PCR colorimetric dot-blot assay and clinical pretest probability for diagnosis of Pulmonary Tuberculosis in Smear-Negative patients

Abstract Background Smear-negative pulmonary tuberculosis (SNPTB) accounts for 30% of Pulmonary Tuberculosis (PTB) cases reported annually in developing nations. Polymerase chain reaction (PCR) may provide an alternative for the rapid detection of Mycobacterium tuberculosis (MTB); however little data are available regarding the clinical utility of PCR in SNPTB, in a setting with a high burden of TB/HIV co-infection. Methods To evaluate the performance of the PCR dot-blot in parallel with pretest probability (Clinical Suspicion) in patients suspected of having SNPTB, a prospective study of 213 individuals with clinical and radiological suspicion of SNPTB was carried out from May 2003 to May 2004, in a TB/HIV reference hospital. Respiratory specialists estimated the pretest probability of active disease into high, intermediate, low categories. Expectorated sputum was examined by direct microscopy (Ziehl-Neelsen staining), culture (Lowenstein Jensen) and PCR dot-blot. Gold standard was based on culture positivity combined with the clinical definition of PTB. Results In smear-negative and HIV subjects, active PTB was diagnosed in 28.4% (43/151) and 42.2% (19/45), respectively. In the high, intermediate and low pretest probability categories active PTB was diagnosed in 67.4% (31/46), 24% (6/25), 7.5% (6/80), respectively. PCR had sensitivity of 65% (CI 95%: 50%–78%) and specificity of 83% (CI 95%: 75%–89%). There was no difference in the sensitivity of PCR in relation to HIV status. PCR sensitivity and specificity among non-previously TB treated and those treated in the past were, respectively: 69%, 43%, 85% and 80%. The high pretest probability, when used as a diagnostic test, had sensitivity of 72% (CI 95%:57%–84%) and specificity of 86% (CI 95%:78%–92%). Using the PCR dot-blot in parallel with high pretest probability as a diagnostic test, sensitivity, specificity, positive and negative predictive values were: 90%, 71%, 75%, and 88%, respectively. Among non-previously TB treated and HIV subjects, this approach had sensitivity, specificity, positive and negative predictive values of 91%, 79%, 81%, 90%, and 90%, 65%, 72%, 88%, respectively. Conclusion PCR dot-blot associated with a high clinical suspicion may provide an important contribution to the diagnosis of SNPTB mainly in patients that have not been previously treated attended at a TB/HIV reference hospital.

THE NEGATIVE EFFECTS OF ALCOHOL HANGOVER ON HIGH-ANXIETY PHENOTYPE RATS ARE INFLUENCED BY THE GLUTAMATE RECEPTORS OF THE DORSAL MIDBRAIN

Alcoholism is a chronic disorder characterized by the appearance of a withdrawal syndrome following the abrupt cessation of alcohol intake that includes symptoms of physical and emotional disturbances, anxiety being the most prevalent symptom. In humans, it was shown that anxiety may increase the probability of relapse. In laboratory animals, however, the use of anxiety to predict alcohol preference has remained difficult. Excitatory amino acids as glutamate have been implicated in alcohol hangover and may be responsible for the seizures and anxiety observed during withdrawal. The dorsal periaqueductal gray (DPAG) is a midbrain region critical for the modulation/expression of anxiety- and fear-related behaviors and the propagation of seizures induced by alcohol withdrawal, the glutamate neurotransmission being one of the most affected. The present study was designed to evaluate whether low- (LA) and high-anxiety rats (HA), tested during the alcohol hangover phase, in which anxiety is the most prevalent symptom, are more sensitive to the reinforcing effects of alcohol when tested in a voluntary alcohol drinking procedure. Additionally, we were interested in investigating the main effects of reducing the excitatory tonus of the dorsal midbrain, after the blockade of the ionotropic glutamate receptors into the DPAG, on the voluntary alcohol intake of HA and LA motivated rats that were made previously experienced with the free operant response of alcohol drinking. For this purpose, we used local infusions of the N-metil D-Aspartato (NMDA) and alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-kainate receptors antagonist DL-2-Amino-7-phosphonoheptanoic acid - DL-AP7 (10 nmol/0.2 mu l) and L-glutamic acid diethyl ester - GDEE (160 nmol/0.2 mu l) respectively. Alcohol intoxication was produced by 10 daily bolus intraperitonial (IP) injections of alcohol (2.0 g/kg). Peak-blood alcohol levels were determined by gas-chromatography analysis in order to assess blood-alcohol content. Unconditioned and conditioned anxiety-like behavior was assessed by the use of the fear-potentiated startle procedure (FPS). Data collected showed that anxiety and alcohol drinking in HA animals are positively correlated in animals that were made previously familiarized with the anxiolytic effects of alcohol. In addition, anxiety-like behavior induced during alcohol hangover seems to be an effect of changes in glutamatergic neurotransmission into DPAG possibly involving AMPA/kainate and NMDA receptors, among others. (C) 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.