Jan Verbakel

Prof. Jan Verbakel

University of Leuven, Belgium
+1
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2019 in Journal of Clinical Epidemiology
Verified
Journal Article
Closed access
ECEvangelia Christodoulou
Evangelia Christodoulou
JMJie Ma
Jie Ma
GCGary S. Collins
Gary S. Collins
ESEwout W. Steyerberg
Ewout W. Steyerberg
Jan VerbakelJan Verbakel
Jan Verbakel
BCBen Van Calster
Ben Van Calster

1 December 2018 in European Urology
Verified
Journal Article
Closed access
BCBen Van Calster
Ben Van Calster
LWLaure Wynants
Laure Wynants
JVJan Verbeek
Jan Verbeek
Jan VerbakelJan Verbakel
Jan Verbakel
ECEvangelia Christodoulou
Evangelia Christodoulou
ESEwout W. Steyerberg
Ewout W. Steyerberg

27 August 2022 in The Lancet
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Journal Article
Closed access
NCNathalie Conrad
Nathalie Conrad
GVGeert Verbeke
Geert Verbeke
GMGeert Molenberghs
Geert Molenberghs
LGLaura Goetschalckx
Laura Goetschalckx
TCThomas Callender
Thomas Callender
Jan VerbakelJan Verbakel
Jan Verbakel

1 March 2012 in Health Technology Assessment
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Journal Article
Open access
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ELEmma Loveman
Emma Loveman
ABAnn Van Den Bruel
Ann Van Den Bruel
Jan VerbakelJan Verbakel
Jan Verbakel
MLM Lakhanpaul
M Lakhanpaul
THT Haj-Hassan
T Haj-Hassan
DMD Mant
D Mant
Background Although the vast majority of children with acute infections are managed at home, this is one of the most common problems encountered in children attending emergency departments (EDs) and primary care. Distinguishing children with serious infection from those with minor or self-limiting infection is difficult. This can result in misdiagnosis of children with serious infections, which results in a poorer health outcome, or a tendency to refer or admit children as a precaution; thus, inappropriately utilising secondary-care resources. Objectives We systematically identified clinical features and laboratory tests which identify serious infection in children attending the ED and primary care. We also identified clinical prediction rules and validated those using existing data sets. Data sources We searched MEDLINE, Medion, EMBASE, Cumulative Index to Nursing and Allied Health Literature and Database of Abstracts of Reviews of Effects in October 2008, with an update in June 2009, using search terms that included terms related to five components: serious infections, children, clinical history and examination, laboratory tests and ambulatory care settings. We also searched references of included studies, clinical content experts, and relevant National Institute for Health and Clinical Excellence guidelines to identify relevant studies. There were no language restrictions. Studies were eligible for inclusion if they were based in ambulatory settings in economically developed countries. Review methods Literature searching, selection and data extraction were carried out by two reviewers. We assessed quality using the quality assessment of diagnostic accuracy studies (QUADAS) instrument, and used spectrum bias and validity of the reference standard as exclusion criteria. We calculated the positive likelihood ratio (LR+) and negative likelihood ratio (LR–) of each feature along with the pre- and post-test probabilities of the outcome. Meta-analysis was performed using the bivariate method when appropriate. We externally validated clinical prediction rules identified from the systematic review using existing data from children attending ED or primary care. Results We identified 1939 articles, of which 35 were selected for inclusion in the review. There was only a single study from primary care; all others were performed in the ED. The quality of the included studies was modest. We also identified seven data sets (11,045 children) to use for external validation. The most useful clinical features for ruling in serious infection was parental or clinician overall concern that the illness was different from previous illnesses or that something was wrong. In low- or intermediate-prevalence settings, the presence of fever had some diagnostic value. Additional red flag features included cyanosis, poor peripheral circulation, rapid breathing, crackles on auscultation, diminished breath sounds, meningeal irritation, petechial rash, decreased consciousness and seizures. Procalcitonin (LR+ 1.75–2.96, LR– 0.08–0.35) and C-reactive protein (LR+ 2.53–3.79, LR– 0.25–0.61) were superior to white cell counts. The best performing clinical prediction rule was a five-stage decision tree rule, consisting of the physician’s gut feeling, dyspnoea, temperature ≥ 40 °C, diarrhoea and age. It was able to decrease the likelihood of serious infections substantially, but on validation it provided good ruling out value only in low-to-intermediate-prevalence settings (LR– 0.11–0.28). We also identified and validated the Yale Observation Scale and prediction rules for pneumonia, meningitis and gastroenteritis. Limitations Only a single study was identified from primary-care settings, therefore results may lack generalisability. Conclusions Several clinical features are useful to increase or decrease the probability that a child has a serious infection. None is sufficient on its own to substantially raise or lower the risk of serious infection. Some are highly specific (‘red flags’), so when present should prompt a more thorough or repeated assessment. C-reactive protein and procalcitonin demonstrate similar diagnostic characteristics and are both superior to white cell counts. However, even in children with a serious infection, red flags will occur infrequently, and their absence does not lower the risk. The diagnostic gap is currently filled by using clinical ‘gut feeling’ and diagnostic safety-netting, which are still not well defined. Although two prediction rules for serious infection and one for meningitis provided some diagnostic value, we do not recommend widespread implementation at this time. Future research is needed to identify predictors of serious infection in children in primary-care settings, to validate prediction rules more widely, and determine the added fvalue of blood tests in primar-care settings. Funding The National Institute for Health Research Health Technology Assessment programme.

1 May 2016 in European Journal of Cancer
Verified
Journal Article
Closed access
EME.M.J. Meys
E.M.J. Meys
JKJ. Kaijser
J. Kaijser
RKRoy Kruitwagen
Roy Kruitwagen
BSB.F.M. Slangen
B.F.M. Slangen
BCBen Van Calster
Ben Van Calster
TGToon Van Gorp
Toon Van Gorp

11 September 2018 in Human Reproduction Update
Verified
Journal Article
Open access
JFJessica Farren
Jessica Farren
NMNicola Mitchell-Jones
Nicola Mitchell-Jones
Jan VerbakelJan Verbakel
Jan Verbakel
DTDirk Timmerman
Dirk Timmerman
MJMaria Jalmbrant
Maria Jalmbrant
TBTom Bourne
Tom Bourne
Early pregnancy loss (EPL) is a common event, with scope for long-term personal and societal impact. There are three decades worth of published evidence of profound psychological sequelae in a significant proportion of women. However, the wide variety of outcomes, screening instruments, assessment timings and geographical locations makes it challenging to form a coherent picture of the morbidity within the whole group and its subgroups. This review aims to investigate three questions. (1) What is the evidence for depression, anxiety and post-traumatic stress disorder (PTSD) following a miscarriage or an ectopic pregnancy in women and/or their partners? (2) What is the intensity and duration of these conditions, and how do they compare to those without losses? (3) Which patients have been found to be at highest risk of psychopathology? Answers to these questions are salient not only in day-to-day clinical interactions with those experiencing EPL, whose psychological needs may not be prioritized, but should also form the basis for tailoring healthcare policy in terms of screening for and treating the associated psychological morbidity. The following databases were searched, from the start of each database up to July 2017: MEDLINE (Ovid interface, 1948 onwards), Embase classic + Embase (Ovid interface, 1947 onwards), and PsychINFO (Ovid interface, 1806 onwards). Search strategies were developed using medical subject headings (MeSH). The concepts of psychological morbidity (anxiety, depression or PTSD) and pregnancy loss (miscarriage or ectopic pregnancy) were first expanded with the Boolean operator 'or', then linked together using 'and'. Included studies were of prospective cohort design, including women or men following EPL (with the majority to have experienced losses before 24 weeks gestation), and reporting standardized psychometric measures for anxiety, depression and post-traumatic stress disorder. The timing of follow-up had to be specified and standardized across participants. Manuscript quality and risk of bias was assessed using the Newcastle-Ottawa Scale. We found evidence of significant depression and anxiety in the first month following EPL in women. Partners were also shown to display depression and anxiety, albeit to a generally lower level. There is also evidence of post-traumatic stress symptoms relating to the EPL in three studies. In view of their high frequency, EPLs can significantly contribute to the overall burden of psychopathology within a population. Recognition of this impact is important, so that severely affected individuals may be screened and treated appropriately. Further research to establish risk factors to promptly identify and treat these patients, and to optimize their management, is crucial.