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Resistant hypertension (RH) includes hypertensive patients with uncontrolled blood pressure (BP) while receiving ≥3 BP-lowering medications or with controlled BP while receiving ≥4 BP-lowering medications. The exact prevalence of RH is challenging to quantify. However, a reasonable estimate of true RH is around 5% of the hypertensive population. Patients with RH have higher cardiovascular risk as compared with hypertensive patients in general. Standardized office BP measurement, confirmation of medical adherence, search for drug- or substance-induced BP elevation, and ambulatory or home BP monitoring are mandatory to exclude pseudoresistance. Appropriate further investigations, guided by clinical data, should be pursued to exclude possible secondary causes of hypertension. The management of RH includes the intensification of lifestyle interventions and the modification of antihypertensive drug regimens. The essential aspects of lifestyle modification include sodium restriction, body weight control, regular exercise, and healthy sleep. Step-by-step adjustment of the BP-lowering drugs based on the available evidence is proposed. The suitable choice of diuretics according to patients\' renal function is presented. Sacubitril/valsartan can be carefully substituted for the prior renin-angiotensin system blockers, especially in those with heart failure with preserved ejection fraction. If BP remains uncontrolled, device therapy such as renal nerve denervation should be considered. Since device-based treatment is an invasive and costly procedure, it should be used only after careful and appropriate case selection. In real-world practice, the management of RH should be individualized depending on each patient\'s characteristics.

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BACKGROUND: Large language models (LLMs) have the potential to support promising new applications in health informatics. However, practical data on sample size considerations for fine-tuning LLMs to perform specific tasks in biomedical and health policy contexts are lacking.
OBJECTIVE: This study aims to evaluate sample size and sample selection techniques for fine-tuning LLMs to support improved named entity recognition (NER) for a custom data set of conflicts of interest disclosure statements.
METHODS: A random sample of 200 disclosure statements was prepared for annotation. All \"PERSON\" and \"ORG\" entities were identified by each of the 2 raters, and once appropriate agreement was established, the annotators independently annotated an additional 290 disclosure statements. From the 490 annotated documents, 2500 stratified random samples in different size ranges were drawn. The 2500 training set subsamples were used to fine-tune a selection of language models across 2 model architectures (Bidirectional Encoder Representations from Transformers [BERT] and Generative Pre-trained Transformer [GPT]) for improved NER, and multiple regression was used to assess the relationship between sample size (sentences), entity density (entities per sentence [EPS]), and trained model performance (F1-score). Additionally, single-predictor threshold regression models were used to evaluate the possibility of diminishing marginal returns from increased sample size or entity density.
RESULTS: Fine-tuned models ranged in topline NER performance from F1-score=0.79 to F1-score=0.96 across architectures. Two-predictor multiple linear regression models were statistically significant with multiple R2 ranging from 0.6057 to 0.7896 (all P<.001). EPS and the number of sentences were significant predictors of F1-scores in all cases ( P<.001), except for the GPT-2_large model, where EPS was not a significant predictor (P=.184). Model thresholds indicate points of diminishing marginal return from increased training data set sample size measured by the number of sentences, with point estimates ranging from 439 sentences for RoBERTa_large to 527 sentences for GPT-2_large. Likewise, the threshold regression models indicate a diminishing marginal return for EPS with point estimates between 1.36 and 1.38.
CONCLUSIONS: Relatively modest sample sizes can be used to fine-tune LLMs for NER tasks applied to biomedical text, and training data entity density should representatively approximate entity density in production data. Training data quality and a model architecture\'s intended use (text generation vs text processing or classification) may be as, or more, important as training data volume and model parameter size.

Background: While the PRISMA 2020 statement is intended to guide the reporting of original systematic reviews, updated systematic reviews, and living systematic reviews (LSRs), its explanation and elaboration document notes that additional considerations for updated systematic reviews and LSRs may need to be addressed. This paper reports the protocol for developing an extension of the PRISMA 2020 statement for LSRs. Methods: We will follow the EQUATOR Network\'s guidance for developing health research reporting guidelines. We will review the literature to identify possible items of the PRISMA 2020 checklist that need modification, as well as new items that need to be added. Then, we will survey representatives of different stakeholder groups for their views on the proposed modifications of the PRISMA 2020 checklist. We will summarize, present, and discuss the results of the survey in an online meeting, aiming to reach consensus on the content of the LSR extension. We will then draft the checklist, explanation and elaboration for each item, and flow diagram for the PRISMA 2020 extension. Then, we will share these initial documents with stakeholder representatives for final feedback and approval. Discussion: We anticipate that the PRISMA 2020 extension for LSRs will benefit LSR authors, editors, and peer reviewers of LSRs, as well as different users of LSRs, including guideline developers, policy makers, healthcare providers, patients, and other stakeholders.

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This scoping review analyzed statements from 22 medical organizations in the United States to identify commonalities in the definition and governance of point-of-care ultrasound (POCUS). A total of 41 statements were included. The review found that the most commonly used elements in defining POCUS were \"focused,\" \"bedside,\" and \"patient care.\" In terms of governance, consistent requirements included specific training programs, documentation in medical records, continuous quality assurance, and standards for credentialing and privileging. These findings suggest the existence of essential commonalities that could facilitate communication and the development of standardized POCUS programs in the future.

The document summarizes the statement of the expert discussion panel of the 1st Point- of-Care Ultrasonography, which took place on 14 November 2022 in Prague and which led to the foundation of the Czech Multidisciplinary Task Force Group for standards,education and research in Point-of-Care ultrasound (Czech POCUS group).

Brodalumab is a recombinant, fully human immunoglobulin IgG2 monoclonal antibody specifically targeted against interleukin-17RA that has been approved for the treatment of moderate-to-severe psoriasis in Europe. We developed a Delphi consensus document focused on brodalumab for the treatment of moderate-to-severe psoriasis. Based on published literature and their clinical experience a steering committee drafted 17 statements covering 7 domains specific to the treatment of moderate-to-severe psoriasis with brodalumab. A panel of 32 Italian dermatologists indicated their level of agreement using a 5-point Likert scale (from 1 = \"strongly disagree\" to 5 = \"strongly agree\") using an online modified Delphi method. After the first round of voting (32 participants), positive consensus was reached for 15/17 (88.2%) of the proposed statements. Following a face-to-face virtual meeting, the steering committee decided that 5 statements would form \"main principles\" and 10 statements formed the final list. After a second round of voting, consensus was reached in 4/5 (80%) of the main principles and 8/10 (80%) for consensus statements. The final list of 5 main principles and 10 consensus statements identify key indications specific to the use of brodalumab in the treatment of moderate-to-severe psoriasis in Italy. These statements aid dermatologists in the management of patients with moderate-to-severe psoriasis.

BACKGROUND: The high-quality evidence on managing COVID-19 patients requiring extracorporeal membrane oxygenation (ECMO) support is insufficient. Furthermore, there is little consensus on allocating ECMO resources when scarce. The paucity of evidence and the need for guidance on controversial topics required an international expert consensus statement to understand the role of ECMO in COVID-19 better. Twenty-two international ECMO experts worldwide work together to interpret the most recent findings of the evolving published research, statement formulation, and voting to achieve consensus.
OBJECTIVE: To guide the next generation of ECMO practitioners during future pandemics on tackling controversial topics pertaining to using ECMO for patients with COVID-19-related severe ARDS.
METHODS: The scientific committee was assembled of five chairpersons with more than 5 years of ECMO experience and a critical care background. Their roles were modifying and restructuring the panel\'s questions and, assisting with statement formulation in addition to expert composition and literature review. Experts are identified based on their clinical experience with ECMO (minimum of 5 years) and previous academic activity on a global scale, with a focus on diversity in gender, geography, area of expertise, and level of seniority. We used the modified Delphi technique rounds and the nominal group technique (NGT) through three face-to-face meetings and the voting on the statement was conducted anonymously. The entire process was planned to be carried out in five phases: identifying the gap of knowledge, validation, statement formulation, voting, and drafting, respectively.
RESULTS: In phase I, the scientific committee obtained 52 questions on controversial topics in ECMO for COVID-19, further reviewed for duplication and redundancy in phase II, resulting in nine domains with 32 questions with a validation rate exceeding 75% (Fig. 1). In phase III, 25 questions were used to formulate 14 statements, and six questions achieved no consensus on the statements. In phase IV, two voting rounds resulted in 14 statements that reached a consensus are included in four domains which are: patient selection, ECMO clinical management, operational and logistics management, and ethics.
CONCLUSIONS: Three years after the onset of COVID-19, our understanding of the role of ECMO has evolved. However, it is incomplete. Tota14 statements achieved consensus; included in four domains discussing patient selection, clinical ECMO management, operational and logistic ECMO management and ethics to guide next-generation ECMO providers during future pandemic situations.