Dataset Information

Quantitative serological antibody testing for suspected neuroborreliosis.

ABSTRACT: OBJECTIVE:To assess the importance of serum IgG/IgM antibody titers for the differentiation of Lyme neuroborreliosis (LNB) from its mimics. METHOD:This was a retrospective, cross-sectional study conducted at two German neurological centers. Serological parameters (ELISA or CLIA analysis) and clinical presentation of 28 patients with definite LNB were compared to those of 36 patients with neurological symptoms mimicking LNB (mimics). Analysis was performed using receiver operating characteristic (ROC) and binary logistic regression. RESULTS:Elevated IgG-titers had a high sensitivity for neuroborreliosis in both centers (0.95 and 1.0). The optimal cutoff-values were set to 26.35 in center A (ELISA), and 64.0 in center B (CLIA). Diagnostic specificity was 0.41 and 0.89 in this constellation. Elevated IgM-titers showed a high diagnostic specificity for a cutoff at 68.10 (A) and 47.95 (B) (0.93 and 0.89). Sensitivity was 0.45 and 0.5. Overall diagnostic accuracy was low in both centers (A: IgG AUC?=?0.665, IgM AUC?=?0.629; B: IgG AUC?=?0.917, IgM AUC?=?0.556). In logistic regression of antibody titers and clinical measures, prediction of LNB was significantly better than the "null hypothesis". Clinical measures showed the highest odds ratio. CONCLUSION:Data show that in addition to the clinical presentation of patients with symptoms suggesting central or peripheral nervous system manifestation, serum IgG- and IgM-titers help to identify LNB-patients. The results should guide physicians counseling patients with suspected LNB about further diagnostic steps and treatment.

SUBMITTER: Schneider C

PROVIDER: S-EPMC7184039 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Quantitative serological antibody testing for suspected neuroborreliosis.

Schneider Christian C Gielen Jörg J Röth Philip P Albrecht Philipp P Schroeter Michael M Fink Gereon R GR Wunderlich Gilbert G Lehmann Helmar C HC

Journal of neurology 20200201 5

<h4>Objective</h4>To assess the importance of serum IgG/IgM antibody titers for the differentiation of Lyme neuroborreliosis (LNB) from its mimics.<h4>Method</h4>This was a retrospective, cross-sectional study conducted at two German neurological centers. Serological parameters (ELISA or CLIA analysis) and clinical presentation of 28 patients with definite LNB were compared to those of 36 patients with neurological symptoms mimicking LNB (mimics). Analysis was performed using receiver operating ...[more]

PMID: 32008071

Similar Datasets

Project description:PurposeAnti-N-methyl- d -aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis.MethodsA retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors.ResultsTwenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ 2 (1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2 ) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated ( P = 0.04) with an increased likelihood of poor outcome.ConclusionsIn this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated.

Project description:Laboratory diagnosis of Lyme neuroborreliosis (LNB) is challenging, and validated diagnostic algorithms are lacking. Therefore, this retrospective cross-sectional study aimed to compare the diagnostic performance of seven commercial antibody assays for LNB diagnosis. Random forest (RF) modeling was conducted to investigate whether the diagnostic performance using the antibody assays could be improved by including several routine cerebrospinal fluid (CSF) parameters (i.e., leukocyte count, total protein, blood-CSF barrier functionality, and intrathecal total antibody synthesis), two-tier serology on serum, the CSF level of the B-cell chemokine (C-X-C motif) ligand 13 (CXCL13), and a Borrelia species PCR on CSF. In total, 156 patients were included who were classified as definite LNB (n = 10), possible LNB (n = 7), or non-LNB patient (n = 139) according to the criteria of the European Federation of Neurological Societies using a consensus strategy for intrathecal Borrelia-specific antibody synthesis. The seven antibody assays showed sensitivities ranging from 47.1% to 100% and specificities ranging from 95.7% to 100%. RF modeling demonstrated that the sensitivities of most antibody assays could be improved by including other parameters to the diagnostic repertoire for diagnosing LNB (range: 94.1% to 100%), although with slightly lower specificities (range: 92.8% to 96.4%). The most important parameters for LNB diagnosis are the detection of intrathecally produced Borrelia-specific antibodies, two-tier serology on serum, CSF-CXCL13, Reibergram classification, and pleocytosis. In conclusion, this study shows that LNB diagnosis is best supported using multiparameter analysis. Furthermore, a collaborative prospective study is proposed to investigate if a standardized diagnostic algorithm can be developed for improved LNB diagnosis. IMPORTANCE The diagnosis of LNB is established by clinical symptoms, pleocytosis, and proof of intrathecal synthesis of Borrelia-specific antibodies. Laboratory diagnosis of LNB is challenging, and validated diagnostic algorithms are lacking. Therefore, this retrospective cross-sectional study aimed to compare the diagnostic performance of seven commercial antibody assays for LNB diagnosis. Multiparameter analysis was conducted to investigate whether the diagnostic performance using the antibody assays could be improved by including several routine (CSF) parameters. The results of this study show that LNB diagnosis is best supported using the detection of intrathecally produced Borrelia-specific antibodies, two-tier serology on serum, CSF-CXCL13, Reibergram classification, and pleocytosis. Furthermore, we propose a collaborative prospective study to investigate the potential role of constructing a diagnostic algorithm using multiparameter analysis for improved LNB diagnosis.

Project description:BackgroundHuman cytomegalovirus infection is associated with a variety of pathological conditions including retinitis, pneumonia, hepatitis and encephalitis that may be transmitted congenitally, horizontally and parenterally and occurs both as a primary infection and as reactivation in immunocompromised individuals. Currently, there is a need for improved quantitative serological tests to document seropositivity with high sensitivity and specificity.MethodsHere we investigated whether luciferase immunoprecipitation systems (LIPS) would provide a more quantitative and sensitive method for detecting anti-CMV antibodies. Four protein fragments of immunodominant regions of CMV antigens pp150 and pp65 were generated as Renilla luciferase (Ruc) fusion proteins and used in LIPS with two cohorts of CMV positive and negative sera samples previously tested by ELISA.ResultsAnalysis of the antibody responses to two of these antigen fragments, pp150-d1 and pp150-d2, revealed geometric mean antibody titers in the first cohort that were 100-1000 fold higher in the CMV positive sera compared to the CMV negative samples (p < 0.0001) and infection status exactly matched the ELISA results for the 46 samples of the first cohort (100% sensitivity and 100% specificity). Two additional antigen fragments, pp65-d1 and pp65-d2 also showed robust antibody titers in some CMV-infected sera and yielded 50% and 96% sensitivity, respectively. Analysis of a second cohort of 70 samples using a mixture of the 4 antigens, which simplifies data collection and analysis, yielded values which correlated well with the sum of the values from the 4 separate tests (rs = 0.93, p < 0.00001). While comparison of the LIPS results from this second cohort with ELISA showed 100% sensitivity, LIPS detected six additional CMV positive samples that were not detected by ELISA. Heat map analysis revealed that several of the LIPS positive/ELISA negative samples had positive LIPS immunoreactivity with 3-4 of the CMV antigens.ConclusionThese results suggest that LIPS provides a highly robust and quantitative method for studying anti-CMV antibodies and has the potential to more accurately document CMV infection than standard ELISA.

Dataset Information

Quantitative serological antibody testing for suspected neuroborreliosis.

Publications

Quantitative serological antibody testing for suspected neuroborreliosis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets