Karel G M Moons

University Medical Center Utrecht, Utrecht, Utrecht, Netherlands

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Publications (371)1670.36 Total impact

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    ABSTRACT: The value of measuring levels of glycated hemoglobin (HbA1c) for the prediction of first cardiovascular events is uncertain. To determine whether adding information on HbA1c values to conventional cardiovascular risk factors is associated with improvement in prediction of cardiovascular disease (CVD) risk. Analysis of individual-participant data available from 73 prospective studies involving 294,998 participants without a known history of diabetes mellitus or CVD at the baseline assessment. Measures of risk discrimination for CVD outcomes (eg, C-index) and reclassification (eg, net reclassification improvement) of participants across predicted 10-year risk categories of low (<5%), intermediate (5% to <7.5%), and high (≥7.5%) risk. During a median follow-up of 9.9 (interquartile range, 7.6-13.2) years, 20,840 incident fatal and nonfatal CVD outcomes (13,237 coronary heart disease and 7603 stroke outcomes) were recorded. In analyses adjusted for several conventional cardiovascular risk factors, there was an approximately J-shaped association between HbA1c values and CVD risk. The association between HbA1c values and CVD risk changed only slightly after adjustment for total cholesterol and triglyceride concentrations or estimated glomerular filtration rate, but this association attenuated somewhat after adjustment for concentrations of high-density lipoprotein cholesterol and C-reactive protein. The C-index for a CVD risk prediction model containing conventional cardiovascular risk factors alone was 0.7434 (95% CI, 0.7350 to 0.7517). The addition of information on HbA1c was associated with a C-index change of 0.0018 (0.0003 to 0.0033) and a net reclassification improvement of 0.42 (-0.63 to 1.48) for the categories of predicted 10-year CVD risk. The improvement provided by HbA1c assessment in prediction of CVD risk was equal to or better than estimated improvements for measurement of fasting, random, or postload plasma glucose levels. In a study of individuals without known CVD or diabetes, additional assessment of HbA1c values in the context of CVD risk assessment provided little incremental benefit for prediction of CVD risk.
    JAMA The Journal of the American Medical Association 03/2014; 311(12):1225-33. · 29.98 Impact Factor
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    ABSTRACT: Before considering whether to use a multivariable (diagnostic or prognostic) prediction model, it is essential that its performance be evaluated in data that were not used to develop the model (referred to as external validation). We critically appraised the methodological conduct and reporting of external validation studies of multivariable prediction models. We conducted a systematic review of articles describing some form of external validation of one or more multivariable prediction models indexed in PubMed core clinical journals published in 2010. Study data were extracted in duplicate on design, sample size, handling of missing data, reference to the original study developing the prediction models and predictive performance measures. 11,826 articles were identified and 78 were included for full review, which described the evaluation of 120 prediction models. in participant data that were not used to develop the model. Thirty-three articles described both the development of a prediction model and an evaluation of its performance on a separate dataset, and 45 articles described only the evaluation of an existing published prediction model on another dataset. Fifty-seven percent of the prediction models were presented and evaluated as simplified scoring systems. Sixteen percent of articles failed to report the number of outcome events in the validation datasets. Fifty-four percent of studies made no explicit mention of missing data. Sixty-seven percent did not report evaluating model calibration whilst most studies evaluated model discrimination. It was often unclear whether the reported performance measures were for the full regression model or for the simplified models. The vast majority of studies describing some form of external validation of a multivariable prediction model were poorly reported with key details frequently not presented. The validation studies were characterised by poor design, inappropriate handling and acknowledgement of missing data and one of the most key performance measures of prediction models i.e. calibration often omitted from the publication. It may therefore not be surprising that an overwhelming majority of developed prediction models are not used in practice, when there is a dearth of well-conducted and clearly reported (external validation) studies describing their performance on independent participant data.
    BMC Medical Research Methodology 03/2014; 14(1):40. · 2.21 Impact Factor
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    ABSTRACT: Background: chronic dyspnoea is common in older people and is often of cardiac or pulmonary aetiology. Information on the exact prevalence and distribution of underlying causes is scarce. Our aim was to review the literature on prevalence and underlying causes of dyspnoea in the older population.Methods: two MEDLINE searches were conducted: the first on studies on the prevalence of dyspnoea in older persons aged ≥65 years using the Medical Research Council (MRC) dyspnoea scale and the second on the underlying causes of dyspnoea in this population. Quality assessment was performed for all included studies. Random effects models based on the logit transformed prevalences were used to calculate pooled prevalence with 95% confidence intervals (95% CI).Results: a total of 21 articles from 20 different populations reported the prevalence in the general older population with a median sample size of 600 (Interquartile range 262-1289). The pooled prevalence was 36% (95% CI: 27-47%) for an MRC of ≥2, 16% (95% CI: 12-21%) for an MRC of ≥3 and 4% (95% CI: 2-9%) for an MRC of ≥4. Prevalence rates were higher in women than in men.Only one article investigated the underlying causes of dyspnoea in older persons; in 70% of these patients, the dyspnoea was considered to be of cardiac or pulmonary origin.Conclusion: dyspnoea is very common in older people, but estimates vary considerably between studies. Only one study describes the underlying causes.
    Age and Ageing 01/2014; · 3.82 Impact Factor
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    ABSTRACT: In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.
    PLoS ONE 01/2014; 9(4):e93755. · 3.73 Impact Factor
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    ABSTRACT: To assess the accuracy of the Wells rule for excluding deep vein thrombosis and whether this accuracy applies to different subgroups of patients. Meta-analysis of individual patient data. Authors of 13 studies (n=10 002) provided their datasets, and these individual patient data were merged into one dataset. Studies were eligible if they enrolled consecutive outpatients with suspected deep vein thrombosis, scored all variables of the Wells rule, and performed an appropriate reference standard. Multilevel logistic regression models, including an interaction term for each subgroup, were used to estimate differences in predicted probabilities of deep vein thrombosis by the Wells rule. In addition, D-dimer testing was added to assess differences in the ability to exclude deep vein thrombosis using an unlikely score on the Wells rule combined with a negative D-dimer test result. Overall, increasing scores on the Wells rule were associated with an increasing probability of having deep vein thrombosis. Estimated probabilities were almost twofold higher in patients with cancer, in patients with suspected recurrent events, and (to a lesser extent) in males. An unlikely score on the Wells rule (≤1) combined with a negative D-dimer test result was associated with an extremely low probability of deep vein thrombosis (1.2%, 95% confidence interval 0.7% to 1.8%). This combination occurred in 29% (95% confidence interval 20% to 40%) of patients. These findings were consistent in subgroups defined by type of D-dimer assay (quantitative or qualitative), sex, and care setting (primary or hospital care). For patients with cancer, the combination of an unlikely score on the Wells rule and a negative D-dimer test result occurred in only 9% of patients and was associated with a 2.2% probability of deep vein thrombosis being present. In patients with suspected recurrent events, only the modified Wells rule (adding one point for the previous event) is safe. Combined with a negative D-dimer test result (both quantitative and qualitative), deep vein thrombosis can be excluded in patients with an unlikely score on the Wells rule. This finding is true for both sexes, as well as for patients presenting in primary and hospital care. In patients with cancer, the combination is neither safe nor efficient. For patients with suspected recurrent disease, one extra point should be added to the rule to enable a safe exclusion.
    BMJ (Clinical research ed.). 01/2014; 348:g1340.
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    ABSTRACT: Objective To review the prognostic value of cardiac magnetic resonance (CMR) imaging findings for future cardiovascular events in patients with a recent myocardial infarction (MI) and patients with suspected or known coronary artery disease (CAD). Background Although the diagnostic value of CMR findings is established, the independent prognostic association with future cardiovascular events remains largely unclear. Methods Studies published until February 2013 identified by systematic MEDLINE and EMBASE searches were reviewed for associations between CMR findings (left ventricular ejection fraction [LVEF], (inducible) wall motion abnormalities [WMA], abnormal myocardial perfusion, microvascular obstruction [MVO], late gadolinium enhancement, edema, intramyocardial haemorrhage), and hard events (all-cause mortality, cardiac death, cardiac transplantation, and myocardial infarction) or major adverse cardiovascular events (MACE: hard events and other cardiovascular events defined by the authors of the evaluated articles) were included. Results Fifty-six studies (25,497 patients) were evaluated. For patients with recent MI, too few patients were evaluated to establish associations between CMR findings and hard events. LVEF (range of adjusted Hazard Ratios (adjHRs): 1.03-1.05 per % decrease) was independently associated with MACE. In patients with suspected or known CAD, WMA (adjHR: 1.87-2.99), inducible perfusion defects (adj HR: 3.02-7.77), LVEF (adjHR: 0.72-0.82 per 10% increase), and infarction (adjHR: 2.82-9.43) were independently associated with hard events, and presence of inducible perfusion defects was associated with MACE (adjHRs 1.76-3.21). Conclusion Independent predictors of future cardiovascular events were LVEF for patients with a recent MI and WMA, inducible perfusion defects, LVEF and presence of infarction for patients with suspected or known CAD.
    Journal of the American College of Cardiology 01/2014; · 14.09 Impact Factor
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    ABSTRACT: Published clinical prediction models are often ignored during the development of novel prediction models despite similarities in populations and intended usage. The plethora of prediction models that arise from this practice may still perform poorly when applied in other populations. Incorporating prior evidence might improve the accuracy of prediction models and make them potentially better generalizable. Unfortunately, aggregation of prediction models is not straightforward, and methods to combine differently specified models are currently lacking. We propose two approaches for aggregating previously published prediction models when a validation dataset is available: model averaging and stacked regressions. These approaches yield user-friendly stand-alone models that are adjusted for the new validation data. Both approaches rely on weighting to account for model performance and between-study heterogeneity but adopt a different rationale (averaging versus combination) to combine the models. We illustrate their implementation in a clinical example and compare them with established methods for prediction modeling in a series of simulation studies. Results from the clinical datasets and simulation studies demonstrate that aggregation yields prediction models with better discrimination and calibration in a vast majority of scenarios, and results in equivalent performance (compared to developing a novel model from scratch) when validation datasets are relatively large. In conclusion, model aggregation is a promising strategy when several prediction models are available from the literature and a validation dataset is at hand. The aggregation methods do not require existing models to have similar predictors and can be applied when relatively few data are at hand. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 01/2014; · 2.04 Impact Factor
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    ABSTRACT: This study aimed to gather insights in physicians' considerations for decisions to either refer for- or to withhold additional diagnostic investigations in nursing home patients with a suspicion of venous thromboembolism. Our study was nested in an observational study on diagnostic strategies for suspected venous thromboembolism in nursing home patients. Patient characteristics, bleeding-complications and mortality were related to the decision to withhold investigations. For a better understanding of the physicians' decisions, 21 individual face-to-face in-depth interviews were performed and analysed using the grounded theory approach. Referal for additional diagnostic investigations was forgone in 126/322 (39.1%) patients with an indication for diagnostic work-up. 'Blind' anticoagulant treatment was initiated in 95 (75.4%) of these patients. The 3month mortality rates were higher for patients in whom investigations were withheld than in the referred patients, irrespective of anticoagulant treatment (odds ratio 2.45; 95% confidence interval 1.40 to 4.29) but when adjusted for the probability of being referred (i.e. the propensity score), there was no relation of non-diagnosis decisions to mortality (odds ratio 1.75; 0.98 to 3.11). In their decisions to forgo diagnostic investigations, physicians incorporated the estimated relative impact of the potential disease; the potential net-benefits of diagnostic investigations and whether performing investigations agreed with established management goals in advance care planning. Referral for additional diagnostic investigations is withheld in almost 40% of Dutch nursing home patients with suspected venous thromboembolism and an indication for diagnostic work-up. We propose that, given the complexity of these decisions and the uncertainty regarding their indirect effects on patient outcome, more attention should be focused on the decision to either use or withhold additional diagnostic tests.
    PLoS ONE 01/2014; 9(3):e90395. · 3.73 Impact Factor
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    ABSTRACT: Accurate visualization of the distal ascending aorta (DAA) can guide the surgical management and hence prevent dislodgment of atherogenic emboli during cardiac surgery. Conventional transoesophageal echocardiography (TEE) has a poor sensitivity; modified TEE was previously shown to accurately visualize atherosclerosis of the DAA. We studied the added value of modified TEE beyond the patient history and TEE screening. Included were 421 patients from a previous diagnostic study, which compared the diagnosis of severe atherosclerosis with modified TEE and epiaortic ultrasound (EUS; reference test). We fitted three models, which predicted presence of atherosclerosis Grade ≥3 of the DAA. Model 1 included preoperative patient characteristics; in Model 2 conventional TEE was added; Model 3 additionally included modified TEE results. For each model, the area under the receiver-operating curve (AUC), the 'net reclassification improvement' (NRI) and the 'integrated discrimination improvement' (IDI) were determined. Missing data were imputed.The AUCs of Models 1, 2, and 3 were 0.73 (95% CI: 0.68-0.78), 0.80 (95% CI: 0.76-0.85), and 0.93 (95% CI: 0.90-0.96), respectively. Comparing Model 3 with Model 2, the AUC was significantly higher (P < 0.001), the NRI was 0.60 (95% CI: 0.54-0.66; P < 0.001), and the IDI was 0.30 (95% CI: 0.28-0.32; P < 0.001), indicating that visualization of the DAA with modified TEE significantly improved reclassification. Visualization of atherosclerosis of the DAA with modified TEE provided information beyond patient history and conventional TEE screening, which resulted in an improved diagnosis of atherosclerosis.
    European heart journal cardiovascular Imaging. 12/2013;
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    ABSTRACT: Bronchopulmonary dysplasia (BPD) is a common complication of preterm birth. Very different models using clinical parameters at an early postnatal age to predict BPD have been developed with little extensive quantitative validation. The objective of this study is to review and validate clinical prediction models for BPD. We searched the main electronic databases and abstracts from annual meetings. The STROBE instrument was used to assess the methodological quality. External validation of the retrieved models was performed using an individual patient dataset of 3229 patients at risk for BPD. Receiver operating characteristic curves were used to assess discrimination for each model by calculating the area under the curve (AUC). Calibration was assessed for the best discriminating models by visually comparing predicted and observed BPD probabilities. We identified 26 clinical prediction models for BPD. Although the STROBE instrument judged the quality from moderate to excellent, only four models utilised external validation and none presented calibration of the predictive value. For 19 prediction models with variables matched to our dataset, the AUCs ranged from 0.50 to 0.76 for the outcome BPD. Only two of the five best discriminating models showed good calibration. External validation demonstrates that, except for two promising models, most existing clinical prediction models are poor to moderate predictors for BPD. To improve the predictive accuracy and identify preterm infants for future intervention studies aiming to reduce the risk of BPD, additional variables are required. Subsequently, that model should be externally validated using a proper impact analysis before its clinical implementation.
    BMC Pediatrics 12/2013; 13(1):207. · 1.98 Impact Factor
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    ABSTRACT: To compare the accuracy of data from hospital administration databases and a national clinical cardiac surgery database and to compare the performance of the Dutch hospital standardised mortality ratio (HSMR) method and the logistic European System for Cardiac Operative Risk Evaluation, for the purpose of benchmarking of mortality across hospitals. Information on all patients undergoing cardiac surgery between 1 January 2007 and 31 December 2010 in 10 centres was extracted from The Netherlands Association for Cardio-Thoracic Surgery database and the Hospital Discharge Registry. The number of cardiac surgery interventions was compared between both databases. The European System for Cardiac Operative Risk Evaluation and hospital standardised mortality ratio models were updated in the study population and compared using the C-statistic, calibration plots and the Brier-score. The number of cardiac surgery interventions performed could not be assessed using the administrative database as the intervention code was incorrect in 1.4-26.3%, depending on the type of intervention. In 7.3% no intervention code was registered. The updated administrative model was inferior to the updated clinical model with respect to discrimination (c-statistic of 0.77 vs 0.85, p<0.001) and calibration (Brier Score of 2.8% vs 2.6%, p<0.001, maximum score 3.0%). Two average performing hospitals according to the clinical model became outliers when benchmarking was performed using the administrative model. In cardiac surgery, administrative data are less suitable than clinical data for the purpose of benchmarking. The use of either administrative or clinical risk-adjustment models can affect the outlier status of hospitals. Risk-adjustment models including procedure-specific clinical risk factors are recommended.
    Heart (British Cardiac Society) 12/2013; · 5.01 Impact Factor
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    ABSTRACT: Latent class models (LCMs) combine the results of multiple diagnostic tests through a statistical model to obtain estimates of disease prevalence and diagnostic test accuracy in situations where there is no single, accurate reference standard. We performed a systematic review of the methodology and reporting of LCMs in diagnostic accuracy studies. This review shows that the use of LCMs in such studies increased sharply in the past decade, notably in the domain of infectious diseases (overall contribution: 59%). The 64 reviewed studies used a range of differently specified parametric latent variable models, applying Bayesian and frequentist methods. The critical assumption underlying the majority of LCM applications (61%) is that the test observations must be independent within 2 classes. Because violations of this assumption can lead to biased estimates of accuracy and prevalence, performing and reporting checks of whether assumptions are met is essential. Unfortunately, our review shows that 28% of the included studies failed to report any information that enables verification of model assumptions or performance. Because of the lack of information on model fit and adequate evidence "external" to the LCMs, it is often difficult for readers to judge the validity of LCM-based inferences and conclusions reached.
    American journal of epidemiology 11/2013; · 5.59 Impact Factor
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    ABSTRACT: Combining several tests is a common way to improve the final classification of disease status in diagnostic accuracy studies but is often used ambiguously. This article gives advice on proper use and reporting of composite reference standards.
    BMJ British medical journal 10/2013; · 13.66 Impact Factor
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    ABSTRACT: Clinical prediction models have been shown to have moderate sensitivity and specificity, yet their use will depend on implementation in clinical practice. The authors hypothesized that implementation of a prediction model for postoperative nausea and vomiting (PONV) would lower the PONV incidence by stimulating anesthesiologists to administer more "risk-tailored" prophylaxis to patients. A single-center, cluster-randomized trial was performed in 12,032 elective surgical patients receiving anesthesia from 79 anesthesiologists. Anesthesiologists were randomized to either exposure or nonexposure to automated risk calculations for PONV (without patient-specific recommendations on prophylactic antiemetics). Anesthesiologists who treated less than 50 enrolled patients were excluded during the analysis to avoid too small clusters, yielding 11,613 patients and 57 anesthesiologists (intervention group: 5,471 and 31; care-as-usual group: 6,142 and 26). The 24-h incidence of PONV (primary outcome) and the number of prophylactic antiemetics administered per patient were studied for risk-dependent differences between allocation groups. There were no differences in PONV incidence between allocation groups (crude incidence intervention group 41%, care-as-usual group 43%; odds ratio, 0.97; 95% CI, 0.87-1.1; risk-dependent odds ratio, 0.92; 95% CI, 0.80-1.1). Nevertheless, intervention-group anesthesiologists administered more prophylactic antiemetics (rate ratio, 2.0; 95% CI, 1.6-2.4) and more risk-tailored than care-as-usual-group anesthesiologists (risk-dependent rate ratio, 1.6; 95% CI, 1.3-2.0). Implementation of a PONV prediction model did not reduce the PONV incidence despite increased antiemetic prescription in high-risk patients by anesthesiologists. Before implementing prediction models into clinical practice, implementation studies that include patient outcomes as an endpoint are needed.
    Anesthesiology 10/2013; · 5.16 Impact Factor
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    ABSTRACT: Background Survivors of critical illness often have a prolonged and disabling form of cognitive impairment that remains inadequately characterized. Methods We enrolled adults with respiratory failure or shock in the medical or surgical intensive care unit (ICU), evaluated them for in-hospital delirium, and assessed global cognition and executive function 3 and 12 months after discharge with the use of the Repeatable Battery for the Assessment of Neuropsychological Status (population age-adjusted mean [±SD] score, 100±15, with lower values indicating worse global cognition) and the Trail Making Test, Part B (population age-, sex-, and education-adjusted mean score, 50±10, with lower scores indicating worse executive function). Associations of the duration of delirium and the use of sedative or analgesic agents with the outcomes were assessed with the use of linear regression, with adjustment for potential confounders. Results Of the 821 patients enrolled, 6% had cognitive impairment at baseline, and delirium developed in 74% during the hospital stay. At 3 months, 40% of the patients had global cognition scores that were 1.5 SD below the population means (similar to scores for patients with moderate traumatic brain injury), and 26% had scores 2 SD below the population means (similar to scores for patients with mild Alzheimer's disease). Deficits occurred in both older and younger patients and persisted, with 34% and 24% of all patients with assessments at 12 months that were similar to scores for patients with moderate traumatic brain injury and scores for patients with mild Alzheimer's disease, respectively. A longer duration of delirium was independently associated with worse global cognition at 3 and 12 months (P=0.001 and P=0.04, respectively) and worse executive function at 3 and 12 months (P=0.004 and P=0.007, respectively). Use of sedative or analgesic medications was not consistently associated with cognitive impairment at 3 and 12 months. Conclusions Patients in medical and surgical ICUs are at high risk for long-term cognitive impairment. A longer duration of delirium in the hospital was associated with worse global cognition and executive function scores at 3 and 12 months. (Funded by the National Institutes of Health and others; BRAIN-ICU ClinicalTrials.gov number, NCT00392795 .).
    New England Journal of Medicine 10/2013; 369(14):1306-1316. · 51.66 Impact Factor
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    ABSTRACT: In diagnostic studies, a single and error-free test that can be used as the reference (gold) standard often does not exist. One solution is the use of panel diagnosis, i.e., a group of experts who assess the results from multiple tests to reach a final diagnosis in each patient. Although panel diagnosis, also known as consensus or expert diagnosis, is frequently used as the reference standard, guidance on preferred methodology is lacking. The aim of this study is to provide an overview of methods used in panel diagnoses and to provide initial guidance on the use and reporting of panel diagnosis as reference standard. PubMed was systematically searched for diagnostic studies applying a panel diagnosis as reference standard published up to May 31, 2012. We included diagnostic studies in which the final diagnosis was made by two or more persons based on results from multiple tests. General study characteristics and details of panel methodology were extracted. Eighty-one studies were included, of which most reported on psychiatry (37%) and cardiovascular (21%) diseases. Data extraction was hampered by incomplete reporting; one or more pieces of critical information about panel reference standard methodology was missing in 83% of studies. In most studies (75%), the panel consisted of three or fewer members. Panel members were blinded to the results of the index test results in 31% of studies. Reproducibility of the decision process was assessed in 17 (21%) studies. Reported details on panel constitution, information for diagnosis and methods of decision making varied considerably between studies. Methods of panel diagnosis varied substantially across studies and many aspects of the procedure were either unclear or not reported. On the basis of our review, we identified areas for improvement and developed a checklist and flow chart for initial guidance for researchers conducting and reporting of studies involving panel diagnosis. Please see later in the article for the Editors' Summary.
    PLoS Medicine 10/2013; 10(10):e1001531. · 15.25 Impact Factor
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    ABSTRACT: Recently, prediction models for hemoglobin (Hb) deferral risk have been developed. These models consider the previous Hb level plus change in Hb. Here, we investigated if the performance of models could be improved by considering more information on Hb level history. Data of 166,497 Dutch whole blood donors with sequential Hb measurements during 2 years (760,444 in total) were used to develop and internally validate three different regression models: two simple linear models with Hb level history included as 1) Hb at the previous visit plus change in Hb or 2) mean of all previous Hb levels and one mixed-effect model including measurements of all previous Hb levels. Thirteen percent of men and 21% of women were deferred because of a low Hb level at least once in 2 years. The simple linear models and the mixed-effect model performed similar, if an estimate of the random intercept of the mixed-effect model was used for individual donors to calculate the predicted Hb level. In men, the concordance (c)-statistic ranged from 0.87 to 0.89 and the R(2) ranged from 0.42 to 0.45. In women, the c-statistic ranged from 0.81 to 0.84. Values of R(2) in women were higher for the simple linear models than for the mixed-effect model, 0.37 and 0.40 versus 0.30, respectively. Previous Hb levels could be summarized with one predictor as the mean value of all previous Hb levels. This predictor can be used in an easy-to-use simple linear regression model.
    Transfusion 09/2013; · 3.53 Impact Factor
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    ABSTRACT: Pacing technology and care have improved notably over the past decade, justifying an update on the long-term prognosis and pre-implantation determinants of prognosis of bradycardia pacemaker (PM) recipients. Prospective cohort study. 23 Dutch pacemaker centres PATIENTS: Pre-implantation characteristics of 1517 patients receiving a first bradycardia PM between 2003-2007 were studied in relation to survival. None; patients were followed up during routine clinical practice. Cause and time to death. At the end of a mean follow-up of 5.8 (SD 1.1) years, 512 patients (33%) died, mostly of non-cardiac cause (67%). There were two PM related deaths. Survival rates were 93%, 81%, 69%, and 61% after 1, 3, 5 and 7 years, respectively. PM recipients without concomitant cardiovascular disease at implantation showed survival rates comparable to age and sex matched controls. Predictors at time of implantation associated with cardiac mortality were: age, coronary artery disease (CAD), diabetes, heart failure, valve disease, and the indication for PM implantation. Predictors for all cause mortality were: male gender, age, body mass index, CAD, cardiac surgery, diabetes, heart failure, and maintained atrioventricular synchrony. A pre-implantation history of heart failure, CAD, and diabetes are the most important predictors for worse prognosis in PM recipients. Without baseline heart disease, survival rates equal that of the general population, suggesting that the prognosis of contemporary PM recipients is mainly determined by comorbid diseases and a bradycardia pacing indication as such does not influence survival. ClinicalTrials.gov Identifier: NCT00135174.
    Heart (British Cardiac Society) 08/2013; · 5.01 Impact Factor
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    ABSTRACT: A universal challenge in studies that quantify the accuracy of diagnostic tests is establishing whether each participant has the disease of interest. Ideally, the same preferred reference standard would be used for all participants; however, for practical or ethical reasons, alternative reference standards that are often less accurate are frequently used instead. The use of different reference standards across participants in a single study is known as differential verification.Differential verification can cause severely biased accuracy estimates of the test or model being studied. Many variations of differential verification exist, but not all introduce the same risk of bias. A risk-of-bias assessment requires detailed information about which participants receive which reference standards and an estimate of the accuracy of the alternative reference standard. This article classifies types of differential verification and explores how they can lead to bias. It also provides guidance on how to report results and assess the risk of bias when differential verification occurs and highlights potential ways to correct for the bias.
    Annals of internal medicine 08/2013; 159(3):195-202. · 13.98 Impact Factor

Publication Stats

6k Citations
1,670.36 Total Impact Points

Institutions

  • 2000–2014
    • University Medical Center Utrecht
      • • Julius Center for Health Sciences and Primary Care
      • • Department of Anesthesiology
      Utrecht, Utrecht, Netherlands
  • 2013
    • University of Exeter
      Exeter, England, United Kingdom
    • Gelderse Vallei Hospital
      Ede, Gelderland, Netherlands
  • 2001–2013
    • Erasmus MC
      • Research Group for Public Health
      Rotterdam, South Holland, Netherlands
  • 2012
    • University of Amsterdam
      • Faculty of Medicine AMC
      Amsterdam, North Holland, Netherlands
  • 2009–2012
    • University of Oxford
      • Centre for Statistics in Medicine
      Oxford, ENG, United Kingdom
    • Medical Research Council (UK)
      • MRC Clinical Trials Unit
      London, ENG, United Kingdom
  • 2011
    • Sanquin Blood Supply Foundation
      Amsterdamo, North Holland, Netherlands
  • 2010
    • Certara
      San Luis, Missouri, United States
  • 1998–2010
    • Universiteit Utrecht
      Utrecht, Utrecht, Netherlands
  • 2006–2009
    • Kitasato University
      • Graduate School of Medical Sciences
      Edo, Tōkyō, Japan
  • 2008
    • Amphia Ziekenhui
      Breda, North Brabant, Netherlands
    • Wageningen University
      • Division of Human Nutrition
      Wageningen, Provincie Gelderland, Netherlands
  • 2007
    • Isala Klinieken
      Zwolle, Overijssel, Netherlands
  • 2000–2001
    • Het Oogziekenhuis Rotterdam
      Rotterdam, South Holland, Netherlands
  • 1997–1998
    • Erasmus Universiteit Rotterdam
      Rotterdam, South Holland, Netherlands