Quality of Care for Patients With Type 2 Diabetes in Primary Care in Norway Is Improving: Results of cross-sectional surveys of 33 general practices in 1995 and 2005

OBJECTIVE—To assess changes in the quality of care in Norway for patients with type 2 diabetes

Detection of diphtheria antitoxin by four different methods

ObjectiveTo investigate the reliability of the different methods used in Norway and Russia for detection of diphtheria antitoxin.MethodsOne hundred and twenty-two sera were selected among Russian serum samples previously collected for seroepidemiologic studies of diphtheria antitoxin. The sera were selected to cover the total antitoxin range and were analyzed by four different antidiphtheria toxin assays: an in vitro toxin neutralization test using Vero cells (in vitro NT), an in vivo neutralization test using rabbit skin inoculation (in vivo NT), an indirect enzyme immunoassay (EIA) and a passive hemagglutination assay (PHA). The results were expressed according to the international standard as: not protected (<0.01 IU/mL), relatively protected (0.01–0.1 IU/mL) or protected (≤0.1 IU/mL). The sensitivity, specificity and inter-rater agreement (K or Kw) of each method were related to the in vitro NT selected as the reference method.ResultsThe in vivo NT test corresponded very well with the in vitro NT in its ability to differentiate between protection/relative protection and no protection (sensitivity 97%, specificity 87% and K=0.84). The EIA test showed a high sensitivity (96%), but since many sera were categorized as protected rather than not protected, the specificity (30%) and inter-rater agreement (K=0.29) were low. The PHA test had a very high specificity (100%) but a low sensitivity (86%).ConclusionsThe agreement between the two neutralization tests was high. If none of the neutralization assays is routinely available, the PHA test can be used to predict the need for vaccination on an individual basis but should not be used for seroepidemiologic studies, since the protection rate for diphtheria would be falsely too low, due to the lower sensitivity. The indirect EIA test used in this study should not be used routinely

The frequencies of IFNγ+IL2+TNFα+ PPD-specific CD4+CD45RO+ T-cells correlate with the magnitude of the QuantiFERON® gold in-tube response in a prospective study of healthy Indian adolescents

Background: QuantiFERON-TB Gold In-Tube (QFT) is an IFNγ-release assay used in the diagnosis of Mycobacterium tuberculosis (MTB) infection. The risk of TB progression increases with the magnitude of the MTB-specific IFNγ-response. QFT reversion, also associated with low Tuberculin Skin Test responses, may therefore represent a transient immune response with control of M. tuberculosis infection. However, studies at the single cell level have suggested that the quality (polyfunctionality) of the T-cell response is more important than the quantity of cytokines produced. Objective: To explore the quality and/or magnitude of mycobacteria-specific T-cell responses associated with QFT reversion and persistent QFT-positivity. Methods: Multi-color flowcytometry on prospectively collected peripheral blood mononuclear cells was applied to assess mycobacteria-specific T-cell responses in 42 QFT positive Indian adolescents of whom 21 became QFT negative (reverters) within one year. Ten QFT consistent negatives were also included as controls. Results: There was no difference in the qualitative PPD-specific CD4+ T-cell response between QFT consistent positives and reverters. However, compared with QFT consistent positives, reverters displayed lower absolute frequencies of polyfunctional (IFNγ+IL2+TNFα+) CD4+ T-cells at baseline, which were further reduced to the point where they were not different to QFT negative controls one year later. Moreover, absolute frequencies of these cells correlated well with the magnitude of the QFT-response. Conclusion: Whereas specific polyfunctional CD4+ T-cells have been suggested to protect against TB progression, our data do not support that higher relative or absolute frequencies of PPD-specific polyfunctional CD4+ T-cells in peripheral blood can explain the reduced risk of TB progression observed in QFT reverters. On the contrary, absolute frequencies of these cells correlated with the QFT-response, suggesting that this readout reflects antigenic load

Validation of the cardiovascular risk model NORRISK 2 in South Asians and people with diabetes

To evaluate the predictive ability of the previously published NORRISK 2 cardiovascular risk model in Norwegian-born and immigrants born in South Asia living in Norway, and to add information about diabetes and ethnicity in an updated model for South Asians and diabetics (NORRISK 2-SADia). Design. We included participants (30–74 years) born in Norway (n = 13,885) or South Asia (n = 1942) from health surveys conducted in Oslo 2000–2003. Cardiovascular disease (CVD) risk factor information including self-reported diabetes was linked with information on subsequent acute myocardial infarction (AMI) and acute cerebral stroke in hospital and mortality registry data throughout 2014 from the nationwide CVDNOR project. We developed an updated model using Cox regression with diabetes and South Asian ethnicity as additional predictors. We assessed model performance by Harrell’s C and calibration plots. Results. The NORRISK 2 model underestimated the risk in South Asians in all quintiles of predicted risk. The mean predicted 13-year risk by the NORRISK 2 model was 3.9% (95% CI 3.7–4.2) versus observed 7.3% (95% CI 5.9–9.1) in South Asian men and 1.1% (95% CI 1.0–1.2) versus 2.7% (95% CI 1.7–4.2) observed risk in South Asian women. The mean predictions from the NORRISK 2-SADia model were 7.2% (95% CI 6.7–7.6) in South Asian men and 2.7% (95% CI 2.4–3.0) in South Asian women. Conclusions. The NORRISK 2-SADia model improved predictions of CVD substantially in South Asians, whose risks were underestimated by the NORRISK 2 model. The NORRISK 2-SADia model may facilitate more intense preventive measures in this high-risk population.publishedVersio

Validation of the cardiovascular risk model NORRISK 2 in South Asians and people with diabetes

Objectives To evaluate the predictive ability of the previously published NORRISK 2 cardiovascular risk model in Norwegian-born and immigrants born in South Asia living in Norway, and to add information about diabetes and ethnicity in an updated model for South Asians and diabetics (NORRISK 2-SADia). Design. We included participants (30–74 years) born in Norway (n = 13,885) or South Asia (n = 1942) from health surveys conducted in Oslo 2000–2003. Cardiovascular disease (CVD) risk factor information including self-reported diabetes was linked with information on subsequent acute myocardial infarction (AMI) and acute cerebral stroke in hospital and mortality registry data throughout 2014 from the nationwide CVDNOR project. We developed an updated model using Cox regression with diabetes and South Asian ethnicity as additional predictors. We assessed model performance by Harrell’s C and calibration plots. Results. The NORRISK 2 model underestimated the risk in South Asians in all quintiles of predicted risk. The mean predicted 13-year risk by the NORRISK 2 model was 3.9% (95% CI 3.7–4.2) versus observed 7.3% (95% CI 5.9–9.1) in South Asian men and 1.1% (95% CI 1.0–1.2) versus 2.7% (95% CI 1.7–4.2) observed risk in South Asian women. The mean predictions from the NORRISK 2-SADia model were 7.2% (95% CI 6.7–7.6) in South Asian men and 2.7% (95% CI 2.4–3.0) in South Asian women. Conclusions. The NORRISK 2-SADia model improved predictions of CVD substantially in South Asians, whose risks were underestimated by the NORRISK 2 model. The NORRISK 2-SADia model may facilitate more intense preventive measures in this high-risk population.publishedVersio

Variation in the achievement of HbA1c, blood pressure and LDL cholesterol targets in type 2 diabetes in general practice and characteristics associated with risk factor control.

Aims To identify population, general practitioner, and practice characteristics associated with the achievement of HbA1c, blood pressure and LDL cholesterol targets, and to describe variation in the achievement of risk factor control. Methods We conducted a cross‐sectional survey of 9342 people with type 2 diabetes, 281 general practitioners and 77 general practices in Norway. Missing values (7.4%) were imputed using multiple imputation by chained equations. We used three‐level logistic regression with the achievement of HbA1c, blood pressure and LDL cholesterol targets as dependent variables, and factors related to population, general practitioners, and practices as independent variables. Results Treatment targets were achieved for HbA1c in 64%, blood pressure in 50%, and LDL cholesterol in 52% of people with type 2 diabetes, and 17% met all three targets. There was substantial heterogeneity in target achievement among general practitioners and among practices; the estimated proportion of a GPs diabetes population at target was 55–73% (10–90 percentiles) for HbA1c, 36–63% for blood pressure, and 47–57% for LDL cholesterol targets. The models explained 11%, 5% and 14%, respectively, of the total variation in the achievement of HbA1c, blood pressure and LDL cholesterol targets. Use among general practitioners of a structured diabetes form was associated with 23% higher odds of achieving the HbA1c target (odds ratio 1.23, 95% confidence interval (CI) 1.02–1.47) and 17% higher odds of achieving the LDL cholesterol target (odds ratio 1.17, 95% CI 1.01–1.35). Conclusions Clinical diabetes management is difficult, and few people meet all three risk factor control targets. The proportion of people reaching target varied among general practitioners and practices. Several population, general practitioner and practice characteristics only explained a small part of the total variation. The use of a structured diabetes form is recommended.publishedVersio

Host blood RNA transcript and protein signatures for sputum-independent diagnostics of tuberculosis in adults

To achieve the ambitious targets for tuberculosis (TB) prevention, care, and control stated by the End TB Strategy, new health care strategies, diagnostic tools are warranted. Host-derived biosignatures are explored for their TB diagnostic potential in accordance with the WHO target product profiles (TPPs) for point-of-care (POC) testing. We aimed to identify sputum-independent TB diagnostic signatures in newly diagnosed adult pulmonary-TB (PTB) patients recruited in the context of a prospective household contact cohort study conducted in Andhra Pradesh, India. Whole-blood mRNA samples from 158 subjects (PTB, n = 109; age-matched household controls, n = 49) were examined by dual-color Reverse-Transcriptase Multiplex Ligation-dependent Probe-Amplification (dcRT-MLPA) for the expression of 198 pre-defined genes and a Mesoscale discovery assay for the concentration of 18 cytokines/chemokines in TB-antigen stimulated QuantiFERON supernatants. To identify signatures, we applied a two-step approach; in the first step, univariate filtering was used to identify and shortlist potentially predictive biomarkers; this step may be seen as removing redundant biomarkers. In the second step, a logistic regression approach was used such that group membership (PTB vs. household controls) became the binary response in a Lasso regression model. We identified an 11-gene signature that distinguished PTB from household controls with AUCs of >= 0.98 (95% CIs: 0.94-1.00), and a 4-protein signature (IFN gamma, GMCSF, IL7 and IL15) that differentiated PTB from household controls with AUCs of >= 0.87 (95% CIs: 0.75-1.00), in our discovery cohort. Subsequently, we evaluated the performance of the 11-gene signature in two external validation data sets viz, an independent cohort at the Glenfield Hospital, University Hospitals of Leicester NHS Trust, Leicester, UK (GSE107994 data set), and the Catalysis treatment response cohort (GSE89403 data set) from South Africa. The 11-gene signature validated and distinguished PTB from healthy and asymptomatic M. tuberculosis infected household controls in the GSE107994 data set, with an AUC of 0.95 (95% CI: 0.91-0.98) and 0.94 (95% CI: 0.89-0.98). More interestingly in the GSE89403 data set, the 11-gene signature distinguished PTB from household controls and patients with other lung diseases with an AUC of 0.93 (95% CI: 0.87-0.99) and 0.73 (95% CI: 0.56-0.89). These criteria meet the WHO TTP benchmarks for a non-sputum-based triage test for TB diagnosis. We suggest that further validation is required before clinical implementation of the 11-gene signature we have identified markers will be possible.Immunogenetics and cellular immunology of bacterial infectious disease

Novel transcriptional signatures for sputum-independent diagnostics of tuberculosis in children

Pediatric tuberculosis (TB) is challenging to diagnose, confirmed by growth of Mycobacterium tuberculosis at best in 40% of cases. The WHO has assigned high priority to the development of non-sputum diagnostic tools. We therefore sought to identify transcriptional signatures in whole blood of Indian children, capable of discriminating intra-thoracic TB disease from other symptomatic illnesses. We investigated the expression of 198 genes in a training set, comprising 47 TB cases (19 definite/28 probable) and 36 asymptomatic household controls, and identified a 7- and a 10-transcript signature, both including NOD2, GBP5, IFITM1/3, KIF1B and TNIP1. The discriminatory abilities of the signatures were evaluated in a test set comprising 24 TB cases (17 definite/7 probable) and 26 symptomatic non-TB cases. In separating TB-cases from symptomatic non-TB cases, both signatures provided an AUC of 0.94 (95%CI, 0.88–1.00), a sensitivity of 91.7% (95%CI, 71.5–98.5) regardless of culture status, and 100% sensitivity for definite TB. The 7-transcript signature provided a specificity of 80.8% (95%CI, 60.0–92.7), and the 10-transcript signature a specificity of 88.5% (95%CI, 68.7–96.9%). Although warranting exploration and validation in other populations, our findings are promising and potentially relevant for future non-sputum based POC diagnostic tools for pediatric TB.publishedVersio