Establishment of Brucellosis Relapse and Complications Registry: A Study Protocol

Brucellosis is an endemic bacterial zoonotic disease in developing countries; that is a serious public health problem in Iran. Brucellosis is a life-threatening multi-system disease in human with different clinical manifestations, complications and relapse. The incidence of brucellosis in Hamadan province, west of Iran is high. In addition, there is few reliable and population-based studies regarding relapse and complications of brucellosis in developing countries, therefore establishment of the registry system in areas with adequate occurrence of cases is needed to better understand the predictors of brucellosis relapse and complications and management of the disease. Detecting occurrence of relapse and complications over time and by geographical area provide information for further investigations and identification of health system deficiencies in the management of patients

Comparison between doxycycline–rifampin–amikacin and doxycycline–rifampin regimens in the treatment of brucellosis

SummaryBackgroundCombination drug therapy of brucellosis leads to recovery of symptoms, shortening of symptomatic interval, and decrease in morbidity rate, but single drug therapy is associated with more relapse episodes and a higher rate of drug resistance. Different drug combinations have been evaluated in the treatment of brucellosis. Considering the failure of treatment and relatively high rate of relapse of the disease with the World Health Organization's (WHO) recommended therapeutic regimen, we evaluated a new regimen that we assumed would increase the success of treatment and decrease the rate of relapse. In this study we compare the standard regimen of the WHO, doxycycline–rifampin (DR), to triple therapy with doxycycline–rifampin–amikacin (ADR).MethodsTwo hundred and twenty-eight consecutive patients with brucellosis, who attended Hamedan Sina Hospital between 1999 and 2001, whether seen as outpatients or as inpatients, were enrolled in the study. The participants were randomly allocated to the DR group (receiving doxycycline 100mg twice a day and rifampin 10mg/kg body weight/day every morning, both taken orally for eight weeks) or the ADR group (receiving doxycycline 100mg twice a day and rifampin 10mg/kg body weight/day every morning, both taken orally for eight weeks, plus 7.5mg/kg amikacin intramuscularly twice a day for seven days). The patients were checked for the relief of symptoms, drug side-effects, and relapse of disease during the treatment and follow-up.ResultsOf the 228 patients enrolled, eight were withdrawn – four patients from the DR group and four from the ADR group. Of the remaining 220 participants (110 in the ADR group and 110 in the DR group), 107 were male (48.6%) and 113 were female (51.4%). Mean age was 35.7±17 years in the ADR group and 37±18.4 years in the DR group (p=0.5). In the DR group, 97 (88.2%) and in the ADR group, 106 (96.4%) of the patients had relief of symptoms (a significant difference by Chi-square test (p=0.04)). After completion of treatment, and at the sixth month follow-up, nine (9.3%) patients in the DR group and six (5.7%) in the ADR group experienced a relapse of the disease, with no significant difference (p=0.4). Mild side-effects were found in only 10 patients, and none required discontinuation of the therapeutic regimen. Of these patients, four were from DR group and six from ADR group; no significant difference was observed (p=0.7).ConclusionsGiven the fact that the ADR regimen had a higher efficacy and more rapid action in terms of relief of symptoms compared to the DR regimen, and that no significant difference in drug side-effects and disease relapse existed in the patients of either group, adding amikacin to the DR standard treatment regimen seems beneficial

Isolated hepatitis B core antibody in HIV infected patients--can response to hepatitis B vaccine help to elucidate the cause?

Background: Concomitant hepatitis B and HIV infections are common. In some of these patients, HBcAb is the only serologic marker of hepatitis B. This study was conducted to elucidate the cause of isolated HBcAb in HIV-infected patients via hepatitis B vaccination. Methods: In this interventional study during 2014-15 in the HIV Clinic in Hamadan, thirty four patients with HIV infection and isolated HBcAb positive isolate, received hepatitis B vaccine and their responses to vaccination were investigated. Demographic data, stage of disease, and status of CD4 and HCV Ab were extracted from the patients' medical records and were entered in a checklist. Results: Of the 103 HIV positive patients, the prevalence of HBs Ag, and HBc Ab isolates were 6.79% (n=7) and 46.6% (n=48), respectively. All of the patients with isolated HBcAb were positive for HCV Ab. Among the 48 patients with isolated HBc Ab, 34 (70.8%) were available and examined for HBV DNA in serum samples. The result of PCR was negative in all. After the first round of hepatitis B vaccination, HBs Ab titer exceeded 10 International Units Per Liter (IU/L) in 58.8% of patients with isolated HBc Ab. With the completion of the three-dose of vaccine, this titer was observed in 97% of patients. Significant correlation was observed between titer of antibodies and values of CD4 cells. Conclusions: Due to favorable response to hepatitis B vaccination in HIV positive patients with isolated HBc Ab, false positive HBc Ab and recovery from previous infection were more probable than hidden hepatitis B

Interpretable generalized neural additive models for mortality prediction of COVID-19 hospitalized patients in Hamadan, Iran

Abstract Background The high number of COVID-19 deaths is a serious threat to the world. Demographic and clinical biomarkers are significantly associated with the mortality risk of this disease. This study aimed to implement Generalized Neural Additive Model (GNAM) as an interpretable machine learning method to predict the COVID-19 mortality of patients. Methods This cohort study included 2181 COVID-19 patients admitted from February 2020 to July 2021 in Sina and Besat hospitals in Hamadan, west of Iran. A total of 22 baseline features including patients' demographic information and clinical biomarkers were collected. Four strategies including removing missing values, mean, K-Nearest Neighbor (KNN), and Multivariate Imputation by Chained Equations (MICE) imputation methods were used to deal with missing data. Firstly, the important features for predicting binary outcome (1: death, 0: recovery) were selected using the Random Forest (RF) method. Also, synthetic minority over-sampling technique (SMOTE) method was used for handling imbalanced data. Next, considering the selected features, the predictive performance of GNAM for predicting mortality outcome was compared with logistic regression, RF, generalized additive model (GAMs), gradient boosting decision tree (GBDT), and deep neural networks (DNNs) classification models. Each model trained on fifty different subsets of a train-test dataset to ensure a model performance. The average accuracy, F1-score and area under the curve (AUC) evaluation indices were used for comparison of the predictive performance of the models. Results Out of the 2181 COVID-19 patients, 624 died during hospitalization and 1557 recovered. The missing rate was 3 percent for each patient. The mean age of dead patients (71.17 ± 14.44 years) was statistically significant higher than recovered patients (58.25 ± 16.52 years). Based on RF, 10 features with the highest relative importance were selected as the best influential features; including blood urea nitrogen (BUN), lymphocytes (Lym), age, blood sugar (BS), serum glutamic-oxaloacetic transaminase (SGOT), monocytes (Mono), blood creatinine (CR), neutrophils (NUT), alkaline phosphatase (ALP) and hematocrit (HCT). The results of predictive performance comparisons showed GNAM with the mean accuracy, F1-score, and mean AUC in the test dataset of 0.847, 0.691, and 0.774, respectively, had the best performance. The smooth function graphs learned from the GNAM were descending for the Lym and ascending for the other important features. Conclusions Interpretable GNAM can perform well in predicting the mortality of COVID-19 patients. Therefore, the use of such a reliable model can help physicians to prioritize some important demographic and clinical biomarkers by identifying the effective features and the type of predictive trend in disease progression

Assessment of Health-related Quality of Life among Patients with Tuberculosis in Hamadan, Western Iran

Objectives: Tuberculosis is one of the oldest infections known to affect humans. The aim of the study was to assess the quality of life including physiological, general health perception and social role functioning among patients with tuberculosis in Hamadan, Western Iran. Methods: A cross sectional analytical study was conducted between December 2009 and March 2011, the quality of life scores of 64 tuberculosis cases were measured by SF-36 questionnaire before treatment, after the initial phase and at the end of treatment and were compared with those of 120 controls. The association of the quality of life with age, type of tuberculosis, sputum smear, duration of disease, and the stage of treatment were assessed among the patients. Results: Before treatment, all scores of tuberculosis patients were lower than those of the controls (p<0.05). The patients’ score increased significantly after two months of treatment (p=0.01), but the difference was not significant between two and six months after treatment (p=0.07). The lowest score in tuberculosis patients was related to physical functioning and energy (45 ± 42, 44 ± 24, respectively). Conclusion: According to the results, tuberculosis patients still have a low quality of life in spite of receiving new care strategies. Therefore, enhancement in quality of life may improve adherence to anti-tuberculosis treatment, functioning and well-being of patients with tuberculosis

Evaluation of Fibronectin and C-Reactive Protein Levels in Patients with Sepsis: A Case-Control Study

Sepsis is a significant health problem with an estimated 750,000 new cases in the USA annually. It is also the third leading cause of death in developed countries, equaling the number of fatalities from acute myocardial infarction. The high sepsis-related mortalities mean there is an urgent need to improve the diagnosis and management of sepsis patients. The aim of this study was the evaluation of fibronectin and C-reactive protein (CRP) plasma levels in patients with sepsis and other infectious diseases without sepsis. In a case-control study, 90 patients with sepsis and 90 patients with other infectious diseases without sepsis were studied. Serum levels of fibronectin and CRP were measured. The data were analyzed by SPSS version 15. The mean levels of fibronectin in the cases and controls were 288.97±89.10 mg/l and 341.24±110.53 mg/l respectively (P=0.001). The mean levels of CRP in the cases and controls were 89.42±54.05 µg/ml and 27.42±25.89 µg/ml respectively (P<0.001). Concerning the source of infection, the mean CRP levels were significantly higher in septic patients with urinary tract infection, pneumonia, and soft tissue infection (P<0.001). Decreased levels of fibronectin and increased levels of CRP may be considered as reliable diagnostic markers for sepsis. Also, CRP could be a better predictive factor for sepsis than fibronectin