Henk J. Brouwer

Epilepsy is a risk factor for sudden cardiac arrest in the general population.

Background People with epilepsy are at increased risk for sudden death. The most prevalent cause of sudden death in the general population is sudden cardiac arrest (SCA) due to ventricular fibrillation (VF). SCA may contribute to the increased incidence of sudden death in people with epilepsy. We assessed whether the risk for SCA is increased in epilepsy by determining the risk for SCA among people with active epilepsy in a community-based study. Methods and Results This investigation was part of the Amsterdam Resuscitation Studies (ARREST) in the Netherlands. It was designed to assess SCA risk in the general population. All SCA cases in the study area were identified and matched to controls (by age, sex, and SCA date). A diagnosis of active epilepsy was ascertained in all cases and controls. Relative risk for SCA was estimated by calculating the adjusted odds ratios using conditional logistic regression (adjustment was made for known risk factors for SCA). We identified 1019 cases of SCA with ECG-documented VF, and matched them to 2834 controls. There were 12 people with active epilepsy among cases and 12 among controls. Epilepsy was associated with a three-fold increased risk for SCA (adjusted OR 2.9 [95%CI 1.1–8.0.], p = 0.034). The risk for SCA in epilepsy was particularly increased in young and females. Conclusion Epilepsy in the general population seems to be associated with an increased risk for SCA.

Idiopathic Superficial Thrombophlebitis and the Incidence of Cancer in Primary Care Patients

PURPOSE The association of spontaneous venous thromboembolism with occult malignancy is well established. Less clear is the incidence of subsequent cancer in patients with superficial thrombophlebitis. We wanted to determine the incidence of cancer after an episode of spontaneous superficial thrombophlebitis in a large general practice population. METHODS The objective of this study was to assess the incidence of newly diagnosed malignancies in patients within 2 years after the diagnosis of a spontaneous episode of superficial thrombophlebitis and to compare this incidence with nonexposed matched control patients and the Dutch population. The patients and their controls were identified by a search in the electronic patient records of 5 primary health care centers in Amsterdam, the Netherlands. A standardized morbidity ratio was calculated using data of the Dutch cancer registry. RESULTS A total number of 277 patients with superficial thrombophlebitis were identified, of which 250 patients had no cancer at study entry. In 5 of these 250 patients (2%; 95% confidence interval [CI], 1%–5%), a new malignancy was diagnosed within 2 years after their superficial thrombophlebitis compared with 2% (95% CI, 1%–4%) in the control group. The standardized morbidity ratio was 1.1 (95% CI, 0.5–2.7). A recurrent episode of superficial thrombophlebitis was observed in 18 of the 250 patients, and in 1 patient cancer was diagnosed within 24 months after the first episode of superficial thrombophlebitis. CONCLUSION We conclude that a single episode of unprovoked superficial thrombophlebitis diagnosed by a family physician is not associated with an increased risk of subsequent cancer.

What factors explain the differences in morbidity estimations among general practice registration networks in the Netherlands? A first analysis

Background: Information on the incidence and prevalence of diseases is a core indicator for public health. There are several ways to estimate morbidity in a population (e.g., surveys, healthcare registers). In this paper, we focus on one particular source: general practice based registers. Dutch general practice is a potentially valid source because nearly all non-institutionalized inhabitants are registered with a general practitioner (GP), and the GP fulfils the role as “gatekeeper”. However, there are some unexplained differences among morbidity estimations calculated from the data of various general practice registration networks (GPRNs). Objective: To describe and categorize factors that may explain the differences in morbidity rates from different GPRNs, and to provide an overview of these factors in Dutch GPRNs. Results: Four categories of factors are distinguished: “healthcare system”, “methodological characteristics”, “general practitioner”, and “patient”. The overview of 11 Dutch GPRNs reveals considerable differences in factors. Conclusion: Differences in morbidity estimation depend on factors in the four categories. Most attention is dedicated to the factors in the “methodology characteristics” category, mainly because these factors can be directly influenced by the GPRN.

Atrial Fibrillation Is an Independent Risk Factor for Ventricular Fibrillation A Large-Scale Population-Based Case-Control Study

Background—Atrial fibrillation (AF) is associated with sudden cardiac death. We aimed to study whether AF is associated with ventricular fibrillation (VF), the most common cause of sudden cardiac death and whether this association is independent of confounders, ie, concomitant disease, use of antiarrhythmic or QT-prolonging drugs, and acute myocardial infarction. Methods and Results—We performed a community-based case-control study. Cases were patients with out-of-hospital cardiac arrest because of ECG-documented VF. Controls were age-/sex-matched non-VF subjects from the community. VF risk in AF patients was studied by means of (conditional) logistic regression, adjusting for all available confounders. We studied 1397 VF cases and 3474 controls. AF occurred in 215 cases (15.4%) and 90 controls (2.6%). AF was associated with a 3-fold increased risk of VF (adjusted odds ratio, 3.1 [2.1–4.5]). VF risk in AF cases was increased to the same extent across all age/sex groups and in AF cases who had no comorbidity (adjusted odds ratio 3.0 [1.6–5.5]) or used no confounding drugs (antiarrhythmics, 2.4 [1.4–4.3]; QT-prolonging drugs, 3.1 [1.8–5.4]). VF risk was similarly increased in AF cases with acute myocardial infarction–related VF (adjusted odds ratio 2.6 [1.4–4.8]), and those with non-acute myocardial infarction–related VF (adjusted odds ratio 4.3 [1.9–10.1]). Conclusions—AF is independently associated with a 3-fold increased risk of VF. Comorbidity, use of antiarrhythmic or QT-prolonging drugs, or acute myocardial infarction does not fully account for this increased risk.Background— Atrial fibrillation (AF) is associated with sudden cardiac death. We aimed to study whether AF is associated with ventricular fibrillation (VF), the most common cause of sudden cardiac death and whether this association is independent of confounders, ie, concomitant disease, use of antiarrhythmic or QT-prolonging drugs, and acute myocardial infarction. Methods and Results— We performed a community-based case-control study. Cases were patients with out-of-hospital cardiac arrest because of ECG-documented VF. Controls were age-/sex-matched non-VF subjects from the community. VF risk in AF patients was studied by means of (conditional) logistic regression, adjusting for all available confounders. We studied 1397 VF cases and 3474 controls. AF occurred in 215 cases (15.4%) and 90 controls (2.6%). AF was associated with a 3-fold increased risk of VF (adjusted odds ratio, 3.1 [2.1–4.5]). VF risk in AF cases was increased to the same extent across all age/sex groups and in AF cases who had no comorbidity (adjusted odds ratio 3.0 [1.6–5.5]) or used no confounding drugs (antiarrhythmics, 2.4 [1.4–4.3]; QT-prolonging drugs, 3.1 [1.8–5.4]). VF risk was similarly increased in AF cases with acute myocardial infarction–related VF (adjusted odds ratio 2.6 [1.4–4.8]), and those with non-acute myocardial infarction–related VF (adjusted odds ratio 4.3 [1.9–10.1]). Conclusions— AF is independently associated with a 3-fold increased risk of VF. Comorbidity, use of antiarrhythmic or QT-prolonging drugs, or acute myocardial infarction does not fully account for this increased risk.

Usefulness of primary care electronic networks to assess the incidence of chlamydia, diagnosed by general practitioners

BackgroundChlamydia is the most common curable sexually transmitted infection (STI) in the Netherlands. The majority of chlamydia diagnoses are made by general practitioners (GPs). Baseline data from primary care will facilitate the future evaluation of the ongoing large population-based screening in the Netherlands. The aim of this study was to assess the usefulness of electronic medical records for monitoring the incidence of chlamydia cases diagnosed in primary care in the Netherlands.MethodsIn the electronic records of two regional and two national networks, we identified chlamydia diagnoses by means of ICPC codes (International Classification of Primary Care), laboratory results in free text and the prescription of antibiotics. The year of study was 2007 for the two regional networks and one national network, for the other national network the year of study was 2005. We calculated the incidence of diagnosed chlamydia cases per sex, age group and degree of urbanization.ResultsA large diversity was observed in the way chlamydia episodes were coded in the four different GP networks and how easily information concerning chlamydia diagnoses could be extracted. The overall incidence ranged from 103.2/100,000 to 590.2/100,000. Differences were partly related to differences between patient populations. Nevertheless, we observed similar trends in the incidence of chlamydia diagnoses in all networks and findings were in line with earlier reports.ConclusionsElectronic patient records, originally intended for individual patient care in general practice, can be an additional source of data for monitoring chlamydia incidence in primary care and can be of use in assessing the future impact of population-based chlamydia screening programs. To increase the usefulness of data we recommend more efforts to standardize registration by (specific) ICPC code and laboratory results across the existing GP networks.

Predictability of Persistent Frequent Attendance in Primary Care: A Temporal and Geographical Validation Study

Background Frequent attenders are patients who visit their general practitioner exceptionally frequently. Frequent attendance is usually transitory, but some frequent attenders become persistent. Clinically, prediction of persistent frequent attendance is useful to target treatment at underlying diseases or problems. Scientifically it is useful for the selection of high-risk populations for trials. We previously developed a model to predict which frequent attenders become persistent. Aim To validate an existing prediction model for persistent frequent attendance that uses information solely from General Practitioners’ electronic medical records. Methods We applied the existing model (N = 3,045, 2003–2005) to a later time frame (2009–2011) in the original derivation network (N = 4,032, temporal validation) and to patients of another network (SMILE; 2007–2009, N = 5,462, temporal and geographical validation). Model improvement was studied by adding three new predictors (presence of medically unexplained problems, prescriptions of psychoactive drugs and antibiotics). Finally, we derived a model on the three data sets combined (N = 12,539). We expressed discrimination using histograms of the predicted values and the concordance-statistic (c-statistic) and calibration using the calibration slope (1 = ideal) and Hosmer-Lemeshow tests. Results The existing model (c-statistic 0.67) discriminated moderately with predicted values between 7.5 and 50 percent and c-statistics of 0.62 and 0.63, for validation in the original network and SMILE network, respectively. Calibration (0.99 originally) was better in SMILE than in the original network (slopes 0.84 and 0.65, respectively). Adding information on the three new predictors did not importantly improve the model (c-statistics 0.64 and 0.63, respectively). Performance of the model based on the combined data was similar (c-statistic 0.65). Conclusion This external validation study showed that persistent frequent attenders can be prospectively identified moderately well using data solely from patients’ electronic medical records.

Prevalence and medical risks of body packing in the Amsterdam area

AIM Body packing is a way to deliver packets of drugs across international borders by ingestion. The aim of the study was to provide an estimate of the medical risks of body packing, describe predictors for hospital referral in detained body packers and provide an estimate for the prevalence of body packing in the Amsterdam area. METHODS From May 2007 to December 2008, we studied medical records of body packers immediately detained after arrival at Amsterdam Schiphol airport, hospital records of both detained body packers and self-referrers at two emergency departments of hospitals in Amsterdam and records kept by forensic physicians in charge of post-mortem examinations of all unnatural deaths in the area (years 2005-2009). RESULTS In airport detainees, the hospital referral rate was 4.2% (30 out of 707 detained body packers), the surgery rate was 1.3%. Significant predictors of hospital referral were delayed production of drug packets after arrest, cigarette smoking and country of departure. The surgery rate in self-referrers was comparable to the rate observed in those referred from the detention centre to hospital (30% vs. 31%). In addition, from 2005 to 2009, 20 proven cases of lethal body packing were identified. Based on our data, it is estimated that minimally 38% of all incoming body packers were missed by airport controls. CONCLUSION The risk for lethal complications due to body packing is low on a population basis and comparable to other studies. This also applies for the hospital referral and surgery rates found in this study. Cigarette smoking has not yet been described in the literature as a potential predictor for hospital referral in detained body packers and therefore deserves attention in future research. A substantial fraction of body packers manages to remain undiscovered.

Welke gezondheidsproblemen zien huisartsen in opleiding

Abstract Vintges M, Van Weert HC, Van der Wiele E, Mohrs J, Brouwer HJ, Wigersma L. Welke gezondheidsproblemen zien huisartsen in opleiding? Diagnosen uit het elektronisch medisch dossier vergeleken met de eindtermen van de beroepsopleiding. Huisarts Wet 2001;44(11): 485-9.Doel In het rapport Eindtermen huisartsopleiding 2000 worden de gezondheidsproblemen beschreven waarmee huisartsen aan het einde van hun huisartsopleiding bekend moeten zijn. Een kwantitatieve onderbouwing ontbreekt. Het doel van dit onderzoek is om via het HIS na te gaan hoeveel en welk soort patiëntencontacten huisartsen in opleiding (haio’s) hebben gedurende hun stagejaren in de huisartspraktijk.Methode De diagnosen van de reguliere consulten en visites die gedurende acht maanden verricht werden door acht haio’s en hun opleiders werden uit het HIS geëxtraheerd, waarbij het ging om de ICPC-code van de E-regels van deelcontacten. De resultaten werden omgerekend naar een periode van twee volledige stagejaren.Resultaten De database bevatte ruim 25.000 ICPC-gecodeerde diagnosen. De haio’s hadden gemiddeld bij 42% van de 122 gezondheidsproblemen uit het Eindtermenrapport minder dan vijf deelcontacten in de twee stagejaren tezamen. Als de in het rapport gehanteerde ruime definiëring van de gezondheidsproblemen werd gebruikt waarbij ook de verwante klachten en ziekten werden geïncludeerd, dan was dat bij 14% van de gezondheidsproblemen het geval. De complete tabel van de aandoeningen uit het Eindtermenrapport met van elk de aantallen deelcontacten is in te zien via de website www.artsennet/henw.nl.Conclusie Het bleek mogelijk om met behulp van de routinematig in het EMD geregistreerde gegevens inzicht te krijgen in de aard en kwantiteit van patiëntencontacten van haio’s. Deze gegevens zouden een rol kunnen vervullen bij de sturing van haio’s in hun praktisch leerproces en bij de karakterisering van huisartspraktijken ten behoeve van de opleiding.

Is frequent attendance of longer duration related to less transient episodes of care? A retrospective analysis of transient and chronic episodes of care

Objectives Frequent attenders (FAs) suffer more and consult general practitioners (GPs) more often for chronic physical and psychiatric illnesses, social difficulties and distress than non-FAs. However, it is unclear to what extent FAs present transient episodes of care (TECs) compared with non-FAs. Design Retrospective analysis of all episodes of care (ECs) in 15 116 consultations in 1 year. Reasons for encounter (RFEs) linked to patients’ problem lists were defined as chronic ECs (CECs), other episodes as TECs. Setting 1 Dutch urban primary healthcare centre served by 5 GPs. Participants All 5712 adult patients were enlisted between 2007 and 2009. FAs were patients whose attendance rate ranked within the top decile of their sex and age group in at least one of the years between 2007 and 2009. Outcome measures Number of RFEs linked to TECs/CECs for non-FAs and 1-year (1yFAs), 2-year (2yFAs) and 3-year FAs (3yFAs), and the adjusted effect of frequent attendance of different duration on the number of TECs. Results The average number of RFEs linked to TECs (non-FAs 1.4; 3yFAs 7.3) and to CECs (non-FAs 0.9; 3yFAs 6.2) increased substantially with the duration of frequent attendance. The ratio of TECs to all ECs differed little for FAs (52–54%) and non-FAs (64%). Compared with non-FAs, the adjusted additional number of TECs was 3.4 (95% CI 3.2 to 3.7, 1yFAs), 6.6 (95% CI 6.1 to 7.0, 2yFAs) and 9.4 (95% CI 8.8 to 10.1, 3yFAs). Conclusions FAs present more TECs and CECs with longer duration of frequent attendance. The constant ratio of TECs might be a sign of a low threshold for FAs to consult their GP. The large numbers of TECs in FAs might be associated with their high level of anxiety and low mastery. The consultation pattern of FAs may best be characterised by describing both TECs and CECs.

Persistent frequent attenders

We read with great interest the article by Luciano et al about frequent attendance in the BJGP .1 The authors state that ‘neither definition (has taken) into account that certain patients need to make more consultations than others,’ and therefore, they study a two-stage approach in that they define frequent attenders according to four clinical profiles and to the top 25 and 10% top attenders. Obviously sick patients will make more appointments with their …