Liver Retransplantation in Patients With HIV-1 Infection: An International Multicenter Cohort Study

Liver retransplantation is performed in HIV-infected patients, although its outcome is not well known. In an international cohort study (eight countries), 37 (6%; 32 coinfected with hepatitis C virus [HCV] and five with hepatitis B virus [HBV]) of 600 HIV-infected patients who had undergone liver transplant were retransplanted. The main indications for retransplantation were vascular complications (35%), primary graft nonfunction (22%), rejection (19%), and HCV recurrence (13%). Overall, 19 patients (51%) died after retransplantation. Survival at 1, 3, and 5 years was 56%, 51%, and 51%, respectively. Among patients with HCV coinfection, HCV RNA replication status at retransplantation was the only significant prognostic factor. Patients with undetectable versus detectable HCV RNA had a survival probability of 80% versus 39% at 1 year and 80% versus 30% at 3 and 5 years (p = 0.025). Recurrence of hepatitis C was the main cause of death in the latter. Patients with HBV coinfection had survival of 80% at 1, 3, and 5 years after retransplantation. HIV infection was adequately controlled with antiretroviral therapy. In conclusion, liver retransplantation is an acceptable option for HIV-infected patients with HBV or HCV coinfection but undetectable HCV RNA. Retransplantation in patients with HCV replication should be reassessed prospectively in the era of new direct antiviral agents.

Early molecular diagnosis of acute Chagas disease after transplantation with organs from Trypanosoma cruzi-infected donors

Organ transplantation (TX) is a novel transmission modality of Chagas disease. The results of molecular diagnosis and characterization of Trypanosoma cruzi acute infection in naïve TX recipients transplanted with organs from infected deceased donors are reported. Peripheral blood and cerebrospinal fluid samples from the TX recipients of organs from infected donors were prospectively and sequentially studied for detection of T. cruzi by means of kinetoplastid DNA polymerase chain reaction (kDNA-PCR). In positive blood samples, a PCR algorithm for identification of T. cruzi Discrete Typing Units (DTUs) and quantitative real-time PCR (qPCR) to quantify parasitic loads were performed. Minicircle signatures of T. cruzi infecting populations were also analyzed using restriction fragment length polymorphism (RFLP)-PCR. Eight seronegative TX recipients from four infected donors were studied. In five, the infection was detected at 68.4 days post-TX (36-98 days). In one case, it was transmitted to two of three TX recipients. The comparison of the minicircle signatures revealed nearly identical RFLP-PCR profiles, confirming a common source of infection. The five cases were infected by DTU TcV. This report reveals the relevance of systematic monitoring of TX recipients using PCR strategies in order to provide an early diagnosis allowing timely anti-trypanosomal treatment.

HIV Lipodystrophy Case Definition using Artificial Neural Network Modelling

Objective

A case definition of HIV lipodystrophy has recently been developed from a combination of clinical, metabolic and imaging/body composition variables using logistic regression methods. We aimed to evaluate whether artificial neural networks could improve the diagnostic accuracy.

Methods

The database of the case-control Lipodystrophy Case Definition Study was split into 504 subjects (265 with and 239 without lipodystrophy) used for training and 284 independent subjects (152 with and 132 without lipodystrophy) used for validation. Back-propagation neural networks with one or two middle layers were trained and validated. Results were compared against logistic regression models using the same information.

Results

Neural networks using clinical variables only (41 items) achieved consistently superior performance than logistic regression in terms of specificity, overall accuracy and area under the ROC curve. Their average sensitivity and specificity were 72.4 and 71.2%, as compared with 73.0 and 62.9% for logistic regression, respectively (area under the ROC curve, 0.784 vs 0.748). The discriminating performance of the neural networks was largely unaffected when built excluding 13 parameters that patients may not have readily available. The average sensitivity and specificity of the neural networks remained the same when metabolic variables were also considered (total 60 items) without a clear advantage against logistic regression (overall accuracy 71.8%). The performance of networks considering also body composition variables was similar to that of logistic regression (overall accuracy 78.5% for both).

Conclusions

Neural networks may offer a means to improve the discriminating performance for HIV lipodystrophy, when only clinical data are available and a rapid approximate diagnostic decision is needed. In this context, information on metabolic parameters is apparently not helpful in improving the diagnosis of HIV lipodystrophy, unless imaging and body composition studies are also obtained.

Streptococcus pyomyositis occurring in a patient with dermatomyositis in a country with temperate climate

We describe a man in whom pyomyositis developed in a temperate climate. Three facts make this case unique. First the pyomyositis developed in someone with underlying dermatomyositis, this being the second reported case to our knowledge. Second, the organism involved was a Streptococcus and not a Staphylococcus as in most cases described, and the course of the disease was acute and not subacute as is usually reported. Finally, contrary to most described cases, surgical drainage was not necessary, probably because of the early diagnosis. Pyomyositis should be considered a possible cause of localized pain in patients with underlying inflammatory muscle disease.