Postoperative pulmonary complications (PPCs) represent a significant cause of postoperative morbidity and even mortality. However, there is a lack of consensus regarding this composite endpoint, the definition of the individual components, classification and optimal outcome measures. This study aims to refine the PPCs composite framework by evaluating its construct validity, assessing the necessity and risks of a composite measure and exploring the feasibility of differentiating severity categories.

A Delphi consensus process will be conducted, engaging an international multidisciplinary group of 30–40 panellists, including clinicians, researchers, patients, public representatives and health economists. Through iterative rounds, the study will seek agreement on the individual components of the PPCs composite. Additionally, consensus will establish a framework for a composite outcome measure based on a standardised severity classification, appropriate timeframes and weighted grading of PPCs.

Consensus, defined by ≥75% concurrence in multiple choice questions or on Likert–scale statements, will be evaluated from round 2 onwards. Delphi rounds will be continued until all statements have reached stability of responses evaluated by ² tests or the Kruskal-Wallis test.

The study will be conducted in strict compliance with the principles of the Declaration of Helsinki and will adhere to ACCORD guidance for reporting. Ethics approval has been obtained for this study from the University of Wolverhampton, UK (SOABE/202425/staff/3). Informed consent will be obtained from all panellists before the commencement of the Delphi process. The results of the study will be published in a peer–reviewed journal with the authorship assigned in accordance with ICMJE requirements.

NCT06916598 (clinicaltrials.gov).

It is unclear how mis- and disinformation regarding healthcare policy changes propagate throughout Latino communities via social media. This may lead to chilling effects that dissuade eligible individuals from enrolling in critical safety net programmes such as Medicaid. This study will examine pathways and mechanisms by which sentiment in response to mis- and disinformation regarding healthcare policies on social media differentially impact health disparity populations, thus supporting the design of tailored social media interventions to mitigate this.

We will search social media from X/Twitter, Facebook/Instagram and Reddit for keywords relating to health benefit programmes. Demographic, geographical location and other characteristics of users will be used to stratify social media data. Posts will be classified as fake-news-related or fact-related based on curated lists of fake-news-related websites. The number, temporal dissemination and positive or negative sentiment in reacting to posts and threads will be examined using the Python-based Valence Aware Dictionary and sEntiment Reasoner (VADER). Using a crowd-sourcing methodology, a novel Spanish-language VADER (S-VADER) will be created to rate sentiment to social media among Spanish-speaking Latinos. With the proposed approach, we will explore reactions to the dissemination of fake-news- or fact-related social media tweets and posts and their sources. Analyses of social media posts in response to healthcare-related policies will provide insights into fears faced by Latinos and Spanish speakers, as well as positive or negative perceptions relating to the policy over time among social media users.

Our study protocol was approved by the University of California, Los Angeles IRB (IRB#23–0 01 123). Results from this study will be disseminated in peer-reviewed journals and conference presentations, and S-VADER will be disseminated to public repositories such as GitHub.

Investigate determinants of post-COVID-19 condition (PCC) clinic attendance among participants not hospitalised versus hospitalised during the SARS-CoV-2 infection.

Retrospective cohort study.

Six population-based registers with high coverage to cover all adults residing in Stockholm County, Sweden.

Adults residing in Stockholm County on 31 January 2020, with a SARS-CoV-2 infection through 30 November 2022, who did not die or move out of Stockholm County within 90 days.

PCC clinic attendance from 90 days after the SARS-CoV-2 test until date of death, date of moving out, or 30 November 30,2023.

Of non-hospitalised and hospitalised participants, 737 of 464 674 (0.2%) and 433 of 23 374 (1.9%), respectively, attended a PCC clinic. A total of 75 878 (16.3%) of non-hospitalised participants and 6190 (26.5%) of hospitalised participants presented with new-onset symptoms that could indicate PCC in primary care. The strongest determinants of attendance among non-hospitalised participants were mental health disorder (adjusted risk ratio (aRR) 2.57, 95% CI 2.21 to 2.98), asthma (2.39, 1.97–2.92) and >4 PCC symptoms in 2019 (2.27, 1.60–3.24), and among hospitalised participants were >31 sick days in 2019 (1.94, 1.47–2.56), 1–30 sick days in 2019 (1.56, 1.06–2.29) and obesity (1.51, 1.19–1.93). The most common clinical presentation was fatigue (n=526, 71.4%) among non-hospitalised and dyspnoea (n=148, 34.2%) among hospitalised participants.

PCC clinic attendance characteristics differed between non-hospitalised and hospitalised participants. Distinguishing PCC from conditions with overlapping symptoms and determining the appropriate level of care may be challenging, with risk of resource displacement effects and inappropriate care.

To determine whether an invasive approach is associated with favourable long-term outcomes among elderly medical patients in the intensive care unit (ICU), compared with a conservative approach.

Nationwide observational study (OCTO-REVERSE study) using data prospectively collected in the National French Healthcare Database (covering 99% of the population, 66 million people).

Comprehensive multicentre study through the linkage of large-scale national registries (including all public or private facilities) from 2013 to 2018 to avoid ambiguities related to the COVID-19 pandemic.

All non-surgical patients aged 80 years or older admitted to an ICU in France during the period (n=107 014 patients at 822 hospitals).

The main outcome was the 1-year survival rate. The association of the two approaches with 1-year survival was estimated using a time-dependent Cox model and a propensity score (PS) adapted to time-to-event analysis, yielding the average treatment effect in the treated and extended weighted Kaplan–Meier curves.

107 014 patients were categorised into two groups based on the type of care received: invasive (n=51 680 (48%) received invasive ventilation and/or vasopressor support) or conservative (n=55 334 (52%) received neither). 1-year survival rate was significantly lower in the invasive group than in the conservative group (27% vs 59% estimated with extended time-dependent Kaplan–Meier method). The risk of death in the invasive group remained significantly higher after time-dependent PS weighting (HR 1.64; 95% CI 1.60 to 1.69; p

Among the whole population of critically ill elderly medical patients in France, the invasive approach was unknowingly associated with end-of-life care in nearly three quarters of cases. Further research is needed to align intensive care with compassionate goals.

Deep brain stimulation (DBS) is a proven effective treatment for Parkinson’s disease (PD). However, titrating DBS stimulation parameters is a labourious process and requires frequent hospital visits. Additionally, its current application uses continuous high-frequency stimulation at a constant intensity, which may reduce efficacy and cause side effects. The objective of the AI-DBS study is to identify patient-specific patterns of neuronal activity that are associated with the severity of motor symptoms of PD. This information is essential for the development of advanced responsive stimulation algorithms, which may improve the efficacy of DBS.

This longitudinal prospective observational cohort study will enrol 100 patients with PD who are bilaterally implanted with a sensing-enabled DBS system (Percept PC, Medtronic) in the subthalamic nucleus as part of standard clinical care. Local neuronal activity, specifically local field potential (LFP) signals, will be recorded during the first 6 months after DBS implantation. Correlations will be tested between spectral features of LFP data and symptom severity, which will be assessed using (1) inertial sensor data from a wearable smartwatch, (2) clinical rating scales and (3) patient diaries and analysed using conventional descriptive statistics and artificial intelligence algorithms. The primary objective is to identify patient-specific profiles of neuronal activity that are associated with the presence and severity of motor symptoms, forming a ‘neuronal fingerprint’.

Ethical approval was granted by the local ethics committee of the Amsterdam UMC (registration number 2022.0368). Study findings will be disseminated through scientific journals and presented at national and international conferences.

To explore interprofessional team members’ experiences of teamwork at an intensive care unit.

Qualitative content analysis of focus group interviews with members from the intensive care teams.

University hospital in Sweden.

In total, 31 participants were interviewed. Enrolled nurses (n=7), critical care registered nurses (n=16), and intensive care physicians (n=8) employed at an intensive care unit were divided into nine focus groups organised according to the profession.

The overall theme, Balancing behaviour and knowledge in teamwork, emerged from the two categories of creating a safe atmosphere when working in an unknown environment and counteracting and mitigating destructive team dynamics. The theme captures how well-functioning teamwork must take into account members not acting as team players while also building a secure environment when working in new surroundings outside the intensive care unit. The categories describe how mutual respect, effective teamwork and a safe atmosphere were fostered through support without taking over tasks and countering power structures.

Navigating teamwork during critical situations is inherently complex, making it essential to understand team interactions and factors influencing individual behaviour. To ensure patient safety, the interprofessional team must recognise, understand and manage diverse behaviours and knowledge in dynamic settings. This research contributes to existing knowledge on teamwork in the intensive care context by providing insights into how knowledge and behaviour in teamwork can be optimised to enhance patient safety.