Anxiety, depression, fatigue, and headache burden in the pediatric hydrocephalus population

Kathrin Zimmerman Department of Neurosurgery, Division of Pediatrics; Departments of

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Bobby May School of Medicine, University of Mississippi Medical Center, Jackson, Mississippi

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Katherine Barnes Department of Neurosurgery, Division of Pediatrics; Departments of

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Anastasia Arynchyna Department of Neurosurgery, Division of Pediatrics; Departments of

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Elizabeth N. Alford Department of Neurosurgery, Division of Pediatrics; Departments of

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Caroline Arata Wessinger Department of Neurosurgery, Division of Pediatrics; Departments of

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Laura Dreer Psychology and

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Inmaculada Aban Statistics, University of Alabama at Birmingham, Alabama; and

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James M. Johnston Department of Neurosurgery, Division of Pediatrics; Departments of

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Curtis J. Rozzelle Department of Neurosurgery, Division of Pediatrics; Departments of

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Jeffrey P. Blount Department of Neurosurgery, Division of Pediatrics; Departments of

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Brandon G. Rocque Department of Neurosurgery, Division of Pediatrics; Departments of

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OBJECTIVE

Childhood hydrocephalus is a common chronic medical condition. However, little is known about the burden of headache and psychological comorbidities in children living with hydrocephalus. The purpose of this study was to determine the prevalence and severity of these conditions among the pediatric hydrocephalus population.

METHODS

During routine neurosurgery clinic visits from July 2017 to February 2018, the authors administered four surveys to children ages 7 years and older: Pediatric Migraine Disability Assessment (PedMIDAS), Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety, PROMIS Depression, and PROMIS Fatigue. The PedMIDAS is an assessment of headache disability in pediatric and adolescent patients. The PROMIS measures are pediatric self-reported instruments to assess social and emotional health. PROMIS measures utilize T-scores (mean 50, SD 10) to compare anxiety, depression, and fatigue in specific populations to those in the US general population. Clinical and demographic data were collected from the medical record (hydrocephalus etiology, shunt infection, race, etc.) and tested for associations with survey measure scores.

RESULTS

Forty children completed the PedMIDAS. Ten percent of them were in the severe headache range, 5% were in the moderate range, and 5% were in the mild range. There was a statistically significant association between undergoing a cluster of shunt operations and headache burden (p = 0.003).

Forty children completed all three PROMIS measures. The mean anxiety score was 45.8 (SD 11.7), and 2.5% of children scored in the severe anxiety range, 17.5% in the moderate range, and 20% in the mild range. The mean depression score was 42.7 (SD 10.0), with 2.5% of children scoring in the severe depression range, 5% in the moderate range, and 12.5% in the mild range. The mean fatigue score was 45.1 (SD 16.4), with 15% percent of children scoring in the severe fatigue range, 10% in the moderate range, and 7.5% in the mild range. There were no statistically significant associations between child anxiety, depression, or fatigue and clinical or demographic variables.

CONCLUSIONS

Children with hydrocephalus have an average burden of headache, anxiety, depression, and fatigue as compared to the general population overall. Having a cluster of shunt operations correlates with a higher headache burden, but no clinical or demographic variable is associated with anxiety, depression, or fatigue.

ABBREVIATIONS

ETV = endoscopic third ventriculostomy; PedMIDAS = Pediatric Migraine Disability Assessment; PROMIS = Patient-Reported Outcomes Measurement Information System.

OBJECTIVE

Childhood hydrocephalus is a common chronic medical condition. However, little is known about the burden of headache and psychological comorbidities in children living with hydrocephalus. The purpose of this study was to determine the prevalence and severity of these conditions among the pediatric hydrocephalus population.

METHODS

During routine neurosurgery clinic visits from July 2017 to February 2018, the authors administered four surveys to children ages 7 years and older: Pediatric Migraine Disability Assessment (PedMIDAS), Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety, PROMIS Depression, and PROMIS Fatigue. The PedMIDAS is an assessment of headache disability in pediatric and adolescent patients. The PROMIS measures are pediatric self-reported instruments to assess social and emotional health. PROMIS measures utilize T-scores (mean 50, SD 10) to compare anxiety, depression, and fatigue in specific populations to those in the US general population. Clinical and demographic data were collected from the medical record (hydrocephalus etiology, shunt infection, race, etc.) and tested for associations with survey measure scores.

RESULTS

Forty children completed the PedMIDAS. Ten percent of them were in the severe headache range, 5% were in the moderate range, and 5% were in the mild range. There was a statistically significant association between undergoing a cluster of shunt operations and headache burden (p = 0.003).

Forty children completed all three PROMIS measures. The mean anxiety score was 45.8 (SD 11.7), and 2.5% of children scored in the severe anxiety range, 17.5% in the moderate range, and 20% in the mild range. The mean depression score was 42.7 (SD 10.0), with 2.5% of children scoring in the severe depression range, 5% in the moderate range, and 12.5% in the mild range. The mean fatigue score was 45.1 (SD 16.4), with 15% percent of children scoring in the severe fatigue range, 10% in the moderate range, and 7.5% in the mild range. There were no statistically significant associations between child anxiety, depression, or fatigue and clinical or demographic variables.

CONCLUSIONS

Children with hydrocephalus have an average burden of headache, anxiety, depression, and fatigue as compared to the general population overall. Having a cluster of shunt operations correlates with a higher headache burden, but no clinical or demographic variable is associated with anxiety, depression, or fatigue.

In Brief

The authors studied anxiety, depression, fatigue, and headache burden in the pediatric hydrocephalus population. This study is important because knowing the prevalence of these factors in this population provides an opportunity to potentially increase the quality of life by addressing these psychosocial comorbidities.

Hydrocephalus is the most common condition treated by pediatric neurosurgeons and the most common reason for brain surgery in children.1 There are an estimated one million people in the US with hydrocephalus, the majority of whom were diagnosed in childhood and have lived with hydrocephalus for most of their lives.2 Anecdotally, pediatric neurosurgeons have noted that children with hydrocephalus may suffer from chronic headaches more commonly than those without hydrocephalus. While headache is the most common symptom of shunt malfunction or inadequately treated hydrocephalus, it can also be present in the absence of a shunt-related problem (malfunction, overdrainage, infection, etc.). However, there are no studies that assess the burden of headache in children with hydrocephalus.

Similarly, children with chronic medical conditions can suffer from associated psychological comorbidities. The psychological and physical stress of a chronic medical condition can cause long-lasting psychosocial impact on patients and caregivers. Previous studies have examined the relationship between disease and psychological comorbidities, such as depression, anxiety, and fatigue.3–12 For example, a link has been shown between anxiety and headache in patients with chronic migraine.13 However, evaluation of the psychological comorbidities of pediatric hydrocephalus has not been performed.

The purpose of this study was to determine the prevalence and severity of headache, depression, anxiety, and fatigue in a sample of children with hydrocephalus. Understanding these factors may play a crucial role in improving the care provided to children with hydrocephalus and their families, enhancing outcomes and quality of life.

Methods

Study Setting and Population

From July 2017 to February 2018, we performed a cross-sectional analysis of headache, anxiety, depression, and fatigue in children and adolescents with hydrocephalus. Patients were enrolled during routine neurosurgical clinic visits at a large children’s hospital. Annually, the center follows over 600 patients with hydrocephalus and performs approximately 450 operations for treatment of the disorder.

Patients ages 7–21 years with surgically treated hydrocephalus, cerebrospinal fluid (CSF) shunting, or endoscopic third ventriculostomy (ETV) were eligible for enrollment. Eligibility criteria included the ability to independently complete a study questionnaire, as assessed by the patient’s caregiver and the research team. Children who did not have the maturity or mental capacity to complete the surveys were excluded. For the purposes of our research question, it was important to include only “well” children, ensuring that the headache, anxiety, depression, and fatigue symptoms reported were unrelated to potential shunt malfunction. Therefore, children who had undergone a surgical procedure for their hydrocephalus within 30 days of the clinic visit were excluded.

Data Collection

Approval for this study was obtained from the Institutional Review Board of the University of Alabama at Birmingham. Informed consent and assent were obtained as appropriate based on patient age. Study data were collected and managed using Research Electronic Data Capture (REDCap) tools hosted at the University of Alabama at Birmingham.14 Four surveys were administered to study participants: Pediatric Migraine Disability Assessment (PedMIDAS), Patient-Reported Outcomes Measurement Information System (PROMIS) Anxiety, PROMIS Depression, and PROMIS Fatigue.

Data on the social factors of caregiver age, caregiver marital status, caregiver education, child insurance status, child sex, and child race were collected from the Psychosocial Assessment Tool 2.0 (PAT), administered to caregivers on the day of the clinic visit. Clinical data on the etiology of hydrocephalus, number of shunt revisions, whether the child’s hydrocephalus was treated with ETV alone (no history of CSF shunt), gestational age at birth, distance from residence to hospital, history of shunt infection, and number of external ventricular drains in a lifetime were collected from the electronic medical record and the prospectively maintained Hydrocephalus Clinical Research Network (HCRN) institutional database.

Recognizing that shunts can fail repeatedly, we defined a new variable to capture those patients who had a history of a cluster of shunt revisions. A “shunt cluster” was defined as undergoing three or more shunt operations within a 2-month period. The purpose of the cluster variable was to capture those patients who experienced a period of frequent shunt failure and multiple operations. Furthermore, this allowed us to differentiate this group from patients who may have had a large number of shunt revisions but never a cluster of many within a short time. The cluster variable was defined prior to data collection and analysis. Prior surgical history in the electronic medical record was reviewed to identify whether a patient had an identifiable shunt cluster.

PedMIDAS

The PedMIDAS is a pediatric version (validated for ages 4–18) of the adult MIDAS survey that was created by Lipton and Stewart for adults ages 20–50 years.15,16 The pediatric survey has six questions that ask how many days out of the last 3 months a child has been incapable of performing adequately in the areas of school, sports, and home activities (such as homework or chores). Responses to the survey are added up and scored according to the PedMIDAS grading scale: score ≤ 10, little to no headache-related disability; score 11–30, mild disability; score 31–50, moderate disability; and score > 50, severe disability due to headaches. For the analysis of their relationship to clinical variables, the PedMIDAS scores were categorized into a binary outcome (little/none vs mild/moderate/severe). This cutoff was chosen because of the small number of observations with scores > 0.

PROMIS Survey

The PROMIS Anxiety, Depression, and Fatigue measures are a subset of surveys created within the HealthMeasures program through Northwestern University.17 The format of these surveys asks patients how often they have experienced certain feelings (e.g., “I felt nervous”) and asks them to assign a numerical value, with 1 indicating never and 5 indicating almost always. These instruments are scored on a T-score metric, with 50 being the mean score in the general population with an SD of 10. A score above 50 indicates a higher propensity to suffer from the symptom being measured (depression, anxiety, and/or fatigue). According to the HealthMeasures program, scores up to 0.5 SD above the mean (a score between 50 and 55) indicate mild symptoms or impairment compared to the general population. Scores 0.5 to 1.5 SD above the mean (between 55 and 65) indicate moderate symptoms or impairment, and a score higher than 1.5 SD (scaled score of 65 or higher) indicates severe symptoms or impairment.

Statistical Analysis

The PedMIDAS results and the three PROMIS measures were each analyzed for associations with categorical clinical and demographical variables using the Kruskal-Wallis test. The Spearman rank correlation was used to analyze associations between survey scores and continuous demographic and clinical variables. To investigate the association between the PedMIDAS binary outcome and the PROMIS scores, we again used the Kruskal-Wallis test. Missing clinical and demographic data are explained by the following: participant did not complete all survey measures; participant was not enrolled in the HCRN registry, so not all variables were available; and information was not available in the electronic medical record.

A p value < 0.05 was considered significant. No adjustment due to multiple testing was performed, as this study is exploratory: the intention of the study was to identify possible associations that will help determine what follow-up studies need to be conducted. All analyses were done in SAS version 9.4 (SAS Institute).

Results

Sixty patients were eligible for inclusion in the study, and 40 children consented to participate. Patients who were eligible for inclusion but chose not to participate often did so because of time constraints, as survey completion required an average of 30 minutes and frequently required staying additional time after the provider visit concluded. No subjects were excluded after data collection. Twenty patients (50%) were male and 25 (63%) were non-Hispanic white. Among the primary caregivers, 33 (87%) were at least 21 years old, 18 (47%) had received at least a college degree, and 21 (55%) were either married or partnered. The majority of the children (54%) were covered by public insurance. The most common underlying etiologies of hydrocephalus were myelomeningocele (22%) and intraventricular hemorrhage of prematurity (22%). Two patients (6%) had hydrocephalus treated with ETV alone. Seven (18%) had experienced at least one shunt infection, and 6 (15%) had experienced a cluster of hydrocephalus surgeries. A summary of demographic and clinical variables is provided in Table 1.

TABLE 1.

Summary of demographic and clinical variables in pediatric patients with hydrocephalus

VariableMedian (min, max) or No. (%)
Age in yrs (n = 39)13.5 (7, 21)
Gestational age at birth in wks (n = 32)37.5 (22, 41)
No. of procedures (n = 37)2 (1, 35)
Distance from hospital in miles (n = 36)78.75 (6.2, 202.0)
Sex (n = 40)
 Male20 (50)
 Female20 (50)
Race (n = 40)
 White25 (63)
 Non-white15 (38)
Caregiver age in yrs (n = 38)
 21 & over33 (87)
 Below 215 (13)
Caregiver education (n = 38)
 College/grad school18 (47)
 Other20 (53)
Caregiver marital status (n = 38)
 Married/partnered21 (55)
 Other17 (45)
Child insurance status (n = 37)
 Private17 (46)
 Public20 (54)
ETV alone (n = 36)
 Yes2 (6)
 No/none34 (94)
No. of clusters (n = 35)
 None29 (83)
 At least 16 (17)
Shunt infection (n = 37)
 None30 (81)
 At least 17 (19)
No. of EVDs (n = 36)
 None24 (67)
 At least 112 (33)
Etiology of HCP (n = 37)
 Aqueductal stenosis1 (3)
 IVH8 (22)
 MMC8 (22)
 Other*20 (54)

grad = graduate; HCP = hydrocephalus; IVH = intraventricular hemorrhage; MMC = myelomeningocele; n = number of cases.

Postinfectious, 2 cases; spontaneous hemorrhage, 1 case; midbrain tumor or other midbrain lesion, 3 cases; post–head injury, 2 cases; posterior fossa cyst, 2 cases; communicating congenital hydrocephalus, 8 cases; unknown, 2 cases.

Headache severity as measured by the PedMIDAS was found to have a mean score of 20.2 with an SD of 66.1 (range 0–386.0). Thirty-two participants (80%) fell into the little to no headache-related disability range. Ten percent of children scored in the severe headache range, 5% scored in the moderate range, and 5% scored in the mild range. The three PROMIS measures for depression, anxiety, and fatigue were each scored separately. The PROMIS Depression survey had a mean score of 42.7 with an SD of 10.0 (range 35.2–80.5), with 2.5% of the children scoring in the severe depression range, 5% in the moderate range, and 12.5% in the mild range. The PROMIS Anxiety survey had a mean score of 45.8 with an SD of 11.7 (range 33.5–73.0), and 2.5% of the children scored in the severe anxiety range, 17.5% in the moderate range, and 20% in the mild range. The PROMIS Fatigue survey had a mean score of 45.1 with an SD of 16.4 (range 30.3–84). Fifteen percent of children scored in the severe fatigue range, 10% in the moderate range, and 7.5% in the mild range. A summary of PROMIS and PedMIDAS scores is provided in Table 2.

TABLE 2.

Summary of PROMIS and PedMIDAS scoring

MeasureMean Score (SD)Median ScoreMin ScoreMax ScoreScores in Mild, Moderate, & Severe Ranges, No. (%)
PedMIDAS20.2 (66.1)00386Little/none: 32 (80); mild 2 (5); moderate 2 (5); severe 4 (10); total abnormal: 8 (20)
PROMIS Depression42.7 (10.0)37.835.280.5w/in normal limits: 32 (80); mild 5 (12.5); moderate 2 (5); severe 1 (2.5); total abnormal: 8 (20)
PROMIS Anxiety45.8 (11.7)41.933.573.0w/in normal limits: 24 (60); mild 8 (20); moderate 7 (17.5); severe 1 (2.5); total abnormal: 16 (40)
PROMIS Fatigue45.1 (16.4)37.930.384.0w/in normal limits: 27 (67.5); mild 3 (7.5); moderate 4 (10); severe 6 (15); total abnormal: 14 (35)

Table 3 gives a summary of the association between PedMIDAS and PROMIS scores and the clinical and demographic variables. There was a statistically significant association between PedMIDAS score and having at least one cluster of hydrocephalus surgeries (p = 0.003).

TABLE 3.

Score associations with clinical and demographic variables

Spearman Correlation or Median Score (min, max)
VariableDepressionAnxietyFatiguePedMIDAS
Age (n = 39)0.059 (p = 0.719)−0.108 (p = 0.5137)0.029 (p = 0.862)0.128 (p = 0.437)
Gestational age at birth (n = 32)0.329 (p = 0.066)0.09 (p = 0.625)0.092 (p = 0.618)0.092 (p = 0.618)
No. of procedures (n = 37)−0.051 (p = 0.763)0.22 (p = 0.191)−0.110 (p = 0.516)0.277 (p = 0.097)
Distance from hospital (n = 36)0.215 (p = 0.2077)0.292 (p = 0.084)0.128 (p = 0.457)0.024 (p = 0.890)
Sexp = 0.896p = 0.426p = 0.039p = 0.26
 Male (n = 20)37.9 (35.2, 56.1)41.3 (33.5, 70.4)34.7 (30.3, 67.1)0.0 (0.0, 386)
 Female (n = 20)37.8 (35.2, 80.5)45.0 (33.5, 64.8)47.8 (30.3, 84.0)0.0 (0.0, 12)
Racep = 0.8p = 0.81p = 0.943p = 0.687
 White (n = 25)40.6 (35.2, 53.9)42.1 (33.5, 70.4)41.3 (30.3, 77.8)0.0 (0.0, 386)
 Non-white (n = 15)35.2 (35.2, 80.5)41.7 (33.5, 62.9)35.1 (30.3, 84.0)0.0 (0.0, 50)
Caregiver age in yrsp = 0.664p = 0.794p = 0.843p = 0.758
 21 & over (n = 33)40.4 (35.2, 80.5)41.7 (33.5, 70.4)41.3 (30.3, 77.8)0.0 (0.0, 386)
 Below 21 (n = 5)41.4 (35.2, 64.5)46.4 (33.5, 53.5)35.1 (30.3, 84)0.0 (0.0, 54)
Caregiver educationp = 0.142p = 0.536p = 0.721p = 0.653
 College/grad school (n = 18)45.6 (35.2, 56.1)44.4 (33.5, 70.4)43.4 (30.3, 77.8)0.0 (0.0, 386)
 Other (n = 20)35.2 (35.2, 80.5)42.1 (33.5, 64.8)35.1 (30.3, 84.0)0.0 (0.0, 170)
Marital statusp = 0.8p = 0.917p = 0.612p = 0.06
 Married/partnered (n = 21)41.3 (35.2, 64.5)41.7 (33.5, 70.4)37.8 (30.3, 72.0)0.0 (0.0, 170)
 Other (n = 17)35.2 (35.2, 80.5)43.3 (33.5, 62.9)45.4 (30.3, 84.0)3.0 (0.0, 386)
Child insurance statusp = 0.132p = 0.489p = 0.329p = 0.304
 Private (n = 17)48.7 (35.2, 64.5)46.4 (33.5, 70.4)35.1 (30.3, 77.8)0.0 (0.0, 386)
 Other (n = 20)35.2 (35.2, 80.5)41.3 (33.5, 64.8)41.9 (30.3, 84.0)1.0 (0.0, 170)
ETV alonep = 0.601p = 0.972p = 0.777p = 0.7
 Yes (n = 2)37.8 (35.2, 40.4)46.0 (33.5, 58.6)51.15 (30.3, 72.0)15.5 (0.0, 31)
 No/none (n = 34)35.2 (35.2, 80.5)41.3 (33.5, 70.4)36.45 (30.3, 84.0)0.0 (0.0, 386)
No. of clustersp = 0.811p = 0.123p = 0.281p = 0.003
 0 (n = 29)35.2 (35.2, 80.5)38.8 (33.5, 70.4)35.1 (30.3, 84.0)0.0 (0.0, 50)
 At least 1 (n = 6)35.2 (35.2, 51.6)51.0 (33.5, 64.8)51.7 (30.3, 77.8)47 (0.0, 386)
Shunt infectionp = 0.213p = 0.15p = 0.579p = 0.303
 None (n = 30)35.2 (35.2, 56.1)39.9 (33.5, 70.4)36.5 (30.3, 84.0)0.0 (0.0, 170)
 At least 1 (n = 7)46.8 (35.2, 80.5)50.9 (33.5, 62.9)42.5 (30.3, 77.8)2.0 (0.0, 386)
No. of EVDsp = 0.942p = 0.644p = 0.99p = 0.293
 None (n = 24)37.8 (35.2, 56.1)39.9 (33.5, 70.4)36.5 (30.3, 84.0)0.0 (0.0, 170)
 At least 1 (n = 12)35.2 (35.2, 80.5)45.0 (3.5, 62.9)38.5 (30.3, 77.8)1.0 (0.0, 386)
Etiology of HCPp = 0.1p = 0.291p = 0.633p = 0.551
 Aqueductal stenosis (n = 1)35.2 (NA)33.5 (NA)30.3 (NA)0 (NA)
 IVH (n = 8)35.2 (35.2, 49.4)39.0 (33.5, 64.8)40.2 (30.3, 68.3)0.0 (0.0, 170)
 MMC (n = 8)48.2 (35.2, 80.5)49.4 (33.5, 62.9)43.4 (30.3, 64.6)2.0 (0.0, 18)
 Other (n = 20)35.2 (35.2, 51.6)39.8 (33.5, 70.4)35.0 (30.3, 84.0)0.0 (0.0, 386)

NA = not applicable.

Boldface type indicates statistical significance.

When testing PROMIS measures for associations with clinical and demographic factors, there were no statistically significant associations between depression, anxiety, or fatigue scores and any clinical or demographic factor.

Finally, we tested for associations between anxiety, depression, or fatigue, as measured by the PROMIS instruments, and headache burden (PedMIDAS). Considering PedMIDAS as a dichotomous variable (little/none vs mild/moderate/severe headache burden), headache burden was significantly associated with anxiety (p = 0.004) and fatigue (p = 0.0001). There was no correlation between headache burden and depression. These findings can be seen in Figs. 13.

FIG. 1.
FIG. 1.

Boxplot of PROMIS Anxiety scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

FIG. 2.
FIG. 2.

Boxplot of PROMIS Depression scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

FIG. 3.
FIG. 3.

Boxplot of PROMIS Fatigue scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

Discussion

We have conducted a cross-sectional study of children with hydrocephalus during routine pediatric neurosurgery clinic visits. There have been very few studies on the burden of headache in children with hydrocephalus, even though these children are thought to be at high risk for chronic headache complaints.18 In addition, this is the first study to quantify the severity of important psychological symptoms (anxiety, depression, and fatigue) in children with hydrocephalus. It is important to note that the children included in this study were attending routine follow-up clinic visits without signs or symptoms of shunt malfunction. Therefore, these results apply to children living with hydrocephalus as a chronic disease.

The PedMIDAS instrument was designed to measure the burden of disease from headaches and has primarily been used in studies of children with migraine or other types of headache. In the present study, we used the PedMIDAS as a screening tool for chronic headache in children with hydrocephalus. There is precedent for using the PedMIDAS in this way.19–21 In our sample, 20% of the children reported mild, moderate, or severe disability from headache symptoms. Our findings are similar to the burden of headache-related disability found in studies of children without chronic disease.19–21

We observed a correlation between headache burden and whether a child had ever had a cluster of shunt failures. While one possible explanation for this finding is that shunt operations increase headache burden, it is also possible that children with more headaches are more frequently evaluated and surgically treated for shunt malfunction. It is important to note that this association is based on a relatively small number of observations, and it should be considered as hypothesis generating. Further study will be required to better understand the relationship between chronic headache symptoms and number of shunt surgeries.

In this sample of children with hydrocephalus, mean scores for anxiety, depression, and fatigue were all below the population means by approximately 0.5 SDs. Of note, the SD in our sample for each of these measures was close to the expected SD of 10 (with the exception of fatigue, which was 16.4). This indicates that our sample behaved as expected for this instrument, with a slightly greater spread in the fatigue scores. The mean scores in this study are similar to mean scores on the PROMIS Anxiety, Depression, and Fatigue measures found in a study of pediatric asthma, cancer, and chronic kidney disease patients, indicating levels of psychological comorbidity in children with hydrocephalus similar to those in other chronic conditions.22 Despite reassuring mean scores for children with hydrocephalus, there were children whose scores indicated above-average levels of psychological comorbidities (20% depression, 40% anxiety, and 35% fatigue). Identifying these children may provide an opportunity to improve care delivery. In an attempt to determine risk factors for psychological comorbidities, we tested for associations between PROMIS scores and clinical and demographic variables. This testing yielded no significant association between any of the tested variables and anxiety, depression, or fatigue scores.

Finally, we observed a significant association between headache burden and two psychological variables: anxiety and fatigue. This analysis showed correlation only, so it may be that children who are more anxious then have more difficulty with headache or that a worse headache contributes to anxiety and fatigue. Further study will be required to explore these relationships in more depth. However, this association reinforces the importance of attention to psychological factors in attempts to improve overall well-being in these children.

In summary, we found a burden of headache, anxiety, depression, and fatigue in a sample of children with hydrocephalus that is similar to the burden in the general population or other samples of children without chronic disease. We hypothesized that these children would have a higher burden of headache and psychological comorbidities. Most children with hydrocephalus are diagnosed and first treated shortly after birth. Therefore, a child with hydrocephalus has never known life without the disorder. While their surgeons see the burden of their disease, it may be that they are well adjusted to life with hydrocephalus and are doing reasonably well. Nevertheless, as in any pediatric chronic condition, there may be benefit to screening for psychological comorbidities, so help can be provided where it is needed.

Study Limitations

This study has a number of limitations. The sample size was small, representing less than 10% of the children who are followed and treated for hydrocephalus at our institution. Patients were approached during a routine clinic visit, and survey completion required on average 30 minutes. Patients declined to participate because of time constraints, as enrollment in the study and completion of study measures frequently required staying additional time after the clinic visit had concluded. Nevertheless, the sampling method should have produced a relatively representative sample, and the demographic makeup of the sample was similar to that of the clinic as a whole. Moreover, this was a single-institution study. While the findings are likely generalizable to patients in our region, they may not be applicable nationally or worldwide. Further, participation in this study was voluntary; therefore, it is possible that those who chose to participate are more differentially affected than those who did not. Since all outcomes were self-reported, recall bias may be present. The PedMIDAS questionnaire asks a number of questions about headache leading to missed days of school in the last month. Therefore, administration in the summer months, when there is no school, may result in falsely low scores. Some of our sample was collected in the summer months and is therefore a limitation of our data set.

Conclusions

In this study, we performed the first formal evaluation of the burden of headache, anxiety, depression, and fatigue on children with hydrocephalus. On average, children with hydrocephalus do not have a greater headache or psychological symptom burden than their healthy peers. A higher burden of headache may be associated with having a cluster of shunt operations. Anxiety, depression, and fatigue were not significantly associated with any clinical or demographic variable. A screening program for psychological comorbidity may be warranted during routine hydrocephalus care to identify children who may benefit from additional mental health evaluation.

Acknowledgments

This work was supported by National Institutes of Health grant no. TL1 5TL1TR001418-03.

Disclosures

The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper.

Author Contributions

Conception and design: Rocque, Zimmerman, Arynchyna, Dreer. Acquisition of data: Zimmerman, May, Barnes, Arynchyna, Arata Wessinger. Analysis and interpretation of data: Rocque, Zimmerman, May, Arynchyna, Aban. Drafting the article: all authors. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Rocque. Statistical analysis: Rocque, Zimmerman, May, Aban. Administrative/technical/material support: Rocque, Arynchyna. Study supervision: Rocque, Arynchyna, Johnston, Rozzelle, Blount.

Supplemental Information

Previous Presentations

Portions of this work were presented as an oral presentation at the 2018 AANS/CNS Section on Pediatric Neurosurgery held in Nashville, Tennessee, on December 6–9, 2018, and the 2019 AANS Annual Meeting held in San Diego, California, on April 13–17, 2019.

References

  • 1

    Simon TD, Riva-Cambrin J, Srivastava R, et al. Hospital care for children with hydrocephalus in the United States: utilization, charges, comorbidities, and deaths. J Neurosurg Pediatr. 2008;1(2):131137.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Kahle KT, Kulkarni AV, Limbrick DD Jr, Warf BC. Hydrocephalus in children. Lancet. 2016;387(10020):788799.

  • 3

    Burke P, Meyer V, Kocoshis S, et al. Depression and anxiety in pediatric inflammatory bowel disease and cystic fibrosis. J Am Acad Child Adolesc Psychiatry. 1989;28(6):948951.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Cruz I, Marciel KK, Quittner AL, Schechter MS. Anxiety and depression in cystic fibrosis. Semin Respir Crit Care Med. 2009;30(5):569578.

  • 5

    Dantzer C, Swendsen J, Maurice-Tison S, Salamon R. Anxiety and depression in juvenile diabetes: a critical review. Clin Psychol Rev. 2003;23(6):787800.

  • 6

    Kellerman J, Zeltzer L, Ellenberg L, et al. Psychological effects of illness in adolescence. I. Anxiety, self-esteem, and perception of control. J Pediatr. 1980;97(1):126131.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Knight A, Weiss P, Morales K, et al. Identifying differences in risk factors for depression and anxiety in pediatric chronic disease: a matched cross-sectional study of youth with lupus/mixed connective tissue disease and their peers with diabetes. J Pediatr. 2015;167(6):13971403.e1.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Kumar S, Powars D, Allen J, Haywood LJ. Anxiety, self-concept, and personal and social adjustments in children with sickle cell anemia. J Pediatr. 1976;88(5):859863.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Mackner LM, Crandall WV, Szigethy EM. Psychosocial functioning in pediatric inflammatory bowel disease. Inflamm Bowel Dis. 2006;12(3):239244.

  • 10

    Moreira JM, Bouissou Morais Soares CM, Teixeira AL, et al. Anxiety, depression, resilience and quality of life in children and adolescents with pre-dialysis chronic kidney disease. Pediatr Nephrol. 2015;30(12):21532162.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Oguz A, Kurul S, Dirik E. Relationship of epilepsy-related factors to anxiety and depression scores in epileptic children. J Child Neurol. 2002;17(1):3740.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Vila G, Nollet-Clemençon C, de Blic J, et al. Prevalence of DSM IV anxiety and affective disorders in a pediatric population of asthmatic children and adolescents. J Affect Disord. 2000;58(3):223231.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Tomé-Pires C, Solé E, Racine M, et al. The relative importance of anxiety and depression in pain impact in individuals with migraine headaches. Scand J Pain. 2016;13:109113.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377381.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Hershey AD, Powers SW, Vockell AL, et al. PedMIDAS: development of a questionnaire to assess disability of migraines in children. Neurology. 2001;57(11):20342039.

  • 16

    Stewart WF, Lipton RB, Dowson AJ, Sawyer J. Development and testing of the Migraine Disability Assessment (MIDAS) Questionnaire to assess headache-related disability. Neurology. 2001;56(6)(suppl 1):S20S28.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Hinds PS, Nuss SL, Ruccione KS, et al. PROMIS pediatric measures in pediatric oncology: valid and clinically feasible indicators of patient-reported outcomes. Pediatr Blood Cancer. 2013;60(3):402408.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Beez T, Bellstädt L, Steiger H-J, Sarikaya-Seiwert S. Headache and shunt-related impact on activities of daily life in patients growing up with a ventriculoperitoneal shunt. J Neurol Surg A Cent Eur Neurosurg. 2018;79(3):196199.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Albers L, Straube A, Landgraf MN, et al. Migraine and tension type headache in adolescents at grammar school in Germany—burden of disease and health care utilization. J Headache Pain. 2015;16:534.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Bektaş Ö, Uğur C, Gençtürk ZB, et al. Relationship of childhood headaches with preferences in leisure time activities, depression, anxiety and eating habits: a population-based, cross-sectional study. Cephalalgia. 2015;35(6):527537.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Torres-Ferrus M, Vila-Sala C, Quintana M, et al. Headache, comorbidities and lifestyle in an adolescent population (The TEENs Study). Cephalalgia. 2019;39(1):9199.

  • 22

    DeWalt DA, Gross HE, Gipson DS, et al. PROMIS® pediatric self-report scales distinguish subgroups of children within and across six common pediatric chronic health conditions. Qual Life Res. 2015;24(9):21952208.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Collapse
  • Expand

Illustration from Aldave (pp 572–577). Images created by Katherine Relyea and printed with permission from Baylor College of Medicine.

  • FIG. 1.

    Boxplot of PROMIS Anxiety scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

  • FIG. 2.

    Boxplot of PROMIS Depression scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

  • FIG. 3.

    Boxplot of PROMIS Fatigue scores by PedMIDAS categorized scores (little/none vs mild/moderate/severe).

  • 1

    Simon TD, Riva-Cambrin J, Srivastava R, et al. Hospital care for children with hydrocephalus in the United States: utilization, charges, comorbidities, and deaths. J Neurosurg Pediatr. 2008;1(2):131137.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 2

    Kahle KT, Kulkarni AV, Limbrick DD Jr, Warf BC. Hydrocephalus in children. Lancet. 2016;387(10020):788799.

  • 3

    Burke P, Meyer V, Kocoshis S, et al. Depression and anxiety in pediatric inflammatory bowel disease and cystic fibrosis. J Am Acad Child Adolesc Psychiatry. 1989;28(6):948951.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 4

    Cruz I, Marciel KK, Quittner AL, Schechter MS. Anxiety and depression in cystic fibrosis. Semin Respir Crit Care Med. 2009;30(5):569578.

  • 5

    Dantzer C, Swendsen J, Maurice-Tison S, Salamon R. Anxiety and depression in juvenile diabetes: a critical review. Clin Psychol Rev. 2003;23(6):787800.

  • 6

    Kellerman J, Zeltzer L, Ellenberg L, et al. Psychological effects of illness in adolescence. I. Anxiety, self-esteem, and perception of control. J Pediatr. 1980;97(1):126131.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 7

    Knight A, Weiss P, Morales K, et al. Identifying differences in risk factors for depression and anxiety in pediatric chronic disease: a matched cross-sectional study of youth with lupus/mixed connective tissue disease and their peers with diabetes. J Pediatr. 2015;167(6):13971403.e1.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 8

    Kumar S, Powars D, Allen J, Haywood LJ. Anxiety, self-concept, and personal and social adjustments in children with sickle cell anemia. J Pediatr. 1976;88(5):859863.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 9

    Mackner LM, Crandall WV, Szigethy EM. Psychosocial functioning in pediatric inflammatory bowel disease. Inflamm Bowel Dis. 2006;12(3):239244.

  • 10

    Moreira JM, Bouissou Morais Soares CM, Teixeira AL, et al. Anxiety, depression, resilience and quality of life in children and adolescents with pre-dialysis chronic kidney disease. Pediatr Nephrol. 2015;30(12):21532162.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 11

    Oguz A, Kurul S, Dirik E. Relationship of epilepsy-related factors to anxiety and depression scores in epileptic children. J Child Neurol. 2002;17(1):3740.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 12

    Vila G, Nollet-Clemençon C, de Blic J, et al. Prevalence of DSM IV anxiety and affective disorders in a pediatric population of asthmatic children and adolescents. J Affect Disord. 2000;58(3):223231.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 13

    Tomé-Pires C, Solé E, Racine M, et al. The relative importance of anxiety and depression in pain impact in individuals with migraine headaches. Scand J Pain. 2016;13:109113.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 14

    Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377381.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 15

    Hershey AD, Powers SW, Vockell AL, et al. PedMIDAS: development of a questionnaire to assess disability of migraines in children. Neurology. 2001;57(11):20342039.

  • 16

    Stewart WF, Lipton RB, Dowson AJ, Sawyer J. Development and testing of the Migraine Disability Assessment (MIDAS) Questionnaire to assess headache-related disability. Neurology. 2001;56(6)(suppl 1):S20S28.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17

    Hinds PS, Nuss SL, Ruccione KS, et al. PROMIS pediatric measures in pediatric oncology: valid and clinically feasible indicators of patient-reported outcomes. Pediatr Blood Cancer. 2013;60(3):402408.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 18

    Beez T, Bellstädt L, Steiger H-J, Sarikaya-Seiwert S. Headache and shunt-related impact on activities of daily life in patients growing up with a ventriculoperitoneal shunt. J Neurol Surg A Cent Eur Neurosurg. 2018;79(3):196199.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 19

    Albers L, Straube A, Landgraf MN, et al. Migraine and tension type headache in adolescents at grammar school in Germany—burden of disease and health care utilization. J Headache Pain. 2015;16:534.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 20

    Bektaş Ö, Uğur C, Gençtürk ZB, et al. Relationship of childhood headaches with preferences in leisure time activities, depression, anxiety and eating habits: a population-based, cross-sectional study. Cephalalgia. 2015;35(6):527537.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 21

    Torres-Ferrus M, Vila-Sala C, Quintana M, et al. Headache, comorbidities and lifestyle in an adolescent population (The TEENs Study). Cephalalgia. 2019;39(1):9199.

  • 22

    DeWalt DA, Gross HE, Gipson DS, et al. PROMIS® pediatric self-report scales distinguish subgroups of children within and across six common pediatric chronic health conditions. Qual Life Res. 2015;24(9):21952208.

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation

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