the UK, from the Clinical Research Practice Datalink. Fibromyalgia patients without prior cancer who were new opioid users were included. Logistic regression, a random forest model and Boruta feature selection were used to identify risk factors related to long-term opioid use. Adjusted ORs (aORs) and feature importance scores were calculated to gauge the strength of these associations. RESULTS: In this study, 28 552 fibromyalgia patients initiating opioids were identified of which 7369 patients (26%) had long-term opioid use. High initial opioid dose (aOR: 31.96, mean decrease accuracy (MDA) 135), history of self-harm (aOR: 2.01, MDA 44), obesity (aOR: 2.43, MDA 36), high deprivation (aOR: 2.00, MDA 31) and substance use disorder (aOR: 2.08, MDA 25) were the factors most strongly associated with long-term use. CONCLUSIONS: High dose of initial opioid prescription, a history of self-harm, obesity, high deprivation, substance use disorder and age were associated with long-term opioid use. This study underscores the importance of recognising these individual risk factors in fibromyalgia patients to better navigate the complexities of opioid use and facilitate patient-centred care.

Comparing Predictive Performance of Time Invariant and Time Variant Clinical Prediction Models in Cardiac Surgery.

Clinical prediction models are increasingly used across healthcare to support clinical decision making. Existing methods and models are time-invariant and thus ignore the changes in populations and healthcare practice that occur over time. We aimed to compare the performance of time-invariant with time-variant models in UK National Adult Cardiac Surgery Audit data from Manchester University NHS Foundation Trust between 2009 and 2019. Data from 2009-2011 were used for initial model fitting, and data from 2012-2019 for validation and updating. We fitted four models to the data: a time-invariant logistic regression model (not updated), a logistic model which was updated every year and validated it in each subsequent year, a logistic regression model where the intercept is a function of calendar time (not updated), and a continually updating Bayesian logistic model which was updated with each new observation and continuously validated. We report predictive performance over the complete validation cohort and for each year in the validation data. Over the complete validation data, the Bayesian model had the best predictive performance.

Associations of the glycaemic index and the glycaemic load with risk of type 2 diabetes in 127 594 people from 20 countries (PURE): a prospective cohort study.

BACKGROUND: The association between the glycaemic index and the glycaemic load with type 2 diabetes incidence is controversial. We aimed to evaluate this association in an international cohort with diverse glycaemic index and glycaemic load diets. METHODS: The PURE study is a prospective cohort study of 127 594 adults aged 35-70 years from 20 high-income, middle-income, and low-income countries. Diet was assessed at baseline using country-specific validated food frequency questionnaires. The glycaemic index and the glycaemic load were estimated on the basis of the intake of seven categories of carbohydrate-containing foods. Participants were categorised into quintiles of glycaemic index and glycaemic load. The primary outcome was incident type 2 diabetes. Multivariable Cox Frailty models with random intercepts for study centre were used to calculate hazard ratios (HRs). FINDINGS: During a median follow-up of 11·8 years (IQR 9·0-13·0), 7326 (5·7%) incident cases of type 2 diabetes occurred. In multivariable adjusted analyses, a diet with a higher glycaemic index was significantly associated with a higher risk of diabetes (quintile 5 vs quintile 1; HR 1·15 [95% CI 1·03-1·29]). Participants in the highest quintile of the glycaemic load had a higher risk of incident type 2 diabetes compared with those in the lowest quintile (HR 1·21, 95% CI 1·06-1·37). The glycaemic index was more strongly associated with diabetes among individuals with a higher BMI (quintile 5 vs quintile 1; HR 1·23 [95% CI 1·08-1·41]) than those with a lower BMI (quintile 5 vs quintile 1; 1·10 [0·87-1·39]; p interaction=0·030). INTERPRETATION: Diets with a high glycaemic index and a high glycaemic load were associated with a higher risk of incident type 2 diabetes in a multinational cohort spanning five continents. Our findings suggest that consuming low glycaemic index and low glycaemic load diets might prevent the development of type 2 diabetes. FUNDING: Full funding sources are listed at the end of the Article.

Attraction of pollinators to atemoya (Magnoliales: Annonaceae) in Puerto Rico: a synergistic approach using multiple nitidulid lures.

Atemoya, a hybrid between Annona squamosa (L.) and A. cherimola Miller (Annonaceae), has potential to be a major fruit crop in tropical and subtropical areas. A major setback to fruit production throughout the world is low fruit-set because of inadequate pollinator visits, typically Nitidulidae beetles. We identified beetle visitors to atemoya flowers in an orchard in Puerto Rico and used Universal moth traps to monitor the attractiveness of two commercially available Nitidulidae lures. The most common visitors to atemoya flowers were an unidentified Europs species (Coleoptera: Monotomidae), followed by Loberus testaceus (Coleoptera: Erotylidae), neither of which have been previously reported as visitors to Annona flowers. The commercial lures attracted few or no beetles when used separately, but attracted a large number of beetles, especially Carpophilus dimidiatus (Coleoptera: Nitidulidae) and Europs, when used in combination. This attraction is synergistic and increases with dose at the doses assayed (0-4 lures), and decreases over time with >50% of trap captures occurring in the first week and no beetles collected after 5 wk. This is the first report of aggregation pheromone lures in nitidulids acting synergistically to attract other species, including beetles not in the Nitidulidae. The results are discussed as they pertain to increasing fruit set, as well as the potential for altering fruit size and shape in atemoya.