Idiopathic hypersomnia symptoms over Time: Longitudinal follow up from the Hypersomnia Foundation registry.

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Published in final edited form as: Sleep Med. 2025 Jun 1;133:106627. doi: 10.1016/j.sleep.2025.106627 Idiopathic Hypersomnia Symptoms Over Time: Longitudinal follow up from the Hypersomnia Foundation Registry Audrika Chattaraj 1 , Amanda A Freeman 2 , Kendall J Nichols 3, 4 , Jason C Ong 5 , David T Plante 6 , Prabhjyot Saini 7 , Catherine Friederich Murray 8 , Rebecca King 9 , Donald L Bliwise 3, 4 , Lynn Marie Trotti 3, 4, * Author information Article notes Copyright and License information 1 Emory University, Atlanta, GA USA 2 Center for the Study of Human Health, Emory University, Atlanta, GA USA 3 Department of Neurology, Emory University School of Medicine 4 Sleep Center, Emory Healthcare, Atlanta, GA USA 5 Director of Behavioral Sleep Medicine and Clinical Science, Nox Health, Inc, Atlanta, GA USA 6 Department of Psychiatry, University of Wisconsin Madison, WI USA 7 Department of Human Genetics and Montreal Neurological Institute, McGill University, Montreal, Quebec Canada 8 prior Founding Board member, Hypersomnia Foundation, Atlanta, GA USA 9 current Board member, Hypersomnia Foundation, Atlanta, GA USA * Corresponding Author: 12 Executive Park Dr NE, Atlanta, GA 30329, Lbecke2@emory.edu , (404) 712-8145 (fax) Issue date 2025 Sep. PMC Copyright notice PMCID: PMC12335360  NIHMSID: NIHMS2088052  PMID: 40472564 The publisher's version of this article is available at Sleep Med Abstract Introduction: Limited data are available regarding the long-term course of idiopathic hypersomnia. We analyzed longitudinal data from the Hypersomnia Foundation Registry at CoRDS to evaluate changes in symptoms and medication usage over time. Methods: Registry participants reporting a diagnosis of idiopathic hypersomnia were included if they completed the registry questionnaire at least twice, with at least six months before first and last questionnaire. Responses were analyzed using paired t-test for continuous variables and McNemar test for categorical variables, comparing first and last responses. Results: Data from three hundred twenty-three participants were included, with a mean age 35.0 +/− 12.2 and 86.5% women. Average time between first and last response was 2.4 +/− 1.4 years. Symptoms remained largely stable over the 2 ½ year period, with persistent difficulty awakening (in 78.7% at baseline and 73.0% at follow up), daytime sleepiness (62.7% and 61.8%), trouble waking up and functioning with normal alertness (56.4% and 56.4%), requiring multiple alarms (53.4% and 55.3%), brain fog (46.3% and 48.4%), and memory problems (42.7% and 43.4%). Average nightly sleep duration on workdays and non-workdays and average nap duration were all stable over time. Participants made an average of 0.8 (+/− 1.1) medication changes, with most (55.4%) participants remaining on the same medications. Comorbid mood disorders were relatively common, with a modest increase in anxiety diagnoses. Conclusions: Symptoms of idiopathic hypersomnia remained relatively stable over an average of 2.4 years of follow up. Despite persistent symptoms being experienced by the majority of participants, medication changes were infrequent. Keywords: idiopathic hypersomnia, natural history, longitudinal, patient registry, treatment Introduction: Idiopathic hypersomnia (IH) is a chronic neurological disorder characterized by excessive daytime sleepiness, difficulty awakening, long sleep durations, and brain fog/cognitive problems ( 1 ). There is no consensus on pathophysiology and definite, biologically based diagnostic criteria for IH are not yet available ( 2 ). There are several proposed mechanisms for the pathophysiology of IH. These include enhanced GABA-A receptor activity ( 3 ), circadian system dysregulation ( 4 – 6 ), autonomic dysfunction ( 7 , 8 ), and altered functional connectivity or regional brain activity ( 9 – 12 ), although consistent results have not been found across all investigations into these potential mechanisms ( 13 – 15 ). Current treatments work primarily to manage symptoms of excessive daytime sleepiness rather than reducing all symptoms of IH ( 16 ). There are several medications that have shown improvements in symptoms for IH participants in moderately-sized clinical trials, such as calcium, magnesium, potassium, sodium oxybate ( 17 ) and modafinil ( 18 , 19 ), and clinical series or smaller trials suggest benefit of stimulants (methylphenidate and amphetamines), clarithromycin, and flumazenil ( 20 – 23 ). However, these studies have usually not examined the impact of pharmacological interventions on longitudinal symptoms for long durations. Furthermore, because a single sleep center may have few patients with IH, many clinical studies of IH are composed of fewer than 100 participants. Web-based registries expand the diversity and scope of data collection for physical signs, symptoms, and physiological changes in participants, particularly for rare conditions ( 24 ). Registries have the potential to create a generalizable data set that may track symptoms and outcomes of clinical interventions ( 25 , 26 ). Registry data have been used to study rare conditions such as sarcoidosis and neurofibromatosis, as well as common conditions such as chronic back pain or multiple sclerosis ( 27 – 30 ). Our previous registry-based study of IH reported the frequency of symptoms and the experience of people with IH in a large cohort, using data from a single timepoint per participant ( 31 ). To expand the body of knowledge of phenotypic information of IH to a longitudinal setting involving a greater number of participants, the present study evaluated changes over time in participants in this registry. The aims of this study were to 1) analyze longitudinal changes in symptoms in a large population of IH participants, and 2) understand changes in medication usage and their real-world effectiveness. Methods: Hypersomnia Foundation Registry The Hypersomnia Foundation, a nonprofit organization for people with IH and related disorders ( hypersomniafoundation.org ), launched an online patient registry in 2016, as previously described ( 31 ). The registry is hosted in partnership with the Coordination of Rare Diseases at Sanford (CoRDS, Sanford Research, Sioux Falls, South Dakota; cords.sanfordresearch.org ). Participants were recruited by the Hypersomnia Foundation through online advertisements, presentations at patient meetings, and fliers placed in physician offices. After providing informed consent, participants completed the registry questionnaires via the CoRDS online platform or by mail and were encouraged to complete the registry questionnaires annually. Questionnaire responses from June 2016 through June 2023 were eligible for inclusion. Coded data without any identifiers were obtained from CoRDS. This study was approved by the Institutional Review Boards of Sanford/CoRDS and Emory University. Inclusion Criteria & IH diagnosis validation Although the Hypersomnia Foundation registry is open to participants with any central disorder of hypersomnolence, the majority of participants report diagnoses of IH. Thus, for these longitudinal analyses, only participants with IH were included, meeting the following criteria: Diagnosed with IH. Completed the registry questionnaires at least twice. At least 6 months of time elapsed between first and last completion of registry questionnaires. The diagnosis of IH was validated within the registry as previously described ( 31 ). This was a multi-step diagnosis validation process. First, participants had to select IH as their diagnosis from a dropdown menu of diagnoses included in the CoRDS registry. Second, when completing the Registry questionnaire, participants had to select that they had a current diagnosis of IH or had been told by a doctor that IH explains their symptoms. Participants who endorsed more than one hypersomnolence diagnosis (e.g., IH and narcolepsy type 2) were excluded. Finally, to exclude misdiagnosis related to short sleep durations, participants had to report at least 7 hours sleep/night, calculated as weekly sleep/7. All these criteria had to be met at both timepoints that the questionnaire was completed to be included in the present analyses. Registry Questionnaire Items The questionnaire asked participants to evaluate their symptoms using two temporal references: 1) at the current time (within the past 30 days); and 2) when symptoms were estimated by the participant to have been the worst they had ever been (questionnaire available in data supplement for ( 31 )). For these analyses, current time/past 30 day responses were included. Although the questionnaire assesses symptoms of central disorders of hypersomnolence other than IH, because this investigation was specific to participants with IH, we focused on typical IH symptoms. Question responses were either continuous (e.g., hours of sleep) or categorical (based on symptom frequency). The questionnaire also asked participants to specify, for individual medications, if they had previously tried, were currently taking it at least once weekly, were currently taking it daily or almost every day, or if they had never taken it. Medication changes were defined as starting, restarting, stopping, or starting and stopping a medication between the two survey timepoints. Because new medication options became available after the launching of the Registry questionnaire in 2016, they were not directly queried. To capture these medications, we searched and included all free text responses regarding medication use for pitolisant, solriamfetol, serdexmethylphenidate-dexmethylphenidate, and calcium, magnesium, potassium, sodium oxybate. In incorporating these free text responses, we included generic names, brand names, and common nicknames (e.g., low sodium oxybate, lower sodium oxybate). Because of small numbers using some of these newer agents, we combined serdexmethylphenidate-dexmethylphenidate and dexmethylphenidate responses with methylphenidate and combined all oxybate preparations into a single category (i.e., “oxybates”) for analysis. Statistical analyses Categorical variables with more than two levels were dichotomized for analyses. This included symptom frequency (dichotomized to daily or less than daily) and medication use (currently taking at least once per week or not taking at least once per week). Nightly sleep duration was calculated by averaging weekday sleep duration * 5 and weekend sleep duration * 2. Nap duration was analyzed after excluding reported nap durations of > 6 hours, as these may have represented major sleep periods rather than naps. We analyzed changes between the first and last questionnaire completed by each participant, regardless of the total number of questionnaires completed. Responses were analyzed using paired t-test for continuous variables and McNemar test for categorical variables. Results: Data from three hundred twenty-three participants were included in the analyses, which was 69.0% of IH respondents included in the initial report on this registry ( 31 ). Most (86.5%) of the participants were women, and the mean age was 35.0 years (SD 12.2) at the time of the first response. The average time between the first response and the last response was 2.4 years (SD 1.4, range 0.5 to 6.8 years). For 32.5% of participants, time between first and last responses was at least 3 years; these participants were similar to those with shorter follow up duration in terms of age, gender, and baseline symptoms. Symptoms remained largely stable over the 2 ½ year period (see Table 1 and Figure 1 ). The most commonly endorsed daily symptoms at baseline and at follow up were difficulty awakening for the day (78.7% and 73.0%, respectively), daytime sleepiness (62.7% and 61.8%), having trouble waking up and functioning with normal alertness (56.4% and 56.4%), requiring multiple alarms (53.4% and 55.3%), brain fog (46.3% and 48.4%), and problems with memory (42.7% and 43.4%). The only symptoms to show significant change over time were a small decrease in the proportion with difficulty awakening for the day (78.7% in the first response and 73.0% in the last response) and a small increase in the proportion with daily automatic behaviors (9.9% in the first response and 12.8% in the last response). Table 1. Proportion with daily symptoms at first and last time point of survey completion Symptom Stable symptom (present daily at baseline and follow up) Improved (symptom daily at baseline, less than daily at follow up) Worsened (Symptom not daily at baseline, daily at follow up) Absence of symptom (not present daily at either time point) p-value Excessive daytime sleepiness (n = 322) 180 (55.9%) 22 (6.8%) 19 (5.9%) 101 (31.4%) 0.64 Long sleep time (n=322) 39 (12.1%) 11 (3.4%) 10 (3.1%) 262 (81.4%) 0.83 Intentional naps (n=321) 30 (9.4%) 8 (2.5%) 12 (3.7%) 271 (84.4%) 0.37 Daytime sleep (n=322) 14 (4.4%) 6 (1.9%) 4 (1.2%) 298 (92.6%) 0.53 Requiring multiple alarms (n=322) 161 (50.0%) 11 (3.4%) 17 (5.3%) 133 (41.3%) 0.26 Trouble waking up and functioning with normal alertness (n=321) 159 (49.5%) 22 (6.9%) 22 (6.9%) 118 (36.8%) 1.00 Difficulty awakening for the day (n = 315) 218 (69.2%) 30 (9.5%) 12 (3.8%) 55 (17.5%) 0.006 Brain fog (n=320) 130 (40.6%) 18 (5.6%) 25 (7.8%) 147 (45.9%) 0.29 Poor memory (n=316) 121 (38.3%) 14 (4.4%) 16 (5.1%) 165 (52.2%) 0.72 Automatic behaviors (n=304) 24 (7.9%) 6 (2.0%) 15 (4.9%) 259 (85.2%) 0.0495 Open in a new tab Each symptom is dichotomized into daily (present) or less than daily (absent). Values are reported as number (percent). P-values reflect McNemar test for paired, categorical variables. Variables in bold were statistically significant at p < 0.05. Figure 1: Open in a new tab Change in cardinal symptoms of IH between first and last questionnaire completion On the baseline questionnaire, average nightly sleep duration on workdays was 8.6 (SD 1.6) hours, the average nightly sleep duration on non-workdays was 10.4 (SD 1.9) hours, and the average nap duration was 2.0 (SD 1.4) hours. At follow up, average durations for all three measures were within 10 minutes of baseline measures, without significant differences between the two timepoints on paired testing (all p-values non-significant). Medications Most participants had used IH medication within the last 30 days of the first response (86.0%) and the last response (85.1%, see Table 2 ). Between these two time points, participants experienced an average of 0.8 (+/− 1.1) medication changes, with 179 (55.4%) participants remaining on the same medications, 68 (21.1%) making a single medication change, and 76 (23.5%) making two or more medication changes; the most medication changes made during the study period was 4, by 11 (3.4%) of participants. Number of medication changes was modestly correlated with time between questionnaires (Pearson r = 0.21, p = 0.0001) but was unrelated to frequency of symptoms or sleep durations at either time point (p > 0.05 for all). The only medication for which there was a significant usage change over time was modafinil, which was stopped by 33 (11.3%) of participants but started by only 11 (3.8%). At some point prior to or during the study period, most participants had tried modafinil (75.3%), methylphenidate or dexmethylphenidate (64.4%), amphetamine-dextroamphetamine (58.3%), and armodafinil (54.5%). Very few participants had ever taken clarithromycin (n = 31), oxybates (n = 29), flumazenil (n = 18), solriamfetol (n = 11), or pitolisant (n = 4). Table 2: Proportion taking medications at first and last time point of survey completion Medication Stopped before first questionnaire Continued (usage at baseline and follow up) Stopped during study period (usage at baseline, no usage at follow up) Started during study period (no usage at baseline, usage at follow up) Never used (no usage prior to first questionnaire or during study period) p-value Used medication in the last 30 days (n=322) -- 256 (79.5%) 21 (6.5%) 18 (5.6%) 27 (8.4%) 0.63 Methylphenidate * (n=267) 78 (29.2%) 52 (19.5%) 21 (7.9%) 21 (7.9%) 95 (35.6%) 1.0 Lisdexamfetamine (n=235) 31 (13.2%) 14 (6.0%) 6 (2.6%) 8 (3.4%) 176 (74.9%) 0.59 Amphetamine-dextroamphetamine (n=252) 60 (23.8%) 52 (20.6%) 18 (7.1%) 17 (6.8%) 105 (41.7%) 0.87 Dextro-amphetamine (n=244) 27 (11.1%) 20 (8.2%) 4 (1.6%) 3 (1.2%) 190 (77.9%) 0.71 Modafinil (n=292) 111 (38.0%) 65 (22.3%) 33 (11.3%) 11 (3.8%) 72 (24.7%) 0.0009 Armodafinil (n=244) 76 (31.2%) 33 (13.5%) 15 (6.2%) 9 (3.7%) 111 (45.5%) 0.22 Oxybate (any formulation) (n=241) 17 (7.1%) 5 (2.1%) 1 (0.4%) 6 (2.5%) 212 (88.0%) 0.06 Clarithromycin (n=238) 23 (9.7%) 2 (0.8%) 5 (2.1%) 1 (0.4%) 207 (87.0%) 0.10 Flumazenil (n=239) 12 (5.0%) 4 (1.7%) 1 (0.4%) 1 (0.4%) 221 (92.5%) 1.0 Open in a new tab P-value reflects the McNamar Test comparing currently using vs not currently using a given medication at the two questionnaire time points. Variables in bold were statistically significant at p < 0.05. * methylphenidate category also includes a small number of participants who had taken dexmethylphenidate and/or serdexmethylphenidate Considering only those medications ever taken by at least 50 respondents, there was no single medication that continued to be taken by more than half of participants who had tried it, by the final time point ( Figure 2 ). For modafinil and armodafinil, the percentage of participants who had tried these medications who continued to take them at follow up were 34.5% and 31.6%. For methylphenidate and dexmethylphenidate, 41.9% of people who had attempted any of these medications were still taking one of them at the final timepoint. For the amphetamines, the percentages of participants continuing each medication ranged from 37.3% (lisdexamfetamine) to 46.9% (amphetamine-dextroamphetamine). Figure 2: Open in a new tab Proportion of participants who had ever taken a medication who were still taking it at final questionnaire completion Figure is limited to medications taken by at least 50 participants. Abbreviations: amp-dex = amphetamine-dextroamphetamine New comorbidity diagnoses Comorbid mood disorders were relatively common, with anxiety and depression being present at both timepoints in 47.0% and 44.8%, respectively (see Table 3 ). Both anxiety and depression were present in the same individual in 34.3% at baseline and 35.8% at follow up. Depression diagnoses remained stable between the two timepoints, whereas there was a modest increase in anxiety diagnoses (6.3% with new anxiety diagnoses vs 2.1% reporting resolution of anxiety, p = 0.01). Although other comorbidities were less common, there were significant increases in diagnoses of attention deficit hyperactivity disorder (10 new diagnoses), dysautonomia (4 new diagnoses), fibromyalgia (4 new diagnoses), and Ehlers Danlos (5 new diagnoses). Table 3: Proportion diagnosed with comorbidities at first and last time point of survey completion Comorbidity Stable diagnosis (present at baseline and follow up) New diagnosis (not present at baseline, present at follow up) Resolved (present at baseline, not present at follow up) Never diagnosed p-value Dysautonomia 5 (1.9%) 4 (1.5%) 0 250 (96.5%) 0.046 Postural Orthostatic Tachycardia 5 (2.0%) 5 (2.0%) 1 (0.4%) 246 (95.7%) 0.10 Systemic exertion intolerance disorder/Chronic fatigue syndrome 4 (1.6%) 3 (1.2%) 1 (0.4%) 245 (96.8%) 0.32 Fibromyalgia 13 (5.0%) 4 (1.6%) 0 241 (93.4%) 0.046 Ehlers Danlos 5 (1.9%) 5 (1.9%) 0 248 (96.1%) 0.03 Anxiety 135 (47.0%) 18 (6.3%) 6 (2.1%) 128 (44.6%) 0.01 Depression 132 (44.8%) 12 (4.1%) 14 (4.8%) 137 (46.4%) 0.69 Bipolar disorder 9 (3.4%) 2 (0.8%) 2 (0.8%) 250 (95.1%) 1.0 Attention deficit hyperactivity disorder 33 (12.5%) 10 (3.8%) 0 221 (83.7%) 0.002 Hypothyroidism 33 (12.3%) 4 (1.5%) 1 (0.4%) 230 (85.8%) 0.18 Open in a new tab P-values reflect McNemar test for paired, categorical variables. Variables in bold were statistically significant at p < 0.05. Discussion In this relatively large, longitudinal, online registry of participants with IH, we have demonstrated that core symptoms of IH remain stable across a two-and-a-half-year period. At both timepoints, daytime sleepiness and difficulty with sleep inertia were present in more than half of survey respondents, with cognitive symptoms present in over 40% as well. Despite persistent symptoms in the majority of participants, medication changes were relatively infrequent. There were modest increases in diagnoses of comorbidities including anxiety, attention deficit hyperactivity disorder, dysautonomia, fibromyalgia, and Ehlers Danlos across the study period. Little is known about the natural history of IH and its individual symptoms of excessive sleepiness, sleep inertia, long sleep durations, and cognitive dysfunction. A spontaneous remission rate of IH ranging from 14 to 33% has been reported in clinical samples ( 32 – 35 ). Within the Wisconsin Sleep Cohort, a population-based study enriched for participants with snoring, roughly 40% of people initially meeting IH diagnostic criteria reported non-pathologic levels of sleepiness when followed over 12 years, in those with longitudinal data for analysis ( 36 ). However, it is not known whether other IH symptoms (e.g., sleep inertia, etc) may or may not have persisted in these individuals. Our data suggest that most IH symptoms are relatively stable over time, at least within a 2.4 year period. On one hand, this may be reassuring information for participants with IH and their clinicians, that the natural course of IH does not appear to be one of relentlessly progressive symptom worsening. On the other hand, because the majority of participants still had daily IH symptoms, in most cases despite medication treatment for IH, the lack of improvement over time may suggest that current treatment options are not sufficient to adequately control symptoms for most people with IH. The only symptom to show a significant decrease in frequency between first and last questionnaire administration was difficulty waking up for the day, which decreased from being present daily in 78.7% to 73.0%. Two other questions intended to capture the experience of severe sleep inertia, requiring multiple alarms and having trouble waking up with normal alertness, did not show significant changes over time. This may point to the current challenges in quantifying sleep inertia in people with IH and related central disorders of hypersomnolence. Current self-report tools include the sleep inertia questionnaire ( 37 ), a visual analog score ( 17 ), and selected questions from the Idiopathic Hypersomnia Severity Scale ( 38 ); objective measurement with the psychomotor vigilance task, before and after daytime naps or before and after night sleep, also show promise ( 39 , 40 ). However, none of these tools had been validated for this use when the Hypersomnia Foundation Registry was launched. Regardless of what may eventually be determined as optimal for capturing the experience of severe sleep inertia in people with IH, the high proportion of participants endorsing all three descriptors at both time points speaks to the commonality and persistence of this problematic symptom. In light of the chronicity of symptom profile over time, the relative stability of medication use over time may be surprising. Persistent sleepiness, sleep inertia, and cognitive symptoms reported to a sleep provider should be expected to prompt a change in management, when alternate approaches are available. This may be most straightforward for excessive daytime sleepiness, for which there are multiple treatment approaches known in IH or related disorders to improve excessive sleepiness. The 60% of participants with daily excessive sleepiness may have been expected to have medications adjusted multiple times within the study period, but such adjustments were infrequently made, with the majority of participants (55%) showing no medication changes between their first and last survey responses. Adjusting medications to target other symptoms such as sleep inertia and cognitive dysfunction may be more challenging, as some treatment options have been proposed but few have been systematically studied within IH ( 22 ). Evidence for the relative failure of available medications to effectively manage IH with an acceptable balance of benefits and adverse events is shown by the relatively small numbers of participants continuing any given medication that they tried. Not a single medication was continued to the final questionnaire administration by at least half of people who had tried it. The medication continued by the highest percentage of people who tried it was amphetamine-dextroamphetamine, continued by 47%. In a recent trial comparing amphetamine-dextroamphetamine to modafinil in a combined group of IH and narcolepsy type 2 participants, Epworth scores improved from pre- to post-treatment with both medications but non-inferiority of amphetamine-dextroamphetamine was not demonstrated for Epworth scores ( 21 ). Non-inferiority was demonstrated on a number of important secondary outcomes, including cognitive dysfunction, sleep inertia, and overall disease severity, which may suggest these other benefits also contribute to the decision to remain on a medication. Calcium, magnesium, potassium, sodium oxybate is the only medication currently FDA-approved for the treatment of IH. In the open label extension of the pivotal IH trial of this oxybate preparation, 62% of participants who started on calcium, magnesium, potassium, sodium oxybate were still taking it at the end of the six-month open label extension ( 41 ). In our sample, considering all oxybates together, oxybates were continued by only 38% of the IH participants who had tried this medication class, over a longer period of follow up. However, numbers of participants who had ever tried oxybates remained quite low in our population at 29 participants; a larger sample of participants with IH taking oxybates would be needed to have a more robust estimate of how often these medications are continued in the real world. The role of comorbid conditions in IH is currently debated. Diagnostic criteria clearly state that other conditions that better explain the symptoms cannot be present if an IH diagnosis is to be made ( 1 ). However, it is not fully known what conditions should be considered exclusionary for an IH diagnosis, and people with IH diagnoses frequently have comorbid conditions or symptoms, such as those related to dysautonomia or mood disorders ( 8 , 42 , 43 ). In our population, comorbid mood disorders were common, occurring in nearly half of participants, but such diagnoses were relatively stable over time. New medical comorbidities were rarely reported. One potential benefit of registry studies is that they are less susceptible to referral bias and regional variation in practice patterns compared to single-site studies. For IH in particular, studies attempting to determine prevalence have shown markedly different results, depending on a variety of factors including study design, time in which the study was performed, and clinical location. In the US-based Wisconsin Sleep Cohort, a population-based study, the estimated prevalence of IH is 1.5% (95% CI 0.7–2.5%) ( 36 ). In contrast, the estimated prevalence of IH from US-based claims data is only 0.01% ( 44 ). Earlier studies of IH may have overestimated IH due to lack of recognition of other sleep disorders with similar symptoms ( 45 ). In contrast, IH may have been underestimated due to lack of awareness of the disorder ( 46 ), which may in part explain increasing prevalence over time based on US claims data ( 44 ). Clinical series do not directly measure prevalence but can provide insight into the relative proportion of patients with IH compared to narcolepsy (either NT1 or combined groups). These estimates have been similarly quite variable, as low as 5% and higher than 40% reported in one comprehensive review ( 47 ), with the lower bound from France ( 48 ) and the higher bound from the Czech Republic ( 49 ). Our study has several limitations. Because the Registry is composed of patient-entered information about symptoms, rather than investigator-entered data also including diagnostic testing results, we could not conclusively rule out the possibility that some participants do not meet full diagnostic criteria for IH. This might have occurred either because of a misdiagnosis by a medical provider or a misunderstanding of their diagnosis by an individual completing the registry. We excluded participants endorsing insufficient sleep durations but otherwise relied on the diagnosing medical provider to have properly excluded other causes that better explained the symptoms. Furthermore, the high rates of anxiety and depression raise the possibility that some participants might have had a true underlying diagnosis of hypersomnia comorbid to psychiatric disorder rather than the IH diagnosis they were given. However, at current time there is no clear standard to differentiate these entities in clinical practice other than clinician judgement, so we relied on this judgment. Similarly, given symptom overlap between IH and some of its comorbidities, such as ADHD, it is currently difficult to know whether all symptoms are explained by a single disorder or if two disorders are truly comorbid. In the absence of a mechanistic understanding of IH that would allow clinicians and researchers to conclusively make these distinctions, we have assumed that if a diagnosis was rendered by a medical provider, it should be considered a separate comorbidity rather than just additional symptoms of IH. Included questions were developed specifically for the registry, rather than using existing, validated questionnaires. Medication availability has changed since the launch of the registry questionnaire, such that some medications were assessed by free text entry, and as a result may have been underreported. Participants with IH who completed the registry more than once were only a subset of all IH participants, and thus may not be representative of the full population of IH participants. In particular, as spontaneous remission of IH has been reported, it is possible that people whose symptoms resolved would be less likely to complete the questionnaire on a second session. We were not able to track why participants chose not to complete the survey a second time, so we can neither support nor refute this speculation. Additionally, our population was relatively young. Further evaluation of the natural history of this condition through middle age and older adulthood is also needed. Despite these limitations, this work provides a unique, longitudinal assessment of real-world IH symptoms over time in a large population not constrained by a single sleep center. Participants answered questionnaires at least twice, averaging 2.4 yrs between answers Idiopathic hypersomnia symptoms remained mostly stable between responses Most participants were medicated but did not change medications despite IH symptoms Acknowledgements: Data for this manuscript were provided by the CoRDS Registry at Sanford Research in Sioux Falls, South Dakota. Funding was provided by R01 NS111280 from the National Institute of Neurological Disorders and Stroke/National Institutes of Health. Footnotes Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Disclosures: Dr. Trotti is a member of the Board of Directors of the American Academy of Sleep Medicine. Any opinions expressed are those of the authors and do not necessarily reflect those of the AASM. Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. References 1. International Classification of Sleep Disorders, 3rd edition, text revision (ICSD-3-TR). Darien, IL: American Academy of Sleep Medicine; 2023. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Billiard M, Sonka K. Idiopathic Hypersomnia: Historical Account, Critical Review of Current Tests and Criteria, Diagnostic Evaluation in the Absence of Biological Markers and Robust Electrophysiological Diagnostic Criteria. Nat Sci Sleep. 2022;14:311–22. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Rye DB, Bliwise DL, Parker K, Trotti LM, Saini P, Fairley J, et al. Modulation of Vigilance in the Primary Hypersomnias by Endogenous Enhancement of GABAA Receptors. Sci Transl Med. 2012;4(161):161ra51. [ DOI ] [ PubMed ] [ Google Scholar ] 4. Materna L, Halfter H, Heidbreder A, Boentert M, Lippert J, Koch R, et al. Idiopathic Hypersomnia Patients Revealed Longer Circadian Period Length in Peripheral Skin Fibroblasts. Frontiers in neurology. 2018;9:424. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 5. Lippert J, Halfter H, Heidbreder A, Rohr D, Gess B, Boentert M, et al. Altered dynamics in the circadian oscillation of clock genes in dermal fibroblasts of patients suffering from idiopathic hypersomnia. PLoS One. 2014;9(1):e85255. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 6. Nevsimalova S, Blazejova K, Illnerova H, Hajek I, Vankova J, Pretl M, et al. A contribution to pathophysiology of idiopathic hypersomnia. Suppl Clin Neurophysiol. 2000;53:366–70. [ DOI ] [ PubMed ] [ Google Scholar ] 7. Sforza E, Roche F, Barthelemy JC, Pichot V. Diurnal and nocturnal cardiovascular variability and heart rate arousal response in idiopathic hypersomnia. Sleep Med. 2016;24:131–6. [ DOI ] [ PubMed ] [ Google Scholar ] 8. Miglis MG, Schneider L, Kim P, Cheung J, Trotti LM. Frequency and Severity of Autonomic Symptoms in Idiopathic Hypersomnia. J Clin Sleep Med. 2020. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Pomares FB, Boucetta S, Lachapelle F, Steffener J, Montplaisir J, Cha J, et al. Beyond sleepy: structural and functional changes of the default-mode network in idiopathic hypersomnia. Sleep. 2019. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Boucetta S, Montplaisir J, Zadra A, Lachapelle F, Soucy JP, Gravel P, et al. Altered Regional Cerebral Blood Flow in Idiopathic Hypersomnia. Sleep. 2017;40(10). [ DOI ] [ PubMed ] [ Google Scholar ] 11. Dauvilliers Y, Evangelista E, de Verbizier D, Barateau L, Peigneux P. [18F]Fludeoxyglucose-Positron Emission Tomography Evidence for Cerebral Hypermetabolism in the Awake State in Narcolepsy and Idiopathic Hypersomnia. Frontiers in neurology. 2017;8:350. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Trotti LM, Saini P, Crosson B, Meltzer CC, Rye DB, Nye JA. Regional brain metabolism differs between narcolepsy type 1 and idiopathic hypersomnia. Sleep. 2021;44(8). [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 13. Adam T, Barateau L, Tanty J, Dauvilliers Y. Absence of dysregulation in amplitude and phase of circadian rhythm of core body temperature in idiopathic hypersomnia: A case-control study. Sleep. 2024. [ DOI ] [ PubMed ] [ Google Scholar ] 14. Dauvilliers Y, Evangelista E, Lopez R, Barateau L, Jaussent I, Cens T, et al. Absence of gamma-aminobutyric acid-a receptor potentiation in central hypersomnolence disorders. Ann Neurol. 2016;80(2):259–68. [ DOI ] [ PubMed ] [ Google Scholar ] 15. Moody OA, Talwar S, Jenkins MA, Freeman AA, Trotti LM, Garcia PS, et al. Rigor, reproducibility, and in vitro cerebrospinal fluid assays: The devil in the details. Ann Neurol. 2017;81(6):904–7. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Saini P, Rye DB. Hypersomnia: Evaluation, Treatment, and Social and Economic Aspects. Sleep Med Clin. 2017;12(1):47–60. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Dauvilliers Y, Arnulf I, Foldvary-Schaefer N, Morse AM, Sonka K, Thorpy MJ, et al. Efficacy and Safety of Lower-Sodium Oxybate in Adults With Idiopathic Hypersomnia: A Phase 3, Placebo-Controlled, Double-Blind, Randomized Withdrawal Study. Lancet Neurol. 2022. [ DOI ] [ PubMed ] [ Google Scholar ] 18. Mayer G, Benes H, Young P, Bitterlich M, Rodenbeck A. Modafinil in the treatment of idiopathic hypersomnia without long sleep time-a randomized, double-blind, placebo-controlled study. J Sleep Res. 2015;24(1):74–81. [ DOI ] [ PubMed ] [ Google Scholar ] 19. Inoue Y, Hirata K. The effectiveness of modafinil for the treatment of idiopathic hypersomnia. Sleep. 2017;40:A250–A1. [ Google Scholar ] 20. Arnulf I, Thomas R, Roy A, Dauvilliers Y. Update on the treatment of idiopathic hypersomnia: Progress, challenges, and expert opinion. Sleep Med Rev. 2023;69:101766. [ DOI ] [ PubMed ] [ Google Scholar ] 21. Trotti LM, Blake T, Hoque R, Rye DB, Sharma S, Bliwise DL. Modafinil Versus Amphetamine-Dextroamphetamine For Idiopathic Hypersomnia and Narcolepsy Type 2: A Randomized, Blinded, Non-inferiority Trial. CNS Drugs. 2024;38(11):909–20. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. Maski K, Trotti LM, Kotagal S, Auger RR, Swick TJ, Rowley JA, et al. Treatment of central disorders of hypersomnolence: an American Academy of Sleep Medicine systematic review, meta-analysis, and GRADE assessment. Journal of Clinical Sleep Medicine. 2021;17(9):1895–945. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 23. Trotti LM, Saini P, Bliwise DL, Freeman AA, Jenkins A, Rye DB. Clarithromycin in gamma-aminobutyric acid-Related hypersomnolence: A randomized, crossover trial. Ann Neurol. 2015;78(3):454–65. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Javaid MK, Forestier-Zhang L, Watts L, Turner A, Ponte C, Teare H, et al. The RUDY study platform - a novel approach to patient driven research in rare musculoskeletal diseases. Orphanet J Rare Dis. 2016;11(1):150. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Hornik CP, Gelfand AA, Szperka CL, Pezzuto T, Utevsky A, Kessel S, et al. Development of a Prospective Real-World Data Clinical Registry of Children and Adolescents With Migraine. Headache. 2020;60(2):405–15. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 26. Kazemi-Arpanahi H, Moulaei K, Shanbehzadeh M. Design and development of a web-based registry for Coronavirus (COVID-19) disease. Med J Islam Repub Iran. 2020;34:68. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Gerke AK, Tang F, Cozier YC, Lash MT, Schappet J, Phillips E, et al. A web-based registry for patients with sarcoidosis. Sarcoidosis Vasc Diffuse Lung Dis. 2017;34(1):26–34. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 28. Seidlin M, Holzman R, Knight P, Korf B, Rangel Miller V, Viskochil D, et al. Characterization and utilization of an international neurofibromatosis web-based, patient-entered registry: An observational study. PLoS One. 2017;12(6):e0178639. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Kent P, Kongsted A, Jensen TS, Albert HB, Schiottz-Christensen B, Manniche C. SpineData - a Danish clinical registry of people with chronic back pain. Clin Epidemiol. 2015;7:369–80. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 30. Salter A, Stahmann A, Ellenberger D, Fneish F, Rodgers WJ, Middleton R, et al. Data harmonization for collaborative research among MS registries: A case study in employment. Mult Scler. 2020:1352458520910499. [ DOI ] [ PubMed ] [ Google Scholar ] 31. Trotti LM, Ong JC, Plante DT, Friederich Murray C, King R, Bliwise DL. Disease symptomatology and response to treatment in people with idiopathic hypersomnia: initial data from the Hypersomnia Foundation registry. Sleep Med. 2020;75:343–9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 32. Kim T, Lee JH, Lee CS, Yoon IY. Different fates of excessive daytime sleepiness: survival analysis for remission. Acta Neurol Scand. 2016;134(1):35–41. [ DOI ] [ PubMed ] [ Google Scholar ] 33. Anderson KN, Pilsworth S, Sharples LD, Smith IE, Shneerson JM. Idiopathic hypersomnia: a study of 77 cases. Sleep. 2007;30(10):1274–81. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 34. Bassetti C, Aldrich MS. Idiopathic hypersomnia. A series of 42 patients. Brain. 1997;120(8):1423–35. [ DOI ] [ PubMed ] [ Google Scholar ] 35. Sonka K, Feketeova E, Nevsimalova S, Horvat EM, Prihodova I, Dostalova S, et al. Idiopathic hypersomnia years after the diagnosis. J Sleep Res. 2024;33(2):e14011. [ DOI ] [ PubMed ] [ Google Scholar ] 36. Plante DT, Hagen EW, Barnet JH, Mignot E, Peppard PE. Prevalence and Course of Idiopathic Hypersomnia in the Wisconsin Sleep Cohort Study. Neurology. 2024;102(2):e207994. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 37. Sung ER, Maness CB, Cook JD, Vascan AM, Moron D, Saini P, et al. Validation and performance of the sleep inertia questionnaire in central disorders of hypersomnolence. Sleep Med. 2024;121:352–8. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 38. Dauvilliers Y, Evangelista E, Barateau L, Lopez R, Chenini S, Delbos C, et al. Measurement of symptoms in idiopathic hypersomnia: The Idiopathic Hypersomnia Severity Scale. Neurology. 2019;92(15):e1754–e62. [ DOI ] [ PubMed ] [ Google Scholar ] 39. Trotti LM, Saini P, Bremer E, Mariano C, Moron D, Rye DB, et al. The Psychomotor Vigilance Test as a measure of alertness and sleep inertia in people with central disorders of hypersomnolence. J Clin Sleep Med. 2022;18(5):1395–403. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 40. Evangelista E, Rassu AL, Lopez R, Biagioli N, Chenini S, Barateau L, et al. Sleep inertia measurement with the psychomotor vigilance task in idiopathic hypersomnia. Sleep. 2022;45(1). [ DOI ] [ PubMed ] [ Google Scholar ] 41. Morse AM, Dauvilliers Y, Arnulf I, Thorpy MJ, Foldvary-Schaefer N, Chandler P, et al. Long-term efficacy and safety of low-sodium oxybate in an open-label extension period of a placebo-controlled, double-blind, randomized withdrawal study in adults with idiopathic hypersomnia. J Clin Sleep Med. 2023;19(10):1811–22. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 42. Haubjerg Osterby NC, Baandrup L, Jennum PJ. Psychiatric comorbidity in Danish patients with narcolepsy type 1, narcolepsy type 2, and idiopathic hypersomnia: a case-control study. Sleep Adv. 2024;5(1):zpae073. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 43. Anderson J, Yee BJ, Grunstein R, Matar E, Chadwick M, Machan E, et al. Insights from a 10-year Australasian idiopathic hypersomnia patient data registry study. J Clin Sleep Med. 2024;20(12):1955–64. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Acquavella J, Mehra R, Bron M, Suomi JM, Hess GP. Prevalence of narcolepsy and other sleep disorders and frequency of diagnostic tests from 2013–2016 in insured patients actively seeking care. J Clin Sleep Med. 2020;16(8):1255–63. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 45. Billiard M DY. Idiopathic Hypersomnia. Sleep Med Rev. 2001;5:349–58. [ DOI ] [ PubMed ] [ Google Scholar ] 46. Thorpy MJ, Krahn L, Ruoff C, Foldvary-Schaefer N. Clinical considerations in the treatment of idiopathic hypersomnia. Sleep Med. 2024;119:488–98. [ DOI ] [ PubMed ] [ Google Scholar ] 47. Billiard M, Sonka K. Idiopathic hypersomnia. Sleep Med Rev. 2016;29:23–33. [ DOI ] [ PubMed ] [ Google Scholar ] 48. Dauvilliers Y, Paquereau J, Bastuji H, Drouot X, Weil JS, Viot-Blanc V. Psychological health in central hypersomnias: the French Harmony study. J Neurol Neurosurg Psychiatry. 2009;80(6):636–41. [ DOI ] [ PubMed ] [ Google Scholar ] 49. Narcolepsy Roth B. and hypersomnia: review and classification of 642 personally observed cases. Schweiz Arch Neurol Neurochir Psych. 1976;119:31–41. [ PubMed ] [ Google Scholar ] ACTIONS View on publisher site PDF (417.0 KB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

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