Lahr, Brian D.

AbstractCytomegalovirus (CMV) pneumonia causes major morbidity and mortality. Its diagnosis requires demonstration of viral cytopathic changes in tissue, entailing risks of lung biopsy. This study aimed to determine CMV viral load (VL) thresholds in bronchoalveolar lavage fluid (BALF) for diagnosis of CMV pneumonia in immunocompromised patients. CMV VL in BALF was studied in 17 patients (83% transplant recipients) and 21 control subjects with and without CMV pneumonia, respectively, using an FDA‐approved PCR assay (Cobas® AmpliPrep/Cobas TaqMan® CMV Test, Roche Molecular Systems, Inc.) calibrated to the WHO International Standard for CMV DNA (NIBSC: 09/162). Receiver operating characteristic curve analysis produced a BALF CMV VL threshold of 34 800, IU/mL with 91.7% sensitivity and 100.0% specificity for diagnosis of possible, probable, and proven CMV pneumonia in transplant patients, while a threshold of 656 000 IU/mL yielded 100% sensitivity and specificity among biopsy‐proven cases. For all immunocompromised patients, a VL threshold of 274 IU/mL was selected. VL thresholds also were normalized to BALF cell count yielding a threshold of 0.32 IU/106 cells with 91.7% sensitivity and 90.5% specificity for possible, probable, and proven CMV pneumonia in transplant recipients. Monitoring CMV VL in BALF may be a less invasive method for diagnosing CMV pneumonia in immunocompromised patients.

Wait times have increased for patients approved for heart transplants. We reviewed United Network for Organ Sharing (UNOS) data for 14,242 patients listed for isolated heart transplant (2009–2013) to develop a risk score model for timing left ventricular assist device (LVAD) implantation in bridge-to-transplant patients. We used a multivariable Cox proportional hazards regression model with subsequent bootstrap resampling for internal validation to develop a scoring system that combined risk factors, weighted by the corresponding regression coefficients, to define an individual’s risk score. Four risk factors were identified (body mass index, blood type, region, and urgency status) to be significantly and independently associated with wait time (p < 0.001), showing adequate model discrimination (C = 0.704) and calibration. Higher risk scores correlated with shorter wait times. Our model corresponded closely with observed transplant rates, predicting longer wait times for lower status, larger size, certain blood groups, and some UNOS regions. This tool has the potential to more accurately describe the wait-time duration for an individual patient, which may influence care decisions. The wait-time discrepancies (blood types/regions) reinforce the need to reevaluate the geographic-allocation policy. The proposed review of the UNOS heart allocation policy may make this model especially relevant.

Abstract Objective: This study determined whether two different formulations of hormone therapy (HT): oral conjugated equine estrogens (o-CEE; 0.45 mg/d, n = 209), transdermal 17β-estradiol (t-E2; 50 μg/d, n = 201) plus cyclic progesterone (Prometrium, 200 mg) or placebo (PBO, n = 243) affected sleep domains in participants of the Kronos Early Estrogen Prevention Study. Methods: Participants completed the Pittsburgh Sleep Quality Index at baseline and during the intervention at 6, 18, 36, and 48 months. Global sleep quality and individual sleep domain scores were compared between treatments using analysis of covariance, and correlated with vasomotor symptom (VMS) scores using Spearman correlation coefficients. Results: Global Pittsburgh Sleep Quality Index scores (mean 6.3; 24% with score >8) were similar across groups at baseline and were reduced (improved sleep quality) by both HT (average change −1.27 [o-CEE] and −1.32 [t-E2]) when compared with PBO (−0.60; P = 0.001 [o-CEE vs PBO] and P = 0.002 [t-E2 vs PBO]). Domain scores for sleep satisfaction and latency improved with both HT. The domain score for sleep disturbances improved more with t-E2 than o-CEE or PBO. Global sleep scores significantly correlated with VMS severity (r s = 0.170, P < 0.001 for hot flashes; r s = 0.177, P < 0.001 for night sweats). Change in scores for all domains except sleep latency and sleep efficiency correlated with change in severity of VMS. Conclusions: Poor sleep quality is common in recently menopausal women. Sleep quality improved with both HT formulations. The relationship of VMS with domains of sleep suggests that assessing severity of symptoms and domains of sleep may help direct therapy to improve sleep for postmenopausal women.

Abstract Background Quantification of cytomegalovirus (CMV) deoxyribonucleic acid (DNA) has important diagnostic, prognostic, and therapeutic implications in the management of transplant recipients. We aimed to assess a viral load in plasma and whole blood that distinguishes CMV disease from asymptomatic infection in a cohort of solid organ and hematopoietic stem cell transplantation. Methods We prospectively measured and compared CMV viral load in paired plasma and whole blood samples collected from transplant recipients with CMV infection and disease. Cytomegalovirus viral loads were determined by a commercially available US Food and Drug Administration-approved quantitative assay (COBAS AmpliPrep/COBAS TaqMan CMV Test [CAP/CTM CMV]) calibrated to the first World Health Organization International Standard for CMV DNA quantification. Results Moderate agreement of CMV viral load was observed between plasma and whole blood, with 31% of samples having discordant findings, particularly among samples with low DNA levels. Among the subset of samples where both paired samples had quantifiable levels, we observed a systematic bias that reflected higher viral load in whole blood compared with plasma. Based on receiver operating curve analysis, an initial plasma CMV viral load threshold of 1700 IU/mL in solid organ transplant recipients (sensitivity 80%, specificity 74%) and 1350 IU/mL in allogeneic hematopoietic stem cell transplant recipients (sensitivity 87%, specificity 87%) distinguished CMV disease and asymptomatic infection. Conclusions This study identifies standardized viral load thresholds that distinguish CMV disease from asymptomatic infection using CAP/CTM CMV assay. We propose these thresholds as potential triggers to be evaluated in prospective studies of preemptive therapy. Plasma was better than whole blood for measuring viral load using the CAP/CTM CMV assay.

The epidemiology of infections after living donor liver transplantation (LDLT) is limited. We aimed to study the epidemiology and risk factors of infections after LDLT. The medical records of 223 adult patients who underwent LDLT from January 1, 2000 to August 31, 2015 were reviewed for all infections occurring up to 1 year. We estimated the cumulative incidence of infection using the Kaplan‐Meier product limit method. Risk factors were analyzed with time‐dependent Cox regression modeling. The majority of patients were Caucasian (94.6%) and male (64.6%), and the median age at transplantation was 55 years. The most common indication for transplantation was primary sclerosing cholangitis (37.7%). A total of 122 patients developed an infection during the follow‐up period (1‐year cumulative event rate of 56%), with the majority (66%) of these occurring within 30 days after transplantation.Enterococcus sp. was the most frequent pathogen identified. Multivariate analysis showed that increased Model for End‐Stage Liver Disease (MELD) score (per 10‐point change: hazard ratio [HR], 1.59), history of recurrent infections prior to transplant (HR, 2.01), Roux‐en‐Y anastomosis (HR, 2.37), increased log‐number of packed red blood cell transfusions (HR, 1.39), and biliary complications (HR, 4.26) were independently associated with a higher risk of infection. Infections occur commonly after LDLT, with most infections occurring early and being related to the hepatobiliary system. Higher MELD scores, the type of biliary anastomosis, presence of biliary complications, and prior pretransplant infections are independently associated with a higher risk for infections.Liver Transplantation 23 465–4772017 AASLD.