ABSTRACT Aim Postnatally acquired cytomegalovirus (pCMV) infection may cause severe disease in extremely preterm infants, but its clinical significance remains uncertain. We investigated the incidence, timing, disease burden, and diagnostic performance of saliva screening. Method In this prospective cohort study, infants born at < 28 weeks of gestation or with a birth weight < 1200 g to CMV‐seropositive mothers and fed untreated mothers' own milk underwent weekly saliva and urine CMV polymerase chain reaction testing. Outcomes before discharge and at 2 years corrected age were compared between CMV‐positive and CMV‐negative infants. Results Forty‐five infants were included, of whom 20 (44%) acquired pCMV. CMV was detected at a median age of 44 days in saliva, 50 days in urine, and 55 days in blood. Two (10%) infected infants developed severe disease requiring antiviral treatment. No significant differences were observed in neonatal morbidity, hospitalisation duration, mortality, or neurodevelopmental outcomes. Saliva PCR demonstrated a sensitivity of 86% and a specificity of 93%. Conclusion pCMV transmission was common in extremely preterm infants receiving mothers' own milk, but clinically significant disease occurred in only a minority of infected infants. Saliva‐based screening demonstrated acceptable diagnostic performance and may facilitate early recognition and targeted management of clinically significant pCMV infection.
Immunosuppressed individuals are at higher risk for influenza-related complications, yet vaccination rates remain low, particularly among young and middle-aged adults. This secondary analysis of the NUDGE-FLU-CHRONIC trial assessed the impact of letter-based nudges on influenza vaccine uptake by immunosuppression status.Table 1:Baseline Characteristics by Immunosuppression StatusTable 2:Baseline Characteristics by Randomization to Any Letter or Usual Care in Participants with Immunosuppression All Danish citizens aged 18–64 with chronic conditions eligible for free influenza vaccination during the 2023/24 season were enrolled. Participants were randomly assigned to no letter (usual care), or one of six electronic nudges delivered via the national governmental electronic letter system. All data were obtained from national registries. Immunosuppression was defined as a diagnosis of HIV, congenital immunodeficiency, or transplantation ≤10 years before randomization, or ≥1 filled prescription for an immunosuppressant or systemic glucocorticoid ≤180 days before randomization. The primary endpoint was influenza vaccination by January 1, 2024. Vaccination rates were compared using χ² tests and presented as absolute differences in proportions. Effect modification by immunosuppression status was assessed using binomial regression models with interaction terms.Figure 1:Vaccination rates by immunosuppression statusBar chart with 95% confidence intervals of influenza vaccination rates according to immunosuppression status (green vs patterned) in all NUDGE-FLU-CHRONIC participants (n=299,881), and among immunosuppression subgroups (green vs teal) among participants with immunosuppression (n=29,277). ICD-10 codes for immunsuppression included diagnosis of HIV (B20-B24, O98.7, Z21), congenital immunodeficiency (D80-D84, D89) or transplantation (Z94.0-Z94.4, Z94.8A). ATC codes for immunosuppressive medications included filled prescriptions for immunosuppressants (L04) or systemic glucocorticoids (H02AB).Figure 2.Effectiveness of Electronically Delivered Behavioral Nudges by Immunosuppression Status Among 299,881 participants (median age 52 years, 53% female), 29,277 (10%) were immunosuppressed. Immunosuppressed individuals were more likely to have chronic lung or kidney disease but had lower rates of diabetes, cardiovascular disease, and cancer (Table 1). Baseline characteristics were balanced by randomization group among immunosuppressed individuals (Table 2). Vaccination rates were higher in individuals with immunosuppression than those without (45% vs. 35%, p < 0.001; Figure 1). Any letter-based nudge improved vaccine uptake more in individuals with vs. without immunosuppression (+13.3 vs. +11.5 percentage points; p for interaction = 0.007), with similar patterns for the standard letter, cardiovascular-gain frame and loss-framing interventions, but no effect modification for other letter types (Figure 2). Electronically delivered letter-based nudges effectively increased influenza vaccination compared with usual care among individuals with immunosuppression. Muthiah Vaduganathan, MD, MPH, American Regent: Grant/Research Support|Amgen: Grant/Research Support|AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|Baxter Healthcare: Grant/Research Support|Bayer AG: Advisor/Consultant|Bayer AG: Grant/Research Support|BMS: Grant/Research Support|Boehringer Ingelheim: Grant/Research Support|Chiesi: Grant/Research Support|Cytokinetics: Grant/Research Support|Fresenius Medical Care: Grant/Research Support|Galmed: Advisor/Consultant|Idorsia Pharmaceuticals: Grant/Research Support|Impulse Dynamics: Advisor/Consultant|Lexicon Pharmaceuticals: Grant/Research Support|Merck: Grant/Research Support|Milestone Pharmaceuticals: Grant/Research Support|Novartis: Advisor/Consultant|Novartis: Grant/Research Support|Novo Nordisk: Advisor/Consultant|Novo Nordisk: Grant/Research Support|Occlutech: Advisor/Consultant|Pharmacosmos: Grant/Research Support|Relypsa: Grant/Research Support|Roche Diagnostics: Grant/Research Support|Sanofi: Grant/Research Support|Tricog Health: Grant/Research Support Ankeet S. Bhatt, MD, MBA, ScM, Merck: Honoraria|Novo Nordisk: Honoraria|Sanofi: Honoraria Brian L. Claggett, PhD, Alnylam: Advisor/Consultant|Cardior: Advisor/Consultant|Cardurion: Advisor/Consultant|CVRx: Advisor/Consultant|Cytokinetics: Advisor/Consultant|Eli Lilly: Advisor/Consultant|Intellia: Advisor/Consultant|Rocket: Advisor/Consultant Joshua A. Hill, MD, Allovir: Advisor/Consultant|Allovir: Grant/Research Support|CSL Behring: Advisor/Consultant|Gilead Sciences: Advisor/Consultant|Gilead Sciences: Grant/Research Support|Karius: Advisor/Consultant|Merck: Grant/Research Support|Moderna: Advisor/Consultant|Takeda: Advisor/Consultant|Takeda: Grant/Research Support Carsten S. Larsen, MD, DMSc, Danske Lægers Vaccinations Service: Employed as chief physician|GSK: Advisor/Consultant|MSD: Advisor/Consultant|Pfizer: Advisor/Consultant|Takeda: Advisor/Consultant|Valneva: Advisor/Consultant Lars Køber, MD, DMSc, AstraZeneca: Honoraria|Bayer: Honoraria|Boehringer Ingelheim: Honoraria|Novartis: Honoraria|Novo Nordisk: Honoraria Scott D. Solomon, MD, Abbott: Advisor/Consultant|Action: Advisor/Consultant|Akros: Advisor/Consultant|Alexion: Advisor/Consultant|Alexion: Grant/Research Support|Alnylam: Advisor/Consultant|Alnylam: Grant/Research Support|Amgen: Advisor/Consultant|Applied Therapeutics: Grant/Research Support|Arena: Advisor/Consultant|AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|Bayer: Advisor/Consultant|Bayer: Grant/Research Support|Bellerophon: Grant/Research Support|BMS: Advisor/Consultant|BMS: Grant/Research Support|Boston Scientific: Grant/Research Support|Cardior: Advisor/Consultant|Cardurion: Advisor/Consultant|Corvia: Advisor/Consultant|Cytokinetics: Advisor/Consultant|Cytokinetics: Grant/Research Support|Edgewise: Grant/Research Support|Eidos/BridgeBio: Grant/Research Support|Gossamer: Grant/Research Support|GSK: Advisor/Consultant|GSK: Grant/Research Support|Ionis: Grant/Research Support|Lilly: Advisor/Consultant|Lilly: Grant/Research Support|Moderna: Advisor/Consultant|Novartis: Advisor/Consultant|Novartis: Grant/Research Support|NovoNordisk: Grant/Research Support|Quantum Genomics: Advisor/Consultant|Respicardia: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant|Sanofi Pasteur: Grant/Research Support|Tenaya: Advisor/Consultant|Tenaya: Grant/Research Support|Theracos: Advisor/Consultant|Theracos: Grant/Research Support|US2.AI: Grant/Research Support Tor Biering-Sørensen, MD, PhD, Amgen: Advisor/Consultant|AstraZeneca: Grant/Research Support|AstraZeneca: Honoraria|Bayer: Grant/Research Support|Bayer: Honoraria|Boston Scientific: Grant/Research Support|CSL Seqirus: Advisor/Consultant|GE Healthcare: Grant/Research Support|GE Healthcare: Honoraria|GSK: Advisor/Consultant|GSK: Grant/Research Support|GSK: Honoraria|IQVIA: Advisor/Consultant|Novartis: Grant/Research Support|Novartis: Honoraria|Novo Nordisk: Advisor/Consultant|Novo Nordisk: Grant/Research Support|Parexel: Advisor/Consultant|Pfizer: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant|Sanofi Pasteur: Grant/Research Support|Sanofi Pasteur: Honoraria
Immunosuppressed (IS) individuals are at high risk of severe respiratory syncytial virus (RSV) complications. This prespecified analysis of DAN-RSV evaluated the effectiveness of a bivalent RSV prefusion F protein-based vaccine (RSVpreF) in preventing RSV-related and all-cause cardio-respiratory hospitalizations among individuals with and without IS.Table 1.Baseline characteristics according to immunosuppression status.Values are presented as mean ± SD or n (%) with p-values from t-test or Pearson chi-squared test.Figure 1.Hospitalization rates according to immunosuppression status in the overall study population.P-values from Poisson regression models. The DAN-RSV trial was a pragmatic, open-label randomized clinical trial conducted during the 2024/25 northern hemisphere winter. Adults aged ≥60 years were enrolled (Nov-Dec 2024) and randomized 1:1 to RSVpreF or no vaccine; only the RSVpreF arm were required to attend a study visit. Baseline and outcome data were obtained from nationwide registries. IS was defined using ICD10 or procedure codes and required ≥1 hospital encounter . Follow-up was from 14 days after vaccination/scheduled visit until May 31, 2025. The primary endpoint was hospitalization for RSV-related respiratory tract disease (RTD); secondary endpoints included hospitalizations for any respiratory and cardio-respiratory disease.Figure 2.Vaccine effectiveness of RSVpreF compared with no vaccine according to immunosuppression status.Vaccine effectiveness was calculated as (1-incidence rate ratio*100%. Interaction p-values were estimated using a Poisson model with a sub-group-by-randomized treatment interaction term included. Abbreviations: PY = person-years; RSVpreF = respiratory syncytial virus prefusion F protein-based vaccine; VE = vaccine effectiveness. Among 131,276 participants (65,642 RSVpreF; 65,634 no vaccine), 5,199 (4.0%) were IS. IS participants were older with more comorbidities (Table 1), as well as higher hospitalization rates (Fig. 1). Among the unvaccinated group, RSV-related RTD hospitalization rates were >9 times higher among IS persons (9.26; 4.96/0.5) (Fig. 2). Incidence of RSV-related RTD was lower in the RSVpreF group than in the no-vaccination group, with consistent effects regardless of baseline IS status (1.85 events vs. 4.68 events per 1000 person-years (PY); vaccine effectiveness (VE) 60.5% [95% CI: -147.3 to 96.1] in participants with IS compared with 0.04 events vs. 0.50 events per 1000 PY; VE 92.3% [95% CI: 48.8 to 99.8] in those without; pinteraction = 0.22). Consistent beneficial effects on hospitalization rates for were observed in the RSVpreF group vs no vaccine for other outcomes (p for interaction >0.05 for all). In adults ≥60 years, RSVpreF vaccination reduced hospitalizations for RSV-related cardio-respiratory disease, with consistent effects across immunosuppression subgroups. High rates of severe RSV related disease support the need for vaccination in this population. All Authors: No reported disclosures
Background Heart failure (HF) and frailty often coexist. However, it is unknown how the interplay between HF and frailty at HF onset impacts prognosis of frail patients with HF and how this has evolved over time.Methods and Results We identified 131 235 patients with new-onset HF (median age 74 years, 39.7% women) from Danish nationwide registers in 1999 to 2017. Stratification according to the Hospital Frailty Risk Score resulted in (1) 102 635 (78%) nonfrail, (2) 26 054 (20%) moderately frail, and (3) 2609 (2%) severely frail patients. The proportion of moderately frail patients increased from 13.2% to 24.9%. Five-year absolute risks of all-cause mortality, HF hospitalization, and non-HF hospitalization were calculated using the Kaplan-Meier and Aalen-Johansen estimators. From 1999 to 2002 to 2003 to 2017, all-cause mortality risk (95% CI) declined from 56.4% (55.8%-57.0%) to 33.3% (32.6%-34.1%), 79.8% (78.5%-81.0%) to 58.6% (57.2%-60.1%), and 90.8% (85.6%-96.0%) to 79.8% (76.4%-83.2%) in nonfrail, moderately frail, and severely frail patients, respectively. HF hospitalization risk remained almost constant over the study period. Non-HF hospitalization risk declined from 74.0% (73.5%-74.5%) to 65.8% (65.0%-66.5%) in nonfrail patients and remained stable overall in moderately frail and severely frail patients over the study period.Conclusions We observed an increase in frail patients. Mortality decreased for all frailty groups but remained high for severely frail patients. These findings indicate the need for further evidence on the optimization of care for frail patients with HF, and future research should address the development of comprehensive management strategies, integrating frailty assessment into standard clinical care and focused care for older patients with HF.
