Identifying Growth Hormone Deficiency in Brain-Injured Patients: The Quality of Life Scale-99

Abstract

Traumatic brain injury (TBI) is frequently associated with hypopituitarism. The hypothalamic–pituitary axis appears to be susceptible to the same forces that cause injury to the parenchyma of the brain. Following even a mild TBI (mTBI), patients may suffer transient or permanent decreases in anterior pituitary hormones, including somatotropin (growth hormone [GH]), gonadotropins (luteinizing hormone and follicle-stimulating hormone), thyrotropin, and adrenocorticotropic hormone, with the most frequent long-term deficiency being GH deficiency (GHD). GHD is common after mTBI and is often the cause of persistent post-concussive symptoms a year or more post-injury. GHD is known to cause physical and cognitive fatigue, cognitive inefficiency, metabolic changes, and a range of psychological symptoms. Confusing the picture is that some symptoms of GHD are also common to brain injury itself. To facilitate the detection of GHD when comorbid with TBI, we utilized a new symptom inventory, the Quality-of-Life Scale-99 (QoLS-99), and administered it to a cohort of chronic TBI subjects with and without GHD, distinguished using the insulin tolerance test (ITT). Between 2018 and 2023, 371 patients completed the QoLS-99, of which 263 underwent GH testing with the ITT. Of these 263 patients, 136 (52%) were diagnosed with GHD. A retrospective comparison of QoLS-99 scores found that loss of libido (p < 0.006), a reliance on sleep aids (p < 0.011), and feeling overweight (p < 0.015) were the strongest univariate predictors of GHD. Most survey items did not elicit a significant difference in response between the GHD groups, and for those that did, effect sizes were mild to moderate. Still, initial findings demonstrate strong predictive value in a subset of survey items (i.e., GHD symptoms) that are most discriminating in the sample of patients with TBI. A multivariate prediction model using this subset of questions was able to differentiate GHD status in patients with TBI, correctly identifying 88% of GHD cases with a 37% false positive rate. Based on these findings, we recommend that clinicians inquire about libido, insomnia, and body image as potential markers for GHD. Furthermore, given the amenability of patients with GHD to growth hormone replacement therapy, we strongly encourage clinicians and basic scientists to develop interventions for the large and underserved population of patients with TBI with comorbid GHD.

Introduction

The annual occurrence of traumatic brain injury (TBI) in the United States is estimated at 2.8 million per year.¹ Most of these injuries are classified as “mild” (mTBI), which, despite the implication, carries a significant risk for chronic symptoms. Fifty-three percent of patients with mTBI treated at health care centers in the United States will have persistent injury-related difficulties after 1 year.² Many struggle to resume their professional lives, leading to an estimated $17 billion per year in lost productivity.³

Chronic symptoms of TBI can be categorized into one of three functional domains: cognitive, psychological, or physical. Cognitive symptoms include impaired attention and memory, reduced processing speed, and difficulty multitasking, among many others. Psychological issues include depression, anxiety, mood lability, and irritability/anger. Physical symptoms include but are not limited to balance dysfunction, headache, hypersensitivity to sensory stimulus, and fatigue.⁴ Underlying these symptoms are pathologies that vary from patient to patient. Symptoms may be caused by neuronal (brain) injury, peripheral auditory–vestibular dysfunction, pituitary injury/hypofunction, autonomic dysfunction, and post-traumatic stress disorder. To date, successful interventions have been limited for post-concussive syndrome.⁵

Neuroendocrine derangement is likely an underdiagnosed cause of chronic disability following TBI.⁶ The hypothalamic–pituitary axis is susceptible to shear injury from forces that cause parenchymal TBI.⁷ Any damage to the pituitary stalk can result in derangement of the hypothalamic–adrenal, thyroid, gonadal, or growth hormone (GH) axes. In patients with TBI, the most frequent chronic deficiencies are seen in the GH axis,⁸ which includes GH-releasing hormone (GHRH) produced by the hypothalamus, GH by the pituitary, and insulin-like growth factor-1 (IGF-1) produced primarily in the liver but also throughout the body. GH and IGF-1 regulate each other but also act independently,⁹ mediating linear growth in childhood as well as blood glucose, fatty acid utilization, and various anabolic processes throughout life.¹⁰ Receptors for both hormones are expressed throughout the body, including various structures of the brain^11,12 where IGF-1 has a role in maintaining cerebrovascular health.^13
–15

Symptoms of growth hormone deficiency (GHD) are responsive to growth hormone replacement therapy (GHRT), which was first introduced in the 1950s for pediatric patients with GHD.¹⁶ Since then, the ongoing need for GH in adulthood has been demonstrated, leading to the recognition of adult GHD (AGHD) as well.^17,18 GHRT for the treatment of AGHD was approved by the U.S. Food and Drug Administration in 1996¹⁹ and is currently recommended in the latest guidelines of the Endocrine Society.²⁰ The relation between GHD and head trauma, however, is a relatively recent finding, with Medline showing a spike in citations in the mid-2000s.

Some degree of overlap between GHD symptoms and post-concussive syndrome^21,22 has hampered the ability to differentiate the two conditions. GHD may be a causal factor in many patients with brain injury who do not recover.²³ For such cases, GHRT may significantly improve the quality of life for many persons with brain injury and GHD.

GHD in children and adults

GHD was first recognized in the early 20th century as the cause of pituitary dwarfism, manifesting as delayed childhood growth and severely short adult stature if left untreated.^24,25 Physicians first treated the condition in the 1950s by administering replacement GH extracted from human cadavers. Upon diagnosis, replacement therapy began in childhood and involved regular administration of human GH through the completion of puberty and bone growth.¹⁶ These interventions were effective but supply-limited until the introduction of synthetic recombinant human GH (rhGH) in 1985. With rhGH available in practically unlimited quantities, widespread treatment of childhood GHD virtually eradicated pituitary dwarfism.

Despite reaching normal stature, many pediatric “graduates” of GHRT did not produce GH naturally, and discontinuation of therapy in these individuals caused a prompt return to a deficient state, accompanied by severe physiological and neurobehavioral ailments that now define AGHD.^26

–29 Some studies on AGHD expand the syndrome to include emotional reaction, social isolation, and sexual impairment as well.³⁰ AGHD was first observed in adults with congenital GHD, but the syndrome clearly affects people with adult-onset GHD caused by immune-mediated disease,³¹ pituitary adenoma, irradiation, medical interventions, and TBI.³²

GHD and brain injury

A meta-analysis of patients with TBI reporting to U.S. trauma centers found an overall GHD prevalence of 22%.³³ Emelifeonwu et al.’s (2020) meta-analysis showed a range between 2.7% and 63.6%, with the uncertainty attributable to varying research methods and conflicting definitions/thresholds of deficiency, among other reasons. Given the volume of TBIs that occur annually, even the most conservative of these estimates implies the existence of a large population of patients with TBI with undiagnosed GHD, as others have noted.^34,35

Patients with TBI with comorbid GHD have higher rates of fatigue, depression, cognitive impairment, loss of muscle mass, and gains in omental fat.³⁶ Such patients also report social isolation, sleep disturbance, and reduced quality of life at higher rates than brain-injured patients with normal pituitary function.³⁷ Depression, sleep disturbance, and social difficulties are among the most discouraging symptoms of chronic post-concussive syndrome and are risk factors for TBI-related suicide.³⁸ While the authors are not aware of a study that directly links TBI-related suicide with GHD, it is clear that these suicide risk factors—depressed mood,^27,39 sleep disorder,^27,37 and social isolation^27,37,40—are consistent with adult-onset GHD and thus may be reversible with GHRT.

Adults with GHD generally show positive physiological and psychological responses to GHRT.^41,42 A small number of studies have replicated these findings in adults with GHD secondary to TBI.^8,43
–45 In this group the benefits may be more profound; a recent analysis of longitudinal treatment studies in the Pfizer International Metabolic Database (KIMS) found that relative to pituitary adenoma patients, patients with TBI on GHRT experienced greater improvements to quality of life, particularly on measures of socialization and self-confidence.⁴⁶

Regardless of TBI history, the latest recommendation of the Endocrine Society is to offer GH replacement to adults with no contraindications and confirmed deficiency.²⁰ Although TBI is a known risk factor for GHD, universal testing of patients with TBI is not feasible. Definitive testing for GHD most often requires initial administration of a provocative agent to stimulate the pituitary to secrete GH, followed by hours of timed blood sampling under the supervision of a physician. Owing to the laborious nature of this testing, Endocrine Society guidelines recommend against testing patients for GHD without first establishing a high level of clinical suspicion.²⁰ This poses a challenge for TBI clinicians, who must raise this suspicion on the basis of symptoms, wherein there may be considerable overlap between GHD and other TBI sequelae.^21
–23

A questionnaire that assesses AGHD symptoms was introduced and validated in 1999.²⁸ It was formed through conversations and pilot studies on adults who had been treated for GHD as adolescents and on adults who had acquired GHD following surgical interventions involving the pituitary gland. To date, there exists no such validated instrument to flag GHD in patients with TBI. In the TBI population, this instrument would have the additional burden of identifying GHD amid other chronic (>1 year) TBI sequelae with significant overlap of symptoms. However, the benefit of such an instrument is undeniable, since GHD has a high prevalence in TBI and treatment with rhGH would represent a major advance for a condition (i.e., TBI) currently lacking effective treatment options. Prescreening patients with a sensitive, TBI-specific instrument would improve the cost–benefit ratio of invasive GH stimulation testing.

A survey instrument to assess GHD with comorbid TBI

To investigate the symptomatology of TBI with and without comorbid GHD and ultimately create a screening instrument, the authors used the Quality-of-Life Scale-99 (QoLS-99). The QoLS-99 is a 99-item survey intended to probe previously reported symptoms of GHD as well as candidate symptoms based on clinical observation of patients with TBI treated for GHD over a 10-year period. Based on our clinical experience and the growing body of research on TBI-comorbid GHD, we hypothesize that GHD can be differentiated from other TBI sequelae using this subjective, symptom-based instrument.

Methods

A cross-sectional study was carried out on the incidence and symptoms of GHD in a clinical sample of 371 patients with TBI with persistent symptoms at least 1 year post-injury. Most of the subjects were involved in litigation and had been referred for medical or medicolegal evaluation at two Detroit metropolitan area clinics. Incoming patients were required to obtain a negative COVID-19 test within 2 weeks of their appointment. Prior to clinical examination, patients were asked to complete the QoLS-99 along with the Assessment of Growth Hormone Deficiency in Adults (AGHDA).⁴⁷ Based on the results of clinical evaluation and AGHDA scores, patients suspected of GHD were referred for GH stimulation testing with the insulin tolerance test (ITT). Items on the QoLS-99 that correlated with deficiency were then used to construct a multivariate, predictive, symptom-based model of deficiency.

Insulin-induced hypoglycemia test

In patients suspected of GHD, pituitary function was evaluated using the insulin-induced hypoglycemia test, also referred to as the ITT, the gold standard for assessing GHD.⁴⁸ An initial blood sample was taken to measure baseline blood glucose and GH serum concentration. This was followed by IV administration of 1 unit (30 µg) of insulin. Blood samples were taken at 30–45-min intervals until symptoms of hypoglycemia emerged or blood glucose concentration went below 40 ng/mL. Additional units of insulin were administered until one of these conditions was met. Patients were identified as “GHD” if they met the following criteria:

Confirmation of insulin-induced hypoglycemia. This was identified by the emergence of symptoms or a serum glucose concentration under 40 ng/mL.

Adequate sampling of GH to capture its dynamic response to hypoglycemia.

Peak serum GH concentration <5 ng/mL.

The first two criteria indicate a valid test, and the third indicates deficiency. Using a threshold serum concentration of 5 ng/mL, patients who underwent bioassay were categorized as “growth hormone-normal” (GHN) or “GHD”. If hypoglycemia was not successfully induced or if the temporal GH response was poorly captured due to sampling issues, the testing was considered invalid, and the subject was excluded from the study.

Survey

The QoLS-99 is a 99-item, 11-point response survey consisting of six sections differentiated by functional domain (cognitive, affective, and physical), with each domain subdivided into “positive” questions gauging patient satisfaction and “negative” questions gauging levels of dissatisfaction. The survey includes 40 “positive” questions and 59 “negative” questions, each querying the patient for an integer response from 0 to 10, inclusively. A composite score is then taken as the sum of all responses, counting responses to the “negative” questions as negative values. Consequently, the possible scores range from −590 to +400. The complete set of questions is given in Supplementary Appendix SA1. All patients arriving at the study sites during the study period were given the QoLS-99.

Brain imaging

Group differences in extent or type of brain injury were considered as a possible covariate of deficiency state. Most of the study subjects had a multi-sequence brain magnetic resonance imaging (MRI) as part of their evaluation. Results of susceptibility weighted imaging (SWI) and diffusion tensor imaging (DTI) were used to assess and code intracranial hemorrhage and diffuse axonal injury, respectively. SWI results were coded as the presence or absence of intracranial hemorrhage/microhemorrhage. DTI imaging was used to measure fractional anisotropy (FA) of the brain white matter.

FA measurements were coded by two metrics, both in reference to a set of 49 healthy control subjects scanned on the same machine (Siemens Magnetom 3T Trio). The first metric was an individual’s age-corrected global white matter FA percentile. The second FA metric used is the number of atlas-defined white matter regions⁴⁹ (out of 50) where the mean FA was below that of its corresponding region in the control group.

The chi-squared test was used to compare the incidence of intracranial hemorrhage between study groups (GHD, GHN, and TBI Control). The Mann–Whitney U test was used to test the relationship between FA measures (global and regional) and GH status.

TBI severity

Emergency medical personnel often monitor acute symptom progression using the Glassgow Coma Scale (GCS). The GCS is an integer scale (3–15) classification system that assigns points based on patients’ eye movement, verbal coherence, and motor response immediately after a head injury. Injuries are classified as mild, moderate, or severe based on threshold scores. Two additional categories are included for this analysis: “unknown” for patients without sufficient documentation to indicate TBI severity and “non-traumatic” for patients with no history of closed head injury (but who do have a history of electrical injury, hypoxia, or surgical intervention). Although the GCS was designed to assist in managing the acute phase of injury, attempts have been made to correlate the metric with long-term pituitary outcome, with mixed results.⁵⁰ One obvious limitation of these correlations is that GCS is usually coded by unnamed emergency personnel, likely without concern for data integrity. However, the authors recognize TBI severity as a potential predictor for long-term pituitary outcome and include the metric in this report. TBI severity was tabulated using GCS scores obtained from patients’ emergency medical records. If these records were not available, TBI severity was assessed retroactively through clinical interviews with the patient.

Participant selection

All study participants were over the age of 18, presented to one of the two clinics during the study period with a history of brain injury, and completed the QoLS-99. Subjects were excluded from the study if they were referred for GH testing but did not obtain reliable results from the ITT.

From October 2018 to September 2022, 371 patients (180 female, 191 male) aged 18–80 (median = 44 years) were seen at the two clinics. All subjects were seeking treatment for a remote injury at least 1 year post-injury, with a median time of 2.2 years between the causal event and presentation to the clinic. Mechanisms of injury included motor vehicle accidents (68%), blunt force trauma (10%), falls (10%), athletic injuries (4%), and hypoxic injury (2%). Twenty-seven individuals were excluded from the study for lack of valid ITT results (n = 16), absence of brain injury (n = 10), and one subject was excluded for being underage (n = 1).

In total, 232 of the patients had AGHDA scores >8 and were suspected of GHD by the PI following clinical evaluation. Additionally, six patients had AGHDA scores ≤8 but were nonetheless suspected of GHD based on further clinical evaluation. All 238 of these patients were referred to an endocrinologist for pituitary hormone testing via the ITT. Patients were categorized as GHN or GHD based on ITT results.

Clinical suspicion of GHD was an inclusion criterion for all patients in both the GHD and GHN groups. Only 6 of these patients (3 GHD, 3 GHN) scored ≤8 on the AGHDA. Consequently, the QoLS-99 responses of both groups were expected to skew towards negative/GHD-symptomatic scores. Therefore, a third group was selected to represent the symptom burden of patients with TBI whose symptoms were least suggestive of GHD. This group, “TBI control” (n = 36), was selected from the patients who were not referred for endocrine testing, whose clinical symptoms did not suggest GHD, and whose AGHDA score was ≤13. The revision to the survey’s threshold score (≤8) was necessary to select a large enough sample. The specific cutoff value (≤13) was found by maximizing the survey’s ability to differentiate GHN from patients with GHD. The QoLS-99 was also administered to a group of 49 healthy volunteers recruited via social media and selected to match the income, education, race, age, and gender demographics of the 2010 U.S. Census. The online signup form included a self-disclosure of significant medical conditions, which was used to select a sample of presumed “healthy” candidates. Volunteers were blinded to the inclusion criteria and screened by phone to reaffirm their responses to the online signup form. Subjects who were deemed healthy were then directed to complete the QoLS-99 survey online and subsequently paid.

Results

Of the 238 patients tested for GHD, 138 (58% of those tested, or 37% of all patients seen) had a valid ITT test showing a peak GH serum concentration below 5 ng/mL. These patients were diagnosed and categorized as “GHD.” In total, 85 patients had a valid ITT test with at least one GH titer in excess of 5 ng/mL, indicating a “normal” GH response. These patients were categorized as “GHN.” In total, 15 patients were removed from the study due to unreliable ITT test results.⁵¹

The structural imaging results were similar across patient categories. Patients with GHN had a higher prevalence of hemorrhage (20%) than patients with GHD (9%), with TBI controls falling in between them at 18%. DTI metrics were similar among the GHD, GHN, and TBI control categories. In both metrics used (global fractional anisotropy and regional fractional anisotropy) and across all patient categories, DTI results fell within one standard deviation of the value expected in a sample of healthy control subjects.

Injury severity was categorized as mild, moderate, severe, unknown, and non-traumatic. These categories were similarly represented in both GHD and GHN categories, and the chi-squared test found no significant association (p = 0.80) between the two variables.

Table 1 shows sample characteristics of three comparison groups—GHD, GHN, and TBI control.

Table 1.

Sample Characteristics of Three Comparison Groups

	GHD (n = 123)	GHN (n = 85)	TBI control (n = 38)	p-Value(Kruskal–Wallace)
Age, years, (median ± SD)	41 (± 16)	45 (± 16)	48 (± 18)	0.3
Time from injury to evaluation, years, (median ± SD)	1.8 (± 6.7)	2.6 (± 4.2)	2.2 (± 9.4)	0.27
Sex
Male	67 (55%)	44 (52%)	18 (47%)	0.86
Female	55 (45%)	41 (48%)	20 (53%)	0.86
TBI severity
Mild	100 (82%)	70 (82%)	32 (84%)	0.66
Moderate	0 (0%)	1 (1%)	0 (0%)
Severe	5 (4%)	4 (5%)	3 (8%)
Unknown	13 (11%)	9 (10%)	1 (3%)
Ischemic/hypoxic injury	4 (3%)	1 (1%)	2 (5%)
Imaging
Hemorrhage (SWI)*	11 (9%)	17 (20%)	7 (18%)	0.74
Global FA**	58 (± 40)	64 (± 40)	43 (± 41)	0.67
Regional FA***	27 (± 14)	22 (± 16)	31 (± 15)	0.24

Hemorrhage is defined as the presence (or non-presence) of brain hemorrhages based on susceptibility weighted imaging (SWI).

Global FA is defined as the median global fractional anisotropy percentile relative to 50 control subjects.

***

Regional FA is defined as the median number of predefined regions (out of 50) with local FA falling below the mean value of corresponding regions among 50 control subjects.

FA, fractional anisotropy; GHD, growth hormone deficiency; SD, standard deviation; SWI, susceptibility weighted imaging; TBI, traumatic brain injury.

Sensitivity of QoLS-99 to GH status

Composite scores demonstrated a stepwise response across patient categories. The mean GHD score was −174, significantly lower than the mean GHN score of −117 (p = 0.008). TBI control patients had a mean composite score of 89, and non-TBI controls had a mean composite score of 105. A comparative chart of composite scores by patient category is given in Figure 1. Similar charts comparing sub-scores for each QoLS-99 subcategory (cognition, affect, and physical) are given in Supplementary Appendix SA2.

FIG. 1.

Quartile plot showing QoLS-99 composite scores across comparison group. Composite scores are calculated by taking the difference in sums of positive and negative response scores across the entire survey. Outliers are plotted with a circle. QoLS-99, Quality-of-Life Scale-99.

QoLS-99 item analysis, factor analysis, and predictive modeling

Composite scores of the QoLS-99 demonstrated sensitivity to GH status. However, although patients with GHN had significantly higher scores than patients with GHD (p = 0.008), there was a high level of overlap between the groups. Discrimination of GH-status using a QoLS-99 composite score would have a poor sensitivity/selectivity tradeoff, as demonstrated in Figure 1. Toward improving the discriminating power of the survey, an item analysis was conducted on the QoLS-99.

Item analysis

Groupwise median and mean response scores were calculated for each question. For 52 out of 99 questions, median response scores for the GHD group showed lower satisfaction, or higher level of difficulty, compared with the GHN group. The median response of the two groups was equal to 43 of 99 questions. For 4 of 99 questions, a paradoxical but not significant result was obtained, where patients with GHD reported higher satisfaction than patients with GHN. For each question, the difference in median response was tested using the Mann–Whitney U test, a nonparametric significance test suitable for ordinal data comparisons. p-Values and effect sizes were calculated. Sixteen (16) of the 99 items showed significant (p < 0.05) group differences. Test statistics for these items are given in Table 2. See Supplementary Appendix SA1 for statistics on all 99 items.

Table 2.

Test Statistics for Discriminative Survey Items

Survey item	GHD_n	GHD_med	GHN_n	GHN_med	U	p	Effect size
76. Libido or sex drive	120	3	81	4	3740.5	0.005	0.20
81. Needed pills to get to sleep	119	5	81	1	5813	0.010	0.17
48. Feeling overweight	120	7	81	4	5842	0.014	0.17
30. Getting along with people	122	5	81	6	3947.5	0.015	0.17
33. Engaging in hobbies	122	3	81	4	3977.5	0.018	0.16
29. Feeling relaxed and at peace	122	3	81	4	4008	0.022	0.16
19. Foggy thinking	122	7	83	6	6010.5	0.022	0.16
24. Joy	121	4	83	4	4090.5	0.024	0.16
25. Passion	121	3	83	4	4115.5	0.028	0.15
61. Feeling watched or listened to by others	122	4	80	2	5714	0.036	0.14
55. Irritability with people	121	7	80	6	5675.5	0.037	0.15
93. Shortness of breath with little exertion	120	5	81	3	5682.5	0.040	0.14
32. Desire to go on vacation	121	4	81	6	4070	0.040	0.14
42. Feeling lonely	122	6	81	5	5757	0.045	0.14
53. Agitation	121	7	80	7	5640.5	0.045	0.14
2. Short term memory (recent)	122	3	83	4	4247	0.048	0.14

GHD, growth hormone deficiency; GHN, growth hormone-normal.

The 16 “differentiating” questions listed in Table 2 consist of 8 “positive” questions framed as level of satisfaction and 8 “negative” questions framed as level of difficulty. Median GHD scores were significantly “worse than” median GHN scores for each of these items. Group response means for those items are given in Figure 2A (satisfaction items) and Figure 2B (difficulty items).

FIG. 2.

(A) Group response mean values for differentiating QoLS-99 items across patient categories (positive questions). (B) Group response mean values for differentiating QoLS-99 items across patient categories (negative questions). QoLS-99, Quality-of-Life Scale-99.

Factor analysis

Factor analysis was performed on the 16 survey items identified as discriminatory from item analysis. GHD, GHN, and TBI control patients were included in this analysis. Eight patients (6 GHN, 2 GHD) were excluded because >50% of their survey responses were blank. The resultant matrix of 16 variables over 231 observations satisfied Bartlett’s test of sphericity⁵² and the Kaiser Meyer-Olkin test for sampling adequacy.⁵³ Scree plotting using the “elbow” method⁵⁴ indicated the retention of two factors.

A promax rotation was used to transform the 16-question matrix into two factors. Negative (complaint) questions loaded onto the first factor, and positive (satisfaction) questions loaded onto the second. These factors were labeled negativity and positivity. Four questions loaded onto both factors. They were removed, and the transformation was repeated.

Inferring GH status using QoLS-99 responses

Following factor analysis, the matrix of 231 patient observations across 12 questions was transformed into two independent variables (labeled “negativity” and “positivity”) with GHD status as the binary dependent variable. In total, 75% of the data were used to fit a 2-variable logistic regression. The resultant model was tested for sensitivity and specificity in the remaining 25% of the data. Performance is shown in Figure 3.

FIG. 3.

Receiver operator curve for logistic regression based on QoLS-99 response. QoLS-99, Quality-of-Life Scale-99.

To summarize, an Area Under the Curve (AUC) of 0.74 was achieved by applying variable reduction methods to the set of questions that individually predicted GHD. In terms of the projected clinical value of this approach, 88% of patients with GHD were correctly identified when accepting a 37% false positive rate.

Discussion

In the current study, 137 out of 345 (37%) patients with chronic TBI were demonstrated to have GHD. This rate exceeds a recent TBI-induced GHD prevalence estimate of 22.1% [16.0–28.1], obtained from an independent assessment of 12 high-quality studies.³³ This discrepancy is likely due to sampling differences. Unlike Emelifeonwu’s meta-analysis, the current study is not a random sampling of the population of TBI survivors. It is instead representative of chronic, largely mild, TBI survivors who have symptoms severe enough to form the basis of a lawsuit. Nonetheless, this finding (i.e., 37%) indicates that more than one-third of patients with ongoing symptoms following closed head injury have a treatable cause of at least some of their symptoms. Given the absence of effective treatments for brain injury,⁵⁵ which is a permanent injury, this is an encouraging finding and one that should serve as a catalyst for more broad-based screening of symptomatic patients with TBI at the 1-year mark or thereafter.

Although the sample consists primarily of patients with TBI, five patients in the GHD group had no history of closed head injury. These subjects had been referred to the clinics with a history of hypoxia (three), electrical shock (one), and Wernicke–Korsakoff syndrome (one). The presence of GHD in these cases points to additional causes of acquired GHD beyond sheering of the pituitary axis as seen during closed head injury.⁷ Therefore, history of closed head injury should not be taken as a prerequisite for GHD screening.

QoLS-99: Performance and key findings

Attempts to identify questionnaire items (and, by extension, predictive symptoms) that discriminate GHD status between the TBI groups had mixed results. Most items on the QoLS-99 exhibited sensitivity to GH status. TBI controls were least symptomatic, followed by patients with GHN, followed by patients with GHD. Predictably, the TBI control group responses were well-differentiated from both patients with GHN and patients with GHD. Between patients with GHD and patients with GHN (the two groups referred for hormone testing), patients with GHD had equivalent or worse (i.e., more symptomatic) scores than patients with GHN for 95 of 99 items, with 14 items reaching statistical significance. “Libido or sex drive” and “feeling overweight” were the most discriminative items.

Although cumulative scores of the QoLS-99 were significantly higher in patients with GHN than patients with GHD, summing the QoLS-99 items (or its three subsets) to a composite score did not reliably discriminate GHD from GHN (see Supplementary Appendix SA2 for quartile scores by subsection). The best discrimination was achieved by using only the 16 most sensitive survey items, applying variable reduction methods, and fitting the resultant matrix to a logistic regression that showed 88% sensitivity at a 37% false positive rate (see Fig. 3).

Key symptoms of GHD after brain injury

Questionnaire items about libido, reliance on sleep aids, feeling overweight, and difficulty socializing elicited the most significant differences between patients with GHD and patients with GHN. This is consistent with a similar study on patients with TBI, which found GHD to be the most common hormone deficit among patients with TBI screened for symptoms of hypopituitarism.⁴⁸ Sexual difficulties, sleep disturbances, and emotional lability are fairly common symptoms of TBI, each occurring with 15–45% incidence⁵⁶ at some stage following TBI. Weight gain is observed in roughly 40% of patients with TBI and likely has several causes,⁵⁷ while increased body fat is well described in GHD. There is relatively little research on the association of GH deficiency and libido, while there is some research on sexual dysfunction in association with GHD.⁵⁸

Libido

Libido was the most sensitive item to GHD on the QoLS-99. In their endocrine study on patients with TBI with and without hypopituitarism symptoms, Cuesta et al. found that symptoms of gonadal dysfunction in men and women, particularly erectile dysfunction in men and amenorrhea in females, were predictive of GHD (M: 33%, F: 50%) along with deficiency of Gonadotropin (GT) (M: 58%, F: 60%) and Adrenocorticotropic hormone (ACTH) (M: 33%, F: 90%).⁵⁸ Although loss of libido is related to erectile dysfunction, it is less specific. Sexual interest has been associated with depression secondary to TBI, independently of endocrine disorder.⁵⁹ The QoLS-99 does not explicitly differentiate between sexual interest and sexual dysfunction and may potentially aggregate these complaints under a single survey item. Improvements in questionnaire sensitivity might be achieved by adding sex- and age-specific questions regarding sexual QoL.

Insomnia/reliance on sleep aids

Needing medication to get to sleep was the second most discriminating predictor of GHD. While this result does not imply that GHD causes sleep issues, the involvement of the GH axis in regulation of onset and maintenance of sleep has been well documented in humans^60

–63 and in rats by Obál and colleagues using GHRH^64

–67 secreted by the hypothalamus, promoting non-rapid eye movement sleep. GHRT has been reported to improve fatigue and quality of sleep in adults with GHD.⁶⁸

Feeling overweight

The third most sensitive question reflected self-image regarding body weight. Adverse morphological changes, that is, increased omental fat and decreased muscle mass, are well established clinical features of adult-onset GHD^69,70 as is diminished self-image.²⁷ These findings replicate the findings in the literature but raise the question of whether the negative self-image is proportionate to the actual weight gain or independent of it.

Getting along with people

A small but significant effect was observed between patients with GHD and patients with GHN on this item. Social isolation and emotional reactivity have been demonstrated as symptoms of both adult-onset GHD,³⁰ and independently in TBI.³⁸ As McIntire et al. found, social isolation (along with sleep disturbance) are moderate predictors of TBI-related suicide, so amelioration of these issues with rhGH is desirable. Further research is needed to confirm these benefits.

Study limitations

The selection of comparison groups was a key consideration for this study. The ideal comparison groups would be sets of patients with TBI with and without GH deficiency, established by bloodwork alone, with researchers blinded to symptoms. Symptoms could then be assessed as a truly independent variable. Unfortunately, this approach would require universal provocative testing of patients with TBI, which was not feasible due to cost.

The subjectivity of the QoLS-99 exposes the survey to various factors independent of GHD status. For instance, the fact that the study participants were in litigation potentially biased all respondents towards more negative or “dissatisfied” responses. Caution is warranted when applying these results to patients without litigation stress. Conversely, there are other socioeconomic factors common to TBI survivors that may skew the QoLS-99 differently. These include intimate partner violence (IPV), military service, and athletic pressures, for example.

Another QoL stressor may have been COVID history; from July 2020 through completion of the study, all participants were screened for COVID-19 within 2 weeks of their visit. This would prevent acute COVID-19 symptoms from influencing the data but would account for neither long COVID symptoms nor the economic and social conditions created by the COVID-19 pandemic. However, there is no reason to believe that either of these stressors favored one group of patients over another, and it is likely that COVID status and litigation stress contributed noise rather than systemic bias. This would lead to more conservative results (fewer questions found to be significant) and was thus acceptable to the authors.

Future research

The QoLS-99 is under development as a clinical instrument that pre-screens chronic (>12 months) patients with TBI for definitive endocrine testing. The next effort is to refine the QoLS-99 into a more sensitive and specific clinical instrument, using the results presented as well as further consideration of the survey design. As part of this effort, the authors intend to test the survey in different clinical populations (i.e., athletes, survivors of IPV) to overcome sampling limitations and develop a robust, universal instrument.

As others have noted, GHD is the most common TBI-related hormonal deficit but not the only pituitary hormone relevant to TBI. Indeed, it is likely that the adrenal and gonadal axes are also factors in quality of life one year after TBI. The effort to refine the QoLS-99 will consider all anterior pituitary hormones.

Ultimately, we will undertake a longitudinal GH treatment study on patients with TBI, using the revised QoLS-99, along with broad neuropsychiatric testing to assess treatment response. Given the high prevalence of TBI (and secondarily, GHD), this study may demonstrate that substantial reductions to the global disease burden of TBI are achievable.

Conclusion

This study reinforces previous estimates of GHD prevalence in patients with TBI (37% among chronic patients). More importantly, it suggests that several TBI symptoms such as libido, weight gain, and sleep disruption may be attributable to GHD and other pituitary derangements. If that is the case, then GHD is clearly an overlooked outcome of TBI. Awareness of GHD post-TBI has increased in recent decades, and there have been calls to implement more endocrine screening for TBI. This study observed a 37% GHD prevalence in a sample consisting overwhelmingly of patients with mTBI in the chronic stage. Since there is a poor correlation of GHD incidence with injury severity, GHD should be considered in all cases of TBI, particularly in patients with poor quality of life.

The symptoms of GHD appear to be counter to thriving and, while not life-threatening per se, in the aggregate, result in a much-reduced quality of life. Given that brain injury alone reduces quality of life, identification of hypopituitarism affords the clinician the opportunity to significantly improve the lives of patients who rely on clinicians to parse what is treatable from what is not.

Transparency, Rigor, and Reproducibility Statement

This study was not formally registered because it is a convenience sample drawn from archived clinical records. The analysis plan was not formally pre-registered, but the supervising author, R.B., certifies that the analysis plan was pre-specified. During the study period, 371 patients reported to one of the study clinics and completed the QoLS-99, a 99-item, 11-point response symptom inventory prior to intake. In total, 236 of these patients were clinically suspected of GHD and assayed via the ITT. Using a serum concentration threshold of 5 ng/mL, 123 subjects were found to be GHD, 85 subjects were found to be “GHN,” and 29 subjects were excluded based on invalid bioassay or absence of brain injury. Of 135 patients not referred for the ITT, 36 had AGHDA scores below 14 and were assigned to the “TBI control” group. The QoLS-99 was also administered online to a non-clinical sample of 49 healthy individuals recruited on social media. The Mann–Whitney U test was used to evaluate composite survey scores between GHD and GHN groups. The Mann–Whitney U test was also used to test individual survey items for sensitivity to GHD status. Factor analysis was performed on the subset of survey items that elicited significant (p < 0.05) response differences between GHN and GHD groups. The extracted factors were used to construct a multivariate logistic regression using the truncated survey responses to predict the GH category. The regression model was trained on responses from the GHD, GHN, and TBI control subjects (who are presumed to be GHN), using 75% of the sample to train the model and the remaining 25% to test its performance. Results of this study are part of an ongoing effort to refine the QoLS-99 before further validation.

Footnotes

Acknowledgment

The authors acknowledge Elina Dalaly and Cristi D’Angola for their administrative contributions to this research.

Authors’ Contributions

S.B.: Data curation, formal Analysis, writing—original draft preparation, and visualization. R.B.: Conceptualization, methodology, writing—reviewing and editing, and supervision. V.B.: Conceptualization. R.G.: Investigation. O.A.: Investigation.

Author Disclosure Statement

The author(s) have no competing interest to disclose.

Funding Information

There was no funding provided for this research.

Supplementary Material

Supplementary Appendix SA1

Supplementary Appendix SA2

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