Community-onset bloodstream infections (CO-BSI) caused by gram-negative bacilli are common and associated with significant mortality; those caused by Pseudomonas aeruginosa are associated with worse prognosis and higher rates of inadequateempirical antibiotic treatment. The aims of this study were to describe the characteristics of patients with CO-BSI caused by P. aeruginosa, to identify predictors, and to develop a predictive score for P. aeruginosa CO-BSI. Materials/methods: PROBAC is a prospective cohort including patients >14 years with BSI from 26 Spanish hospitals between October 2016 and May 2017. Patients with monomicrobial P. aeruginosa CO-BSI and monomicrobial Enterobacterales CO-BSI were included. Variables of interest were collected. Independent predictors of Pseudomonas aeruginosa CO-BSI were identified by logistic regression and a prediction score was developed. Results: A total of 78patients with P. aeruginosa CO-BSI and 2572 with Enterobacterales CO-BSI were included. Patients with P. aeruginosa had a median age of 70 years (IQR 60–79), 68.8% were male, median Charlson score was 5 (IQR 3–7), and 30-daymortality was 18.5%. Multivariate analysis identified the following predictors of CO-BSI-PA [adjusted OR (95% CI)]: male gender [1.89 (1.14–3.12)], haematological malignancy [2.45 (1.20–4.99)], obstructive uropathy [2.86 (1.13–3.02)], source of infection other than urinary tract, biliary tract or intra-abdominal [6.69 (4.10–10.92)] and healthcare-associated BSI [1.85 (1.13–3.02)]. Anindex predictive of CO-BSI-PA was developed; scores ≥ 3.5 showed a negative predictive value of 89% and an area under the receiver operator curve (ROC) of 0.66. Conclusions: We did not find a good predictive score of P. aeruginosa CO-BSI due to its relatively low incidence in the overall population. Our model includes variables that are easy to collect in real clinical practice and could be useful to detect patients with very low risk of P. aeruginosa CO-BSI.

Objectives: to undertake a multidisciplinary follow-up at 12 weeks after an acute episode of COVID-19 to assess the functional status, persistence of symptoms and immunoserological situation. Methods: this prospective, observational, single-centre study included outpatients reviewed 12 weeks after an acute infection with SARS-CoV-2. The clinical evaluation included data about the acute episode and epidemiological and clinical variables. The patients were classified as symptomatic or asymptomatic depending on the persistence or otherwise of symptoms. All the patients underwent a full blood test and serology for SARS-CoV-2, as well as imaging tests and spirometry if needed. Results: The mean age of the 108 patients was 55.5 (SD: 15.4) years and 27.8% were health-care workers; 75.9% presented some type of symptoms, with dyspnoea being the most common. A D-dimer >500 ng/mL was detected in 32 (31.4%) patients. All the patients had antibodies against SARS-CoV-2. Being a health-care worker was associated with symptom persistence, with age ≥65 years being a protective factor. Conclusions: The persistence of symptoms in patents with COVID is usual 12 weeks after the acute episode, especially in patients <65 years and health-care workers. All our patients had developed antibodies by 12 weeks.

The Clinical Trial of Sarilumab in Adults With COVID-19 (SARICOR) showed that patients with coronavirus disease 2019 (COVID-19) pneumonia and increased levels of interleukin (IL)-6 might benefit from blockade of the IL-6 pathway. However, the benefit from this intervention might not be uniform. In this subanalysis, we sought to determine if other immunoactivation markers, besides IL-6, could identify which subgroup of patients benefit most from this intervention. The SARICOR trial was a phase II, open-label, multicenter, controlled trial (July 2020–March 2021) in which patients were randomized to receive usual care (UC; control group), UC plus a single dose of sarilumab 200 mg (sarilumab-200 group), or UC plus a single dose of sarilumab 400 mg (sarilumab-400 group). Patients who had baseline serum samples for cytokine determination (IL-8, IL-10, monocyte chemoattractant protein–1, interferon-inducible protein [IP]-10) were included in this secondary analysis. Progression to acute respiratory distress syndrome (ARDS) according to cytokine levels and treatment received was evaluated. One hundred one (88%) of 115 patients enrolled in the SARICOR trial had serum samples (control group: n = 33; sarilumab-200: n = 33; sarilumab-400: n = 35). Among all evaluated biomarkers, IP-10 showed the strongest association with treatment outcome. Patients with IP-10 ≥2500 pg/mL treated with sarilumab-400 had a lower probability of progression (13%) compared with the control group (58%; hazard ratio, 0.19; 95% CI, 0.04–0.90; P = .04). Conversely, patients with IP-10 40 pg/mL. Importantly, IP-10 value <2500 pg/mL might discriminate those individuals who might not benefit from sarilumab therapy among those with high IL-6 levels.

It is not known whether sequential outpatient parenteral antimicrobial (OPAT) is as safe and effective as conventional hospitalization in patients with S. aureus bacteremia (SAB). A post-hoc analysis of the comparative effectiveness of conventional hospitalization versus sequential OPAT was performed in two prospective Spanish cohorts of patients with S. aureus bacteremia. The PROBAC cohort is a national, multicenter, prospective observational cohort of patients diagnosed in 22 Spanish hospitals between October 2016 and March 2017. The DOMUS OPAT cohort is a prospective observational cohort including patients from two university hospitals in Seville, Spain from 2012 to 2021. Multivariate regression was performed, including a propensity score (PS) for receiving OPAT, stratified analysis according to PS quartiles, and matched pair analyses based on PS. Four hundred and thirteen patients were included in the analysis: 150 in sequential OPAT and 263 in the full hospitalization therapy group. In multivariate analysis, including PS and center effect as covariates, 60-day treatment failure was lower in the OPAT group than in the full hospitalization group (p < 0.001; OR 0.275, 95%CI 0.129–0.584). In the PS-based matched analyses, sequential treatment under OPAT was not associated with higher 60-day treatment failure (p = 0.253; adjusted OR 0.660; % CI 0.324–1.345). OPAT is a safe and effective alternative to conventional in-patient therapy for completion of treatment in well-selected patients with SAB, mainly those associated with a low-risk source and without end-stage kidney disease.

BACKGROUND Men who have sex with men (MSM) and LGBTIQ+ populations bear a disproportionate burden of HIV and other sexually transmitted infections (STIs) due to structural stigma and barriers to culturally competent care. Mobile and other digital health technologies, and more recently artificial intelligence (AI)–based tools such as chatbots and risk prediction models, may help improve prevention, testing, and pre-exposure prophylaxis (PrEP) use in these groups. OBJECTIVE This review aimed to (1) synthesize evidence from the past decade on the effectiveness and acceptability of mHealth and other digital sexual health interventions targeting MSM and LGBTIQ+ individuals—focusing on HIV, other STIs, and PrEP—and (2) identify the distinctive features and current evidence base of interventions incorporating AI or advanced automation, particularly conversational agents. METHODS We conducted a critical narrative review with a systematic search following PRISMA recommendations to identify mHealth and other digital sexual health interventions targeting MSM and LGBTIQ+ individuals. Databases searched included PubMed/MEDLINE, Embase, PsycINFO, CINAHL, Web of Science, and the Cochrane Library for studies published between January 1, 2016, and December 31, 2025, complemented by exploratory searches in technology repositories. Eligible studies included MSM and/or LGBTIQ+ participants; evaluated digital sexual health, HIV/STI, or PrEP interventions; and reported quantitative outcomes on behavior, service use, or cognitive/psychosocial variables. Randomized and nonrandomized trials, quasi-experimental, pre–post, pilot, and feasibility studies were included. Two reviewers independently screened records and extracted data. Owing to substantial heterogeneity in designs and outcomes, a narrative synthesis was conducted instead of a meta-analysis. The review protocol was not registered in any public registry. RESULTS Of 12,995 records identified, 15 intervention studies met the inclusion criteria, complemented by 9 recent systematic or scoping reviews on digital and AI-based sexual health interventions. Conventional digital interventions using websites, mobile apps, SMS, social media, and interactive online programs showed modest but relatively consistent improvements in sexual health knowledge, attitudes, HIV/STI testing frequency, and some risk-reduction behaviors among MSM and LGBTIQ+ populations, whereas evidence for PrEP initiation and adherence was sparse and mixed. Interventions explicitly incorporating AI—mainly chatbots for HIV testing support, PrEP decision-making, and sexual health counseling, as well as risk prediction tools often embedded in mobile or web-based platforms—were generally evaluated in pilot or feasibility studies with small samples and short follow-up. These AI-based tools demonstrated high acceptability, perceived confidentiality, and usability, and in some cases facilitated correct HIV self-testing and linkage to services, but robust evidence on sustained behavior change, PrEP uptake and adherence, or clinical outcomes remains very limited. Reporting of equity, data protection, and algorithmic transparency was scarce, and few interventions were specifically co-designed with MSM and LGBTIQ+ communities. CONCLUSIONS Digital and especially mHealth interventions are an established and promising component of HIV and STI prevention for MSM and LGBTIQ+ populations, especially for improving access to information and HIV/STI testing. Evidence on the added value of AI-based tools and conversational agents is still preliminary, largely limited to feasibility and acceptability outcomes, and rarely focused on PrEP. Future research should prioritize rigorously designed, co-designed AI-enhanced mHealth interventions that integrate behavior change theory, ethical safeguards, and equity analyses, and that systematically assess their impact on PrEP initiation and adherence, sexual behaviors, and HIV/STI incidence within community sexual health and HIV prevention services