hominis in isolates from two HIV-infected patients and two patients with ALL (Table 2). The age of Cryptosporidium

infected patients ranged from 29 to 54 years, with a mean of 40.8 ± 0.5 years. Most patients were male (81.8%); of the two infected female patients one had HIV and the other had received a bone marrow transplant. We identified concurrent microbial infections in 5 of 11 patients, all of whom were HIV positive. The mean number of CD4 + T-lymphocytes (cells/mm3) in Cryptosporidium infected individuals was 228.7 Rucaparib ± 1.8; only four HIV positive patients had <100 cells/mm3 (P < 0.0001) (Table 2). Results of univariate analysis are shown in Table 3. We found significant correlations between Cryptosporidium infection and CD4 + cell counts < 100 cells/mm3 (P <

0.0001); diarrhea in household members (P < 0.002) and concomitant microbial infections (P < 0.006). In addition, the presence of diarrhea (P < 0.003), weight loss (P < 0.0001), abdominal pain (P= 0.001), dehydration (P < 0.0001), vomiting (P < 0.015) and nausea (P = 0.001) were significantly predictive of cryptosporidiosis (Table 3). We found no significant association with age, sex, type of diarrhea, fever, contact with pet or farm animals, exposure to lake, river or swimming pool water, type of drinking water and location of dwelling (Table 3). For the multivariate analysis, we used cryptosporidiosis as the main outcome and the significant variables according to univariate analysis selleck products after assessment by the Wald test as explanatory variables. Patients with cryptosporidiosis had a higher risk of developing diarrhea, weight Bortezomib nmr loss and abdominal pain. Most risk factors showing individually significant associations with cryptosporidiosis become non-significant when included in a multivariate model. Exclusion of these factors from the model one at a time did not affect its coefficients, as confirmed by the likelihood ratio test. The best fitting model was

the variable ‘diarrhea of household members’ versus ‘CD4 + cell count < 100 cells/mm3)’ (likelihood ratio test 34.52; 1 d.f.; P < 0.0001). Table 4 shows the model with two variables and Table 5 the final model with only one variable. Only ‘CD4 + <100 cells/mm3)’ maintained a significant association with infection. We found that Cryptosporidium infection was present in 14.9% of patients with AIDS/HIV, 4.6% with ALL, 5.5% with CLL and 7.7% of bone marrow transplant patients, with an overall prevalence of 6% in this sample of immunocompromised patients in Iran. There are few published studies concerning Cryptosporidium infection in Iranian immunocompromised patients. Nahrevanian et al. reported Cryptosporidium infection in 8.7% of AIDS patients and 2.3% of patients with hematological malignancies, with an overall 1.4% prevalence in immunocompromised patients attending 10 health centers in Iran (14). Zali et al.