Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome
by
,
Aravind Thavamani
1
,
Sindhoosha Malay
2,
Jasmine Khatana
3,
Sujithra Velayuthan
1 and
Senthilkumar Sankararaman
1,* 1
Division of Pediatric Gastroenterology, Hepatology and Nutrition, UH Rainbow Babies and Children’s Hospital, Case Western Reserve University School of Medicine, 2101 Adelbert Rd, Cleveland, OH 44106, USA
2
Department of Pediatrics, UH Rainbow Babies and Children’s Hospital, Case Western Reserve University School of Medicine, 2101 Adelbert Rd, Cleveland, OH 44106, USA
3
Department of Pediatrics, Metro Health Medical Center, Case Western Reserve University School of Medicine, 2500 Metrohealth Dr, Cleveland, OH 44109, USA
*
Author to whom correspondence should be addressed.
Medicines 2024, 11(8), 21; https://doi.org/10.3390/medicines11080021
Submission received: 30 July 2024
/
Revised: 6 November 2024
/
Accepted: 3 December 2024
/
Published: 11 December 2024
Abstract
:Introduction: Cyclical vomiting syndrome (CVS) is a recurrent debilitating illness characterized by intense episodes of nausea and emesis with widely varied pharmacological management across the country. Aprepitant is now increasingly used in patients with CVS. The impact of aprepitant as an abortive therapy in the readmission of pediatric patients with CVS is currently unknown. Methodology: We analyzed all pediatric patients with a primary diagnosis of CVS using the ICD-10 code in the Pediatric Health Information System database of the Children’s Hospital Association. We evaluated the demographic data, comorbid conditions, and management details during the inpatient stay. CVS patients who received aprepitant during their inpatient hospitalization were compared with patients without aprepitant use. Seven-day readmission rate for CVS was used as the outcome variable to assess the effectiveness of the aprepitant in aborting an episode. Propensity score matching was used to match the two cohorts. Results: We analyzed 1775 patients of which 96 received aprepitant during the inpatient hospitalization. The aprepitant group had a more severe hospitalization course as evidenced by an increased duration of hospital stay (5 vs. 3 days) and total hospitalization costs ($11,790 vs. $6380). There were no significant differences in the 7-day (17% vs. 16%, p = 0.91) readmission rate and results were not altered by propensity score matching. Conclusions: Aprepitant use as an abortive therapy did not affect the 7-day CVS-related readmission rate. Further prospective studies are needed to explore the role of aprepitant as an abortive agent in the management of CVS in the pediatric population.
1. Introduction
Cyclic vomiting syndrome (CVS) is a disorder of gut–brain interactions (DGBI) characterized by repeated, stereotypical episodes of nausea and vomiting with a return to baseline health in between these episodes [1]. Consequently, patients undergo great distress from these symptoms, including repeated hospitalizations for fluid replacement and symptom management resulting in missed school/workdays, increased health care expenditure, and poor quality of life [2,3,4,5,6]. They also have increased association with disorders such as migraine, other DGBI, and psychiatric comorbidities [3,5,7]. In CVS, the mainstay of abortive therapy includes administration of antiemetics and fluid management. Ondansetron is the most commonly used abortive agent and sumatriptans and aprepitant are increasingly utilized as second line agents [8,9].
Aprepitant, a neurokinin-1 receptor antagonist, exerts its action by preventing the binding of substance P to the neurokinin-1 receptor. Neurokinin-1 receptors are present in the area postrema and solitary nucleus and aprepitant targets the central brain pathways that signal the vomiting reflex and symptoms of nausea and concomitant abdominal pain. The safety and efficacy of aprepitant has been well studied in many disorders such as chemotherapy-induced vomiting and postoperative vomiting [10,11,12]. In adults, aprepitant has also been increasingly utilized in the management of intractable nausea and vomiting related to CVS and gastroparesis [13,14,15]. However, there is limited data on the impact of aprepitant on the readmission of CVS patients in the pediatric age group.
The objective of this study was to analyze the efficacy of aprepitant on the readmission for CVS in the pediatric age group. We hypothesized that aprepitant use may be associated with a decrease in the 7-day readmission rate. We also hypothesized that aprepitant use may be associated with severe CVS.
2. Methods
We analyzed the Pediatric Health Information System (PHIS) database which is an aggregation of inpatient, observation, emergency department, and ambulatory surgery encounter data from more than 50 children’s hospitals across the United States affiliated with the Children’s Hospital Association (Lenexa, KS) [16]. This database was created for the purposes of external benchmarking and quality improvement, the validity and reliability of the datasets are ensured both by the Children’s Hospital Association and the partnering hospitals [17]. The dataset includes patient demographics, admission details, comorbid diagnoses, and procedures based on the International Classification of Diseases, 9th Revision and 10th Revision, Clinical Modification (ICD-9/10-CM) and Current Procedural Terminology codes [17]. Hospitals also submit resource utilization data based on clinical, pharmaceutical, laboratory, and imaging charges. In the PHIS database, data are deidentified at submission and are subjected to reliability and validity checks before inclusion [17].
We included all patients less than 18 years of age admitted to the hospital inpatient or observation units with a primary diagnosis of CVS. We analyzed all patients with hospitalization between 2016 and 2019 during which the International Classification of Diseases (ICD) 10th Revision (ICD-10) codes were employed for coding and billing purposes, thus having a specific code for CVS which was not available in the previous version of ICD. CVS patients who received aprepitant (referred to as the aprepitant group) during their index inpatient hospitalization for CVS were compared with CVS inpatients who were treated without aprepitant (referred to as the control group).
We analyzed various demographic variables, comorbid medical and psychiatric conditions, and management details during their hospital stay. In PHIS, participating hospitals submit race and ethnicity data for each visit according to hospital-specific practices, which include parent/guardian self-report at the time of arrival or hospital registration assignment. The comorbid medical and psychiatric conditions analyzed were migraine, gastroesophageal reflux disease (GERD), anxiety, cannabis use, depression, abdominal migraine, dyspepsia, dysautonomia, obesity, narcotic use, alcohol use, smoking, adjustment disorders, stress reaction, post-traumatic disorders (PTSD), and bipolar disorders as these conditions are increasingly prevalent among patients with CVS and may potentially affect readmission rates after hospitalization [5,18].
The primary outcome variable was the readmission rate within 7 days of the index hospitalization. Secondary outcome variables analyzed were the length of stay, total hospitalization expense of the index hospitalization, and readmission rates at 14 days, 30 days, 90 days, 180 days, and 365 days. As the timing of aprepitant use during the hospitalization could not be obtained in this retrospective study, these secondary outcome variables were not used to determine the efficacy of aprepitant but rather used to analyze the severity of the CVS.
Statistical Analysis
All continuous variables were expressed as median with interquartile range and categorical variables were expressed as frequencies and percentages. All categorical variables were compared using the chi-square test of independence and Fisher’s exact test as applicable and continuous variables were compared using Wilcoxon rank-sum test. The readmission rates were calculated between the study groups and then recalculated after 1:5 propensity score matching (PSM). PSM was performed using MatchIt package in R Studio with the following demographics and clinical comorbidities: covariates: race, ethnicity, insurance, severity level of the disease, and the number of drugs prescribed. A p value < 0.05 was considered statistically significant. All the analyses were performed using SAS software, Version 9.4 (SAS Institute, Cary, NC, USA) and R software, Version 4.3.1.
3. Results
A total of 1775 pediatric patients were analyzed who were hospitalized with a primary diagnosis of CVS during the study period between 2016 and 2019. A total of 96 patients received aprepitant during the index hospitalization and 1679 patients with CVS did not receive aprepitant during their index stay. Patients who received aprepitant were slightly older, more often females, and had private insurance, but these differences were not statistically significant (Table 1). Patients in the aprepitant group significantly belonged to the Caucasian race and non-Hispanic ethnicity, the aprepitant group had slightly lower family income and higher disease severity (as coded by the clinician using the ICD-10). However, no statistical differences were noted between the cohorts for these variables.
The aprepitant group had an increased prevalence of anxiety, depression, abdominal migraine, dysautonomia, PTSD, and bipolar disorder but the differences were not statistically significant. The prevalence of GERD, cannabis use, dyspepsia, obesity, smoking, narcotic use, alcohol use, stress reaction, and adjustment disorder were decreased (or absent) in the aprepitant group and the differences were not statistically significant.
The length of stay, hospitalization charges, and costs were significantly higher in the aprepitant group (p < 0.001 for all these variables, (Table 1)). The readmission rates within 7 days, 14 days, and 30 days of index hospitalization were slightly high in the aprepitant group but no statistical differences were noted. However, patients receiving aprepitant had significantly greater readmission rates at 90 days (70% vs. 57%, p = 0.020), 180 days (81% vs. 68%, p = 0.010), and 365 days (85% vs. 76, p = 0.040 (Supplemental Table S1)).
After 1:5 PSM, there were 96 in the aprepitant group and 480 in the control group with a total of 576 patients (Table 2). All the variables in demographics, and comorbid conditions remain statistically not significant between the groups after PSM. We also compared the medication use between the groups which was overall very similar except for promethazine and diphenhydramine. Promethazine use was significantly lower in the aprepitant group (18% vs. 28%, p = 0.043) and conversely, diphenhydramine use was significantly higher in the aprepitant group (76% vs. 64%, p = 0.03). The length of stay (5.0 vs. 3.0 days, p < 0.001), hospital charges ($31,764 vs. $22,207, p < 0.001), and hospital costs ($11,790 vs. $6690, p < 0.001) remained significantly increased for the aprepitant group (Table 2).
In assessing readmission rates after PSM, there was no significant difference in the 7-day (17% vs. 16%, p = 0.91), 14-day (29% vs. 28%, p = 0.83), or 30-day (47% vs. 41%, p = 0.38) readmission rates. Patients in the aprepitant group had slightly higher readmission rates at 90 days (70% vs. 60%, p = 0.09), 180 days (81% vs. 72%, p = 0.07), and 365 days (85% vs. 79%, p = 0.16) but did not reach statistical significance (Supplemental Table S2).
4. Discussion
Using national-level data, we demonstrated that aprepitant use during the index hospital stay did not result in a reduction of 7-day readmission rate. The aprepitant group had an increased duration of hospital stay and total hospitalization expenses. There was no difference in readmission rates between the groups at 14- and 30 days. Further, no significant differences were noted in the readmission rates between the groups at 90, 180, and 365 days after the PSM.
CVS guidelines in adults published in 2019 emphasized the adjunct role of aprepitant for both prevention as well for acute management [18]. In adults with CVS, Patel and colleagues demonstrated that prophylactic use of aprepitant did significantly decrease the total number of CVS episodes from 14.5 to 6.2 and also decreased hospitalizations from 1.6 to 0.8, p = 0.02 [14]. The North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition (NASPGHAN) consensus statement on CVS was published in 2008 and recommended the use of 5HT3 receptor antagonists (such as ondansetron or Granisetron) or 5HT1B/1D agonists (such as sumatriptan) for abortive management. However, in recent years, the use of aprepitant for managing severe CVS has been increasing based on expert recommendations [19,20,21,22,23]. A single-center study involving a smaller sample in the pediatric population also supported both the acute and prophylactic use of aprepitant in CVS. Aprepitant use was associated with significant reduction in several parameters such as annual CVS episodes, hospital admissions/year, severity of CVS, and improvement in symptom-free interval duration and better school attendance [24]. Here, the authors noted that in 25 pediatric patients with CVS refractory to conventional medications, the use of aprepitant during the early prodromal phase resulted in symptomatic improvement in approximately three-fourths of the patients [24].
In our study, aprepitant use during the index hospital stay did not result in the reduction in 7-day readmission rate. Various reasons could be explained for this lack of significance between the groups. Given limited data on the utility of aprepitant in the pediatric population, we believe that aprepitant is used preferentially as second or third-line medication for severe CVS phenotype. In support of this concept, the aprepitant group had a significantly more severe hospitalization course as noted by an increased duration of hospital stay and total hospitalization expenses. Given the methodology utilized, we were not able to determine the important details of aprepitant therapy such as the timing of administration, frequency and duration of use, dosage details, and response to therapy which might have provided more information on this efficacy.
There are several other limitations which should be taken into account. Since ICD coding was used to assess for cases of CVS, any errors or variances in coding practices may have excluded patients from the study or affected how data were recorded and interpreted. -In this study, patient information was gathered mostly from tertiary care hospitals where there is ready access to specialists and more advanced treatments. Thus, referral bias may have been introduced as these facilities would be seeing a more severe spectrum of CVS cases compared to community hospitals. Specific details relating to the severity and course of the disease were unavailable, such as data related to the number of episodes of emesis, dose and clinical response to medications, details of intravenous hydration, and the time between onset of symptoms and hospital admission. Any medical care received outside of the hospital admission was also unavailable in the database, further limiting the assessment of the CVS disease course.
Despite these limitations, our study has numerous strengths as well. We had a large national-level sample size and analyzed readmission rates at various intervals. Data were taken from when ICD-10 was largely implemented in medical practice, thus minimizing the issue of coding errors and variances previously discussed. Multiple, frequent quality checks were also performed at different points of data collection to ensure reliability of the data through the PHIS database. Further, we used PSM utilizing a nearest matching method with a ratio of 1:5 which helped reducing the confounding variables between the groups.
5. Conclusions
Our study demonstrated that patients in the aprepitant group had a prolonged hospitalization course. Aprepitant use during index hospital stay did not reduce readmission rate in both short- and long-term intervals. Further prospectives are required to confirm or refute our results.
Supplementary Materials
The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/medicines11080021/s1, Table S1: Comparison between the groups before the propensity matching; Table S2: Comparison between the groups after propensity matching.
Author Contributions
Conceptualization, A.T., J.K., S.V. and S.S.; methodology, A.T., J.K., S.V., S.M. and S.S.; software, S.M.; validation, A.T. and S.M.; formal analysis, A.T., S.M. and S.S.; writing—original draft preparation, A.T., J.K. and S.V.; writing—review and editing, A.T. and S.S. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Institutional Review Board at the University Cleveland Medical Center reviewed the study and decided non-human research (STUDY20201208).
Informed Consent Statement
Not applicable.
Data Availability Statement
The data presented in this study are available at the Pediatric Health Information System (PHIS) database at https://www.childrenshospitals.org/content/analytics/product-program/pediatric-health-information-system (accessed on 10 January 2021).
Conflicts of Interest
S.S. is a consultant for Nestle. Other authors declare no conflicts of interest.
References
- Hyams, J.S.; Di Lorenzo, C.; Saps, M.; Shulman, R.J.; Staiano, A.; van Tilburg, M. Childhood Functional Gastrointestinal Disorders: Child/Adolescent. Gastroenterology 2016, 150, 1456–1468.e2. [Google Scholar] [CrossRef] [PubMed]
- Bhandari, S.; Venkatesan, T. Clinical Characteristics, Comorbidities and Hospital Outcomes in Hospitalizations with Cyclic Vomiting Syndrome: A Nationwide Analysis. Dig. Dis. Sci. 2017, 62, 2035–2044. [Google Scholar] [CrossRef] [PubMed]
- Thavamani, A.; Umapathi, K.K.; Khatana, J.; Bhandari, S.; Kovacic, K.; Venkatesan, T. Cyclic Vomiting Syndrome-Related Hospitalizations Trends, Comorbidities & Health Care Costs in Children: A Population Based Study. Children 2022, 9, 55. [Google Scholar] [CrossRef]
- Thavamani, A.; Umapathi, K.K.; Velayuthan, S.; Sankararaman, S. Burden of psychiatric disorders in patients with cyclic vomiting syndrome—Need for aggressive screening and early intervention. Dig. Liver Dis. 2021, 54, 287–289. [Google Scholar] [CrossRef] [PubMed]
- Thavamani, A.; Velayuthan, S.; Patel, D.; Al-Hammadi, N.; Sferra, T.J.; Sankararaman, S. Association of Anxiety and Gastrointestinal Comorbidities in Repeat Hospital Admissions in Pediatric Cyclic Vomiting Syndrome. Am. J. Gastroenterol. 2023, 118, 1439–1445. [Google Scholar] [CrossRef]
- Raucci, U.; Borrelli, O.; Di Nardo, G.; Tambucci, R.; Pavone, P.; Salvatore, S.; Baldassarre, M.E.; Cordelli, D.M.; Falsaperla, R.; Felici, E.; et al. Cyclic Vomiting Syndrome in Children. Front. Neurol. 2020, 11, 583425. [Google Scholar] [CrossRef]
- Chen, Y.J.; Princic, N.; Winer, I.; Richmond, C.; Williams, J.; Thavamani, A.; Levinthal, D.J.; Venkatesan, T. Epidemiology, Comorbidities, and Treatment of Cyclic Vomiting Syndrome in the United States. Am. J. Gastroenterol. 2023, 119, 965–976. [Google Scholar] [CrossRef]
- Li, B.U. Managing cyclic vomiting syndrome in children: Beyond the guidelines. Eur. J. Pediatr. 2018, 177, 1435–1442. [Google Scholar] [CrossRef] [PubMed]
- Gui, S.; Patel, N.; Issenman, R.; Kam, A.J. Acute Management of Pediatric Cyclic Vomiting Syndrome: A Systematic Review. J. Pediatr. 2019, 214, 158–164.e4. [Google Scholar] [CrossRef]
- Singh, P.M.; Borle, A.; Rewari, V.; Makkar, J.K.; Trikha, A.; Sinha, A.C.; Goudra, B. Aprepitant for postoperative nausea and vomiting: A systematic review and meta-analysis. Postgrad. Med. J. 2015, 92, 87–98. [Google Scholar] [CrossRef]
- Zhang, M.; Guo, Q.-L.; Zhang, T.-T.; Fu, M.B.; Bi, H.-T.; Zhang, J.-Y.; Zou, K.-L. Efficacy and safety of Aprepitant-containing triple therapy for the prevention and treatment of chemotherapy-induced nausea and vomiting: A meta-analysis. Medicine 2023, 102, e35952. [Google Scholar] [CrossRef] [PubMed]
- Okumura, L.M.; Rodrigues, F.D.; Ferreira, M.A.P.; Moreira, L.B. Aprepitant in pediatric patients using moderate and highly emetogenic protocols: A systematic review and meta-analyses of randomized controlled trials. Br. J. Clin. Pharmacol. 2017, 83, 1108–1117. [Google Scholar] [CrossRef] [PubMed]
- Pasricha, P.J.; Yates, K.P.; Sarosiek, I.; McCallum, R.W.; Abell, T.L.; Koch, K.L.; Nguyen, L.A.B.; Snape, W.J.; Hasler, W.L.; Clarke, J.O.; et al. Aprepitant has mixed effects on nausea and reduces other symptoms in patients with gastroparesis and related disorders. Gastroenterology 2018, 154, 65–76. [Google Scholar] [CrossRef] [PubMed]
- Patel, M.; Partovi, O.; Mooers, H.; Kovacic, K.; Garacchi, Z.; Venkatesan, T. Efficacy of aprepitant as a prophylactic medication in adults with cyclic vomiting syndrome. Neurogastroenterol. Motil. 2023, 35, e14530. [Google Scholar] [CrossRef]
- Jacobse, J.; Mensink, H.; van der Stoep-Yap, M.Y.E.C.; Kollen, W.J.W.; Bresters, D.; Bredius, R.G.M. Long-term aprepitant for nausea and vomiting associated with gastroparesis in hematopoietic stem cell transplantation. Bone Marrow Transplant. 2018, 53, 1372–1374. [Google Scholar] [CrossRef]
- PHIS. Available online: https://www.childrenshospitals.org/content/analytics/product-program/pediatric-health-information-system (accessed on 4 November 2024).
- Gray, M.M.; Malay, S.; Kleinman, L.C.; Stange, K.C.; Borawski, E.A.; Shein, S.L.; Slain, K.N.D. Child Opportunity Index and Hospital Utilization in Children With Traumatic Brain Injury Admitted to the PICU. Crit. Care Explor. 2023, 5, e0840. [Google Scholar] [CrossRef]
- Venkatesan, T.; Levinthal, D.J.; Tarbell, S.E.; Jaradeh, S.S.; Hasler, W.L.; Issenman, R.M.; Adams, K.A.; Sarosiek, I.; Stave, C.D.; Sharaf, R.N.; et al. Guidelines on management of cyclic vomiting syndrome in adults by the American Neurogastroenterology and Motility Society and the Cyclic Vomiting Syndrome Association. Neurogastroenterol. Motil. 2019, 31, e13604. [Google Scholar] [CrossRef] [PubMed]
- Nivatsi, M.; Aslanidou, I.; Mantadakis, E. Highly effective use of aprepitant in an adolescent girl with severe cyclic vomiting syndrome. BMJ Case Rep. 2021, 14, e241132. [Google Scholar] [CrossRef]
- Tillman, E.M.; Harvath, E.M. Cyclic Vomiting Syndrome in Pediatric Patients: A Review of Therapeutics. J. Pediatr. Pharmacol. Ther. 2021, 27, 12–18. [Google Scholar] [CrossRef]
- Kovacic, K.; Li, B.U.K. Cyclic vomiting syndrome: A narrative review and guide to management. Headache. 2021, 61, 231–243. [Google Scholar] [CrossRef]
- Kovacic, K.; Li, B.U. Cyclic Vomiting Syndrome, Abdominal Migraine, and Chronic Nausea. In Pediatric Neurogastroenterology; Faure, C., Thapar, N., Di Lorenzo, C., Eds.; Springer: Cham, Switzerland, 2023; pp. 495–507. [Google Scholar]
- Li, B.; Kovacic, K. Cyclic Vomiting Syndrome: Comorbidities and Treatment. In Pediatric Neurogastroenterology. Faure, C., Thapar, N., Di Lorenzo, C., Eds.; Springer: Cham, Switzerland, 2017; pp. 423–431. [Google Scholar]
- Cristofori, F.; Thapar, N.; Saliakellis, E.; Kumaraguru, N.; Elawad, M.; Kiparissi, F.; Köglmeier, J.; Andrews, P.; Lindley, K.J.; Borrelli, O. Efficacy of the neurokinin-1 receptor antagonist aprepitant in children with cyclical vomiting syndrome. Aliment. Pharmacol. Ther. 2014, 40, 309–317. [Google Scholar] [CrossRef] [PubMed]
Table 1.
Comparison of baseline demographics, clinical and outcome characteristics between the population.
Table 1.
Comparison of baseline demographics, clinical and outcome characteristics between the population.
| Variables | Overall, N = 1775 1 | Aprepitant Group, N = 96 1 | No Aprepitant Use, N = 1679 1 | p-Value 2 |
|---|---|---|---|---|
| Age (years) | 12.0 (8.0, 16.0) | 13.5 (6.0, 16.0) | 12.0 (8.0, 16.0) | 0.426 |
| Gender | 0.130 | |||
| Female | 1081 (61%) | 66 (69%) | 1015 (60%) | |
| Male | 694 (39%) | 30 (31%) | 664 (40%) | |
| Race | 0.014 | |||
| Black | 346 (19%) | 15 (16%) | 331 (20%) | |
| Other | 327 (18%) | 10 (10%) | 317 (19%) | |
| Unknown | 47 (2.6%) | 0 (0%) | 47 (2.8%) | |
| White | 1055 (59%) | 71 (74%) | 984 (59%) | |
| Ethnicity | 0.006 | |||
| Hispanic or Latino | 300 (17%) | 11 (11%) | 289 (17%) | |
| Not Hispanic or Latino | 1384 (78%) | 85 (89%) | 1299 (77%) | |
| Unknown | 91 (5.1%) | 0 (0%) | 91 (5.4%) | |
| Insurance | 0.060 | |||
| Private | 808 (46%) | 57 (59%) | 751 (45%) | |
| Public | 813 (46%) | 36 (38%) | 777 (46%) | |
| Uninsured | 17 (1.0%) | 0 (0%) | 17 (1.0%) | |
| Others | 134 (7.5%) | 3 (3.1%) | 131 (7.8%) | |
| Income | ||||
| Known income ($) | 44,371 (35,791, 59,505) | 41,410 (38,516, 64,816) | 44,371 (35,693, 59,350) | 0.953 |
| Unknown income (n) | 72 | 3 | 69 | |
| Severity Level | 0.060 | |||
| Extreme | 29 (1.6%) | 2 (2.1%) | 27 (1.6%) | |
| Major | 439 (25%) | 23 (24%) | 416 (25%) | |
| Moderate | 828 (47%) | 55 (57%) | 773 (46%) | |
| Minor | 479 (27%) | 16 (17%) | 463 (28%) | |
| Comorbid Conditions | ||||
| Migraine | 1775 (100%) | 96 (100%) | 1679 (100%) | |
| GERD | 369 (21%) | 12 (12%) | 357 (21%) | 0.054 |
| Anxiety | 379 (21%) | 28 (29%) | 351 (21%) | 0.073 |
| Cannabis use | 189 (11%) | 5 (5.2%) | 184 (11%) | 0.108 |
| Depression | 116 (6.5%) | 7 (7.3%) | 109 (6.5%) | 0.923 |
| Abdominal migraine | 94 (5.3%) | 9 (9.4%) | 85 (5.1%) | 0.109 |
| Dyspepsia | 69 (3.9%) | 2 (2.1%) | 67 (4.0%) | 0.583 |
| Dysautonomia | 27 (1.5%) | 4 (4.2%) | 23 (1.4%) | 0.054 |
| Obesity | 32 (1.8%) | 0 (0%) | 32 (1.9%) | 0.414 |
| Narcotic use | 4 (0.2%) | 0 (0%) | 4 (0.2%) | >0.999 |
| Alcohol use | 1 (<0.1%) | 0 (0%) | 1 (<0.1%) | >0.999 |
| Smoking | 17 (1.0%) | 0 (0%) | 17 (1.0%) | >0.999 |
| Adjustment Disorder | 41 (2.3%) | 2 (2.1%) | 39 (2.3%) | >0.999 |
| Stress reaction | 3 (0.2%) | 0 (0%) | 3 (0.2%) | >0.999 |
| PTSD | 28 (1.6%) | 2 (2.1%) | 26 (1.5%) | 0.661 |
| Bipolar disorder | 21 (1.2%) | 2 (2.1%) | 19 (1.1%) | 0.316 |
| Length of stay (days) | 3.00 (2.00, 5.00) | 5.00 (3.00, 8.00) | 3.00 (2.00, 5.00) | <0.001 |
| Hospital charges ($) | 21,496 (13,444, 35,410) | 31,764 (19,316, 61,943) | 21,054 (13,304, 34,792) | <0.001 |
| Hospital costs ($) | 6560 (4092, 10,696) | 11,790 (6879, 20,767) | 6380 (4000, 10,270) | <0.001 |
| Readmission < 7 Days | 0.918 | |||
| No | 1495 (84%) | 80 (83%) | 1415 (84%) | |
| Yes | 280 (16%) | 16 (17%) | 264 (16%) | |
| Readmission < 14 Days | 0.299 | |||
| No | 1345 (76%) | 68 (71%) | 1277 (76%) | |
| Yes | 430 (24%) | 28 (29%) | 402 (24%) | |
| Readmission < 30 days | 0.103 | |||
| No | 1092 (62%) | 51 (53%) | 1041 (62%) | |
| Yes | 683 (38%) | 45 (47%) | 638 (38%) |
(GERD—gastroesophageal reflux disease, PTSD—post-traumatic stress disorder). 1 Statistics presented: Median (IQR); n (%). 2 Statistical tests performed: Wilcoxon rank-sum test; Fisher’s exact test; chi-square test of independence as appropriate.
Table 2.
Comparison of various demographics, clinical and outcome characteristics after propensity score matching.
Table 2.
Comparison of various demographics, clinical and outcome characteristics after propensity score matching.
| Variables | Overall, N = 576 1 | Aprepitant, N = 96 1 | No Aprepitant, N = 480 1 | p-Value 2 |
|---|---|---|---|---|
| Age (years) | 13.0 (9.0, 16.0) | 13.5 (6.0, 16.0) | 13.0 (9.0, 16.0) | 0.129 |
| Gender | 0.204 | |||
| Female | 360 (62%) | 66 (69%) | 294 (61%) | |
| Male | 216 (38%) | 30 (31%) | 186 (39%) | |
| Race | 0.786 | |||
| Black | 104 (18%) | 15 (16%) | 89 (19%) | |
| Other | 56 (9.7%) | 10 (10%) | 46 (9.6%) | |
| White | 416 (72%) | 71 (74%) | 345 (72%) | |
| Ethnicity | 0.855 | |||
| Hispanic or Latino | 60 (10%) | 11 (11%) | 49 (10%) | |
| Not Hispanic or Latino | 516 (90%) | 85 (89%) | 431 (90%) | |
| Severity level | 0.962 | |||
| Extreme | 13 (2.3%) | 2 (2.1%) | 11 (2.3%) | |
| Major | 151 (26%) | 23 (24%) | 128 (27%) | |
| Minor | 93 (16%) | 16 (17%) | 77 (16%) | |
| Moderate | 319 (55%) | 55 (57%) | 264 (55%) | |
| Insurance | 0.464 | |||
| Others | 11 (1.9%) | 3 (3.1%) | 8 (1.7%) | |
| Private | 328 (57%) | 57 (59%) | 271 (56%) | |
| Public | 237 (41%) | 36 (38%) | 201 (42%) | |
| Income | ||||
| Known income ($) | 46,913 (37,754, 64,592) | 41,410 (38,516, 64,816) | 47,755 (37,710, 64,346) | 0.137 |
| Unknown income (n) | 22 | 3 | 19 | |
| Comorbid conditions | ||||
| Migraine | 576 (100%) | 96 (100%) | 480 (100%) | |
| GERD | 108 (19%) | 12 (12%) | 96 (20%) | 0.115 |
| Anxiety | 148 (26%) | 28 (29%) | 120 (25%) | 0.468 |
| Cannabis use | 58 (10%) | 5 (5.2%) | 53 (11%) | 0.122 |
| Depression | 41 (7.1%) | 7 (7.3%) | 34 (7.1%) | >0.999 |
| Abdominal migraine | 40 (6.9%) | 9 (9.4%) | 31 (6.5%) | 0.420 |
| Dyspepsia | 21 (3.6%) | 2 (2.1%) | 19 (4.0%) | 0.553 |
| Dysautonomia | 11 (1.9%) | 4 (4.2%) | 7 (1.5%) | 0.094 |
| Obesity | 7 (1.2%) | 0 (0%) | 7 (1.5%) | 0.607 |
| Narcotic use | 2 (0.3%) | 0 (0%) | 2 (0.4%) | >0.999 |
| Alcohol use | 0 (0%) | 0 (0%) | 0 (0%) | |
| Smoking | 4 (0.7%) | 0 (0%) | 4 (0.8%) | >0.999 |
| Adjustment disorder | 12 (2.1%) | 2 (2.1%) | 10 (2.1%) | >0.999 |
| Stress reaction | 0 (0%) | 0 (0%) | 0 (0%) | |
| PTSD | 14 (2.4%) | 2 (2.1%) | 12 (2.5%) | >0.999 |
| Bipolar disorder | 10 (1.7%) | 2 (2.1%) | 8 (1.7%) | 0.676 |
| Use of other medications | ||||
| Ondansetron | 504 (88%) | 80 (83%) | 424 (88%) | 0.237 |
| Lorazepam | 364 (63%) | 62 (65%) | 302 (63%) | 0.847 |
| Sumatriptan | 20 (3.5%) | 4 (4.2%) | 16 (3.3%) | 0.758 |
| Promethazine | 153 (27%) | 17 (18%) | 136 (28%) | 0.043 |
| Granisetron | 34 (5.9%) | 6 (6.2%) | 28 (5.8%) | >0.999 |
| Diphenhydramine | 381 (66%) | 73 (76%) | 308 (64%) | 0.033 |
| Length of stay (days) | 3.0 (2.0, 5.0) | 5.0 (3.0, 8.0) | 3.0 (2.0, 5.0) | <0.001 |
| Hospital charges ($) | 23,428 (14,914, 38,975) | 31,764 (19,316, 61,943) | 22,207 (14,688, 37,108) | <0.001 |
| Hospital costs ($) | 7048 (4716, 12,380) | 11,790 (6879, 20,767) | 6690 (4332, 10,965) | <0.001 |
| Readmission < 7 days | >0.999 | |||
| No | 479 (83%) | 80 (83%) | 399 (83%) | |
| Yes | 97 (17%) | 16 (17%) | 81 (17%) | |
| Readmission < 14 days | ||||
| No | 416 (72%) | 68 (71%) | 348 (72%) | 0.835 |
| Yes | 160 (28%) | 28 (29%) | 132 (28%) | |
| Readmission < 30 days | 0.386 | |||
| No | 332 (58%) | 51 (53%) | 281 (59%) | |
| Yes | 244 (42%) | 45 (47%) | 199 (41%) |
(GERD—gastroesophageal reflux disease, PTSD—post-traumatic stress disorder). 1 Statistics presented: Median (IQR); n (%). 2 Statistical tests performed: Wilcoxon rank-sum test; Fisher’s exact test; chi-square test of independence as appropriate.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Thavamani, A.; Malay, S.; Khatana, J.; Velayuthan, S.; Sankararaman, S. Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome. Medicines 2024, 11, 21. https://doi.org/10.3390/medicines11080021
AMA Style
Thavamani A, Malay S, Khatana J, Velayuthan S, Sankararaman S. Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome. Medicines. 2024; 11(8):21. https://doi.org/10.3390/medicines11080021
Chicago/Turabian StyleThavamani, Aravind, Sindhoosha Malay, Jasmine Khatana, Sujithra Velayuthan, and Senthilkumar Sankararaman. 2024. "Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome" Medicines 11, no. 8: 21. https://doi.org/10.3390/medicines11080021
APA StyleThavamani, A., Malay, S., Khatana, J., Velayuthan, S., & Sankararaman, S. (2024). Utility of Aprepitant in the Management of Pediatric Patients with Cyclical Vomiting Syndrome. Medicines, 11(8), 21. https://doi.org/10.3390/medicines11080021
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
