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Yvonne Vergouwe

Publications and source records attributed to Yvonne Vergouwe.

14 recordsLinked to original sources
PubMed2006

A prediction rule for shoulder pain related sick leave: a prospective cohort study.

BACKGROUND: Shoulder pain is common in primary care, and has an unfavourable outcome in many patients. Information about predictors of shoulder pain related sick leave in workers is scarce and inconsistent. The objective was to develop a clinical prediction rule for calculating the risk of shoulder pain related sick leave for individual workers, during the 6 months following first consultation in general practice. METHODS: A prospective cohort study with 6 months follow-up was conducted among 350 workers with a new episode of shoulder pain. Potential predictors included the results of a physical examination, sociodemographic variables, disease characteristics (duration of symptoms, sick leave in the 2 months prior to consultation, pain intensity, disability, comorbidity), physical activity, physical work load, psychological factors, and the psychosocial work environment. The main outcome measure was sick leave during 6 months following first consultation in general practice. RESULTS: Response rate to the follow-up questionnaire at 6 months was 85%. During the 6 months after first consultation 30% (89/298) of the workers reported sick leave. 16% (47) reported 10 days sick leave or more. Sick leave during this period was predicted in a multivariable model by a longer duration of sick leave prior to consultation, more shoulder pain, a perceived cause of strain or overuse during regular activities, and co-existing psychological complaints. The discriminative ability of the prediction model was satisfactory with an area under the curve of 0.70 (95% CI 0.64-0.76). CONCLUSION: Although 30% of all workers with shoulder pain reported sick leave during follow-up, the duration of sick leave was limited to a few days in most workers. We developed a prediction rule and a score chart that can be used by general practitioners and occupational health care providers to calculate the absolute risk of sick leave in individual workers with shoulder pain, which may help to identify workers who need additional attention. The performance and applicability of our model needs to be tested in other working populations with shoulder pain to enable valid and reliable use of the score chart in everyday practice.

Disability Evaluation↗
PubMed2006

Predicting retroperitoneal histology in postchemotherapy testicular germ cell cancer: a model update and multicentre validation with more than 1000 patients.

OBJECTIVES: Surgical resection of postchemotherapy retroperitoneal lymph nodes is often performed in patients with advanced nonseminomatous testicular germ cell cancer. We previously developed a model to predict the probability that the lymph nodes contain only necrotic or fibrotic (benign) tissue versus mature teratoma and viable cancer (tumour) to identify patients who actually need resection. The present study used an updated model with new patient data and studied the validity of the updated model across various settings. METHODS: We combined data of 544 patients from the original model with data of 550 new patients and performed a new logistic regression analysis, which included the same six predictors: histology of the primary tumour, prechemotherapy serum levels of alpha-fetoprotein, human chorionic gonadotropin, lactate dehydrogenase, residual mass size measured on computed tomography, and change in mass size. The validity of the updated model was studied in individual centres. Calibration of the predicted probabilities was assessed graphically and with the Hosmer-Lemeshow test. Discrimination was studied with the concordance (c)-statistic. RESULTS: The updated model had slightly different, although more precise, regression coefficients. Statistically nonsignificant Hosmer-Lemeshow tests confirmed good calibration in most centres. The c-statistic for all centres except one exceeded 0.80. The updated model was valid over the complete range of predicted probabilities across a broad spectrum of centres. CONCLUSIONS: This finding gives confidence in the applicability of the model to select patients for resection, particularly patients with small residual masses and low predicted probabilities of benign tissue (i.e., substantial predicted risks of residual tumour).

Humans↗
PubMed2006

Clinical prediction rules for the prognosis of shoulder pain in general practice.

Shoulder pain is common in primary care and has an unfavourable outcome in many patients. Information about predictors of outcome is scarce and inconsistent. The objective of this study was to develop clinical prediction rules for calculating the absolute risk of persistent shoulder symptoms for individual patients, 6 weeks and 6 month after the first consultation in general practice. A prospective cohort study with 6 months follow-up was carried out in three geographic areas in The Netherlands. In this study, 587 patients with a new episode of shoulder pain were included. The main outcome measure was persistent symptoms at 6 weeks and 6 months, perceived by the patient. Potential predictors included the results of a physical examination, sociodemographic variables, disease characteristics (duration of symptoms, pain intensity, disability and comorbidity), physical activity, physical workload and psychosocial factors. Response rates to the follow-up questionnaires were 83% at 6 weeks and 92% at 6 months. A longer duration of symptoms, gradual onset of pain and high pain severity at presentation were consistently associated with persistent symptoms at 6 weeks and 6 months. The discriminative validity of our prediction rules was satisfactory with area under the curves of 0.74 (95% CI 0.70, 0.79) at 6 weeks and 0.67 (95% CI 0.63, 0.71) at 6 months. The performance of our rules needs to be tested in other populations of patients with shoulder pain to enable valid and reliable use of the rules in everyday clinical practice.

Algorithms↗
PubMed2006

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↗
PubMed2006

Hospitalization for respiratory syncytial virus infection in young children: development of a clinical prediction rule.

BACKGROUND: Because passive immunization against respiratory syncytial virus (RSV) is costly, its use should be restricted to well-defined groups of high risk children. We aimed to develop a clinical prediction rule that estimates the individual monthly risk of hospitalization for RSV infection in young children. METHODS: A retrospective cohort study was conducted in the southwestern part of The Netherlands. We included children born between January 1, 1996 and December 31, 1998. Children hospitalized for proven RSV infection were compared with children not hospitalized for RSV infection. The monthly risk was estimated with a logistic regression model including 5 clinical predictors (gender, gestational age, birth weight, presence of bronchopulmonary dysplasia and age) and the mean seasonal monthly pattern of RSV infections. We compared the predictive performance of the prediction rule with the guidelines of the American Academy of Pediatrics (AAP). FINDINGS: Information was collected on 2469 hospitalized children and 140,661 children who were 1,181,790 months at risk. All predictors were statistically significant, with age and the seasonal monthly RSV pattern having the strongest effects. The clinical prediction rule that included these predictors could better discriminate between high and low risk children than the AAP guidelines and would potentially reduce the number of immunizations by 20%. INTERPRETATION: The prediction rule reliably estimates individual monthly risks of hospitalization for RSV infection in the population studied. It provides an improved index for passive immunization but further validation in other populations is required.

Age Factors↗
PubMed2005

Diagnostic model for sensitization in workers exposed to occupational high molecular weight allergens.

BACKGROUND: Occupational allergy has great impact on workers exposed to high molecular weight (HMW) allergens. The present study is aimed to develop and validate a generic diagnostic model for sensitization to HMW allergens, defined as positive IgE. METHODS: The model was developed in pooled data from Dutch laboratory animal (LA) workers and bakers using logistic regression analysis. Validity was assessed internally by bootstrapping procedure, and externally in British LA workers. RESULTS: The model included working hours/week, work-related symptoms, total IgE, and IgE to common allergen. Significant interactions between the type of work and the predictors resulted in different scores for LA workers and bakers. Internal and external validation showed that the model was satisfactorily calibrated and discriminated between workers at high and low risk of being sensitized. CONCLUSIONS: It is possible to develop a generic model for sensitization to occupational HMW allergens. However, the weighing of predictors differs across specific work environments.

Adult↗
PubMed2005

Substantial effective sample sizes were required for external validation studies of predictive logistic regression models.

BACKGROUND AND OBJECTIVES: The performance of a prediction model is usually worse in external validation data compared to the development data. We aimed to determine at which effective sample sizes (i.e., number of events) relevant differences in model performance can be detected with adequate power. METHODS: We used a logistic regression model to predict the probability that residual masses of patients treated for metastatic testicular cancer contained only benign tissue. We performed standard power calculations and Monte Carlo simulations to estimate the numbers of events that are required to detect several types of model invalidity with 80% power at the 5% significance level. RESULTS: A validation sample with 111 events was required to detect that a model predicted too high probabilities, when predictions were on average 1.5 times too high on the odds scale. A decrease in discriminative ability of the model, indicated by a decrease in the c-statistic from 0.83 to 0.73, required 81 to 106 events, depending on the specific scenario. CONCLUSION: We suggest a minimum of 100 events and 100 nonevents for external validation samples. Specific hypotheses may, however, require substantially higher effective sample sizes to obtain adequate power.

Humans↗
PubMed2004

Anticipated costs of hospitalization for respiratory syncytial virus infection in young children at risk.

BACKGROUND: Reliable estimates of hospitalization costs for severe respiratory syncytial virus (RSV) infection are necessary to perform economic analyses of preventive strategies of severe RSV disease. We aimed to develop a model that predicts anticipated mean RSV hospitalization costs of groups of young children at risk for hospitalization, but not yet hospitalized, based on readily available child characteristics. METHODS: We determined real direct medical costs of RSV hospitalization from a societal perspective, using a bottom-up strategy, in 3458 infants and young children hospitalized for severe RSV disease during the RSV seasons 1996-1997 to 1999-2000 in the Southwest of the Netherlands. We used a linear regression model to predict anticipated mean RSV hospitalization costs of groups of children at risk, based on 4 child characteristics [age, gestational age, birth weight and bronchopulmonary dysplasia (BPD)], expressed in EC Euros as of the year 2000. FINDINGS: The mean RSV hospitalization costs of all patients were 3110 Euros. RSV hospitalization costs were higher for patients with lower gestational age (5555 Euros; gestational age, </=28 weeks), lower birth weight (3895 Euros; birth weight </=2500 g), BPD (5785 Euros; with BPD) and young age (4730 Euros; first month of life). The linear regression model had an adjusted R of 0.08. This indicates a low explanatory ability for hospitalization costs of individual children. However, the model could accurately estimate the anticipated mean hospitalization costs of groups of children with the same characteristics. INTERPRETATION: RSV hospitalization costs were substantial, especially of specific high risk groups. Anticipated mean hospitalization costs of groups of children at risk for RSV hospitalization, but not yet hospitalized, could well be estimated with 4 child characteristics (age, gestational age, birth weight and BPD). These estimated costs can be used for economic analyses of preventive strategies for severe RSV disease.

Age Distribution↗
PubMed2003

Predictors of occult metastasis in clinical stage I nonseminoma: a systematic review.

PURPOSE: Patients with clinical stage I nonseminomatous testicular germ cell tumor should ideally receive adjuvant therapy only when they are at high risk for occult metastasis. We aimed to quantify the importance of predictors for occult metastasis by performing a systematic review of the relevant literature. In addition, we reviewed published multivariable models and risk-adapted treatment policies. PATIENTS AND METHODS: We identified 23 publications between 1979 and 2001, reporting a total of 2,587 patients. Twenty-nine percent of the patients (759 of 2,587 patients) had occult metastases, which was diagnosed either at retroperitoneal lymph node dissection (n = 193) or during follow-up (n = 566). Odds ratios (OR) were pooled using meta-analysis techniques. RESULTS: The presence of vascular invasion of the primary tumor cells had the strongest effect (OR, 5.2; 95% CI, 4.0 to 6.8). Immunohistochemical staining of the primary tumor cells with the MIB-1 monoclonal antibody showing proliferative activity was a promising predictor (OR, 4.7; 95% CI, 2.0 to 11). Intermediate effects were found for embryonal carcinoma in the primary tumor (OR, 2.9; 95% CI, 2.0 to 4.4) and a high pathologic stage of the tumor (OR, 2.6; 95% CI, 1.8 to 3.8). Size of the primary tumor and age of the patient had weaker though also statistically significant associations with occult metastasis. Until now, multivariable models often included vascular invasion and embryonal carcinoma with one or two weaker predictors. None of the published risk-adapted treatment policies included MIB-1 staining. CONCLUSION: Several strong predictors for occult metastasis were identified. A risk-adapted treatment policy should be developed that incorporates all relevant predictors so that adjuvant therapy is targeted better to those with occult metastases.

Adult↗
PubMed2002

Validity of prognostic models: when is a model clinically useful?

Prognostic models combine patient characteristics to predict medical outcomes. Unfortunately, such models do not always perform as well for other patients as those from whose data the models were derived. Therefore, validity of prognostic models needs to be assessed in new patients. Predicted probabilities can be calculated with the model and compared with the actually observed outcomes. We may distinguish several aspects of validity: (1) agreement between predicted probabilities and observed probabilities (calibration), (2) ability of the model to distinguish subjects with different outcomes (discrimination), and (3) ability of the model to improve the decision-making process (clinical usefulness). We discuss those aspects and show some measures by using models for testicular and prostate cancer. We conclude that good calibration and discriminative ability are not sufficient for a model to be clinically useful. Application of a prognostic model is sensible, if the model is able to provide useful additional information for clinical decision making.

Decision Support Techniques↗
PubMedDate not supplied

Validation of two risk models for perioperative mortality in patients undergoing elective abdominal aortic aneurysm surgery.

The authors validated 2 clinical risk models for perioperative mortality in patients scheduled for elective open abdominal aortic aneurysm surgery (AAA surgery). They studied 361 patients who underwent elective AAA surgery between 1991 and 1999 (validation population). Two clinical risk models were validated. The first was developed in 238 patients from Leiden University Hospital (Leiden risk model). The Leiden risk model was modified to provide predictions for the validation population based on 6 predictors including age, gender, a history of previous myocardial infarction, congestive heart failure, renal disease, and pulmonary disease. The second was a recently published simpler risk model developed in 820 patients in the UK Small Aneurysm Trial (UK risk model) and included 3 predictors (age and renal and pulmonary comorbidity). Logistic regression was used to quantify the relationship between predictors and outcome (mortality within 30 days of surgery). Validation further included the concordance statistic (c-statistic) for discriminative ability and the Hosmer-Lemeshow test for model reliability. The perioperative mortality in the validation population was 6.6% (24/361). Predictors had similar odds ratios, with particularly strong effects of congestive heart failure, pulmonary disease, and renal impairment. The Leiden risk model had reasonable good ability (c-statistic 0.72) and showed adequate calibration (chi(2)=3.3, p=0.97). It could particularly identify a low-risk group. The UK risk model did not perform well (c-statistic 0.60), showing statistically significant lack of fit (chi(2)=64.9, p<0.001). This study showed similar predictive ability of previously identified predictors for perioperative mortality. The Leiden risk model could identify a low-risk group, while the UK risk model showed a relatively poor performance. The current study supports the use of the Leiden model for preoperative risk assessment.

Aged↗