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Abstract Context Long COVID is an emerging syndrome affecting 50% to 70% of COVID-19 survivors that still lacks predicting factors. Objective Due to the extraskeletal effects of vitamin D, we retrospectively assessed the association between 25(OH) vitamin D levels and long COVID in COVID-19 survivors 6 months after hospitalization. Methods Long COVID was defined according to NICE guidelines. Fifty long COVID and 50 non–long-COVID subjects matched on a 1:1 basis were enrolled from an outpatient clinic post-COVID cohort seen from August to November 2020. Therapies/comorbidities affecting calcium/vitamin D/bone metabolism, and/or admission to the intensive care unit during hospitalization were exclusion criteria. 25(OH) Vitamin D was measured at hospital admission and 6 months after discharge. Results We observed lower 25(OH) vitamin D levels, evaluated at follow-up, in subjects with long COVID than those without (20.1 vs 23.2 ng/mL, P = .03). Regarding the affected health areas evaluated in the entire cohort, we observed lower 25(OH) vitamin D levels in those with neurocognitive symptoms at follow-up (n = 7) than those without (n = 93) (14.6 vs 20.6 ng/mL, P = .042). In patients presenting vitamin D deficiency (<20 ng/mL), both at admission and at follow-up (n = 42), those affected by long COVID (n = 22) presented lower 25(OH) vitamin D levels at follow-up than those not affected (n = 20) (12.7 vs 15.2 ng/mL, P = .041). In multiple regression analyses, lower 25(OH) vitamin D levels at follow-up were the only variable significantly associated with long COVID in our cohort (P = .008, OR 1.09, CI 1.01-1.16). Conclusion COVID-19 survivors with long COVID have lower 25(OH) vitamin D levels than matched patients without long COVID. Our data suggest that vitamin D levels should be evaluated in COVID-19 patients after hospital discharge. The role of vitamin D supplementation as a preventive strategy of COVID-19 sequelae should be tested in randomized controlled trials.

ObjectivesTo assess the safety and efficacy of interleukin (IL)−6 blockade with sarilumab in patients with severe COVID-19 pneumonia and systemic hyperinflammation.MethodsWe conducted an open-label study of sarilumab in severe COVID-19 pneumonia (PaO2/FiO2 <300 mm Hg) with hyperinflammation (elevated inflammatory markers and serum IL-6 levels). Sarilumab 400 mg was administered intravenously in addition to standard of care and results were compared with contemporary matched patients treated with standard of care alone. Clinical improvement, mortality, safety and predictors of response were assessed at 28 days.ResultsTwenty-eight patients were treated with sarilumab and 28 contemporary patients receiving standard of care alone were used as controls. At day 28 of follow-up, 61% of patients treated with sarilumab experienced clinical improvement and 7% died. These findings were not significantly different from the comparison group (clinical improvement 64%, mortality 18%; p=NS). Baseline PaO2/FiO2 ratio >100 mm Hg and lung consolidation <17% at CT scan predicted clinical improvement in patients treated with sarilumab. Median time to clinical improvement in patients with lung consolidation <17% was shorter after sarilumab (10 days) than after standard treatment (24 days; p=0.01). The rate of infection and pulmonary thrombosis was similar between the two groups.ConclusionsAt day 28, overall clinical improvement and mortality in patients with severe COVID-19 were not significantly different between sarilumab and standard of care. Sarilumab was associated with faster recovery in a subset of patients showing minor lung consolidation at baseline.

Objective To evaluate whether the initial chest X-ray (CXR) severity assessed by an AI system may have prognostic utility in patients with COVID-19. Methods This retrospective single-center study included adult patients presenting to the emergency department (ED) between February 25 and April 9, 2020, with SARS-CoV-2 infection confirmed on real-time reverse transcriptase polymerase chain reaction (RT-PCR). Initial CXRs obtained on ED presentation were evaluated by a deep learning artificial intelligence (AI) system and compared with the Radiographic Assessment of Lung Edema (RALE) score, calculated by two experienced radiologists. Death and critical COVID-19 (admission to intensive care unit (ICU) or deaths occurring before ICU admission) were identified as clinical outcomes. Independent predictors of adverse outcomes were evaluated by multivariate analyses. Results Six hundred ninety-seven 697 patients were included in the study: 465 males (66.7%), median age of 62 years (IQR 52–75). Multivariate analyses adjusting for demographics and comorbidities showed that an AI system-based score ≥ 30 on the initial CXR was an independent predictor both for mortality (HR 2.60 (95% CI 1.69 − 3.99; p < 0.001)) and critical COVID-19 (HR 3.40 (95% CI 2.35–4.94; p < 0.001)). Other independent predictors were RALE score, older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. Conclusion AI- and radiologist-assessed disease severity scores on CXRs obtained on ED presentation were independent and comparable predictors of adverse outcomes in patients with COVID-19. Trial registration ClinicalTrials.gov NCT04318366 ( https://clinicaltrials.gov/ct2/show/NCT04318366 ). Key Points • AI system–based score ≥ 30 and a RALE score ≥ 12 at CXRs performed at ED presentation are independent and comparable predictors of death and/or ICU admission in COVID-19 patients. • Other independent predictors are older age, male sex, coronary artery disease, COPD, and neurodegenerative disease. • The comparable performance of the AI system in relation to a radiologist-assessed score in predicting adverse outcomes may represent a game-changer in resource-constrained settings.

Pathogenesis of endometriosis is still unclear and a role of both innate and adaptive immune system has been postulated. Some recent findings have revealed an increased risk to have concomitant autoimmune disease in women with endometriosis, but no study so far has investigated whether this association could affect endometriosis severity and stage. We retrospectively reviewed medical patients’ notes of women with a confirmed diagnosis of endometriosis who referred to our endometriosis outpatient clinic between January 2015 and December 2019. Cases (endometriosis and an autoimmune disease) were matched in a 1:3 ratio by age and study period with controls (endometriosis without history of autoimmunity). At univariate logistic analysis, concomitant autoimmunity (OR 2.63, 95% CI 1.64–4.21, p < 0.001) and the number of laparoscopic procedures performed (OR 2.81, 95% CI 1.45–5.43, p = 0 . 002) emerged as factors significantly associated with the likelihood of stage IV endometriosis. In the multivariate logistic regression model, concomitant autoimmunity remained a significant predictor of stage IV endometriosis (OR 2.54, 95% CI 1.57–4.10, p = 0.004), whereas the association between the number of laparoscopic procedures performed and stage IV endometriosis was found to be of borderline-significance (OR 2.70, 95% 1.37–5.30, p = 0.050). Our findings suggest that endometriosis is more severe in patients who are also affected by autoimmune disturbances after controlling for relevant confounders.

Seasonal rhythms affect the immune system. Evidence supports the involvement of immuno-inflammatory mechanisms in bipolar disorder (BD), with the neutrophil to lymphocyte ratio (NLR), and the systemic immune-inflammatory index (SII; platelets × neutrophils/lymphocytes) consistently reported to be higher in patients with BD than in HC, but seasonal rhythms of innate and adaptive immunity have never been studied. We retrospectively studied NLR and SII in 824 participants divided into three groups: 321 consecutively admitted inpatients affected by a major depressive episode in course of BD, and 255 consecutively admitted inpatients affected by obsessive–compulsive disorder (OCD; positive psychiatric control), and 248 healthy controls (HC). Patients with BD showed markedly higher markers of systemic inflammation in autumn and winter, but not in spring and summer, in respect to both HC and patients with OCD, thus suggesting a specific effect of season on inflammatory markers in BD, independent of a shared hospital setting and drug treatment. Given that systemic inflammation is emerging as a new marker and as target for treatment in depressive disorders, we suggest that seasonal rhythms should be considered for tailoring antidepressant immuno-modulatory treatments in a precision medicine approach.

Infectious and inflammatory stimuli elicit the generation of chitinase-3-like protein-1 (CHI3L1), involved in tissue damage, repair and remodeling. We evaluated whether plasma CHI3L1 at disease onset predicts clinical outcome of patients with Coronavirus 2019 (COVID-19) disease. Blood from 191 prospectively followed COVID-19 patients were collected at hospital admission between March 18th and May 5th, 2020. Plasma from 80 survivors was collected one month post-discharge. Forty age- and sex-matched healthy volunteers served as controls. Primary outcome was transfer to intensive care unit (ICU) or death. CHI3L1 was higher in COVID-19 patients than controls ( p  < 0.0001). Patients with unfavorable outcome (41 patients admitted to ICU, 47 died) had significantly higher CHI3L1 levels than non-ICU survivors ( p  < 0.0001). CHI3L1 levels abated in survivors one month post-discharge, regardless of initial disease severity ( p  < 0.0001), although remaining higher than controls ( p  < 0.05). Cox regression analysis revealed that CHI3L1 levels predict primary outcome independently of age, sex, comorbidities, degree of respiratory insufficiency and systemic inflammation or time from symptom onset to sampling ( p  < 0.0001). Kaplan–Meier curve analysis confirmed that patients with CHI3L1 levels above the median (361 ng/mL) had a poorer prognosis (log rank test, p  < 0.0001). Plasma CHI3L1 is increased in COVID-19 patients and predicts adverse outcome.

Health care practitioners use clinical decision support systems (CDSS) as an aid in the crucial task of clinical reasoning and decision-making. Traditional CDSS are online repositories (ORs) and clinical practice guidelines (CPG). Recently, large language models (LLMs) such as ChatGPT have emerged as potential alternatives. They have proven to be powerful, innovative tools, yet they are not devoid of worrisome risks. This study aims to explore how medical students perform in an evaluated clinical case through the use of different CDSS tools. The authors randomly divided medical students into 3 groups, CPG, n=6 (38%); OR, n=5 (31%); and ChatGPT, n=5 (31%); and assigned each group a different type of CDSS for guidance in answering prespecified questions, assessing how students' speed and ability at resolving the same clinical case varied accordingly. External reviewers evaluated all answers based on accuracy and completeness metrics (score: 1-5). The authors analyzed and categorized group scores according to the skill investigated: differential diagnosis, diagnostic workup, and clinical decision-making. Answering time showed a trend for the ChatGPT group to be the fastest. The mean scores for completeness were as follows: CPG 4.0, OR 3.7, and ChatGPT 3.8 (P=.49). The mean scores for accuracy were as follows: CPG 4.0, OR 3.3, and ChatGPT 3.7 (P=.02). Aggregating scores according to the 3 students' skill domains, trends in differences among the groups emerge more clearly, with the CPG group that performed best in nearly all domains and maintained almost perfect alignment between its completeness and accuracy. This hands-on session provided valuable insights into the potential perks and associated pitfalls of LLMs in medical education and practice. It suggested the critical need to include teachings in medical degree courses on how to properly take advantage of LLMs, as the potential for misuse is evident and real.

Inherited platelet disorders (IPDs) are rare hematological conditions characterized by abnormal platelet function or number, predisposing patients to bleeding. Even if they apparently lower the risk of venous thromboembolism (VTE), this is not abolished in these patients, and may represent a potential cause of mortality. VTE prevention and treatment in these patients is particularly challenging due to the delicate balance between thrombosis and bleeding risks. Here, we summarize current evidence on the incidence, risk factors, and management strategies for VTE in IPD patients, with a focus on the perioperative setting.

Post-COVID syndrome has unveiled intricate connections between inflammation, depressive psychopathology, and cognitive impairment. This study investigates these relationships in 101 COVID-19 survivors, focusing on sex-specific variations. Utilizing path modelling techniques, we analyzed the interplay of a one-month 48-biomarker inflammatory panel, with three-months of depressive symptoms and cognitive performance. The findings indicate that cognitive impairment is influenced by both inflammation and depression in the overall cohort. However, prominent sex-specific differences emerged. In females, a lingering imbalance between pro- and anti-inflammatory responses—likely reflecting the long-lasting immune alterations triggered by COVID-19—significantly affects cognitive functioning and shows a marginal, though not statistically significant, association with depressive symptoms. This suggests that a mixed inflammatory profile may contribute to these outcomes. Conversely, in males, inflammation was inversely associated with depression severity, with protective effects from regulatory mediators (IL-2, IL-4, IL-6, IL-15, LIF, TNF-α, β-NGF) against depression. In males, cognitive impairment appeared to be driven mainly by depressive symptoms, with minimal influence from inflammatory markers. These results highlight distinct sex-specific pathways in immune and inflammatory responses post-COVID-19, potentially shaped by endocrine mechanisms. The findings suggest that persistent inflammation may foster long-term neuropsychiatric sequelae, possibly through its effects on the brain, and underscore the need for sex-tailored therapeutic strategies to address the lasting impact of COVID-19.

Immune responses against pathogens require that microbial components promote the activation of antigen‐presenting cells (APCs). Autoimmune diseases and graft rejections occur in the absence of pathogens; in these conditions, endogenous molecules, the so‐called ‘innate adjuvants’, activate APCs. Necrotic cells contain and release innate adjuvants; necrotic cells also release high‐mobility group B1 protein (HMGB1), an abundant and conserved constituent of vertebrate nuclei. Here, we show that necrotic HMGB1 −/− cells have a reduced ability to activate APCs, and HMGB1 blockade reduces the activation induced by necrotic wild‐type cell supernatants. In vivo , HMGB1 enhances the primary antibody responses to soluble antigens and transforms poorly immunogenic apoptotic lymphoma cells into efficient vaccines.