Musculoskeletal complaint epidemiology in Australian special operation forces trainees

Intorduction: Elite military trainees are burdened by high numbers of musculoskeletal (MSK) injuries and are a priority military population for injury prevention. This research aims to describe the MSK complaint epidemiology of trainees undertaking special forces (SF) training in the Australian Defence Force (ADF). One barrier to accurate injury surveillance in military populations is that traditional surveillance methods rely on personnel engaging with the military healthcare system to collect injury data. This approach is likely to underestimate the injury burden as it is known that many military personnel, particularly trainees, avoid reporting their injuries because of various motives. Subsequently, the insights from surveillance systems may underestimate the injury burden and limit the ability to inform prevention requirements. This research aims to actively seek MSK complaint information directly from trainees in a sensitive manner to mediate injury-reporting behaviors. Materials and Methods: This descriptive epidemiology study included two consecutive cohorts of ADF SF trainees from 2019 to 2021. Musculoskeletal data items and their respective recording methods were based on international sports injury surveillance guidelines and adapted to a military context. Our case definition encompassed all injuries or physical discomforts as recordable cases. A unit-embedded physiotherapist retrospectively collected MSK complaint data from selection courses and collected prospective data over the training continuum. Data collection processes were external to the military health care system to mediate reporting avoidance and encourage injury reporting. Injury proportions, complaint incidence rates, and incidence rate ratios were calculated and compared between training courses and cohorts. Results: In total, 334 MSK complaints were reported by 103 trainees (90.4%), with a complaint incidence rate of 58.9 per 1,000 training weeks (95% CI, 53.0-65.5). Of these MSK complaints, 6.4% (n = 22) resulted in time loss from work. The lumbar spine (20.6%, n = 71) and the knee (18.9%, n = 65) were the most frequently affected body parts. Most of the MSK complaints were reported during selection courses (41.9%), followed by field survival and team tactics (23.0%) and urban operations courses (21.9%). Physical training accounted for 16.5% of complaints. Fast-roping training was associated with more severe MSK complaints. Conclusions: Musculoskeletal complaints are highly prevalent in ADF SF trainees. Complaints are more frequently reported in selection and qualification training courses than in physical training. These activities are priorities for focused research to understand injury circumstances in ADF elite training programs to inform injury prevention strategies. A strength of our study is the data collection methods which have provided greater MSK complaint information than past research; however, much work remains in conducting consistent and accurate surveillance. Another strength is the use of an embedded physiotherapist to overcome injury-reporting avoidance. Embedded health professionals are recommended as continued practice for ongoing surveillance and early intervention

Are You AI Ready? Investigating AI Tools in Higher Education via the Co-development of Interdisciplinary Student-Partnered AI Training Resources

[EN] This study explores the integration of Artificial Intelligence (AI) in higher education, focusing on its implications for teaching and learning. With AI tools rapidly gaining traction, the research emphasises the necessity of developing proficient AI literacy skills among faculty and students. Employing focus groups and thematic network analysis, the study uncovers faculty and student perspectives on AI’s role in education, with both groups recognising its potential to positively impact all aspects of higher education, while also emphasising concerns about credibility and reliability of AI tool outputs, potential for bias, impact on academic integrity and assessment, as well as concerns about inclusivity. A significant outcome is the development of an AI capabilities matrix, tailored to align with the DigComp 2.2: The Digital Competence Framework for Citizens. Overall, it contributes to the discourse on AI's integration in higher education, setting a foundation for integration and further research on this topic.   Daly, O.; Fogarty, L.; Furlong, E.; Vasquez Del Aguila, E.; Farrell, R.; Morton, S.; Woods, A.... (2024). Are You AI Ready? Investigating AI Tools in Higher Education via the Co-development of Interdisciplinary Student-Partnered AI Training Resources. Editorial Universitat Politècnica de València. https://doi.org/10.4995/HEAd24.2024.1710

Changing use of antidiabetic drugs in the UK: trends in prescribing 2000-2017.

OBJECTIVES: Guidelines for the use of drugs for type 2 diabetes mellitus (T2DM) have changed since 2000, and new classes of drug have been introduced. Our aim was to describe how drug choice at initiation and first stage of intensification have changed over this period, and to what extent prescribing was in accord with clinical guidelines, including adherence to recommendations regarding kidney function. DESIGN: Repeated cross-sectional study. SETTING: UK electronic primary care health records from the Clinical Practice Research Datalink. PARTICIPANTS: Adults initiating treatment with a drug for T2DM between January 2000 and July 2017. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcomes were the proportion of each class of T2DM drug prescribed for initiation and first-stage intensification in each year. We also examined drug prescribing by kidney function and country within the UK. RESULTS: Of 280 241 people initiating treatment with T2DM drugs from 2000 to 2017, 73% (204 238/280 241) initiated metformin, 15% (42 288/280 241) a sulfonylurea, 5% (12 956/280 241) with metformin and sulfonylurea dual therapy and 7% (20 759/280 241) started other options. Clinicians have increasingly prescribed metformin at initiation: by 2017 this was 89% (2475/2778) of drug initiations. Among people with an estimated glomerular filtration rate of ≤30 mL/min/1.73 m2, the most common drug at initiation was a sulfonylurea, 58% (659/1135). In 2000, sulfonylureas were the predominant drug at the first stage of drug intensification (87%, 534/615) but by 2017 this fell to 30% (355/1183) as the use of newer drug classes increased. In 2017, new prescriptions for dipeptidyl peptidase-4 inhibitors (DPP4i) and sodium/glucose cotransporter-2 inhibitors (SGLT2i) accounted for 42% (502/1183) and 22% (256/1183) of intensification drugs, respectively. Uptake of new classes differs by country with DPP4is and SGLT2is prescribed more in Northern Ireland and Wales than England or Scotland. CONCLUSIONS: Our findings show markedly changing prescribing patterns for T2DM between 2000 and 2017, largely consistent with clinical guidelines

Comparative effects of sulphonylureas, dipeptidyl peptidase-4 inhibitors and sodium-glucose co-transporter-2 inhibitors added to metformin monotherapy: a propensity-score matched cohort study in UK primary care.

AIM: To assess the comparative effects of sodium-glucose co-transporter-2 (SGLT2) inhibitors, sulphonylureas (SUs) and dipeptidyl peptidase-4 (DPP-4) inhibitors on cardiometabolic risk factors in routine care. MATERIALS AND METHODS: Using primary care data on 10?631 new users of SUs, SGLT2 inhibitors or DPP-4 inhibitors added to metformin, obtained from the UK Clinical Practice Research Datalink, we created propensity-score matched cohorts and used linear mixed models to describe changes in glycated haemoglobin (HbA1c), estimated glomerular filtration rate (eGFR), systolic blood pressure (BP) and body mass index (BMI) over 96?weeks. RESULTS: HbA1c levels fell substantially after treatment intensification for all drugs: mean change at week 12: SGLT2 inhibitors: -15.2?mmol/mol (95% confidence interval [CI] -16.9, -13.5); SUs: -14.3?mmol/mol (95% CI -15.5, -13.2); and DPP-4 inhibitors: -11.9?mmol/mol (95% CI -13.1, -10.6). Systolic BP fell for SGLT2 inhibitor users throughout follow-up, but not for DPP-4 inhibitor or SU users: mean change at week 12: SGLT2 inhibitors: -2.3?mmHg (95% CI -3.8, -0.8); SUs: -0.8?mmHg (95% CI -1.9, +0.4); and DPP-4 inhibitors: -0.9?mmHg (95% CI -2.1,+0.2). BMI decreased for SGLT2 inhibitor and DPP-4 inhibitor users, but not SU users: mean change at week 12: SGLT2 inhibitors: -0.7?kg/m2 (95% CI -0.9, -0.5); SUs: 0.0?kg/m2 (95% CI -0.3, +0.2); and DPP-4 inhibitors: -0.3?kg/m2 (95% CI -0.5, -0.1). eGFR fell at 12?weeks for SGLT2 inhibitor and DPP-4 inhibitor users. At 60?weeks, the fall in eGFR from baseline was similar for each drug class. CONCLUSIONS: In routine care, SGLT2 inhibitors had greater effects on cardiometabolic risk factors than SUs. Routine care data closely replicated the effects of diabetes drugs on physiological variables measured in clinical trials

Factors associated with choice of intensification treatment for type 2 diabetes after metformin monotherapy: a cohort study in UK primary care.

PURPOSE: To understand the patient characteristics associated with treatment choice at the first treatment intensification for type 2 diabetes. PATIENTS AND METHODS: This is a noninterventional study, using UK electronic primary care records from the Clinical Practice Research Datalink. We included adults treated with metformin monotherapy between January 2000 and July 2017. The outcome of interest was the drug prescribed at first intensification between 2014 and 2017. We used multinomial logistic regression to calculate the ORs for associations between the drugs and patient characteristics. RESULTS: In total, 14,146 people started treatment with an intensification drug. Younger people were substantially more likely to be prescribed sodium-glucose co-transporter-2 inhibitors (SGLT2is), than sulfonylureas (SUs): OR for SGLT2i prescription for those aged <30 years was 2.47 (95% CI 1.39-4.39) compared with those aged 60-70 years. Both overweight and obesity were associated with greater odds of being prescribed dipeptidyl peptidase-4 inhibitor (DPP4i) or SGLT2i. People of non-white ethnicity were less likely to be prescribed SGLT2i or DPP4i: compared with white patients, the OR of being prescribed SGLT2i among South Asians is 0.60 (95% CI 0.42-0.85), and for black people, the OR is 0.54 (95% CI 0.30-0.97). Lower socioeconomic status was also independently associated with reduced odds of being prescribed SGLT2is. CONCLUSION: Both clinical and demographic factors are associated with prescribing at the first stage of treatment intensification, with older and non-white people less likely to receive new antidiabetic treatments. Our results suggest that the selection of treatment options used at the first stage of treatment intensification for type 2 diabetes is not driven by clinical need alone

Determining the contribution of IL33 and IL1RL1 polymorphisms to clinical and immunological features of asthma

Rationale: IL33 (9p24.1) and the IL33 receptor (IL1RL, 2q12) have been reproducibly identified as asthma susceptibility genes. However, the variants driving genetic associations are not yet fully defined. Using a population based birth cohort of 1059 children (Manchester Asthma and Allergy Study-(MAAS)) and 2536 adults with asthma (Genetics of Asthma Severity and Phenotypes- (GASP)) cohort we aimed to define genetic variants associated with clinical and immunological features of asthma. Methods: MAAS samples were genotyped using the Illumina 610 Quad array and imputed using 1000G reference panel. GASP samples were genotyped using two custom designed Affymetrix arrays (UK BiLEVE/UK Biobank array). Datasets were quality controlled for gender mismatches, outliers and relatedness. Data was generated for the IL33/IL1RL1 regions consisting of the genes and surrounding regions (chr9:5715785−6757983 & chr2:102427961−103468497) on the following traits: asthma diagnosis (MAAS), atopy, FEV1 (GASP) and FEV1/FVC (MAAS and GASP) as well as total blood eosinophil counts and serum total IgE levels (GASP). Variables for blood eosinophils and total IgE were log10 transformed. Analysis was carried out in PLINK using linear or logistic regression modelling including appropriate covariates for each trait. Results: In the MAAS cohort, we replicated the association of the IL33 locus with asthma diagnosis, identifying potentially two independent novel signals in that locus (rs10975398; P=1.70E-05; B= -1.519; MAF=0.32 and rs2890697; P=1.10E-04; B= -1.573; MAF=0.43). This association survived a Bonferroni correction for multiple testing. Although not surviving correction, an association was also identified for atopy in the IL1RL1 locus for MAAS (P=1.08E-04; MAF=0.48). In GASP we identified modest associations not in known LD with published loci (P-value range: 5.00E-02 – 7.60E-04) for FEV1, FEV1/FVC, atopy, blood eosinophils and total IgE in both the IL33 and IL1RL1 loci. Multiple SNPs presented nominal association (P<0.01) with more than one trait such as atopy & total IgE, providing supporting evidence for association. Conclusion: We replicated the association of IL33 region SNPs with asthma diagnosis in MAAS, highlighting the role of this locus in childhood asthma. Although trait association signals did not survive correction for multiple testing, nominal association across multiple phenotypes in GASP provides suggestive evidence of the role of the IL33/IL1RL1 genetic polymorphisms in determining clinical and immunological features of asthma

A genome wide association study of moderate-severe asthma in subjects from the United Kingdom

Rationale: Genome wide association studies (GWAS) in asthma have been successful in identifying disease susceptibility genes, however to date these have focused on mild disease. The genetic risk factors for moderate-severe asthma remain unclear. Aim: To identify common genetic variants affecting susceptibility to develop moderate-severe asthma. Methods: We identified asthma cases and controls from UK Biobank and additional cases from the Genetics of Asthma Severity & Phenotypes (GASP) cohort. A genome-wide association study was undertaken in 5,135 European ancestry individuals with moderate-severe asthma based on British Thoracic Society criteria 3 or above and 25,675 controls free from lung disease, allergic rhinitis and atopic dermatitis. After imputation (UK10K + 1000 genomes Phase 3) and standard quality control measures, the association of 33,771,858 single nucleotide polymorphisms (SNPs) were tested. A logistic model of association of asthma status with imputed genotype dose was fitted using SNPTEST adjusted for ancestry principal components. Results: We identified 22 loci showing association (P < 5 × 10(-8)) including novel signals in or near D2HGDH, STAT6, HLA-B, CD247, GATA3, PDCD1LG2, ZNF652, RPAP3, MUC5AC and BACH2. Previously described asthma loci where replicated including signals in or near HLA-DQB1, TSLP, IL1RL1/IL18R1, CLEC16A, GATA3, IL33, SMAD3, SLC22A5/IL13, C11orf30, ZBTB10, IKZF3-ORMDL3 and IKZF4. Conclusion: The largest genome-wide association study of moderate-severe asthma to date was carried out and multiple novel loci where identified. These findings may provide new insight into the molecular mechanisms underlying this difficult to treat population