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AbstractBackgroundKidney transplant recipients are at increased risk for invasive aspergillosis (IA), a disease with poor outcomes and substantial economic burden. We aimed to determine risk factors for posttransplant IA by using a national database and to assess the association of IA with mortality and allograft failure.MethodsUsing the United States Renal Data System database, we performed a retrospective case-control study of patients who underwent kidney transplant from 1998 through 2017. To evaluate risk factors for IA, we performed conditional logistic regression analysis by comparing characteristics between IA-infected patients and their matched uninfected controls. We performed Cox regression analysis to evaluate the effects of IA on mortality and death-censored allograft failure.ResultsWe matched 359 patients with IA to 1436 uninfected controls (1:4). IA was diagnosed at a median of 22.5 months (interquartile range, 5.4–85.2 months) after kidney transplant. Risk factors for IA were Black/African American race, duration of pretransplant hemodialysis, higher Elixhauser Comorbidity Index score, weight loss, chronic pulmonary disease, need for early posttransplant hemodialysis, and a history of cytomegalovirus infection. Receiving an allograft from a living donor was protective against IA. IA was a strong independent predictor of 1-year mortality (adjusted hazard ratio [aHR], 5.02 [95% confidence interval {CI}, 3.58–7.04], P < .001). Additionally, IA was associated with 1-year allograft failure (aHR, 3.37 [95% CI, 1.96–5.77], P < .001).ConclusionsOur findings emphasize the importance of timely transplant to mitigate the risk of posttransplant IA. An individualized approach to disease prevention is essential to decrease mortality and allograft failure.

ImportanceLate-onset meningitis (LOM) has been associated with adverse neurodevelopmental outcomes in children born extremely preterm.ObjectiveTo report the incidence of LOM during birth hospitalization and neurodevelopmental outcomes at 18 to 26 months’ corrected age.Design, Setting, and ParticipantsThis cohort study is a secondary analysis of a multicenter prospective cohort of children born at 22 to 26 weeks’ gestation between 2003 and 2017 with follow-up from 2004 to 2021. The study was conducted at 25 Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers.ExposuresCulture-confirmed LOM.Main Outcomes and MeasuresIncidence and microbiology of LOM (2003-2017); lumbar puncture (LP) performance in late-onset sepsis (LOS) evaluations (2011-2017); composite outcome of death or neurodevelopmental impairment (NDI; 2004-2021).ResultsAmong 13 372 infants (median [IQR] gestational age, 25.4 [24.4-26.1] weeks; 6864 [51%] boys), LOM was diagnosed in 167 (1%); LOS without LOM in 4564 (34%); and neither LOS nor LOM in 8641 (65%). The observed incidence of LOM decreased from 2% (95% CI, 1%-3%) in 2003 to 0.4% (95% CI, 0.7%-1.0%) in 2017 (P < .001). LP performance in LOS evaluations decreased from 36% (95% CI, 33%-40%) in 2011 to 24% (95% CI, 21%-27%) in 2017 (P < .001). Among infants with culture-confirmed LOS, LP performance decreased from 58% (95% CI, 51%-65%) to 45% (95% CI, 38%-51%; P = .008). LP performance varied by center among all LOS evaluations (10%-59%, P < .001) and among those with culture-confirmed LOS (23%-79%, P < .001). LOM occurred in the absence of concurrent LOS in 27 of 167 cases (16%). The most common LOM isolates were coagulase-negative Staphylococcus (98 [59%]), Candida albicans (38 [23%]), and Escherichia coli (27 [16%]). Death or NDI occurred in 22 of 46 children (48%) with LOM due to coagulase-negative Staphylococcus, 43 of 67 (64%) due to all other bacterial pathogens, and 26 of 33 (79%) due to fungal pathogens. The adjusted relative risk of death or NDI was increased among children with LOM (aOR, 1.53; 95% CI, 1.04-2.25) and among those with LOS without LOM (aOR, 1.41; 95% CI, 1.29-1.54) compared with children with neither infection.Conclusions and RelevanceIn this cohort study, LP was performed with decreasing frequency, and the observed incidence of LOM also decreased. Both LOM and LOS were associated with increased risk of death or NDI; risk varied by LOM pathogen. The full association of LOM with outcomes of children born extremely preterm may be underestimated by current diagnostic practices.

Abstract Objective To determine COVID-19 vaccine-related adverse events (AEs) in the seven-day post-vaccination period in patients with SLE vs autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HC). Methods Data were captured through the COVID-19 Vaccination in Autoimmune Diseases (COVAD) questionnaire (March–December 2021). Multivariable regression models accounted for age, gender, ethnicity, vaccine type and background treatment. Results Among 9462 complete respondents, 583 (6.2%) were SLE patients (mean age: 40.1 years; 94.5% females; 40.5% Asian; 42.9% Pfizer-recipients). Minor AEs were reported by 83.0% of SLE patients, major by 2.6%, hospitalization by 0.2%. AE and hospitalization frequencies were similar between patients with active and inactive SLE. Rashes were more frequent in SLE patients vs HC (OR; 95% CI: 1.2; 1.0, 1.5), chills less frequent in SLE vs AIRDs (0.6; 0.4, 0.8) and nrAIDs (0.5; 0.3, 0.8), and fatigue less frequent in SLE vs nrAIDs (0.6; 0.4, 0.9). Pfizer-recipients reported higher overall AE (2.2; 1.1, 4.2) and injection site pain (2.9; 1.6, 5.0) frequencies than recipients of other vaccines, Oxford/AstraZeneca-recipients more body ache, fever, chills (OR: 2.5, 3.0), Moderna-recipients more body ache, fever, chills, rashes (OR: 2.6, 4.3). Hospitalization frequencies were similar across vaccine types. AE frequencies were similar across treatment groups, although chills were less frequent in antimalarial users vs non-users (0.5; 0.3, 0.9). Conclusion While COVID-19 vaccination-related AEs were reported by four-fifths of SLE patients, those were mostly minor and comparable to AEs reported by healthy individuals, providing reassurance regarding COVID-19 vaccination safety in SLE.

AbstractBackgroundAccurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs.ObjectiveDevelop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG.MethodsWe developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data. In Part 1, a derivation cohort was used to evaluate five different classification models: logistic regression (LR), artificial neural network (ANN), Random Forests [RF], support vector machine (SVM), and ensemble learning (EL). In Part 2, a separate validation cohort was used to prospectively evaluate the performance of two LR models using parameters generated from the WCT ECG alone (Solo Model) and paired WCT and baseline ECGs (Paired Model).ResultsOf the 421 patients of the derivation cohort (Part 1), a favorable area under the receiver operating characteristic curve (AUC) by all modeling subtypes: LR (0.96), ANN (0.96), RF (0.96), SVM (0.96), and EL (0.97). Of the 235 patients of the validation cohort (Part 2), the Solo Model and Paired Model achieved a favorable AUC for 103 patients with (Solo Model 0.87; Paired Model 0.95) and 132 patients without (Solo Model 0.84; Paired Model 0.95) a corroborating electrophysiology procedure or intracardiac device recording.ConclusionAccurate WCT differentiation may be accomplished using computerized data of (i) the WCT ECG alone and (ii) paired WCT and baseline ECGs.

Abstract The advent of single-cell biology opens a new chapter for understanding human biological processes and for diagnosing, monitoring, and treating disease. This revolution now reaches the field of cardiovascular disease (CVD). New technologies to interrogate CVD samples at single-cell resolution are allowing the identification of novel cell communities that are important in shaping disease development and direct towards new therapeutic strategies. These approaches have begun to revolutionize atherosclerosis pathology and redraw our understanding of disease development. This review discusses the state-of-the-art of single-cell analysis of atherosclerotic plaques, with a particular focus on human lesions, and presents the current resolution of cellular subpopulations and their heterogeneity and plasticity in relation to clinically relevant features. Opportunities and pitfalls of current technologies as well as the clinical impact of single-cell technologies in CVD patient care are highlighted, advocating for multidisciplinary and international collaborative efforts to join the cellular dots of CVD.

Abstract Background Mycoplasma hominis, Ureaplasma urealyticum, and Ureaplasma parvum may cause post-transplant infections in lung transplant recipients. We evaluated routine pretransplant screening for these Mollicutes. Methods We retrospectively reviewed records of lung transplant recipients at our tri-site institution from 01/01/2015 to 11/15/2019. M. hominis and/or Ureaplasma polymerase chain reaction (PCR) was performed on pretransplant recipient urine specimens and donor bronchial swabs at the time of transplantation. Development of Mollicute infection and hyperammonemia syndrome (HS) was recorded. Results A total of 268 patients underwent lung transplantation during the study period, of whom 105 were screened with at least 1 Mollicute PCR. Twelve (11%) screened positive; 10 donors, 1 recipient, and 1 both. Among positive donors, 3 were positive for M. hominis, 5 for U. urealyticum, and 4 for U. parvum. Preemptive therapy included doxycycline, levofloxacin, and/or azithromycin administered for 1–12 weeks. Despite therapy, 1 case of M. hominis mediastinitis and 1 case of HS associated with Ureaplasma infection occurred, both donor-derived. Of those screened before transplant, cases with positive screening were more likely (P < 0.05) to develop Mollicute infection despite treatment (2/12, 17%) than those who screened negative (1/93, 1%). Conclusions Pretransplant recipient urine screening had a low yield and was not correlated with post-transplant Mollicute infection, likely because most M. hominis and U. parvum/urealyticum infections in lung transplant recipients are donor-derived. Routine donor bronchus swab PCR for M. hominis, U. urealyticum, and U. parvum followed by preemptive therapy did not obviously impact the overall incidence of Mollicute infection or HS in this cohort.