Evidence-based polytherapies and long-term mortality after acute myocardial infarction in very old subjects compared with elderly and adults: a nested case-control study

Background: Clinical trials have demonstrated that selected secondary prevention medications for patients after acute myocardial infarction (AMI) reduce mortality. Yet, these medications are generally underprescribed in daily practice, and older people are often absent from drug trials. Objectives: To examine the relationship between adherence to evidence-based (EB) drugs and post-AMI mortality, focusing on the effects of single therapy and polytherapy in very old patients (≥80 years) compared with elderly and adults (<80 years). Methods: Patients hospitalised for AMI between 01/01/2008 and 30/06/2011 and resident in the Local Health Authority of Bologna were followed up until 31/12/2011. Medication adherence was calculated as the proportion of days covered for filled prescriptions of angiotensin-converting enzyme inhibitors (ACEIs)/angiotensin receptor blockers (ARBs), β-blockers, antiplatelet drugs, and statins. We adopted a risk set sampling method, and the adjusted relationship between medication adherence (PDC≥75%) and mortality was investigated using conditional multiple logistic regression. Results: The study population comprised 4861 patients. During a median follow-up of 2.8 years, 1116 deaths (23.0%) were observed. Adherence to the 4 EB drugs was 7.1%, while nonadherence to any of the drugs was 19.7%. For both patients aged ≥80 years and those aged <80 years, rate ratios of death linearly decreased as the number of EB drugs taken increased. There was a significant inverse relationship between adherence to each of 4 medications and mortality, although its magnitude was higher for ACEIs/ARBs (adj. rate ratio=0.60, 95%CI=0.52–0.69) and statins (0.60, 0.50–0.72), and lower for β-blockers (0.75, 0.61–0.92) and antiplatelet drugs (0.73, 0.63–0.84). Conclusions: The beneficial effect of EB polytherapy on long-term mortality following AMI is evident also in nontrial older populations. Given that adherence to combination therapies is largely suboptimal, the implementation of strategies and initiatives to increase the use of post-AMI secondary preventive medications in old patients is crucial.

Advancing digital healthcare research and machine learning-aided knowledge extraction amidst the COVID-19 pandemic

The rapid progression of biomedical research coupled with the explosion of scientific literature has generated an exigent need for efficient and reliable systems of knowledge extraction. This dissertation contends with this challenge through a concentrated investigation of digital health, Artificial Intelligence, and specifically Machine Learning and Natural Language Processing's (NLP) potential to expedite systematic literature reviews and refine the knowledge extraction process. The surge of COVID-19 complicated the efforts of scientists, policymakers, and medical professionals in identifying pertinent articles and assessing their scientific validity. This thesis presents a substantial solution in the form of the COKE Project, an initiative that interlaces machine reading with the rigorous protocols of Evidence-Based Medicine to streamline knowledge extraction. In the framework of the COKE (“COVID-19 Knowledge Extraction framework for next-generation discovery science”) Project, this thesis aims to underscore the capacity of machine reading to create knowledge graphs from scientific texts. The project is remarkable for its innovative use of NLP techniques such as a BERT + bi-LSTM language model. This combination is employed to detect and categorize elements within medical abstracts, thereby enhancing the systematic literature review process. The COKE project's outcomes show that NLP, when used in a judiciously structured manner, can significantly reduce the time and effort required to produce medical guidelines. These findings are particularly salient during times of medical emergency, like the COVID-19 pandemic, when quick and accurate research results are critical.

Musculoskeletal disorders, research quality, and pelvic floor health in sports: exploring current evidence and new perspectives

Background. Pelvic floor dysfunction (PFD) is an umbrella term that includes a myriad of conditions such as urinary (UI) and anal incontinence, pelvic organ prolapse, pelvic pain, and sexual dysfunction. Literature showed high prevalence rates of PFD among athletes, especially UI, with high-impact sports have been linked with an increased risk of developing symptoms. However, comprehensive research summarising PFD prevalence across sexes, exploring treatment options, and the absence of a standardised referral screening tool are notable gaps. Misinformation is also prevalent in the sports medicine field. Methods. This doctoral project comprises four studies addressing different aspects of pelvic health in athletes. The first two studies were scoping reviews of epidemiological PFD data in male and female athletes, as well as available interventions. Study 3 concerned the development of a new screening tool for PFD in female athletes, aiming to guide sports medicine clinicians in referring patients to PFD specialists through a worldwide Delphi consensus. Study 4 summarised all previous findings, integrating data into an infographic. Results and conclusions. In Study 1, the findings of 100 articles on PFD in both sexes have been collected, highlighting a higher prevalence of studies on female athletes evaluating UI across multiple sports. Other conditions remain rarely investigated. Study 2 found a diverse range of interventions for female PFD, with a notable emphasis on conservative approaches. Recommendations for clinical practice often relied on the transferability of results from the nonathlete population or expert opinions. In Study 3, 41 international experts took part in the consensus development of the Pelvic Floor Dysfunction-ScrEeNing Tool IN fEmale athLetes (PFD-SENTINEL). It incorporates a cluster of PFD symptoms, items (risk factors, clinical, and sports-related characteristics), and a clinical algorithm. Lastly, Study 4 included ten evidence-based information with a relative description concerning pelvic floor health in athletes.