Questionnaire to distinguish between stress and urge urinary incontinence.
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Female↗
Biomedical subjects
Karel G M Moons
Publications and source records attributed to Karel G M Moons.
Development and validation of MIX: comprehensive free software for meta-analysis of causal research data.
BACKGROUND: Meta-analysis has become a well-known method for synthesis of quantitative data from previously conducted research in applied health sciences. So far, meta-analysis has been particularly useful in evaluating and comparing therapies and in assessing causes of disease. Consequently, the number of software packages that can perform meta-analysis has increased over the years. Unfortunately, it can take a substantial amount of time to get acquainted with some of these programs and most contain little or no interactive educational material. We set out to create and validate an easy-to-use and comprehensive meta-analysis package that would be simple enough programming-wise to remain available as a free download. We specifically aimed at students and researchers who are new to meta-analysis, with important parts of the development oriented towards creating internal interactive tutoring tools and designing features that would facilitate usage of the software as a companion to existing books on meta-analysis. RESULTS: We took an unconventional approach and created a program that uses Excel as a calculation and programming platform. The main programming language was Visual Basic, as implemented in Visual Basic 6 and Visual Basic for Applications in Excel 2000 and higher. The development took approximately two years and resulted in the 'MIX' program, which can be downloaded from the program's website free of charge. Next, we set out to validate the MIX output with two major software packages as reference standards, namely STATA (metan, metabias, and metatrim) and Comprehensive Meta-Analysis Version 2. Eight meta-analyses that had been published in major journals were used as data sources. All numerical and graphical results from analyses with MIX were identical to their counterparts in STATA and CMA. The MIX program distinguishes itself from most other programs by the extensive graphical output, the click-and-go (Excel) interface, and the educational features. CONCLUSION: The MIX program is a valid tool for performing meta-analysis and may be particularly useful in educational environments. It can be downloaded free of charge via http://www.mix-for-meta-analysis.info or http://sourceforge.net/projects/meta-analysis.
Causality↗
Review: a gentle introduction to imputation of missing values.
In most situations, simple techniques for handling missing data (such as complete case analysis, overall mean imputation, and the missing-indicator method) produce biased results, whereas imputation techniques yield valid results without complicating the analysis once the imputations are carried out. Imputation techniques are based on the idea that any subject in a study sample can be replaced by a new randomly chosen subject from the same source population. Imputation of missing data on a variable is replacing that missing by a value that is drawn from an estimate of the distribution of this variable. In single imputation, only one estimate is used. In multiple imputation, various estimates are used, reflecting the uncertainty in the estimation of this distribution. Under the general conditions of so-called missing at random and missing completely at random, both single and multiple imputations result in unbiased estimates of study associations. But single imputation results in too small estimated standard errors, whereas multiple imputation results in correctly estimated standard errors and confidence intervals. In this article we explain why all this is the case, and use a simple simulation study to demonstrate our explanations. We also explain and illustrate why two frequently used methods to handle missing data, i.e., overall mean imputation and the missing-indicator method, almost always result in biased estimates.
Bias↗
Imputation of missing values is superior to complete case analysis and the missing-indicator method in multivariable diagnostic research: a clinical example.
BACKGROUND AND OBJECTIVES: To illustrate the effects of different methods for handling missing data--complete case analysis, missing-indicator method, single imputation of unconditional and conditional mean, and multiple imputation (MI)--in the context of multivariable diagnostic research aiming to identify potential predictors (test results) that independently contribute to the prediction of disease presence or absence. METHODS: We used data from 398 subjects from a prospective study on the diagnosis of pulmonary embolism. Various diagnostic predictors or tests had (varying percentages of) missing values. Per method of handling these missing values, we fitted a diagnostic prediction model using multivariable logistic regression analysis. RESULTS: The receiver operating characteristic curve area for all diagnostic models was above 0.75. The predictors in the final models based on the complete case analysis, and after using the missing-indicator method, were very different compared to the other models. The models based on MI did not differ much from the models derived after using single conditional and unconditional mean imputation. CONCLUSION: In multivariable diagnostic research complete case analysis and the use of the missing-indicator method should be avoided, even when data are missing completely at random. MI methods are known to be superior to single imputation methods. For our example study, the single imputation methods performed equally well, but this was most likely because of the low overall number of missing values.
Adult↗
Using the outcome for imputation of missing predictor values was preferred.
BACKGROUND AND OBJECTIVE: Epidemiologic studies commonly estimate associations between predictors (risk factors) and outcome. Most software automatically exclude subjects with missing values. This commonly causes bias because missing values seldom occur completely at random (MCAR) but rather selectively based on other (observed) variables, missing at random (MAR). Multiple imputation (MI) of missing predictor values using all observed information including outcome is advocated to deal with selective missing values. This seems a self-fulfilling prophecy. METHODS: We tested this hypothesis using data from a study on diagnosis of pulmonary embolism. We selected five predictors of pulmonary embolism without missing values. Their regression coefficients and standard errors (SEs) estimated from the original sample were considered as "true" values. We assigned missing values to these predictors--both MCAR and MAR--and repeated this 1,000 times using simulations. Per simulation we multiple imputed the missing values without and with the outcome, and compared the regression coefficients and SEs to the truth. RESULTS: Regression coefficients based on MI including outcome were close to the truth. MI without outcome yielded very biased--underestimated--coefficients. SEs and coverage of the 90% confidence intervals were not different between MI with and without outcome. Results were the same for MCAR and MAR. CONCLUSION: For all types of missing values, imputation of missing predictor values using the outcome is preferred over imputation without outcome and is no self-fulfilling prophecy.
Adult↗
Improving the quality and clinical relevance of diagnostic studies.
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Confidence Intervals↗
Risk and determinants of myocardial injury during off-pump coronary artery bypass grafting.
Perioperative myocardial injury (PMI) after coronary revascularization (bypass surgery using cardiopulmonary bypass or percutaneous intervention) is strongly associated with future adverse events, such as death, myocardial infarction, and coronary intervention. The incidence, determinants, and prognostic significance of PMI after bypass surgery without cardiopulmonary bypass (off-pump surgery) are unknown. The study population comprised the patients who were randomized to off-pump surgery in the Octopus Study. PMI was defined by a creatine kinase isoenzyme-MB/total creatine kinase ratio of >5% during the first 48 hours, postoperatively. PMI occurred in 137 of 260 patients (52%). Using multivariate regression analysis, age, female gender, previous myocardial infarction, preoperative nitrate use, preoperative diuretic use, and number of grafts were independently associated with an increased risk of PMI during off-pump surgery. The presence of preoperative coronary collaterals showed a negative association with PMI. The occurrence of PMI had a crude odds ratio of 7.53 (95% confidence interval 1.59 to 35.63) for an adverse cardiac event at 1 year after off-pump surgery. This odds ratio changed little after adjustment for confounders (odds ratio 6.39, 95% confidence interval 1.41 to 28.93). In conclusion, more severe atherosclerotic disease and female gender were associated with an increased risk of perioperative myocardial injury during off-pump bypass surgery, although the presence of coronary collaterals appeared to be protective. Patients with perioperative myocardial injury during off-pump surgery were at a higher risk of adverse cardiac outcomes at 1 year.
Age Factors↗
Gender as an independent risk factor for herpes zoster: a population-based prospective study.
PURPOSE: Several studies reported a difference in herpes zoster (HZ) incidence between males and females, but limitations in design and analysis impeded the assessment of gender as an independent risk factor for HZ. This study examines the independent etiologic association between gender and HZ. METHODS: A total of 335,714 persons were observed prospectively during 2001. We registered gender and HZ occurrence, as well as other risk factors for HZ. We calculated overall crude and adjusted odds ratios (ORs) and stratified to age. RESULTS: The HZ incidence in females was 3.9/1000 patients/year (95% confidence interval [CI], 3.6-4.2), and in males, 2.5/1000 patients/year (95% CI, 2.3-2.8), with a crude OR of 1.53 (95% CI, 1.36-1.74). After adjustment for potential confounders, the adjusted OR was 1.38 (95% CI, 1.22-1.56). The incidence was greater in females in the middle-aged (age, 25 to 64 years; OR range, 1.36 to 1.83) and youngest group (OR, 1.31; 95% CI, 0.90-1.89). Gender effect was inverse in young adults (age, 15 to 24 years; OR, 0.64; 95% CI, 0.41-1.03). CONCLUSION: Female gender is an independent risk factor for HZ in the 25- to 64-year-old age groups.
Adolescent↗
The PINE study of epidural steroids and local anaesthetics to prevent postherpetic neuralgia: a randomised controlled trial.
BACKGROUND: Postherpetic neuralgia is the most frequent complication of herpes zoster. Treatment of this neuropathic pain syndrome is difficult and often disappointing. We assessed the effectiveness of a single epidural injection of steroids and local anaesthetics for prevention of postherpetic neuralgia in older patients with herpes zoster. METHODS: We randomly assigned 598 patients older than 50 years, with acute herpes zoster (rash <7 days) below dermatome C6, to receive either standard therapy (oral antivirals and analgesics) or standard therapy with one additional epidural injection of 80 mg methylprednisolone acetate and 10 mg bupivacaine. The primary endpoint was the proportion of patients with zoster-associated pain 1 month after inclusion. Analyses were by intention-to-treat. This study is registered as an International Standard Randomised Controlled Trial, number ISRCTN32866390. FINDINGS: At 1 month, 137 (48%) patients in the epidural group reported pain compared with 164 (58%) in the control group (relative risk [RR] 0.83, 95% CI 0.71-0.97, p=0.02). After 3 months these values were 58 (21%) and 63 (24%) respectively (0.89, 0.65-1.21, p=0.47) and, at 6 months, 39 (15%) and 44 (17%; 0.85, 0.57-1.13, p=0.43). We detected no subgroups in which the relative risk for pain 1 month after inclusion substantially differed from the overall estimate. No patient had major adverse events related to epidural injection. INTERPRETATION: A single epidural injection of steroids and local anaesthetics in the acute phase of herpes zoster has a modest effect in reducing zoster-associated pain for 1 month. This treatment is not effective for prevention of long-term postherpetic neuralgia.
Aged↗
Distraction from randomization in diagnostic research.
The ultimate goal of medical care, including diagnostic testing, is to improve patient outcome. Accordingly, it has been advocated widely that when establishing a test's diagnostic accuracy, the impact of the test on patient outcome subsequently must be quantified. When studying patient outcome in medical research, the use of randomized comparisons comes into perspective. In our view, randomized studies often are not necessary to validly estimate the effect of the diagnostic test on patient outcome. Results of cross-sectional diagnostic studies, combined with results from therapeutic studies, often will suffice.
Cross-Sectional Studies↗
The value of clinical findings and D-dimer tests in diagnosing deep vein thrombosis in primary care.
In primary care, the physician has to decide which patients with a suspicion of deep vein thrombosis (DVT) have to be referred for further diagnostic work-up. Accurate referral is of utmost importance because unrecognized and therefore untreated DVT may cause pulmonary embolism. The classic clinical findings are not sufficiently accurate for the diagnosis of DVT. The majority of the referred patients, 70 to 80%, do not have DVT and this puts a burden on both patients and health care budgets. Diagnosis in primary care is different from that in secondary care caused by the referral mechanism or spectrum difference. Diagnostic tests derived in secondary care, therefore, cannot simply be generalized to primary-care patients. The well-known diagnostic rule for DVT, the Wells rule, does not adequately rule out DVT in primary-care patients. A proper diagnostic rule for use in primary care is lacking; therefore, we investigated the data of 1,295 patients in primary care suspected of having DVT. We developed and validated a simple diagnostic decision rule to exclude the presence of DVT safely in primary care. Independent diagnostic indicators of the presence of DVT were male gender, oral contraceptive use, presence of malignancy, recent surgery, absence of leg trauma, vein distension, calf circumference difference, and D-dimer test result. Application of this rule could reduce the number of referrals by at least 23%, whereas only 0.7% of the patients with a DVT would not be referred. A diagnosis strategy is given, together with a practical flow diagram.
Female↗
Validating and updating a prediction rule for neurological sequelae after childhood bacterial meningitis.
Recently, a prediction rule for developing neurological sequelae after childhood bacterial meningitis was developed on a small derivation set. Before implementing in practice a prediction rule must first be tested in new patients (external validation). Our aim was to study the external validity of this rule and, if necessary, to update the rule. The prediction rule was tested on newly available data (validation set) by assessing the rule's calibration and discrimination. We updated the prediction rule by adding extra predictors and re-estimating the regression coefficients of the original predictors in the combined datasets. The rule showed poor agreement between predicted risks and observed frequencies. The ROC area was 0.65 (95% CI 0.57-0.72), which was statistically significantly lower than in the derivation set (0.87 (0.78-0.96)), p-value<0.01. The updated prediction rule showed adequate performance in the combined data sets; the ROC area was 0.77 (95% CI 0.72-0.82). Further study of the generalizability of this updated rule may stimulate application in clinical practice.
Child↗
Effects of an anesthesia preoperative medicine clinic.
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Ambulatory Care Facilities↗
Prognosis following severe head injury: Development and validation of a model for prediction of death, disability, and functional recovery.
BACKGROUND: A prognostic model for head trauma patients is useful only if it predicts clinically relevant outcomes accurately on new subjects in various settings. Most existing models consider only dichotomous outcome and have not been tested externally. We developed and validated a rule for prediction of three functional outcome states after severe head injury, using information from day 1. METHODS: The model was developed in a cohort of 304 adults who were admitted to a Dutch trauma center and had survived and remained comatose for >24 hours following severe head injury. We used ordinal logistic regression analysis to predict the extended Glasgow Outcome Scale after > or =12 months, merged into three categories. We preselected five known predictors of outcome and used bootstrapping techniques to avoid statistical overfitting. The performance of the model was subsequently tested in a cohort of 122 patients from an unrelated hospital. RESULTS: The model contained age (p < 0.0001), best motor response on day 1 (p = 0.002), pupil response after resuscitation (p = 0.005), computed tomography findings (p = 0.004), and presence of arterial hypotension (p = 0.37) as predictor variables. In the external validation cohort, the model showed adequate agreement between observed and predicted outcome probabilities (calibration). The model had a good ability to discriminate patients with different outcomes (c-statistic 0.808). The predictive accuracy was 66% when the model was used to classify patients across the three outcome categories. CONCLUSIONS: We have developed a practical model for predicting the probability of death, survival with major disability, and functional recovery in patients who are comatose 24 hours after severe head injury. The model performed well in an external setting, indicating that measures to avoid statistical overfitting were successful.
Adult↗
Predictive performance of three multivariate difficult tracheal intubation models: a double-blind, case-control study.
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Case-Control Studies↗
Different cut-off values for two D-dimer assays to exclude deep venous thrombosis in primary care.
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Diagnosis, Differential↗
Deep vein thrombosis in primary care: possible malignancy?
BACKGROUND: The increased prevalence of unrecognised malignancy in patients with deep vein thrombosis (DVT) has been well established in secondary care settings. However, data from primary care settings, needed to tailor the diagnostic workup, are lacking. AIM: To quantify the prevalence of unrecognised malignancy in primary care patients who have been diagnosed with DVT. DESIGN: Prospective follow-up study. SETTING: All primary care physicians affiliated/associated with a non-teaching hospital in a geographically circumscribed region participated in the study. METHOD: A total of 430 consecutive patients without known malignancy, but with proven DVT were included in the study and compared with a control group of 442 primary care patients, matched according to age and sex. Previously unrecognised, occult malignancy was considered present if a new malignancy was diagnosed within 2 years following DVT diagnosis (DVT group) or inclusion in the control group. Patients with DVT were categorised in to those with unprovoked idiopathic DVT and those with risk factors for DVT (that is, secondary DVT). RESULTS: During the 2-year follow-up period, a new malignancy was diagnosed 3.6 times more often in patients with idiopathic DVT than in the control group (2-year incidence: 7.4% and 2.0%, respectively). The incidence in patients with secondary DVT was 2.6%; only slightly higher than in control patients. CONCLUSION: Unrecognised malignancies are more common in both primary and secondary care patients with DVT than in the general population. In particular, patients with idiopathic DVT are at risk and they could benefit from individualised case-finding to detect malignancy.
Case-Control Studies↗
Recognising heart failure in elderly patients with stable chronic obstructive pulmonary disease in primary care: cross sectional diagnostic study.
OBJECTIVE: To determine which clinical variables provide diagnostic information in recognising heart failure in primary care patients with stable chronic obstructive pulmonary disease (COPD) and whether easily available tests provide added diagnostic information. DESIGN: Cross sectional diagnostic study. SETTING: 51 primary care practices. PARTICIPANTS: 1186 patients aged > or = 65 years with COPD diagnosed by their general practitioner who did not have a diagnosis of heart failure confirmed by a cardiologist. MAIN OUTCOME MEASURES: Independent diagnostic variables for concomitant heart failure in primary care patients with stable COPD. RESULTS: 405 patients (34% of eligible patients) underwent a systematic diagnostic investigation, which resulted in 83 (20.5%) receiving a new diagnosis of concomitant heart failure. Independent clinical variables for concomitant heart failure were a history of ischaemic heart disease, high body mass index, laterally displaced apex beat, and raised heart rate (area under the receiver operating characteristic curve (ROC area) 0.70, 95% confidence interval 0.64 to 0.76). Addition of measurement of N-terminal pro-brain natriuretic peptide (NT-proBNP) to the reduced "clinical model" had the largest added diagnostic value, with a significant increase of the ROC area to 0.77 (0.71 to 0.83), followed by electrocardiography (0.75, 0.69 to 0.81). C reactive protein and chest radiography had limited added value. A simplified diagnostic model consisting of the four independent clinical variables plus NT-proBNP and electrocardiography was developed. CONCLUSIONS: A limited number of items easily available from history and physical examination, with addition of NT-proBNP and electrocardiography, can help general practitioners to identify concomitant heart failure in individual patients with stable COPD.
Aged↗