Journal of evaluation in clinical practice
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We previously demonstrated that annual review %FEV1 underestimates lung health of adults with CF compared with %FEV1 captured during periods of clinical stability. This has implications in the comparisons against registries with encounter-based FEV1 , such as the United States. It is uncertain whether this bias affects between-centre comparison within the United Kingdom. Previous funnel plot analyses have identified variation in annual review %FEV1 according to centre size; hence, we investigated whether paired differences between annual review and best %FEV1 also vary according to centre size. ⋯ Annual review %FEV1 underestimated lung health of adults from small and large centres in the United Kingdom to a greater extent compared with medium-sized centres. A plot of %FEV1 against centre size (eg, funnel plot comparison) would be affected by systematic bias in annual review %FEV1 . Therefore, annual review %FEV1 is an unreliable metric to compare health outcomes of adult CF centres within the United Kingdom.
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Observational Study
Negative effect of fatty liver on visualization of pancreatic cystic lesions at screening transabdominal ultrasonography.
The aim of this observational study is to identify factors by which some pancreatic cystic lesions (PCLs) were undetectable at transabdominal ultrasonography (TAUS), using magnetic resonance imaging (MRI) as reference standard. ⋯ It should be noted that coexisting fatty liver may lower the detection of PCL, and its size may be underestimated by TAUS.
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Venous thromboembolism (VTE) is a fatal complication and the most common preventable cause of death in hospitals. The risk-to-benefit ratio of thromboprophylaxis depends on the performance of the risk assessment model. A linear model, the Padua model, is recommended for medical inpatients in the United States but is not suitable for Chinese inpatients due to differences in race and disease spectrum. Currently, machine learning (ML) methods show advantages in modeling complex data patterns and have been applied to clinical data analysis. This study aimed to build VTE risk assessment ML models among Chinese inpatients and compare the predictive validity of the ML models with that of the Padua model. ⋯ Advances in ML technology provide powerful tools for medical data analysis, and choosing models conforming to the disease pattern would achieve good performance. Popular ML models do not surpass the Padua model on all indicators of validity, and the drawback of low sensitivity should be improved upon in the future.
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This study aimed to evaluate the attitudes towards and experiences of ethical dilemmas in the treatment decision-making process among medical oncologists who are the members of the Turkish Society of Medical Oncology. ⋯ Our results demonstrate that medical oncologists tend to adopt an approach that respects patient autonomy and that adheres to the principle of proportionality rather than a paternalistic approach when facing ethical dilemmas. Within this context, we suggest an increased use of a multidisciplinary team approach, ethics consultancy services, and training programmes as well as the publication of ethical guidelines tailored to the oncology field.
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Drug-related morbidity is common, which results in suffering for the patients and a high cost to society. SÄKLÄK2 is a multi-professional intervention model aiming at improving drug safety in primary health care. The objective of this study was to elucidate the perceptions of the participants' regarding the efficiency of the intervention and the feasibility to introduce this model widely. ⋯ SÄKLÄK2, a model with self-assessment, peer review, written feedback, and the formation of action agreements was considered by both the participating heads of the PHC centres and the reviewers to be effective to improve drug safety in primary health care. Though time-consuming, this multi-professional model was considered to be feasible to implement on a broad front and might thereby be one way of working with quality improvement regarding drug safety.