Eur J Pediatr (2008) 167:1239–1249 DOI 10.1007/s00431-007-0660-3
ORIGINAL PAPER
Paediatric trauma and trauma care in Flanders (Belgium). Methodology and first descriptive results of the PENTA registry Patrick Van de Voorde & Marc Sabbe & Paul Calle & Emmanuel Lesaffre & Dimitris Rizopoulos & Roula Tsonaka & Daphne Christiaens & Anneleen Vantomme & Annick De Jaeger & Dirk Matthys & On behalf of the PENTA Study Group Received: 2 September 2007 / Revised: 8 December 2007 / Accepted: 12 December 2007 / Published online: 17 January 2008 # Springer-Verlag 2007
Abstract Paediatric injury surveillance and prevention are definite priorities for the European, Belgian, and Flemish authorities. Current available data for Flanders (Belgium) are fragmentary and out-of-date. The PENTA registry (PaEdiatric Network around TraumA) was therefore set up to obtain recent population-based data on trauma and trauma care in children and youngsters in Flanders. Data were collected
Electronic supplementary material The online version of this article (doi:10.1007/s00431-007-0660-3) contains supplementary material, which is available to authorized users. P. Van de Voorde (*) : D. Christiaens : A. De Jaeger : D. Matthys Department of Paediatrics and Paediatric Intensive Care Unit, University Hospital Gent, 1K12IC, De Pintelaan 185, 9000 Gent, Belgium e-mail:
[email protected] M. Sabbe : A. Vantomme Department of Emergency Medicine, University Hospital Leuven–Gasthuisberg, Herestraat 49, 3000 Leuven, Belgium P. Calle Department of Emergency Medicine, University Hospital Gent, De Pintelaan 185, 9000 Gent, Belgium E. Lesaffre : D. Rizopoulos : R. Tsonaka Centre for Biostatistics, University of Leuven, Kapucijnenvoer 35d -bus 7001, 3000 Leuven, Belgium E. Lesaffre Department of Biostatistics, Erasmus MC, Dr. Molewaterplein 40, 3015GD Rotterdam, Netherlands
prospectively in a representative sample (n=18) of Flemish emergency departments (ED). All children (age 0–17 years) who presented at the ED in 2005 or died prehospital due to trauma were included. The registry was split into two levels. The basic A registry (‘all’ trauma) consisted of 30 variables, and the more exhaustive B registry (‘severe trauma’, defined as length of hospitalisation >48 hours, including all nonsurvivors) collected data on 291 variables. The incidence for paediatric trauma presenting at Flemish ED was approximately 119/1000/year. Further data were collected in a random sample of 7,879 cases (21.9% of 35,900 eligible patients). Of all cases, 0.8% were considered ‘severe’ and included in the B registry. In conclusion, the ’burden‘ of injury in Flanders is still enormous. PENTA provides the first population-based data about the circumstances and the extent of injury in children and youngsters for the Flemish region. In this article we present in detail the surplus value of the methods used, the difficulties encountered, and the most relevant epidemiological findings from the registry. Keywords Children . Injury . Epidemiology . Trauma registry Abbreviations PENTA Paediatric network around trauma ED Emergency departments IDB European injury database EMS Emergency medical services MECU Mobile emergency care unit CI Confidence interval ISS Injury severity score SD Standard deviation IQR Interquartile range
1240
Eur J Pediatr (2008) 167:1239–1249
Introduction Trauma is still the first cause of morbidity and mortality in children (>1 year old) and youngsters worldwide; beside the human tragedy, the economic cost for society is enormous [11, 29, 33, 39]. Epidemiological data provide the basis for any preventive or organisational intervention and are therefore indispensable [10, 17]. International data are, however, insufficient in describing the local situation [6, 9]. The European Union asks its member states to take concrete actions concerning injury prevention and to develop a system of local injury surveillance (the European Injury Database [IDB]) [36]. Flanders is the Dutch-speaking part of Belgium; in 2005 it had 6,016,024 inhabitants; 1,205,679 were below 18 years of age [42]. Current available data on paediatric trauma for Flanders appear fragmentary and out-of-date. Moreover, clear problems with terminology and/or methodology have been identified [32]. By initiating the PENTA project (‘a PaEdiatric Network around TraumA‘), we wanted to obtain recent populationbased injury data for children and adolescents in Flanders. In this paper we will describe in detail the design of the PENTA registry, the methods used, and the issues encountered [17, 24, 43]. By doing so, the registry can serve as a template for future surveillance initiatives. Further, we will present the most relevant epidemiological findings, describing ‘the burden of injury’ in children and youngsters in Flanders. We will not compare our findings with those of other countries [39, 40]. This will be addressed in future papers and goes beyond the scope of this article.
Patients and methods The PENTA project began in September 2003, supported by funding from the Flemish Fund for Scientific Research, project Levenslijn. The actual registration period ran from January 2005 to January 2006. PENTA was a hospital-based registry
and the main entry point for patient inclusion was the emergency department (ED). It was designed to be a prospective and population-based observational study. Nineteen of the 71 Flemish hospitals with an accredited ED function participated. Ethical committee approval was obtained in each. For further description of the sample we refer to Table 1. The registry was split into two levels which we will further identify as level A and B. Level A included “all children or youngsters (0–17 years old), with an injury caused by an external physical factor, who presented at the participating ED or were admitted to that hospital after an emergency medical services (EMS) / mobile emergency care unit (MECU) intervention, as well as all deaths-on-scene encountered”. Poisoning by medication was excluded. The datasheet consisted of 30 variables describing the trauma, e.g. patient characteristics, referral patterns, trauma type, location and circumstances, injury diagnoses, etc. Injuries were reported as free text and afterwards coded with ICD9-CM. Eligibility was evaluated upon patient presentation. All eligible patients were registered in a log-book and a predefined random sample of approximately 25% was drawn for further data registration. Each registered patient and registering hospital received a unique code and all collected data were made anonymous before analysis. Level B was meant to describe the children with ‘severe’ injuries. It was initiated in all children who met the A criteria and in addition had “an injury (or “high-energy” trauma mechanism) that was potentially life-threatening or for which the length of hospital stay was expected to exceed 48 hours”. Eventually, we only withheld those children that effectively stayed in hospital for more than 48 hours because of medical reasons (including all deaths). Here, we did not perform any sampling, but registered data in all eligible children. Collected data involved 291 variables, giving detailed information about trauma mechanism and circumstances, patient state and physiologic parameters, and medical care delivered from the moment of incident up to ward admission, including interhospital
Table 1 Characteristics of the participating hospitals (n=18+1) and comparison with the overall group of Flemish hospitals with an accredited ED function (n=71) (situation as in 2002) [41, 42]
Number of hospitals with 100–250 beds Number of hospitals with 250–500 beds Number of hospitals with >500 beds Number of university hospitals or hosp. with univ. characteristics Total number of hospital beds Number of patients visiting the ED yearly Expected number of eligible patients
The PENTA hospitals (n=18+1)
All Flemish hospitals with an accredited ED function (n=71)
2 8 8 (+1) 4 (+1)
27 27 17 10
10,446 (+629) ∼361,000 (+27,000) ∼36,500 (+2500)
26,774 ∼1,450,000 ∼145,000
One of the participating hospitals was not included in the final analysis; we marked the characteristics of this centre separately by ‘(+x)’
Eur J Pediatr (2008) 167:1239–1249
transfer. Emphasis was put on the first hours after trauma. Additional data were provided to describe injury severity and outcome on discharge. Injuries were coded with ICD-9CM as well as AIS ’90 [2]. Statistical methodology Data sheets and electronic database were developed by means of SNAP software [34]. SNAP is a dedicated software to generate questionnaires and registries and is compatible with most statistical and MS Windows-based spreadsheet programs. All analyses were performed in the R statistical software (version 2.4.0) or in StatsDirect software (version 2.6.2) [31, 35]. Nominal data are reported as frequencies, as percentages of the total sample (n=7879), and/or as incidence rates for Flanders (with 95% confidence intervals CI). Incidence rate calculations were based upon the total amount of eligible children as registered in the sitespecific log books. Cases (n=159) were excluded from the A sample if there were more than 25% of the core data missing. The amount of missing or unspecified data in the remaining sample (n=7,879) was for the majority of variables negligible (0–2.5%) and therefore not reported. Missing data were excluded from calculations. For continuous variables we calculated the mean and standard deviation (SD). Where informative, a 95% CI was given for the difference between means (using the unpaired Student t test). Ordinal data are presented as median and interquartile range (IQR). Tests for association between pairs of categorical variables were performed using Chisquare tests (2 by k contingency tables). In cases in which the chi-square approximation to the test statistic was questionable (i.e. having cells with expected frequencies less than five), a Monte Carlo simulation technique was applied to obtain valid p values under the null hypothesis [27]. For selected variables, we also calculated 95% CI for the difference between proportions (using the iterative method of Miettinen and Nurminen) [21]. For quantitative variables the hypothesis of equality of medians between the levels of categorical variables was tested using either a Wilcoxon test (when the categorical variable had two levels) or the Kruskal-Wallis test (for more than 2 categories). P values smaller than 0.05 were considered significant. Reported p values are only exploratory and hence no correction for multiple testing was done.
Methodology: strengths and limitations A population-based registry A hospital-based (ED) patient registry is thought to be a more accurate and effective means of acquiring popula-
1241
tion-based data than through administrative databases or household surveys [3, 9, 28, 43]. In 2005, the Flemish community was served by 71 hospitals with an accredited ED function. Bearing in mind our own logistic limits, we selected a sample of about 25% (in absolute number, as well as in number of patients visiting the ED yearly). The choice of hospitals to include in the network depended not only on their willingness to participate, but also on their anticipated number of eligible patients, their hospital characteristics, and their referral patterns. We tried to include hospitals from different Flemish regions and of different type (see Table 1). The hospitals in our sample were generally larger. This did not have an impact on the relative number of expected eligible patients (still about 25% of the total). In general the severity of injuries encountered was not related to the type of hospital, except for the group of severely injured children admitted to tertiary referral hospitals after interhospital transfer (approx. 25% of all B level cases). Although not selected at random, we consider this sample large and well-selected enough to be representative of the whole Flemish region. It is reasonable to assume that, for the A patient group, this sample makes up approximately 25% and is thus suitable to use for incidence rate calculations. For the B group we have to take into account children transferred from hospitals not participating in the PENTA registry. When estimating incidence rates, this latter group will be ignored. Patient inclusion criteria As our primary point of entry was the ED we did not register children who where seen solely by a general practitioner. Data from other studies suggest that this group, although declining, accounts for 20–50% of all medically treated injuries, most often at the lower end of the severity spectrum [8, 19, 25]. We included all children (0–17 years) who presented in the ED because of injury, even if this was only a minor injury [7]. All injuries have a certain impact on a patient and his/her surroundings (and a cost to society) and quite often the difference between minor and major injury is but a question of seconds (‘the near-miss principle‘). We only excluded “poisoning by medication” in view of the important additional workload this would generate and because abundant data are already available at the National Poison Centre [32]. We included adolescents up to 17 years of age, as this group of older children is very specific with regard to injury (traffic accidents, weekend accidents, etc.). About half of all trauma deaths seem to occur at the site of the accident. They are, however, seldom captured in trauma registries. Most of these on-scene deaths are not influenced by the medical care provided, but they form an important target
1242
Eur J Pediatr (2008) 167:1239–1249
for primary prevention strategies. For some, mortality could be considered preventable and therefore these cases are important to audit. We decided to include all prehospital deaths in the PENTA registry. We were able to do so because in Flanders a MECU team is dispatched to every severe accident and these MECU teams have a uniform registration sheet capturing all core prehospital data. For the B level we wished to include only the severely injured children (i.e. all those needing more specialised care or at risk of long-term consequences). Our inclusion criteria had to be sensitive enough to capture all these children, but too broad criteria would undoubtedly lead to an uncontainable data stream. The injury severity score ISS (based on the definitive anatomical lesions) is difficult to use as inclusion criterion, given the prospective nature of the data collection [4]. Physiological triage scores are easier to collect early-on but often have limited sensitivity and are therefore also not useful for screening eligible patients [20]. Eventually we decided to use (expected) length of stay in hospital as criterion for inclusion, since it was very sensitive and easy to implement. In view of this sensitivity, ‘>48 hour hospital stay’ was set as cut-off rather than the ‘72 hours’ of the major trauma outcome study [44].
and hence this centre was excluded from the definite analysis. By doing so, the number of hospitals diminished from 19 to 18 (see Table 1). Nine of the participating EDs only registered 11 of the postulated 12 months. Further, several centres prematurely stopped entering patients in the logs as soon as all randomisation numbers for a trimester were exhausted. Again, these additional ‘missed cases’ did not influence the random selection process and therefore the representativity of the sample. Yet, since not all eligible patients were captured in the logs, we can only give an approximation of the total number of eligible patients in the 18 ED. Of all initially randomly selected A level patients, 159 needed to be excluded because of insufficient data along with 98 others because they did not meet inclusion criteria. Effective data registration was thus done in 7,879 A cases (21.9% of the total number of eligible patients). Not all A level patients who stayed in hospital for more than 48 hours, were included in the B registry (i.e. they were not included if referred to a nonparticipating hospital, B exclusion criteria, refusal of informed consent, or insufficient data). In the 18 participating hospitals, 244 cases were eventually withheld in the B registry; 62 were also part of the A sample (including 3 deaths).
Patient sampling
Data validity
All eligible A patients were included in site-specific log books. Registering data for all of these patients would, however, be an enormous work and would not necessarily contribute to the information content of the study. The validity of sampling, even when generating population-based epidemiological data, has been described [15, 19, 23]. Therefore, we decided to select a sample of patients for full data registration by site-specific cluster randomisation (per trimester to correct for possible seasonal effects). This random selection process was based on expected inclusion rates (from historical data of the participating hospitals). After the first trimester, it became clear that for some hospitals this was underestimated and corrections were made to the randomisation accordingly. To calculate incidence rates we still would need to be aware of the total number of eligible patients. As expected, given the prospective nature of the registry, a percentage of these cases were ‘missed’ (i.e. eligible but not included in the logs), where others were ‘incorrectly included’ (i.e. not eligible yet included in logs). The cumulative ‘missed cases’ rate was eventually less than 5%, and the number of ‘incorrectly included’ cases just above 1%. Importantly, there was no association between injury characteristics and the fact that a case was missed, thereby avoiding selection bias. For one centre the number of missed cases was significantly higher (roughly 25%),
We used the Utstein guidelines for reporting major trauma and duplicated items from existing “paediatric” registries and the more recent “EuroTARN” project in which the dataset was developed through a modified Delphi method [12–14, 37]. To contain the workload (and so increase accuracy) we limited data collection in the A level registry, putting more emphasis on the B registration. It was this B patient group that would be used eventually for the planned trauma care evaluation (by panel review) and the long-term outcome study (both of which will be reported separately). The primary aim of the A part was to provide us with basic population-based data on epidemiology. Further, we collected more specific data on traffic accidents and head trauma. To keep the A registry feasible, we did not include information on patient comorbidity or on products or persons involved. Injuries were coded with ICD9-CM and then reported by means of the Barell injury matrix [5]. For the small subgroup of patients with more than one lesion reported (4.2%), second or third injuries were coded as far as they generated a different Barell injury code. Unless for subgroup analysis, only the first (‘most important’) diagnostic code was used. The potential bias this introduced was considered negligible, given the small number of patients involved. Paper data sheets were used for on-site registration, as this would make it more likely to register “ad hoc” and be
Eur J Pediatr (2008) 167:1239–1249
easier for data validation afterwards. Central digital input (by the study centre) provided us with a validity checkpoint, yet it was also a possible source of mistakes [16]. Therefore, all data input was done twice, and matched to detect faults. Each mismatch was manually rechecked. Coding of diagnosis (ICD9-CM) and internal consistency were checked using information of the narrative fields. Experiences from other registries demonstrate an inherent high percentage of missing data and incorrect registration [16, 19, 26]. We have therefore put serious effort into data validation. Before use, the A data sheet was piloted in one centre to evaluate feasibility and identify problems with syntax or semantics. A lexicon was provided which specified every term used, as well as a FAQ sheet to aid in case of procedural problems. If necessary, a member of the PENTA team was available for telephone advice. During the period of registration, each participating site was visited approximately every 2 weeks by a member of the study centre. One site every 2 weeks was randomly chosen and log-books were checked for ‘missed cases’. Data sheets were then controlled for completeness and internal consistency. Missing data were looked up using patient files and, if necessary, administrative records or pharmacology reports. The amount of missing data in the A registry was thus in general small (0–5%), except for the hour of incident, which was unavailable in 934 children (11.8%). Some confusion occurred with the interpretation of certain terms (despite the lexicon), e.g. ‘falls’ during ‘sports & play’ and ‘vehicle-related injuries’ not on the ‘public road’. To control for this possible bias one of the principal investigators (PVDV) reviewed each of the 7,879 cases and, by using the available information from the narrative fields, corrected where necessary to meet the outlined definitions. For the B registration, study nurses more often needed to retrieve data retrospectively. Most difficulties were encountered with physiological parameters and time intervals. Other registries have encountered similar problems when recording these parameters [19, 26, 30, 43]. We were unable to calculate a revised trauma score in 40.4% of all B patients, mostly because of the nonrecording (nor in the B data sheets nor in the hospital patient files) of a respiratory rate and/or heart rate. The Glasgow Coma Scale on the other hand was available in all but 12 cases. Overall, B data sheets tended to be more complete for more severely injured children and data were less likely to be lacking if they were considered important to the individual patient’s story. Registry burden Developing a “population-based” registry is complicated and time-consuming, especially if not initiated by a
1243
governing agency and/or without major financial incentives [10, 26]. Although the engagement of individual caregivers was high, it took us slightly less than a year and a lot of meetings and site visits to obtain full support of all participating hospitals, including the local cooperation of all specialities involved and the approval of each hospital’s ethical committee. We needed to make up contracts, adapt procedures to local circumstances, and instruct local teams. At least one individual per centre was invited to participate as co-investigator or study facilitator. Hospitals participated on a completely voluntary basis and received only a small expense allowance. The total budget for the PENTA project (2003–2006) was around €300,000, most of which was personnel costs. The PENTA study centre consisted of 1.3–2.1 full-time equivalent scientific staff and 0.5 full-time equivalent statistic support. This was, in proportion to the extent of the network, less than in other similar projects, and a lot of additional work was done by staff, study promoters, and participants in their spare time [12, 32].
Results The global burden of injury The approximate number of eligible patients in the 18 participating hospitals was 35,900. This was about 10% of all ED consultations and 50% of paediatric consultations. The estimated annual incidence for children and youngsters visiting the ED because of an injury in Flanders was thus 119/1000/year (95% CI = [117.8, 120.3]).The majority of cases were seen after blunt (84.3%) and nonintentional injury. Intentional injury occurred in only 1.7% of the A sample patients (n= 134), who were older on average (mean 13 years; CI=[2.7, 4.1]). Most cases were seen after fighting. There were no shot wounds; in only two cases was injury caused by a knife. Parents were involved in 10.5% of these cases; 9% was self-inflicted injury. Table 2 describes the distribution of regions and nature of (first) diagnosis for the whole sample. Injuries most often occurred at the level of the extremities. The majority of them, especially in younger children, were injuries of the upper extremities. The three most frequent diagnostic codes encountered were: superficial lesions of the extremities (26.4%), open wounds to the head/face or neck region (14.7%), and fractures of the upper extremities (14.4%). In Table 3 we present in more detail the distribution of accident locations and circumstances. Residential injuries made up about 40% of all cases. The majority of these were falls, most often from standing height or just above; only 3% were falls from higher than 2 metres (of which
1244
Eur J Pediatr (2008) 167:1239–1249
Table 2 The distribution of regions and nature of (first) diagnosis Sample N=7,879
Diagnosis region Extremities Head/face/neck (not TBI) Traumatic brain injury Torso Diagnosis nature Superficial lesions Fracture/dislocation Open wounds Sprains & strains Internal lesions
Sample %
Age mean [CI]
0–4 y %
65.7 21.1 6.4 2.9
11 y [3.6,4.2] 6.4 y [−3.8,−4.4] 7 y [−2.3,−3.3] 11.5 y [1.3,2.5]
34.3 21.6 21.3 11.8 6.4
10.8 y [1.4,2] 10.3 y [0.6,1.2] 7.1 y [−2.9,−3.5] 12.2 y [2.6,3.2] 7.18 y [−2.1,−3.1]
5–9 y %
10–14 y %
15–17 y %
% of column total 40* 58.7 39.7 28 12 5.8 0.8 3.4
80.7 9.4 4.1 3.1
26.1* 14.6 34.7 3.4 11.3
39.4 25.6 11.5 16.6 4.1
29.3 23 28.5 8.2 6
Boys % [CI]
Admission % [CI]
78.7 8.9 4.1 4.3
% of row 58.6 [−3.5,1] 63 [2.3,7.6] 61 [−4.6,8] 54.9 [−9,−1]
% of row 4.7 [−8.6,−5.9] 3 [−6.3,−4.1] 42 [32.9,41.6] 9.6 [−0.7,7.1]
40.1 21.7 12.1 18.2 4.3
57 [−5.5,−0.9] 61 [−0.3,5] 64.5 [4.3,9.5] 55.3 [−7.7,−0.9] 55.1 [−8.8, 0.2]
1.9 [−9,−7] 12.7 [5.5,8.8] 1.9 [−7.6,−5.7] 1.1 [−7.8,−5.9] 41.7 [32.6,41.2]
For reasons of clarity, only the most important categories are presented in the table. For each diagnostic category we give the percentage of the total sample, the mean age (with CI for difference between means), the relative distribution within an age group and the percentage of boys and of admissions for that specific diagnostic category (with CI for difference in proportions) * p
