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Introduction: Cerebral palsy (CP) is a nonprogressive movement disorder resulting from a prenatal or perinatal brain injury that benefits from early diagnosis and intervention. The timing of early CP diagnosis remains controversial, necessitating analysis of clinical features in a substantial cohort. Methods: We retrospectively reviewed medical records from a university hospital, focusing on children aged ≥24 months or followed up for ≥24 months and adhering to the International Classification of Diseases-10 for diagnosis and subtyping. Results: Among the 2012 confirmed CP cases, 68.84% were male and 51.44% had spastic diplegia. Based on the Gross Motor Function Classification System (GMFCS), 62.38% were in levels I and II and 19.88% were in levels IV and V. Hemiplegic and diplegic subtypes predominantly fell into levels I and II, while quadriplegic and mixed types were mainly levels IV and V. White matter injuries appeared in 46.58% of cranial MRI findings, while maldevelopment was rare (7.05%). Intellectual disability co-occurred in 43.44% of the CP cases, with hemiplegia having the lowest co-occurrence (20.28%, 58/286) and mixed types having the highest co-occurrence (73.85%, 48/65). Additionally, 51.67% (697/1,349) of the children with CP aged ≥48 months had comorbidities. Conclusions: This study underscores white matter injury as the primary CP pathology and identifies intellectual disability as a common comorbidity. Although CP can be identified in infants under 1 year old, precision in diagnosis improves with development. These insights inform early detection and tailored interventions, emphasizing their crucial role in CP management.

Cerebral palsy (CP) is primarily a neuromotor disorder in children that typically results from brain injuries during the perinatal or neonatal period. It encompasses a range of nonprogressive movement disturbances, abnormal postures, and possible lifelong cognitive and sensory impairments. The incidence of CP varies, with higher rates in developing countries [1], imposing a substantial burden on patients, families, and society owing to its severity and associated costs.

CP is a complex and heterogeneous syndrome that is influenced by diverse factors, resulting in varying clinical presentations, severities, comorbidities, and outcomes. Environmental factors such as preterm birth, perinatal asphyxia, and genetic factors contribute to CP’s etiology [2, 3]. Genetic studies have highlighted the potential of early diagnosis to enable curative treatment in some infants with CP [4].

CP often co-occurs with neurological comorbidities like intellectual disability and epilepsy [5, 6]. As an umbrella term, CP may be misdiagnosed in its early stages [7], and this indicates the importance of understanding its causes for an accurate diagnosis. The prognosis of CP is strongly influenced by clinical features and comorbidities. Although global CP registers [8‒10] and studies in China have reported the clinical characteristics of these comorbidities [11, 12], comprehensive large-sample analyses of these traits in Chinese children with CP are still lacking. This study aimed to analyze the clinical characteristics of confirmed CP cases, assess their severity, identify potential risk factors, categorize CP into subtypes based on functional level, neuroimaging findings, and comorbidities, and explore potential links between CP subtypes, functional levels, and comorbidities using data from the Henan Province CP Register Center.

Study Population

This study included children suspected of having CP who were admitted to the Child Rehabilitation Center of the Third Affiliated Hospital between January 1, 2011, and December 31, 2020. Pediatric neurologists conducted comprehensive evaluations, including pregnancy and birth history, family history, developmental milestones, medical history, physical and neurological examinations, routine cerebral imaging, and laboratory tests. Metabolic or genetic analysis is recommended for children who have no obvious high-risk factors and who have normal brain imaging results. Children were followed up until at least 24 months of age if their last admission to the center was <24 months. Children who were diagnosed with CP and excluded during hospitalization or follow-up were considered false positives, and the children who were found to have abnormal genetic or metabolic features that could explain the “CP” clinical feature were excluded from the CP group and considered to be false positives as well. These children were excluded because CP is an umbrella term and is clinically diagnosed based on delays in motor milestones and abnormalities in muscle tone or reflexes, leading to a potential for false-positive diagnoses of “CP.” This risk is particularly pronounced before the age of 2 years due to the inclusion of conditions that may mimic CP, such as genetic disorders. Data were retrospectively collected from medical records, excluding incomplete records, progressive encephalopathy [13], and loss of follow-up before 24 months of age. False-positive rates were calculated as the number of children considered false positive/(the number of children finally enrolled with CP + the number of children considered false positive).

Clinical Assessment

CP diagnosis relies on medical history, clinical assessment, and cerebral imaging. We utilized ICD-10 codes G80.0-G80.9 to classify CP subtypes, including spastic hemiplegia, spastic diplegia, spastic quadriplegia, dyskinesia, ataxia, and mixed types. For consistency with the latest classification standards, spastic monoplegia is considered a subtype of spastic hemiplegia, and spastic triplegia is considered a subtype of spastic quadriplegia. Hypotonic and rigid CP types were excluded because of their data consistency [14]. Motor function was evaluated using the Gross Motor Function Classification System (GMFCS) [15].

Cranial Imaging Analysis

All cranial images, including both brain MRI and CT scans, were collected and analyzed following the MRI classification system (MRICS) guidelines [16]. The MRI scans were performed using magnetic field strengths of either 1.5 T or 3.0 T. The imaging sequences included T1-weighted, T2-weighted, T2-FLAIR, and diffusion-weighted imaging for axial views, and T1-weighted sequences for sagittal views were used in all scans. Common clinical criteria were employed to assess myelin development [17]. Both a child radiologist and a child rehabilitation physician independently conducted the analysis. In cases of inconsistent results, the authors collaborated to reach the final determination. Both the pediatric radiologist and the pediatric rehabilitation physician were blinded to the information on all children with CP.

Neurological Comorbidities

Intellectual disability criteria were based on an IQ <70 (measured by the Wechsler Intelligence Scale China Revised) or a developmental quotient <75 in adaptive behavior (assessed with the Gesell Developmental Scale II). IQ scores were recorded for children ≥4 years old, and those without an IQ test at age 4 or lacking intelligence-related data were labeled as “missing.” An electroencephalogram (EEG) was ordered for all children with CP. Those who showed signs of epilepsy or an epileptiform pattern on the EEG were further recommended to undergo a long-term video EEG or an ambulatory EEG examination. Epilepsy was defined as more than two afebrile seizures with intervals exceeding 24 h or the use of antiepileptic drugs [18]. Visual impairment encompassed cerebral visual impairment affecting the retrochiasmatic visual pathways and projection areas, including low vision and strabismus [19]. Hearing loss was defined as bilateral hearing loss of 30 dB or greater, detected by auditory evoked potential testing. Positive results before 12 months were confirmed by follow-up testing after 12 months.

Data Collection

We extracted the following data from medical records: residential addresses of families (classified into urban and rural categories), age of the mother at the time of the child’s birth (identified as advanced maternal age if ≥35 years), presence of diseases during pregnancy (including maternal hypertension, maternal diabetes, preeclampsia, and eclampsia), history of adverse pregnancy outcomes (including spontaneous abortion and stillbirth), gravidity, delivery method, parity, sex, age, birth weight, gestational age (categorized as <32 weeks, 32–36 weeks, and ≥37 weeks; preterm birth defined as <37 weeks), multiple births, perinatal asphyxia (Apgar score <7 at 5 min, arterial blood pH <7, or base excess >12 mmol/L) [20], neonatal seizures, and pathologic jaundice (early onset, rapid increase, or sustained elevation) [21]. CP subtype was determined by GMFCS motor function levels, brain MRI/CT findings, and neurological comorbidities (intellectual disability, epilepsy, and visual impairment). In cases of multiple hospitalizations for rehabilitation, data from the last hospitalization were used. Maternal and perinatal information was obtained from the parents by the attending physicians of the children with CP. Obstetric records were required to verify the information about the delivery process obtained during interviews. If the parents did not have obstetric records, discharge notes could be provided as an alternative. If the information obtained during follow-up, including clinical diagnosis, subtype, and comorbidities, differed from the medical records, the follow-up results took precedence.

Statistical Analysis

Stata 16.1 was employed for statistical analysis. Descriptive statistics summarized the population characteristics as the mean ± SD for quantitative data and as the frequency (%) for categorical data. Single-sample rate tests were used to compare the proportions of males between children with CP and the general population. χ2 tests were used to examine the association between gestational weeks and CP subtypes, with a Bonferroni correction applied for post hoc comparisons. The relationship between gestational weeks and GMFCS levels was assessed using Kruskal-Wallis and trend tests, with multiple comparisons handled by Kruskal-Wallis with Bonferroni correction. The association between GMFCS levels and advanced maternal age was evaluated using the Kruskal-Wallis test. Comparisons between CP subtypes and MRICS, between CP subtypes and advanced maternal age, and between gestational age and advanced maternal age were performed using the χ2 test. Statistical significance was set at α = 0.05.

Study Cohort

Throughout the study, 3,070 children received their initial CP diagnosis at the outpatient department of a rehabilitation center. Subsequent evaluation at the hospital with a new diagnosis led to the exclusion of 33 children, while an additional 53 were excluded due to hypotonic or rigid CP. All children were followed up until they reached 24 months of age if they were younger than 24 months at the first visit. Among them, 26 died, 74 were diagnosed with other diseases, and 824 were lost to follow up. Out of the 107 children who received a new diagnosis, 78 were identified with developmental delays or considered normal. Seven children were found to have chromosomal disorders, and 22 were diagnosed with genetic conditions. These conditions include hereditary spastic paraplegia, muscular dystrophy, tuberous sclerosis, and metachromatic leukodystrophy. In total, 2012 cases were analyzed, comprising 1,349 aged ≥48 months and 663 aged 24–48 months (Fig. 1). Additionally, 16 children diagnosed with CP were found to have complications associated with metabolic conditions, including thyroid hypofunction, methylmalonic acidemia or glutaric aciduria, and citrullinemia.

Fig. 1.

Study flow. The schematic flowchart showing the recruitment and exclusion of children with CP during hospitalization and follow-up.

Fig. 1.

Study flow. The schematic flowchart showing the recruitment and exclusion of children with CP during hospitalization and follow-up.

Close modal

Baseline Characteristics

Among the 2012 CP cases, 68.84% were male and 31.16% were female, with an average age of 69.1 ± 34.5 months. The oldest participant in this study was 224 months old, with birth years ranging from 1993 to 2019. Of the 1,996 cases with recorded gestational age, 58.26% were full term and 41.73% were preterm. Among preterm infants, 23.15% were born at ≥32 weeks, 18.59% at <32 weeks, and 28% at ≤28 weeks. A history of perinatal asphyxia was present in 11.23% (226/2,012) of the cases, with no significant difference between full-term and preterm children with CP. Among the full-term infants with a history of asphyxia (10.58%), 62.60% were male and 37.40% were female, with no significant difference in sex distribution.

Of the 88.82% (1,787/2,012) of CP children with recorded maternal age at pregnancy, 14.66% (262/1,787) were born to mothers of advanced maternal age. Children born to mothers of advanced maternal age had higher GMFCS levels than those born to younger mothers (χ2 = 4.433, p = 0.0353). However, there were no significant differences in CP subtypes associated with advanced maternal age (χ2 = 7.6879, p = 0.174), nor was there a significant difference in gestational age between children born to mothers of advanced maternal age and those born to younger mothers (χ2 = 2.1524, p = 0.341).

Among the 2012 children with CP, 25.05% had pathological neonatal jaundice. Among the 804 preterm children, 31.97% experienced neonatal pathological jaundice. Preterm infants with CP had a significantly higher likelihood of neonatal jaundice than term infants (χ2 = 23.02; p < 0.001). A history of intracranial hemorrhage was present in 6.11% of the children, with 73.17% being boys and 52.03% having a gestational age ≥37 weeks. The incidence did not differ significantly by sex or term/preterm status.

Spastic CP was the most prevalent subtype (90.21%; diplegia, 51.44%; quadriplegia, 17.25%; hemiplegia, 21.52%), while the other subtypes collectively comprised 9.79%, including dyskinesia (3.23%), ataxia (1.04%), and mixed subtype (5.52%). Regarding GMFCS, 62.38% of the children with CP fell into the GMFCS I (32.31%) or GMFCS II (30.07%) categories. In addition, 17.74% were GMFCS III, 10.49% were GMFCS IV, and 9.39% were GMFCS V.

CP Early Diagnosis

Of the CP cohort, 5.05% (107/[107 + 2012]) were later excluded with varying false-positive rates, including 7.51% for those diagnosed before 12 months (16/[19 + 16]), 7.97% for ages 12–24 months (72/[831 + 72]), and 1.89% for those diagnosed at or after 24 months (19/[984 + 19]). Notably, all initially diagnosed “CP” children were under 24 months at diagnosis.

Gestational Weeks and CP Subtypes

This study primarily involved term infants, and we explored the relationship between gestational age and CP subtypes (Table 1). Spastic CP was the most common subtype (90.21%, 1,815/2012), especially in preterm infants with a gestational age ≤32 weeks (96.77%, 359/371). Diplegia and quadriplegia predominated among preterm children, with quadriplegia being notably higher in those aged ≤32 weeks (23.72%, 88/371). Hemiplegia and mixed types were most prevalent (27.94% and 6.88%, respectively) in term children. Significant differences existed between gestational weeks and subtypes (χ2 = 127.671, p < 0.001), with variations across all gestational weeks (Table 1). χ2 tests indicated a higher proportion of preterm children with diplegic and quadriplegic CP. We further categorized CP into spastic and non-spastic types and found that the spastic CP ratio correlated with gestational weeks (χ2 = 31.95, p < 0.001), with lower gestational weeks being associated with higher spastic CP ratios.

Table 1.

Gestation weeks and subtypes

Gestational ageDiplegiaHemiplegiaQuadriplegiaMixedDyskinesiaAtaxiaTotal
≥37 weeksa,b 509 (43.77) 325 (27.94) 181 (15.56) 80 (6.88) 50 (4.3) 18 (1.55) 1,163 (100) 
32–36 weeksc 284 (61.47) 68 (14.72) 75 (16.23) 23 (4.98) 10 (2.16) 2 (0.43) 462 (100) 
<32 weeks 233 (62.8) 38 (10.24) 88 (23.72) 6 (1.62) 5 (1.35) 1 (0.27) 371 (100) 
Total 1,026 (51.4) 431 (21.59) 344 (17.23) 109 (5.46) 65 (3.26) 21 (1.05) 1,996 (100) 
Gestational ageDiplegiaHemiplegiaQuadriplegiaMixedDyskinesiaAtaxiaTotal
≥37 weeksa,b 509 (43.77) 325 (27.94) 181 (15.56) 80 (6.88) 50 (4.3) 18 (1.55) 1,163 (100) 
32–36 weeksc 284 (61.47) 68 (14.72) 75 (16.23) 23 (4.98) 10 (2.16) 2 (0.43) 462 (100) 
<32 weeks 233 (62.8) 38 (10.24) 88 (23.72) 6 (1.62) 5 (1.35) 1 (0.27) 371 (100) 
Total 1,026 (51.4) 431 (21.59) 344 (17.23) 109 (5.46) 65 (3.26) 21 (1.05) 1,996 (100) 

aThere was a significant difference between gestational ages ≥37 weeks and 32–36 weeks for the CP subtypes (χ2 = 54.556, p < 0.001).

bThere was a significant difference between gestational ages ≥37 weeks and <32 weeks for CP subtypes (χ2 = 93.43, p < 0.001).

cThere was a significant difference between gestational ages 32–36 weeks and <32 weeks for the CP subtypes (χ2 = 16.78, p = 0.005).

CP GMFCS

We observed that children born at ≥37 weeks had GMFCS I in 35.68% of cases and GMFCS V in 10.58%, whereas children born at <32 weeks had GMFCS I in 25.43% of cases and GMFCS V in 6.47%. Significant differences were found between the gestational age and GMFCS scores (χ2 = 18.21, p = 0.0001). Post hoc analysis revealed no difference between ≥37 weeks and 32–36 weeks in the GMFCS, but a significant difference was seen between 32 and 36 weeks and <32 weeks in the GMFCS (p = 0.004). Lower gestational age showed a linear relationship with higher GMFCS scores (F = 11.63, p < 0.001). Examining CP subtypes, most children with hemiplegic CP (97.00%) achieved GMFCS I–II, while quadriplegia and mixed-type CP had significant motor deficits (72.62% and 73.87% in GMFCS IV–V). Diplegic and ataxic CP showed limited motor function disability (2.90% and 14.29% in GMFCS IV–V). Hemiplegia differed significantly from the other subtypes, while the mixed subtype was not significantly different from quadriplegia and dyskinetic subtypes (p > 0.05) (Table 2).

Table 2.

Gestation weeks, subtypes, and GMFCS of CP

GMFCS IGMFCS IIGMFCS IIIGMFCS IVGMFCS VTotal
Gestational age 
 ≥37 weeksa,b 415 (35.68) 349 (30.01) 182 (15.65) 94 (8.08) 123 (10.58) 1,163 (100) 
 36–32weeksc 140 (30.3) 154 (33.33) 82 (17.75) 45 (9.74) 41 (8.87) 462 (100) 
 <32 weeks 91 (24.53) 100 (26.95) 88 (23.72) 68 (18.33) 24 (6.47) 371 (100) 
Trend test of ordered group z = 4.29, p<0.001 
CP subtypes 
 Diplegia 322 (31.11) 397 (38.36) 286 (27.63) 29 (2.8) 1 (0.1) 1,035 (100) 
 Hemiplegia 309 (71.36) 111 (25.64) 13 (3) 0 (0) 0 (0) 433 (100) 
 Quadriplegia 5 (1.44) 60 (17.29) 30 (8.65) 149 (42.94) 103 (29.68) 347 (100) 
 Mixed 3 (2.7) 16 (14.41) 10 (9.01) 20 (18.02) 62 (55.86) 111 (100) 
 Dyskinesia 4 (6.15) 17 (26.15) 11 (16.92) 11 (16.92) 22 (33.85) 65 (100) 
 Ataxia 7 (33.33) 4 (19.05) 7 (33.33) 2 (9.52) 1 (4.76) 21 (100) 
Statistical value χ2 = 870.631, p = 0.0001 
GMFCS IGMFCS IIGMFCS IIIGMFCS IVGMFCS VTotal
Gestational age 
 ≥37 weeksa,b 415 (35.68) 349 (30.01) 182 (15.65) 94 (8.08) 123 (10.58) 1,163 (100) 
 36–32weeksc 140 (30.3) 154 (33.33) 82 (17.75) 45 (9.74) 41 (8.87) 462 (100) 
 <32 weeks 91 (24.53) 100 (26.95) 88 (23.72) 68 (18.33) 24 (6.47) 371 (100) 
Trend test of ordered group z = 4.29, p<0.001 
CP subtypes 
 Diplegia 322 (31.11) 397 (38.36) 286 (27.63) 29 (2.8) 1 (0.1) 1,035 (100) 
 Hemiplegia 309 (71.36) 111 (25.64) 13 (3) 0 (0) 0 (0) 433 (100) 
 Quadriplegia 5 (1.44) 60 (17.29) 30 (8.65) 149 (42.94) 103 (29.68) 347 (100) 
 Mixed 3 (2.7) 16 (14.41) 10 (9.01) 20 (18.02) 62 (55.86) 111 (100) 
 Dyskinesia 4 (6.15) 17 (26.15) 11 (16.92) 11 (16.92) 22 (33.85) 65 (100) 
 Ataxia 7 (33.33) 4 (19.05) 7 (33.33) 2 (9.52) 1 (4.76) 21 (100) 
Statistical value χ2 = 870.631, p = 0.0001 

aThere was no significant difference between gestational ages ≥37 weeks and 32–36 weeks in the GMFCS (rank mean difference = 39.93, p = 0.10).

bThere was a significant difference between gestational ages ≥37 weeks and 32–36 weeks in the GMFCS (rank mean difference = 146.56, p < 0.001).

cThere was a significant difference between gestational ages 32–36 weeks and <32 weeks in the GMFCS (rank mean difference = 106.63, p = 0.004).

Cerebral Imaging

Among the 2,012 children with CP, 70.53% had cranial MRIs and 18.14% had cranial CT scans. MRI revealed predominant white matter injury in 46.58% (661/1,419), maldevelopments in 7.05% (100/1,419), and 13.46% (191/1,419) of patients with normal MRI results. CT scans showed more normal brain images than MRI scans, with significant MRICS variation (χ2 = 69.11, p < 0.001), but only 18 children had both scans (Table 3). Of 191 children with normal MRI results, 83.77% were born at ≥37 weeks, 9.95% at 32–36 weeks, and 7.28% at <32 weeks. Among them, 72.77% were boys and 7.33% had a history of perinatal asphyxia. Using the χ2 test, we found significant differences among CP subtypes (χ2 = 296.15, p < 0.001). Maldevelopment was common in ataxic (26.67%) and quadriplegic (10.70%) CP, while diplegia (54.1%) and quadriplegia (47.74%) had the highest predominant white matter injury. Dyskinesia and mixed subtypes dominated in children with predominant gray matter injury (48.15% and 44.71%). Among children with normal cranial MRI, dyskinesia (27.78%) and the mixed subtype (22.35%) had the highest proportion (Table 4).

Table 3.

MRICS results and CTICS

MRI, n (%)CT, n (%)MRI or CT, n (%)
Maldevelopments 
 Disorders of cortical formation 31 (2.18) 7 (1.92) 35 (1.98) 
 Other maldevelopments 69 (4.86) 24 (6.58) 92 (5.21) 
 Total 100 (7.05) 31 (8.49) 127 (7.19) 
PWMI 
 PVL 645 (45.45) 118 (32.33) 756 (42.81) 
 Sequelae of IVH or periventricular hemorrhagic infarction 8 (0.56) 2 (0.55) 10 (0.57) 
 Combination of PVL and IVH sequelae 8 (0.56) 8 (0.45) 
 Total 661 (46.58) 120 (32.88) 774 (43.83) 
PGMI 
 Basal ganglia/thalamus lesions 108 (7.61) 6 (1.64) 114 (6.46) 
 Cortico-subcortical lesions 109 (7.68) 17 (4.66) 126 (7.08) 
 Arterial infarctions 7 (0.49) 2 (0.55) 9 (0.51) 
 Total 224 (15.79) 25 (6.85) 249 (14.04) 
Miscellaneous 243 (17.12) 96 (26.3) 334 (18.91) 
Normal 191 (13.46) 93 (25.48)a 283 (16.02) 
Total 1,419 (100) 365 (100) 1,766 (100) 
p value χ2 = 69.11, p < 0.001  
MRI, n (%)CT, n (%)MRI or CT, n (%)
Maldevelopments 
 Disorders of cortical formation 31 (2.18) 7 (1.92) 35 (1.98) 
 Other maldevelopments 69 (4.86) 24 (6.58) 92 (5.21) 
 Total 100 (7.05) 31 (8.49) 127 (7.19) 
PWMI 
 PVL 645 (45.45) 118 (32.33) 756 (42.81) 
 Sequelae of IVH or periventricular hemorrhagic infarction 8 (0.56) 2 (0.55) 10 (0.57) 
 Combination of PVL and IVH sequelae 8 (0.56) 8 (0.45) 
 Total 661 (46.58) 120 (32.88) 774 (43.83) 
PGMI 
 Basal ganglia/thalamus lesions 108 (7.61) 6 (1.64) 114 (6.46) 
 Cortico-subcortical lesions 109 (7.68) 17 (4.66) 126 (7.08) 
 Arterial infarctions 7 (0.49) 2 (0.55) 9 (0.51) 
 Total 224 (15.79) 25 (6.85) 249 (14.04) 
Miscellaneous 243 (17.12) 96 (26.3) 334 (18.91) 
Normal 191 (13.46) 93 (25.48)a 283 (16.02) 
Total 1,419 (100) 365 (100) 1,766 (100) 
p value χ2 = 69.11, p < 0.001  

PWMI, predominant white matter injury; PVL, periventricular leukomalacia; IVH, intraventricular hemorrhage; PGMI, predominant gray matter injury.

aThe normal cranial imaging classification system differed between the two groups: χ2 = 69.11, p < 0.001.

Table 4.

CP subtypes and MRICS

MRICSDiplegiaHemiplegiaQuadriplegiaMixedDyskinesiaAtaxia
Maldevelopments 40 (5.76) 25 (7.65) 26 (10.7) 3 (3.53) 2 (3.7) 4 (26.67) 
PWMI 376 (54.1) 152 (46.48) 116 (47.74) 12 (14.12) 4 (7.41) 1 (6.67) 
PGMI 32 (4.6) 87 (26.61) 41 (16.87) 38 (44.71) 26 (48.15) 0 (0) 
Miscellaneous 132 (18.99) 47 (14.37) 34 (13.99) 13 (15.29) 7 (12.96) 10 (66.67) 
Normal 115 (16.55) 16 (4.89) 26 (10.7) 19 (22.35) 15 (27.78) 0 (0) 
Total 695 (100) 327 (100) 243 (100) 85 (100) 54 (100) 15 (100) 
MRICSDiplegiaHemiplegiaQuadriplegiaMixedDyskinesiaAtaxia
Maldevelopments 40 (5.76) 25 (7.65) 26 (10.7) 3 (3.53) 2 (3.7) 4 (26.67) 
PWMI 376 (54.1) 152 (46.48) 116 (47.74) 12 (14.12) 4 (7.41) 1 (6.67) 
PGMI 32 (4.6) 87 (26.61) 41 (16.87) 38 (44.71) 26 (48.15) 0 (0) 
Miscellaneous 132 (18.99) 47 (14.37) 34 (13.99) 13 (15.29) 7 (12.96) 10 (66.67) 
Normal 115 (16.55) 16 (4.89) 26 (10.7) 19 (22.35) 15 (27.78) 0 (0) 
Total 695 (100) 327 (100) 243 (100) 85 (100) 54 (100) 15 (100) 

PWMI, predominant white matter injury; PGMI, predominant gray matter injury.

CP Comorbidities

In the CP cohort aged ≥48 months, 43.44% had intellectual disabilities, 11.38% had epilepsy, 8.9% had hearing loss, and 8.90% had visual impairment, totaling 51.67% with neurological comorbidities, showing no sex differences (χ2 = 0.447, p = 0.504). Among those with comorbidities, 61.69% were born at ≥37 weeks of gestation and comorbidity prevalence increased with gestational age (χ2 = 16.21, p = 0.0001) (Table 5).

Table 5.

Gestational weeks and comorbidities

With comorbidityWithout comorbidityOdds (95% CI)Score test for trend
Intellectual disability 
 ≥37 weeks 376 385 0.977 (0.847, 1.126) χ2 = 23.40, p < 0.001 
 32–36 weeks 110 202 0.545 (0.432, 0.687) 
 <32 weeks 91 171 0.532 (0.413, 0.686) 
Epilepsy 
 ≥37 weeks 148 1,015 0.146 (0.123, 0.173) χ2 = 5.66, p = 0.0174 
 32–36 weeks 46 416 0.111 (0.082, 0.15) 
 <32 weeks 32 339 0.094 (0.066, 0.136) 
Hearing loss 
 ≥37 weeks 129 1,034 0.125 (0.104, 0.15) χ2 = 17.68, p < 0.001 
 32–36 weeks 34 428 0.079 (0.056, 0.113) 
 <32 weeks 16 355 0.045 (0.027, 0.074) 
Visual impairment 
 ≥37 weeks 81 1,082 0.075 (0.06, 0.094) χ2 = 10.95, p = 0.0009 
 32–36 weeks 55 407 0.135 (0.102, 0.179) 
 <32 weeks 43 328 0.131 (0.095, 0.18) 
Total 
 ≥37 weeks 430 331 1.299 (1.299, 1.126) χ2 = 16.21, p = 0.0001 
 32–36 weeks 142 170 0.835 (0.835, 0.668) 
 <32 weeks 115 147 0.782 (0.782, 0.613) 
With comorbidityWithout comorbidityOdds (95% CI)Score test for trend
Intellectual disability 
 ≥37 weeks 376 385 0.977 (0.847, 1.126) χ2 = 23.40, p < 0.001 
 32–36 weeks 110 202 0.545 (0.432, 0.687) 
 <32 weeks 91 171 0.532 (0.413, 0.686) 
Epilepsy 
 ≥37 weeks 148 1,015 0.146 (0.123, 0.173) χ2 = 5.66, p = 0.0174 
 32–36 weeks 46 416 0.111 (0.082, 0.15) 
 <32 weeks 32 339 0.094 (0.066, 0.136) 
Hearing loss 
 ≥37 weeks 129 1,034 0.125 (0.104, 0.15) χ2 = 17.68, p < 0.001 
 32–36 weeks 34 428 0.079 (0.056, 0.113) 
 <32 weeks 16 355 0.045 (0.027, 0.074) 
Visual impairment 
 ≥37 weeks 81 1,082 0.075 (0.06, 0.094) χ2 = 10.95, p = 0.0009 
 32–36 weeks 55 407 0.135 (0.102, 0.179) 
 <32 weeks 43 328 0.131 (0.095, 0.18) 
Total 
 ≥37 weeks 430 331 1.299 (1.299, 1.126) χ2 = 16.21, p = 0.0001 
 32–36 weeks 142 170 0.835 (0.835, 0.668) 
 <32 weeks 115 147 0.782 (0.782, 0.613) 

Analyzing CP subtypes and comorbidities showed that intellectual disability was the most common, with the lowest occurrence in hemiplegia (20.28%). Quadriplegia had the highest epilepsy occurrence (32.63%), dyskinesia had the highest hearing loss ratio (43.08%), and quadriplegia had the highest visual impairment rate (14.70%). Overall, 51.67% of children aged ≥48 months with CP had at least one comorbidity, with 14.38% having multiple comorbidities. CP subtypes significantly differed in comorbidity numbers (χ2 = 188.49, p < 0.001), with the mixed, dyskinesia, and quadriplegia subtypes having the highest proportions (Fig. 2).

Fig. 2.

CP comorbidities and relationship to clinical subtypes. a The bar graph displays the number and percentage of intellectual disability, epilepsy, hearing loss, and visual impairment in different subtypes of CP. b The bar graph illustrates the relative frequencies of comorbidities in CP subtypes.

Fig. 2.

CP comorbidities and relationship to clinical subtypes. a The bar graph displays the number and percentage of intellectual disability, epilepsy, hearing loss, and visual impairment in different subtypes of CP. b The bar graph illustrates the relative frequencies of comorbidities in CP subtypes.

Close modal

Among the CP cases, 9.64% had multiple comorbidities, with no sex differences (χ2 = 3.299, p = 0.509). Of these, 62.4% were born at ≥37 weeks of gestation, with a significant difference in comorbidity numbers among gestational weeks (χ2 = 17.834, p = 0.0001). Lower gestational age correlated with fewer comorbidities (F = 16.95, p < 0.001) (Table 6).

Table 6.

Sex, gestational weeks, and numbers of comorbidities

ZeroOneTwoThreeFourp value
Sex 
 Male 459 348 108 19 0.41a 
 Female 193 155 46 15 
GAb 
 ≥37 weeks 331 309 93 24 0.0001c 
 32–36 weeks 170 96 36 
 <32 weeks 147 90 23 
ZeroOneTwoThreeFourp value
Sex 
 Male 459 348 108 19 0.41a 
 Female 193 155 46 15 
GAb 
 ≥37 weeks 331 309 93 24 0.0001c 
 32–36 weeks 170 96 36 
 <32 weeks 147 90 23 

aThere were no significant differences in the number of comorbidities between males and females (χ2 = 0.690, p = 0.406).

bLinear trend test showed that for children with CP, the lower the gestational age, the lower the number of comorbidities (F = 16.95, p < 0.001).

cThere were significant differences in the number of comorbidities among different gestational weeks (χ2 = 17.834, p = 0.0001), and post hoc multiple comparisons showed that there were significant differences in the numbers of comorbidities between gestational ages ≥37 weeks and 32–36 weeks (rank means difference = 66.98, p = 0.005), but no significant differences in the numbers of comorbidities between 32 and 36 weeks and <32 weeks (rank means difference = 28.4, p = 0.189).

CP is a common childhood physical disability with a global prevalence of 1.6% [22], and the prevalence is higher in underdeveloped nations [2]. It is more frequent in very preterm or very low birthweight infants [23], boys, and rural residents [11]. Recent studies have shown varying CP prevalence trends, with declines noted in many countries, except in China [20, 24‒27]. Factors contributing to these inconsistencies include early intervention strategies [28, 29].

CP is a complex neurodevelopmental disorder with diverse causes and diagnostic challenges [30]. Diagnosis relies on identifying motor delays and abnormal muscle tone or reflexes, which may not manifest until several months after birth. Early diagnosis is thus crucial for timely interventions [30‒32]. Recent studies suggest that a combination of neuroimaging, general movement observations, and neurological examinations can accurately diagnose CP as early as 3 months of corrected age, thus facilitating targeted interventions for better outcomes [31]. However, reliable diagnosis before 2 years of age remains uncertain due to variability because developmental delay or metabolic/genetic disorders might not be identified at a very young age [33].

CP risk rises with decreasing gestational age [34, 35], and preterm birth is linked to various factors increasing CP risk, including cerebral hemorrhage, infections, medical treatments, and ventilation support [2]. In this study, 41.73% were preterm births, with 18.59% being very preterm births (<32 weeks), similar to rates in other countries [20, 36, 37]. While preterm birth increases CP risk, it is not the primary factor in the Canadian study population, suggesting the potential neglect of follow-up examinations in term infants without obvious risk factors [20]. The correlation between gestational age and CP subtypes indicates a higher prevalence of spastic CP, particularly diplegia, in preterm infants, whereas term infants more frequently exhibit hemiplegia [35, 38]. Spastic CP predominates in preterm infants, whereas non-spastic CP is more common in term infants [38].

Asphyxia is debated as a potential cause of CP, but recent research indicates an increased CP incidence in term and near-term infants compared to healthy neonates, with early hypothermia intervention reducing the risk of CP [29]. Perinatal asphyxia contributed to 11.23% of the CP cases in this study, while pathological jaundice accounted for 25.05%. Effective treatments for hyperbilirubinemia have reduced the incidence of CP linked to jaundice [39]. Severe hyperbilirubinemia remains more common in term infants, possibly because of active monitoring and intervention in preterm infants. Although intracranial hemorrhage is common in preterm infants and increases CP risk [40], this study found no difference in hemorrhage between term and preterm infants, highlighting the need to monitor coagulation factors and potential neurological complications in term infants with high-risk factors.

In this study, although lower gestational age was associated with higher GMFCS scores, the proportion of children with GMFCS level V was lowest among those born at <32 weeks. Similar findings were reported in a study from the western health region of Sweden [41]. This phenomenon might be attributed to two main factors. First, the gestational age reflects the influence of different etiologies [16], which significantly contribute to the GMFCS levels, and second, the brain's capability for compensation or reorganization is enhanced during early development [42].

Cerebral imaging is crucial for assessing brain injuries in CP [43], with MRI being a reliable tool for early diagnosis [16, 30, 44]. In our CP cohort, 86.54% of the imaging results were abnormal, with white matter injury being the most common. Notably, the incidence of normal findings in our cohort was similar to other studies [44, 45]. Genetic analysis may be useful in children with normal cerebral imaging to identify potential genetic or metabolic disorders that resemble CP [46]. White matter damage is prevalent in preterm CP cases, especially spastic diplegic CP [44, 47], and maldevelopment and miscellaneous changes are common in diplegic CP. Gray matter damage includes injuries in the basal nucleus due to kernicterus, asphyxia, and multicystic encephalomalacia [16]. Hemiplegia is associated with basal ganglia/thalamus lesions, while the mixed and dyskinesia subtypes primarily show cortico-subcortical lesions.

CP often co-occurs with comorbidities, such as intellectual disability, epilepsy, hearing loss, and visual impairment [10]. In our study, intellectual disability affected 43.44% of children, which was higher than that in a Norwegian study (28.1%) [10] but consistent with an Australian population-based study (45%) [48] and meta-analysis (49%) [49], while epilepsy affected 11.38%. These prevalence rates vary across reports [9, 49, 50], potentially due to the early age of CP diagnosis in our study preceding the epilepsy diagnosis.

Our study yielded unexpected results regarding the relationship between gestational age and intellectual disability in CP patients. Contrary to clinical expectations, a higher prevalence of intellectual disability was observed with increasing gestational age, consistent with a study from the Victorian CP Register [48]. The decline in intellectual impairment with decreasing gestational age may be linked to CP’s underlying pathogenesis, as term infants with CP are more prone to brain malformations, severe neonatal asphyxia, or unknown genetic factors. A similar trend was observed for epilepsy, albeit with a lower prevalence. Conversely, visual impairment showed an opposite trend, possibly due to retinal damage in preterm infants.

This is the first large-scale analysis in China utilizing an international CP diagnosis and motor function assessment system for comparison. However, notable limitations exist. First, the CP incidence could not be determined due to the hospital-based data collection. Second, the high loss to follow-up rates due to the diverse geographic origins of children with CP might affect the generalizability of the findings. Third, variable accessibility of neonatal screening tests in rural areas can hinder early diagnosis. Finally, the use of parental interviews and surveys may introduce recall bias.

CP is a complex neurodevelopmental disorder, with diverse causes and clinical manifestations. Major risk factors include preterm birth and low gestational age, with spastic CP being more common in preterm infants and non-spastic CP in term infants. Early diagnosis and intervention are essential for improving outcomes in CP-affected and at-risk children. Ongoing improvements in early diagnostic methods and effective risk factor management are key to reducing the burden of CP.

We thank Drs. Erliang Sun, Longyuan He, Keji Cao, and Zhen Yang from the Cerebral Palsy Rehabilitation Center for their help in collecting clinical data. We thank all children and their parents for participating in this study.

This study was approved by the Ethics Committee of the Third Affiliated Hospital of Zhengzhou University and the Medical Academy of Henan Province (201201002) in accordance with the Declaration of Helsinki. Informed consent was not essential according to the Medical Ethics Committee of the Third Affiliated Hospital of Zhengzhou University.

The authors have no conflict of interest to declare.

This study was supported by the National Natural Science Foundation of China (U21A20347), the Health Department of Henan Province (SBGJ202301009, LHGJ20190344), Swedish governmental grants to scientists working in health care (ALFGBG-965197), the Swedish Research Council (2021-01950, 2022-01019), and the Brain Foundation (FO2022-0120).

Changlian Zhu, Xiaoyang Wang, and Kate Himmelmann: conceptualization, data curation, investigation, writing review, editing, and funding acquisition. Junying Yuan: formal analysis, investigation, methodology, and writing – original draft. Menglin Cui, Jie Liu Jiefeng Hu, Shijie Ma, and Dong Li: data curation, validation, and investigation. Dengna Zhu, Jing Wang, Xuejie Wang, and Deyou Ma: resources, data curation, investigation, validation, and supervision. Yiran Xu: methodology and visualization.

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

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