Little research has been done on post-COVID symptoms at 24 months postinfection and on the association these may have on health-related quality of life (HRQOL).

We assessed the prevalence and severity of post-COVID symptoms and quantified EuroQol 5 Dimension 5 Level (EQ-5D-5L), self-perceived health question (EuroQol Visual Analogue Scale (EQ-VAS)) and health utility scores (HUS) up to 24 months follow-up.

The longitudinal multiple cohort CORona Follow-Up (CORFU) study combines seven COVID-19 patient cohorts and a survey among the general public. The participants received questionnaires on several time points. Participants were stratified by: without a known SARS-CoV-2 infection (control group), proven SARS-CoV-2 infection but non-hospitalised, proven SARS-CoV-2 infection hospitalised to the ward, and proven SARS-CoV-2 infection hospitalised to the intensive care unit (ICU).

In this study, data of seven COVID-19 patient cohorts and a survey among the general public are included.

Former COVID-19 patients and controls participated in this cohort study.

Former COVID-19 patients and non-COVID-19 controls were sent questionnaires on symptoms associated with post-COVID condition. The CORFU questionnaire included 14 symptom questions on post-COVID condition using a five-level Likert-scale format. Furthermore, HRQOL was quantified using the EuroQol EQ-5D-5L questionnaire: EQ-VAS and the EQ-5D-5L utility score. The EQ-5D-5L questionnaire includes five domains that are scored on a five-point Likert scale: mobility, self-care, usual activities, pain/discomfort and anxiety/depression.

A total of 901 participants (and 434 controls) responded at 24 months follow-up. In all former COVID-19 patients, the presence of post-COVID condition at 24 months was observed in 62 (42.5%, 95% CI 34.3% to 50.9%) of the non-hospitalised patients, 333 (65.0%, 95% CI 60.7% to 69.2%) of the hospitalised ward patients and 156 (63.2%, 95% CI 56.8% to 69.2%) of the ICU patients, respectively (p

Many former COVID-19 patients experience post-COVID symptoms at 24 months follow-up, with the highest prevalence in hospitalised participants. Also, former patients reported a lower HRQOL.

The CORFU study was registered at clinicaltrials.gov (registration number NCT05240742).

To compare the quality and time efficiency of physician-written summaries with customised large language model (LLM)-generated medical summaries integrated into the electronic health record (EHR) in a non-English clinical environment.

Cross-sectional non-inferiority validation study.

Tertiary academic hospital.

52 physicians from 8 specialties at a large Dutch academic hospital participated, either in writing summaries (n=42) or evaluating them (n=10).

Physician writers wrote summaries of 50 patient records. LLM-generated summaries were created for the same records using an EHR-integrated LLM. An independent, blinded panel of physician evaluators compared physician-written summaries to LLM-generated summaries.

Primary outcome measures were completeness, correctness and conciseness (on a 5-point Likert scale). Secondary outcomes were preference and trust, and time to generate either the physician-written or LLM-generated summary.

The completeness and correctness of LLM-generated summaries did not differ significantly from physician-written summaries. However, LLM summaries were less concise (3.0 vs 3.5, p=0.001). Overall evaluation scores were similar (3.4 vs 3.3, p=0.373), with 57% of evaluators preferring LLM-generated summaries. Trust in both summary types was comparable, and interobserver variability showed excellent reliability (intraclass correlation coefficient 0.975). Physicians took an average of 7 min per summary, while LLMs completed the same task in just 15.7 s.

LLM-generated summaries are comparable to physician-written summaries in completeness and correctness, although slightly less concise. With a clear time-saving benefit, LLMs could help reduce clinicians’ administrative burden without compromising summary quality.

Sepsis is a major cause of death both globally and in the United States. Early identification and treatment of sepsis are crucial for improving patient outcomes. International guidelines recommend hospital sepsis screening programmes, which are commonly implemented in the electronic health record (EHR) as an interruptive sepsis screening alert based on systemic inflammatory response syndrome (SIRS) criteria. Despite widespread use, it is unknown whether these sepsis screening and alert tools improve the delivery of high-quality sepsis care.

The Sepsis Electronic Prompting for Timely Intervention and Care (SEPTIC) master protocol will study two distinct populations in separate trials: emergency department (ED) patients (SEPTIC-ED) and inpatients (SEPTIC-IP). The SEPTIC trials are pragmatic, multicentre, blinded, randomised controlled trials, with equal allocation to compare four SIRS-based sepsis screening alert groups: no alerts (control), nurse alerts only, prescribing clinician alerts only, or nurse and prescribing clinician alerts. Randomisation will be at the patient level. SEPTIC will be performed at eight acute-care hospitals in the greater New York City area and enrol patients at least 18 years old. The primary outcome is the percentage of patients with completion of a modified Surviving Sepsis Campaign (SSC) hour-1 bundle within 3 hours of the first SIRS alert. Secondary outcomes include time from first alert to completion of a modified SSC hour-1 bundle, time from first alert to individual bundle component order and completion, intensive care unit (ICU) transfer, hospital discharge disposition, inpatient mortality at 90 days, positive blood cultures (bacteraemia), adverse antibiotic events, sepsis diagnoses and septic shock diagnoses.

Ethics approval was obtained from the Columbia University Institutional Review Board (IRB) serving as a single IRB. Results will be disseminated in peer-reviewed journal(s), scientific meeting(s) and via social media.

ClinicalTrials.gov: NCT06117605 and NCT06117618.