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3. Inter- and intraobserver agreement of antenatal cardiotocography assessments by maternity care professionals:A prospective study

Author

Neppelenbroek, Elise M., van der Heijden, Olivier W.H., de Vet, Henrica C.W., de Groot, Amanda J.J., Daemers, Darie O.A., de Jonge, Ank, Verhoeven, Corine J.M., Neppelenbroek, Elise M., van der Heijden, Olivier W.H., de Vet, Henrica C.W., de Groot, Amanda J.J., Daemers, Darie O.A., de Jonge, Ank, and Verhoeven, Corine J.M.

Abstract

Objective: In the Netherlands, antenatal cardiotocography (aCTG) to assess fetal well-being is performed in obstetrician-led care. An innovative initiative was started to evaluate whether aCTG for specific indications—reduced fetal movements, external cephalic version, or postdate pregnancy—is feasible in non-obstetrician-led care settings by independent primary care midwives. Quality assessment is essential when reorganizing and shifting tasks and responsibilities. Therefore, we aimed to assess the inter- and intraobserver agreement for aCTG assessments between and within four professional groups involved in Dutch maternity care regarding the overall classification and assessment of the various components of aCTG. Method: This was a prospective study among 47 Dutch primary care midwives, hospital-based midwives, residents, and obstetricians. Ten aCTG traces were assessed twice at a 1 month interval. To ensure a representative sample, we used two different sets of 10 aCTG traces each. We calculated the degree of agreement using the proportions of agreement. Results: The proportions of agreement for interobserver agreement on the classification of aCTG between and within the four professional groups varied from 0.82 to 0.94. The proportions of agreement for each professional group were slightly higher for intraobserver (0.86–0.94) than for interobserver agreement. For the various aCTG components, the proportions of agreement for interobserver agreement varied from 0.64 (presence of contractions) to 0.98 (baseline heart frequency). Conclusion: The proportion of agreement levels between and within the maternity care professionals in the classification of aCTG traces among healthy women were comparable. This means that these professional groups are equally well able to classify aCTGs in healthy pregnant women.

Published
2024

15. Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

Author

Eertink, Jakoba Johanna, Zwezerijnen, Gerben J.C., Wiegers, Sanne E., Pieplenbosch, Simone, Chamuleau, Martine E.D., Lugtenburg, Pieternella J., de Jong, Daphne, Ylstra, Bauke, Mendeville, Matias, Dührsen, Ulrich, Hanoun, Christine, Hüttmann, Andreas, Richter, Julia, Klapper, Wolfram, Jauw, Yvonne W.S., Hoekstra, Otto S., de Vet, Henrica C.W., Boellaard, Ronald, Zijlstra, Josée M., Radiology and nuclear medicine, Hematology, CCA - Cancer Treatment and quality of life, CCA - Cancer biology and immunology, Pathology, AII - Cancer immunology, CCA - Imaging and biomarkers, Epidemiology and Data Science, APH - Methodology, Amsterdam Neuroscience - Brain Imaging, and AII - Infectious diseases

Subjects
Medizin, Hematology
Abstract

We investigated whether the outcome prediction of patients with aggressive B-cell lymphoma can be improved by combining clinical, molecular genotype, and radiomics features. MYC, BCL2, and BCL6 rearrangements were assessed using fluorescence in situ hybridization. Seventeen radiomics features were extracted from the baseline positron emission tomography–computed tomography of 323 patients, which included maximum standardized uptake value (SUVmax), SUVpeak, SUVmean, metabolic tumor volume (MTV), total lesion glycolysis, and 12 dissemination features pertaining to distance, differences in uptake and volume between lesions, respectively. Logistic regression with backward feature selection was used to predict progression after 2 years. The predictive value of (1) International Prognostic Index (IPI); (2) IPI plus MYC; (3) IPI, MYC, and MTV; (4) radiomics; and (5) MYC plus radiomics models were tested using the cross-validated area under the curve (CV-AUC) and positive predictive values (PPVs). IPI yielded a CV-AUC of 0.65 ± 0.07 with a PPV of 29.6%. The IPI plus MYC model yielded a CV-AUC of 0.68 ± 0.08. IPI, MYC, and MTV yielded a CV-AUC of 0.74 ± 0.08. The highest model performance of the radiomics model was observed for MTV combined with the maximum distance between the largest lesion and another lesion, the maximum difference in SUVpeak between 2 lesions, and the sum of distances between all lesions, yielding an improved CV-AUC of 0.77 ± 0.07. The same radiomics features were retained when adding MYC (CV-AUC, 0.77 ± 0.07). PPV was highest for the MYC plus radiomics model (50.0%) and increased by 20% compared with the IPI (29.6%). Adding radiomics features improved model performance and PPV and can, therefore, aid in identifying poor prognosis patients.

Published
2023
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16. Cultural competency of GP trainees and GP trainers: a cross-sectional survey study.

Author

Bouchareb, Siham, van der Heijden, Amber A.W.A, van Diesen, Josine A.Y, van den Muijsenbergh, Maria, Mennink, Sylvia, de Vet, Henrica C.W, Blankenstein, Annette H., and Elders, Petra J.M

Subjects
NATIONAL competency-based educational tests, STATISTICS, HOSPITAL medical staff, PROFESSIONS, CONFIDENCE intervals, FAMILY medicine, ATTITUDES of medical personnel, HEALTH occupations students, CROSS-sectional method, SELF-perception, EMIGRATION & immigration, REGRESSION analysis, T-test (Statistics), CULTURAL competence, QUESTIONNAIRES, DESCRIPTIVE statistics, RESEARCH funding, STUDENT attitudes, STATISTICAL models, DATA analysis, RESIDENTIAL patterns
Abstract

To assess the cultural competence (CC) of GP trainees and GP trainers. Design and setting: A cross-sectional survey study was conducted at the GP Training Institute of Amsterdam UMC. We included 92 GP trainees and 186 GP trainers. We measured the three domains of cultural competency: 1) knowledge, 2) culturally competent attitudes and 3) culturally competent skills. Regression models were used to identify factors associated with levels of CC. Participants rated their self-perceived CC at the beginning and end of the survey, and the correlation between self-perceived and measured CC was assessed. Approximately 94% of the GP trainees and 81% of the GP trainers scored low on knowledge; 45% and 42%, respectively, scored low on culturally competent attitudes. The level of culturally competent skills was moderate (54.3%) or low (48.4%) for most GP trainees and GP trainers. The year of residency and the GP training institute were significantly associated with one or more (sub-)domains of CC in GP trainees. Having >10% migrant patients and experience as a GP trainer were positively associated with one or more (sub-) domains of cultural competence in GP trainers. The correlation between measured and self-perceived CC was positive overall but very weak (Spearman correlation coefficient ranging from −0.1–0.3). The level of cultural competence was low in both groups, especially in the knowledge scores. Cultural competence increased with experience and exposure to an ethnically diverse patient population. Our study highlights the need for cultural competence training in the GP training curricula. General practitioner (GP) trainees find cross-cultural consultations stressful due to a self-perceived lack of cultural competence (CC). The level of CC in general practice is as yet unknown. On average, the level of CC was low for the majority of GP trainees and GP trainers, especially for the scores on knowledge. CC increased with experience and exposure to an ethnically diverse patient population. GP trainees and trainers perceived a lack of covered education on various topics related to the care of migrants. Our study highlights the need for cultural competence training in the GP training curricula. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Discriminative Validity of the Pain Attitudes and Beliefs Scale for Physical Therapists

Author

Eland, Nicolaas D., Kvale, Alice, Ostelo, Raymond W.J.G., De Vet, Henrica C.W., and Strand, Liv I.

Subjects
Surveys, Evaluation, Physical therapists -- Surveys, Health attitudes -- Surveys, Health surveys -- Evaluation, Pain management -- Surveys, Back pain
Abstract

The traditional biomedical view of low back pain (LBP) as a purely structural or biomechanical disorder has been greatly challenged over the past 2 decades. (1,2) There is now a [...], Background. The Pain Attitudes and Beliefs Scale (PABS) for Physical Therapists aims to measure clinicians' biomedical and biopsychosocial treatment orientations regarding nonspecific low back pain. Objective. The objective of this study was to assess whether the PABS can differentiate between subgroups of physical therapists hypothesized to differ in treatment orientations. Design. This study was a cross-sectional survey. Methods. The PABS was completed by 662 Norwegian physical therapists with a diversity of professional backgrounds. Twenty-four a priori hypotheses on expected differences in PABS scores were formulated. Sufficient discriminative ability was defined as a minimum of 75% confirmed hypotheses. Hypotheses on differences in scores were tested for the biomedical and biopsychosocial subscales separately as well as for combinations of the 2 subscales, representing responders with high biomedical and low biopsychosocial PABS scores and vice versa. Results. Of the 24 hypotheses, only 15 (62.5%) were confirmed. Between-group differences concerning the separate subscales were small, varying from -0.63 to 1.70 scale points, representing values up to 6.0% of the total subscale ranges. Between-group differences were larger when combined subscales were used, varying from 1.80 to 6.70 points, representing values up to 25.1% of the total subscale ranges. Despite little spread in scores, 24% of respondents demonstrated extreme attitudes. Limitations. The lack of convincing scientific evidence from previous research on differences in attitudes and beliefs between physical therapists was a limitation for the formulation of hypotheses. Conclusions. Discriminative validity of separate subscales of the PABS was not supported. Combining the 2 subscales into global treatment attitudes enabled better discrimination. Little spread in biomedical and biopsychosocial orientations explains why more than one-third of the hypotheses were not confirmed. Either Norwegian physical therapists are basically similar in their treatment orientation or the PABS is not able to detect any differences between them.

Published
2019
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23. An artificial intelligence method using FDG PET to predict treatment outcome in diffuse large B cell lymphoma patients

Author

Ferrández, Maria C., Golla, Sandeep S.V., Eertink, Jakoba J., de Vries, Bart M., Lugtenburg, Pieternella J., Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pieplenbosch, Simone, Kurch, Lars, Hüttmann, Andreas, Hanoun, Christine, Dührsen, Ulrich, de Vet, Henrica C.W., Zijlstra, Josée M., Boellaard, Ronald, Ferrández, Maria C., Golla, Sandeep S.V., Eertink, Jakoba J., de Vries, Bart M., Lugtenburg, Pieternella J., Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pieplenbosch, Simone, Kurch, Lars, Hüttmann, Andreas, Hanoun, Christine, Dührsen, Ulrich, de Vet, Henrica C.W., Zijlstra, Josée M., and Boellaard, Ronald

Abstract

Convolutional neural networks (CNNs) may improve response prediction in diffuse large B-cell lymphoma (DLBCL). The aim of this study was to investigate the feasibility of a CNN using maximum intensity projection (MIP) images from 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) baseline scans to predict the probability of time-to-progression (TTP) within 2 years and compare it with the International Prognostic Index (IPI), i.e. a clinically used score. 296 DLBCL 18F-FDG PET/CT baseline scans collected from a prospective clinical trial (HOVON-84) were analysed. Cross-validation was performed using coronal and sagittal MIPs. An external dataset (340 DLBCL patients) was used to validate the model. Association between the probabilities, metabolic tumour volume and Dmaxbulk was assessed. Probabilities for PET scans with synthetically removed tumors were also assessed. The CNN provided a 2-year TTP prediction with an area under the curve (AUC) of 0.74, outperforming the IPI-based model (AUC = 0.68). Furthermore, high probabilities (> 0.6) of the original MIPs were considerably decreased after removing the tumours (< 0.4, generally). These findings suggest that MIP-based CNNs are able to predict treatment outcome in DLBCL.

Published
2023

24. An artificial intelligence method using 18F-FDG PET maximum intensity projections to predict 2-year time-to-progression in diffuse large B-cell lymphoma patients

Author

Ferrández, Maria C., primary, Golla, Sandeep S. V., additional, Eertink, Jakoba J., additional, de Vries, Bart M., additional, Lugtenburg, Pieternella. J., additional, Wiegers, Sanne E., additional, Zwezerijnen, Gerben J. C., additional, Pieplenbosch, Simone, additional, Kurch, Lars, additional, Hüttmann, Andreas, additional, Hanoun, Christine, additional, Dührsen, Ulrich, additional, de Vet, Henrica C.W., additional, Zijlstra, Josée M., additional, and Boellaard, Ronald, additional

Published
2023
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29. Physical and Psychological Distress Are Related to Dying Peacefully in Residents With Dementia in Long-Term Care Facilities

Author

Van den Block, Lieve, De Groote, Zeger, Brearley, Sarah, Caraceni, Augusto, Cohen, Joachim, Francke, Anneke, Harding, Richard, Higginson, Irene J., Kaasa, Stein, Linden, Karen, Miccinesi, Guido, Onwuteaka-Philipsen, Bregje, Pardon, Koen, Pasman, Roeline, Pautex, Sophie, Payne, Sheila, LucDeliens, De Roo, Maaike L., Albers, Gwenda, Deliens, Luc, de Vet, Henrica C.W., Francke, Anneke L., and Van Den Noortgate, Nele

Published
2015
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38. External Validation Shows That Baseline PET Radiomics Outperform the IPI Risk Score for Prediction of Outcome in DLBCL

Author

Eertink, Jakoba J, primary, Zwezerijnen, Gerben JC, additional, Heymans, Martijn W, additional, Pieplenbosch, Simone, additional, Wiegers, Sanne E, additional, Dührsen, Ulrich, additional, Hüttmann, Andreas, additional, Kurch, Lars, additional, Hanoun, Christine, additional, Lugtenburg, Pieternella, additional, Barrington, Sally F, additional, Mikhaeel, George, additional, Ceriani, Luca, additional, Zucca, Emanuele, additional, Czibor, Sandor, additional, Györke, Tamás, additional, Chamuleau, Martine E.D., additional, Hoekstra, Otto S, additional, de Vet, Henrica C.W, additional, Boellaard, Ronald, additional, and Zijlstra, Josée M., additional

Published
2022
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46. Proposed New Dynamic Prognostic Index for Diffuse Large B-Cell Lymphoma: International Metabolic Prognostic Index

Author

Mikhaeel, N. George, primary, Heymans, Martijn W., additional, Eertink, Jakoba J., additional, de Vet, Henrica C.W., additional, Boellaard, Ronald, additional, Dührsen, Ulrich, additional, Ceriani, Luca, additional, Schmitz, Christine, additional, Wiegers, Sanne E., additional, Hüttmann, Andreas, additional, Lugtenburg, Pieternella J., additional, Zucca, Emanuele, additional, Zwezerijnen, Gerben J.C., additional, Hoekstra, Otto S., additional, Zijlstra, Josée M., additional, and Barrington, Sally F., additional

Published
2022
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47. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. Translation to Russian

Author

Cohen, Jérémie F., primary, Korevaar, Daniël A., additional, Altman, Douglas G., additional, Bruns, David E., additional, Gatsonis, Constantine A., additional, Hooft, Lotty, additional, Irwig, Les, additional, Levine, Deborah, additional, Reitsma, Johannes B., additional, De Vet, Henrica C.W., additional, and Bossuyt, Patrick M.M., additional

Published
2022
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49. 18F-FDG PET baseline radiomics features improve the prediction of treatment outcome in diffuse large B-cell lymphoma

Author

Eertink, Jakoba J., van de Brug, Tim, Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pfaehler, Elisabeth A.G., Lugtenburg, Pieternella J., van der Holt, Bronno, de Vet, Henrica C.W., Hoekstra, Otto S., Boellaard, Ronald, Zijlstra, Josée M., Eertink, Jakoba J., van de Brug, Tim, Wiegers, Sanne E., Zwezerijnen, Gerben J.C., Pfaehler, Elisabeth A.G., Lugtenburg, Pieternella J., van der Holt, Bronno, de Vet, Henrica C.W., Hoekstra, Otto S., Boellaard, Ronald, and Zijlstra, Josée M.

Abstract

Purpose: Accurate prognostic markers are urgently needed to identify diffuse large B-Cell lymphoma (DLBCL) patients at high risk of progression or relapse. Our purpose was to investigate the potential added value of baseline radiomics features to the international prognostic index (IPI) in predicting outcome after first-line treatment. Methods: Three hundred seventeen newly diagnosed DLBCL patients were included. Lesions were delineated using a semi-automated segmentation method (standardized uptake value ≥ 4.0), and 490 radiomics features were extracted. We used logistic regression with backward feature selection to predict 2-year time to progression (TTP). The area under the curve (AUC) of the receiver operator characteristic curve was calculated to assess model performance. High-risk groups were defined based on prevalence of events; diagnostic performance was assessed using positive and negative predictive values. Results: The IPI model yielded an AUC of 0.68. The optimal radiomics model comprised the natural logarithms of metabolic tumor volume (MTV) and of SUVpeak and the maximal distance between the largest lesion and any other lesion (Dmaxbulk, AUC 0.76). Combining radiomics and clinical features showed that a combination of tumor- (MTV, SUVpeak and Dmaxbulk) and patient-related parameters (WHO performance status and age > 60 years) performed best (AUC 0.79). Adding radiomics features to clinical predictors increased PPV with 15%, with more accurate selection of high-risk patients compared to the IPI model (progression at 2-year TTP, 44% vs 28%, respectively). Conclusion: Prediction models using baseline radiomics combined with currently used clinical predictors identify patients at risk of relapse at baseline and significantly improved model performance.

Published
2022

50. Adding psychosocial factors does not improve predictive models for people with spinal pain enough to warrant extensive screening for them at baseline

Author

Ailliet, Luc, Rubinstein, Sidney M., Hoekstra, Trynke, van Tulder, Maurits W., and de Vet, Henrica C.W.

Subjects
Influence, Psychological aspects, Patient outcomes, Health aspects, Physical therapy -- Patient outcomes, Quality of life -- Psychological aspects -- Health aspects, Health attitudes -- Influence
Abstract

In 1977, Engel highlighted the overall limitations of the traditional biomedical model of disease. (1) Shortly thereafter, Waddell and colleagues (2,3) made an important translation of Engel's idea to the [...], Background. Chiropractors throughout the world by and large focus on patients with musculoskeletal complaints who are generally in good health. Currently, it is widely accepted that neck pain and low back pain are best understood as biopsychosocial phenomena. Objective. The purpose of this study was to determine whether certain psychosocial factors provide added value for predicting recovery. Design. This was a prospective, multicenter, chiropractic, practice-based cohort study in Belgium and the Netherlands. Methods. A total of 917 participants, 326 with neck pain and 591 with low back pain, completed self-administered questionnaires at baseline and at 3, 6, and 12 months. They provided information on several demographic, biomedical, and psychosocial variables. Lasting perceived recovery was used as the outcome measure, that is, recovery at all follow-up assessments from 3 months on. Twenty-seven potential predictors of outcome were used to build the predictive model. Stepwise, backward generalized estimating equation regression models were used to take into account the clustering of participants within practices. For assessment of the added value of psychosocial variables, 2 model fit indexes were compared. Results. After the addition of psychosocial variables, predictors in the final model for neck pain included occupational status, body mass index, duration of complaints, previous treatment, and participant expectations (the model fit was marginally improved from 0.684 to 0.695 for the area under the curve and from 65.0% to 66.1% for the percentage correctly predicted). In the final model for low back pain, the selected predictors included country of treatment, age, duration of complaints, previous imaging, and somatization (the area under the curve changed from 0.669 to 0.715, and the percentage correctly predicted changed from 68.6% to 69.5%). Only a minority of participants had high scores on psychological variables. Limitations. The reliability and validity of lasting recovery as an outcome measure have not been tested. The cohort needs to be seen as a convenience sample. Selection bias, therefore, not be ruled out. There are no indications, however, that patients with complex psychosocial profiles were excluded from this study. Conclusions. Psychosocial variables provided little added value for predicting outcome in people who had neck pain or low back pain and sought chiropractic care. Therefore, chiropractors should not screen extensively for them at baseline. With regard to the identification of the small subgroup of people with high scores on psychosocial variables and a high risk for chronic pain, further investigation is needed.

Published
2016
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