Comparative evaluation of serological tests used for the diagnosis of rickettsial diseases prevalent in the temperate region of North India

PurposeThe clinical manifestations of rickettsial diseases mimic other endemic infections with similar presentations thus posing a serious challenge to clinicians for their diagnosis. For the diagnosis of rickettsial disease serological tests like Weil Felix, ELISA and IFA are used. There are limited studies that have evaluated different serological tests for the diagnosis of rickettsial diseases. Therefore, the present study was undertaken to evaluate the ELISA and Weil Felix test for the diagnosis of rickettsial diseases prevalent in this region.MethodsSamples from 281 patients clinically suspected of rickettsial diseases were tested for spotted fever group (SFG), typhus group (TG) and scrub typhus group (STG) by Weil Felix, ELISA and IFA was taken as the gold standard. Baseline titers and cut-off ODs were calculated by taking samples from healthy blood donors.ResultsThe sensitivity, specificity, positive and negative predictive value of Weil Felix test ranged from 30% to 44%, 83.46%–97.86%, 9%–77%, 92–96% respectively. The sensitivity and specificity, positive and negative predictive value of ELISA ranged from 80.77% to 96.15%, 96.33%–98.43%, 70.21%–88.64%, 92.89%–99.60% respectively. Maximum cross-reactions were observed between SFG and STG by the Weil Felix test and between STG and TG by ELISA.ConclusionsELISA was found to be sensitive and specific for the diagnosis of rickettsial diseases. It is easy to perform, does not require a technical expert for result interpretation and a large number of samples can be processed at a time.     

Risk as a pattern over time: Delineation of time-dependent risk factors in biological,psychological, and social variables in cancer patients

Background

Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.

Methods

Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.

Results

The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.

Conclusions

The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care.     

Calculation of the Biological Efficiency of the Proton Component from 14.8 MeV Neutron Irradiation in Computational Biology with Help of Video Cards

Bulletin of Experimental Biology and Medicine - Fast neutron therapy, which previously has demonstrated effective results, but along with a large number of complications, can again be considered a...     

Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T

Quantitative susceptibility mapping (QSM) has the potential for being a biomarker for various diseases because of its ability to measure tissue susceptibility related to iron deposition, myelin, and hemorrhage from the phase signal of a T₂*-weighted MRI. Despite its promise as a quantitative marker, QSM is faced with many challenges, including its dependence on preprocessing of the raw phase data, the relatively weak tissue signal, and the inherently ill posed relationship between the magnetic dipole and measured phase. The goal of this study was to evaluate the effects of background field removal and dipole inversion algorithms on noise characteristics, image uniformity, and structural contrast for cerebral microbleed (CMB) quantification at both 3T and 7T. We selected four widely used background phase removal and five dipole field inversion algorithms for QSM and applied them to volunteers and patients with CMBs, who were scanned at two different field strengths, with ground truth QSM reference calculated using multiple orientation scans. 7T MRI provided QSM images with lower noise than did 3T MRI. QSIP and VSHARP + iLSQR achieved the highest white matter homogeneity and vein contrast, with QSIP also providing the highest CMB contrast. Compared with ground truth COSMOS QSM images, overall good correlations between susceptibility values of dipole inversion algorithms and the COSMOS reference were observed in basal ganglia regions, with VSHARP + iLSQR achieving the susceptibility values most similar to COSMOS across all regions. This study can provide guidance for selecting the most appropriate QSM processing pipeline based on the application of interest and scanner field strength.     

Intraoperative transösophageale Echokardiographie als Notfalldiagnostik bei nichtkardiochirurgischen Patienten

Die Anaesthesiologie - Durch die Entwicklung von kompakten und mobileren Geräten ist der Einsatz der transösophagealen Echokardiographie (TEE) als Point-of-care-Diagnostikum in...