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Epidemiology of Cerebral Palsy in Northeastern Switzerland

Forni, Ruben PT; Stojicevic, Violeta PT; van Son, Careen PT; Lava, Sebastiano A. G. MD MS; Kuenzle, Christoph MD; Beretta-Piccoli, Matteo MS

Author Information
doi: 10.1097/PEP.0000000000000491
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Cerebral palsy (CP) is the most common type of motor disability in childhood1 and can complicate 0.1% to 0.4% of births.2–4 It covers a group of conditions involving a combined disorder of movement, posture, and motor function. Cerebral palsy is a permanent condition, attributed to nonprogressive disturbances that occurred in the developing fetal or infant brain.5–8

Little is known about children affected by CP in Switzerland because epidemiologic data have not been collected. Hence, a standard algorithm for making the diagnosis has not been created. Despite this, according to Novak and colleagues,9 early diagnoses can be made at the age of 6 months, using history, standardized motor and neurological examination protocols, and neuroimaging, followed by a prompt referral to a diagnostic-specific early intervention to optimize infant motor and cognitive plasticity, prevent secondary complications, and enhance caregiver well-being. Registries have been thus established in most other European countries and, in some cases, supported by the government (eg, Denmark).10

Thus, as a first step toward a future nationwide study, a pilot study in the canton of Saint Gallen was undertaken. This area comprises a typical mixture of small urban and countryside areas. The canton of Saint Gallen is part of the Swiss–German-speaking cantons (which cover about 65%-70% of Switzerland) with a population of approximately 492 000 inhabitants, which corresponds to 6% of the Swiss population and approximately 10% of the Swiss–German-speaking population.

The aims of this pilot study were to (i) collect data about the prevalence and severity of CP in the canton of Saint Gallen; (ii) compare these data with those of the registries participating in the Surveillance of Cerebral Palsy in Europe (SCPE) network; and (iii) study the feasibility of setting up a new registry in the canton of Saint Gallen and develop it further into a registry for Switzerland.

METHODS

Design

A descriptive study design was selected. Data of all children affected by CP born in the canton of Saint Gallen from January 1, 1995, to December 31, 2009, were retrospectively extracted from medical records and analyzed. The study protocol was approved by the local ethics committee of Eastern Switzerland (EKSG 13/034/1B).

Participants and Data Extraction

Data were collected from 3 nearby located pediatric hospitals (Saint Gallen, Zurich, and Chur), where children with CP in the canton of Saint Gallen are treated. Eligible patients were identified according to the International Classification of Functioning, Disability and Health diagnoses G80.0-9. Extraction of data from the medical records of patients according to the minimal data set established by the SCPE11 was done by 2 physical therapists (R.F. and V.S.) under the supervision of a neuropediatrician (C.K.), using the standardized SCPE data collection form. If data were not conclusive to fulfill the criteria, the treating neuropediatrician was contacted to reach agreement. At least 19 variables, corresponding to the required categories of the SCPE data collection form, were extracted from each medical record (Table 1).

TABLE 1 - Key Variables Extracted From Medical Records
Sociodemographic Variables Medical Variables Developmental Variables Other Variables
Date of birth Gestational age GMFCS Mother's date of birth
Date of death Multiple birth BFMF Mother's residency
Sex Delivery mode
Birth weight CP classification
Cognition
Vision
Hearing
Epilepsy
Associated syndromes
Postneonatal CP
Hip dislocation
Abbreviations: BFMF, Bimanual Fine Motor Function Classification; CP, cerebral palsy; GMFCS, Gross Motor Function Classification System.

To be eligible, children older than 4 years at the time of data acquisition had to be diagnosed with CP by a board-certified neuropediatrician according to the criteria set by the SCPE.7 Cerebral palsy was classified into 3 types: spastic (with bilateral and unilateral subtypes), dyskinetic (with choreoathetotic and dystonic subtypes), and ataxic.

In the subset of children with a postneonatal nonprogressive origin of CP, only children whose lesion occurred between day 27 and beginning of the 25th month of age were included. The diagnosis of CP was made until the age of 4 years. Only medical records accompanied by written informed consent from caregivers were included in the study. Children of mothers not living in the canton of Saint Gallen at the time of birth were excluded from analyses (Figure 1).

Fig. 1.
Fig. 1.:
Flowchart showing study participants. CSG indicates canton of Saint Gallen; CP, cerebral palsy.

If there were incomplete data in the medical records, missing information was collected (as far as possible) by contacting parents or legal guardians. Patient data were entered into a standardized case report form (CRF) derived from the original form of the SCPE.7 Before data collection, the CRF was translated into German according to the forward-backward method by native German speakers with extensive experience in pediatrics. Once data collection had been completed, data were anonymized by the neuropediatrician responsible for data collection.

Clinical Features

All the information on clinical features reported was extracted from medical records and classified according to SCPE rules. Our study focused on the demographic characteristics of the mother (age, parity, delivery mode, and multiple births) and the child (sex, weight, gestational age at birth, and date of death).

Gestational age was divided into 4 categories: (1) 37 or more weeks' gestation (term birth); (2) between 32 and 36 weeks (moderately preterm); (3) between 28 and 31 weeks (very preterm); and (4) less than 28 weeks (extremely preterm).10 Birth weight was divided into 3 categories: (1) less than 1500 g; (2) 1500 to 2499 g; and (3) 2500 g or more.

Functional classification was undertaken using the Gross Motor Function Classification System (GMFCS)12,13 and Bimanual Fine Motor Function (BFMF).14–17 Scores were calculated by the authors (R.F., V.S., and C.K.) from the data in the records, according to the SCPE rules; data to score BFMF from 12 patients were missing.

Vision impairment was classified into 3 categories: none, mild, or severe (blind or no useful vision, after correction, on the better eye; the level of vision loss is ≥6/60 or a squint; vision loss is <6/60 [Snellen scale] or <0.1 [decimal scale] in both eyes).

Hearing impairment was classified into 3 categories: none, mild, or severe (severe or profound hearing loss, before correction, in the better ear; mild hearing loss [between 30 and 70 dB]; the level of hearing loss being >70 dB in both ears).

Intellectual impairment was classified into 3 categories of intelligence quotient (IQ) or estimation of IQ according to SCPE: 70 or more (normal intellect but with learning disabilities, normal schooling is possible with some additional support); 50 to 69 (mild-to-moderate intellectual impairment; reading, calculating, and writing abilities but modified school curriculum); less than 50 (severe intellectual impairment, eg, only few or no reading, writing, and calculation abilities, dependent on support in activities of daily living). The following tests were used for IQ testing (German version): Bayley Scales of Infant Development,18 Griffiths Mental Development Scales,19 Kaufman Assessment Battery for Children,20 and Wechsler Intelligence Scale for Children.21 Scores inserted in the SCPE data collection form were calculated by the authors (R.F., V.S., and C.K.) from the data in the records. Epilepsy was defined as 2 or more unprovoked seizures, excluding febrile or neonatal seizures.

Eventually, information about associated syndromes and hip dislocation was collected from the medical records.

Statistical Analyses

To verify the normal distribution of reported values, a nonparametric 1-sample Kolmogorov-Smirnov test was used. A significance of less than .05 indicated a deviation from normality. Subsequently, continuous variables were compared by the Mann-Whitney U test (2-tailed). Statistical correlations were explored using the Spearman rank correlation coefficient. Statistical analyses were undertaken using SPSS v24.0 (IBM, Armonk, New York), and significance was set to α = .05. Data are the median and interquartile range.

RESULTS

A total of 140 patients fulfilling the inclusion criteria were identified. Their demographic characteristics and clinical features are presented in Tables 2 and 3. The distribution of the study cohort according to different CP subgroups, as well as a comparison with SCPE data,22 is presented in Table 4. The registries participating in the SCPE network are population-based and cover either a part or a whole country in Europe.

TABLE 2 - Demographic Characteristics of Participants
Total Number of Patients (N = 140) Median (IQR)
n %
Age, y 11.7 (7.6)
Sex
Boys 84 60
Girls 56 40
Children known to have died 6 4.3
Birth weight total, g 2960 (1480)
Birth weight group
≥2500 g 86 61.4
1500-2499 g 24 17.1
<1500 g 25 17.9
Unknown 5 3.6
Gestational age total, wk 38 (7.5)
Gestational age group
TB 85 60.7
MPT 17 12.1
VPT 7 5
EPT 19 13.6
Unknown 12 8.6
Maternal age, y 29 (6.75)
Delivery mode
Unknown 9 6.2
VD 79 54.1
CS elective/before labor 20 13.7
CS emergency/during labor 32 21.9
Multiple births
Single 128 91.4
Twin 12 8.6
Abbreviations: CS, cesarean section; EPT, extremely preterm; IQR, interquartile range; MPT, moderate-to-late preterm; TB, infants born full-term; VD, vaginal delivery; VPT, very preterm.

TABLE 3 - Impairment Distribution in Children With CP
Total Number of Patients (N = 140)
n %
GMFCS
Level I 68 48.6
Level II 24 17.1
Level III 12 8.6
Level IV 20 14.3
Level V 16 11.4
BFMF
Level 1 63 45
Level 2 29 20.7
Level 3 12 8.6
Level 4 16 11.4
Level 5 12 8.6
Unknown 8 5.7
Associated comorbidities
Cognitive impairment
IQ <50 44 31.5
IQ = 50-69 26 18.6
IQ ≥70 52 37.1
Unspecified 18 12.9
Visual impairment 58 41.4
Unknown 6 4.3
Severe 2 3.4
Hearing impairment 8 5.7
Unknown 12 8.6
Severe 2 25
Epilepsy 47 33.6
Unknown 3 2.1
Hip dislocation 31 22.1
Unknown 13 9.3
Associated syndromes 8 5.7
Unknown 23 16.4
Postneonatal CP 8 5.7
Unknown 8 5.7
Abbreviations: BFMF, Bimanual Fine Motor Function Classification; CP, cerebral palsy; GMFCS, Gross Motor Function Classification System; IQ, intelligence quotient.

TABLE 4 - Distribution of CP Subtype in the Study and in SCPE Data
CP Types n CSG Data, 1995-2009 (n = 140), % SCPE Data, 1980-1990a (n = 4792), % SCPE Data, 1996-2003b (n = 4394), %
Spastic 119 85 85.7 86.3
Bilateral 73 52.1 54.9 60.3
Unilateral 48 34.3 29.2 39.5
Left 21 43.7
Right 27 56.3
Unknown side 19 13.6
Dyskinetic 11 7.9 6.5 8
Ataxic 10 7.1 4.3 3.8
Unknown ... ... 3.7 1.9
Abbreviations: CP, cerebral palsy; CSG, canton of Saint Gallen; SCPE, Surveillance of Cerebral Palsy network in Europe.
aBased on data from “Prevalence and characteristics of children with cerebral palsy in Europe.”22
bBased on data from Sellier et al.1

The distribution of the study cohort according to GMFCS and BFMF scores is depicted in Figures 2A and B. A strong positive correlation was found: rs = 0.7 (P < .0005). High GMFCS scores were associated with a higher risk of hip dislocation (P < .0001) (Figure 3).

Fig. 2.
Fig. 2.:
Distribution of the Gross Motor Function Classification System (A) and Bimanual Fine Motor Function (B) levels across the study population.
Fig. 3.
Fig. 3.:
Distribution of children with hip dislocation according to GMFCS categories. GMFCS indicates Gross Motor Function Classification System.

Based on the findings of magnetic resonance imaging (MRI), the main causes of postneonatal CP, not related to the gestational age, were intracerebral infections (n = 5; 62.5%), acute cerebral ischemic events (n = 2; 25%), and intracranial hemorrhage (n = 1; 12.5%). The MRI dossiers were provided by the hospitals.

DISCUSSION

This was the first study to retrieve epidemiologic data on Swiss children diagnosed with CP. Our results, in the main, confirm data provided by SCPE registries.1,22 The present study is relevant because it describes the prevalence of CP in a Swiss region. Such information may be useful in everyday clinical practice (eg, for management of the comorbidity of children and adolescents with CP). In fact, until present day, management of children with CP in Switzerland depended mainly on an experience-based approach of health care professionals (such as neuropediatricians, neuro-orthopedics, physical therapists, occupational therapists, and speech, language, and special needs teachers). The data-retrieval procedure will be used to create the first registry of children with CP in Switzerland, which is of clinical and academic interest. Based on the collected data, the canton of Saint Gallen will be able to better anticipate the therapeutic needs (care, ambulatory therapies, education facilities, workplaces, homes) in the future and thus better plan measures and interventions.

Most of our results are self-explanatory, but 2 findings merit closer discussion. First, our results confirmed previously reported data about strong correlations between the GMFCS and BFMF.14,23,24 Second, the association between the GMFCS score and a higher risk of hip dislocation observed in our study confirms other observations,25,26 has practical clinical implications, and will be a central aspect of the planned national study to include a hip surveillance program (see later). Children with a GMFCS score of 4 or more have a risk of hip dislocation of 60% or more, whereas the risk of hip dislocation in children with a GMFCS score of 3 or less is less than 30%. Hence, physical therapists and the responsible pediatrician must pay particular attention while taking care of these children, promptly referring them for orthopedic examination (eventually also considering a lower threshold for referral) and offering them interdisciplinary treatments. Moreover, a central aspect to enable early identification and preventive treatment of hip dislocations is a hip surveillance program, which, when first introduced in Australia and Sweden, reduced the prevalence of hip displacement to 0%27,28 in children with CP. According to Rutz and Brunner,29 and as a direct clinical effect of the present study, a multidisciplinary hip surveillance program for children with CP will be introduced in Switzerland. Thus, a critical role in the setting up of a screening protocol for hip displacement will be held by physical therapists who should collaborate with pediatricians to establish ranges of the considered parameters and promote a surveillance program.

The epidemiologic data collected in this study are comparable with the results of other existing registries of the SCPE focused on the incidence of CP, comorbidities, mobility, and manual abilities of children with CP. Moreover, feasibility to collect data from individuals with CP through hospital notes in Switzerland was shown. The effort to provide a nationwide registry, in a federalist country, with several differences in health provision between cantons, will be considerable. Cooperative support by health care professionals will be necessary to achieve a high data quality and at least 95% of completeness. Finally, the collected data confirm previous observations of the increasing risk to develop CP: the more premature a child, the lower his or her birth weight at birth.

The present study had 2 main strengths. The first was the use of standardized scales for assessing motor function. This strategy avoided the effect of interobserver bias and differences in personal interpretation of situations encompassing a broad clinical spectrum with a large range of fine quantitative/qualitative nuances. Second, our study covered 90.9% of the children born in the specified region between January 1, 1995, and December 31, 2009, thereby providing a complete and realistic picture without any selection bias.

The present study had 3 main limitations. The most important limitation was its retrospective and strictly descriptive design. Only few data over an extended time period were extracted; hence, we could not assess the influence and interference of other potential factors (eg, interventions, environment, screening programs, and diagnostic strategies). Second, we did not address factors that could impact the prevalence of CP. These were, for example, monitoring improvements of neonatal care with specific follow-ups, 24-hour a day immediate availability at the hospital of a pediatrician to carry out neonatal resuscitation, availability of intensive neonatal care units, prevention of secondary brain damage by head cooling, maternal health status, and body mass index. Finally, the extraction of retrospective data was a challenging procedure because the information was collected, coded, and stored in very heterogeneous ways. In particular, some medical records presented detailed, extensive, and descriptive reports. This format required a large amount of time and effort to extract relevant information. Nevertheless, more than 95% of the information could be extracted and coded in a standardized and structured way. This result suggests that the use of such standardized scales (also in medical records) should enable more efficient and accurate communication among different types of clinicians, thereby decreasing the workload and possibly also improving the quality of clinical care.

CONCLUSIONS

This pilot study in a Swiss canton demonstrated the feasibility and usefulness of creating a registry of children affected by CP. Consequently, in autumn 2017, a group of Swiss pediatricians and researchers headed by Professor Kuehni will start a new Swiss registry for CP at the Institute of Social and Preventive Medicine at the University of Bern. The aims of this registry will be to (i) promote systematic collections of epidemiologic and clinical data on all children diagnosed with CP in Switzerland; (ii) determine the scope of CP; and (iii) identify factors that contribute to a good long-term outcome and quality of life of children with CP. Moreover, the data retrieved in the present study were accepted and entered into the SCPE registry, thereby filling an information gap because Switzerland was not represented until now.

ACKNOWLEDGMENTS

The authors thank Sally Prentice and Andrea Zbinden for their contributions and technical support.

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Keywords:

cerebral palsy; hip dislocation; prevalence

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