Trends and Associations of Insomnia Medications with Delirium: A Single- Center Cohort Retrospective Study

Trends and Associations of Insomnia Medications with Delirium: A Single- Center Cohort Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trends and Associations of Insomnia Medications with Delirium: A Single- Center Cohort Retrospective Study Mao Washida, Rintaro Sogawa, Yuki Nakano, Toru Murakawa-Hirachi, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8673561/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Clinical guidelines increasingly recommend dual orexin receptor antagonists (DORAs) over benzodiazepine receptor agonists (BZRAs) and non-benzodiazepines (Z-drugs) for insomnia treatment because of their improved safety profiles. Whether these changes in prescribing influence the incidence of delirium or antipsychotic use in hospitalized patients remain unclear, particularly given the multifactorial nature of delirium. Methods We retrospectively analyzed 79,555 inpatients admitted between 2019 and 2024, excluding those in the psychiatry and neurology wards. The monthly proportions of hypnotic use BZRAs, Z-drugs, melatonin receptor agonists (MRA), and DORAs, antipsychotic use, and psychiatrist-confirmed delirium incidence were evaluated using autoregressive integrated moving average (ARIMA) models. Results ARIMA-based time-series analyses showed significantly decreasing trends in monthly BZRAs and Z-drug use and a significantly increasing trend in DORAs use, while MRA prescriptions remained stable. The incidence of delirium did not show any significant temporal changes over the study period. Overall antipsychotic use remained stable; however, agent-specific analyses revealed distinct time-series patterns, including significant first order moving average components for quetiapine and haloperidol and a positive drift for perospirone. Conclusion A substantial shift toward DORAs occurred without a corresponding reduction in delirium or overall antipsychotic use in older adults. Further research in high-risk cohorts, such as older adults with frequent hypnotic exposure, will help clarify the potential patient-level benefits. delirium hypnotic benzodiazepine receptor agonist dual orexin receptor antagonist antipsychotic Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Insomnia treatment includes several classes of medications, such as benzodiazepine receptor agonists (BZRAs), non-benzodiazepines (Z-drugs), melatonin receptor agonists (MRAs), and dual orexin receptor antagonists (DORAs). In recent years, relatively new hypnotic agents have been increasingly recommended, and several clinical guidelines now include DORAs among the preferred options. ( 1 , 2 ) According to expert consensus guidelines for primary care physicians in Japan, orexin receptor antagonists are recommended as the first-line treatment for both sleep onset and sleep maintenance insomnia. ( 3 ) In addition to their efficacy, DORAs have been reported to have no apparent association with an increased risk of falls and fractures, which is a major safety concern related to traditional hypnotics. ( 4 – 6 ) Conversely, BZRAs, which have traditionally been used, are now considered less favorable because of safety concerns. ( 7 ) These developments indicate that the appropriate use of hypnotics is at a turning point. Delirium is an acute state of confusion characterized by disorientation, incoherent speech, and behavioral changes such as agitation, hallucinations, or delusions. The onset of delirium is clinically significant because it is associated with increased mortality and long-term cognitive decline. ( 8 , 9 ) Delirium is considered a multifactorial condition, and its contributing factors are commonly categorized as predisposing, precipitating, and direct, with medications classified as direct factors. ( 10 ) Among these, BZRAs are recognized as representative drugs associated with delirium risk. ( 11 , 12 ) In contrast, recent reports suggest that specific agents, such as MRAs and DORAs, may help reduce delirium risk. ( 13 – 15 ) Therefore, many insomnia medications are key drugs that can either increase or decrease the risk of delirium. We hypothesized that if prescribing trends have shifted, such as a decrease in BZRA use and an increase in MRA or DORA prescriptions, these changes might lead to a reduction in delirium incidence or a decrease in antipsychotic use for delirium treatment. Thus, this study aimed to clarify the impact of changes in prescribing patterns for insomnia medications on delirium. These findings support ongoing efforts to optimize the use of insomnia medications. Methods Study population This study included patients hospitalized at our institution between January 1, 2019, and December 31, 2024. Patients admitted to the Department of Psychiatry and Neurology were excluded from the study. All data were anonymized to ensure patient confidentiality. This study was approved by the Institutional Review Board of Saga University Hospital (Approval No. 2025-02-05). Informed consent was obtained through an opt-out process on the hospital’s website. Study Design In this study, we assessed the monthly drug utilization rates and incidence of delirium. For each month, the number of patients who received the drug and the number of patients who developed delirium were divided by the total number of hospitalized patients to calculate the respective proportions. The medications of interest included hypnotics and antipsychotic agents. Hypnotics were categorized into four classes: BZRAs (brotizolam, estazolam, etizolam, flunitrazepam, lormetazepam, nitrazepam, quazepam, rilmazafone, and triazolam), Z-drugs (eszopiclone, zopiclone, and zolpidem), MRA (ramelteon), and DORAs (lemborexant and suvorexant). The antipsychotic agents included haloperidol, perospirone, quetiapine, and risperidone. Delirium was defined as a diagnosis confirmed through liaison consultation with the Department of Psychiatry and Neurology, excluding cases related to alcohol consumption. Statistical analysis To evaluate temporal trends in the use of insomnia medications (BZRAs, Z-drugs, DORAs, MRAs, and Antipsychotics) and the incidence of delirium among hospitalized patients, time-series analyses were performed using autoregressive integrated moving average (ARIMA) models. The analyzed series consisted of monthly aggregated proportions of prescriptions for each drug class and monthly delirium incidence rates. All analyses were conducted using R (version 4.4.2; R Core Team, Vienna, Austria; https://www.R-project.org/ ) and SAS software (version 9.4; SAS Institute Inc., Cary, NC, USA). Initial model identification was performed in R using the forecast package and the auto.arima function, with stepwise search and approximation disabled. Candidate models were compared using Akaike’s bias-corrected information criterion (AICc). The final ARIMA models were fitted and evaluated in SAS version 9.4 using PROC ARIMA. All figures were generated using R. An ARIMA (p, d, q) model with a drift term is defined for the d-times differenced series as follows (Eq. 1): $$\:{\nabla\:}^{d}{y}^{t}=c+\sum\:_{i=1}^{p}{\phi\:}_{i}{\nabla\:}^{d}{y}_{t-1}+{\epsilon\:}_{t}+\sum\:_{j=1}^{q}{\theta\:}_{j}{\epsilon\:}_{t-j}\:\:\:\left(1\right)$$ where \(\:{y}^{t}\) denotes the observed value at time t , \(\:{\nabla\:}^{d}\) represents the d-order differencing operator, c is the drift term, \(\:{\phi\:}_{i}\) are autoregressive coefficients, \(\:{\theta\:}_{j}\) are moving-average coefficients, and \(\:{\epsilon\:}_{t}\) is a random error term with mean 0 and constant variance. Linear trends were assessed using the drift term c in Eq. (1). Estimates of the drift and first order moving-average term (MA1), together with their 95% confidence intervals (CIs) and p values, are reported. Statistical significance was defined as a two-sided p value < 0.05. Model adequacy was evaluated using residual diagnostics. Specifically, residuals over time, the autocorrelation function (ACF) of the residuals, the partial autocorrelation function (PACF) of the residuals, and histograms of the residuals were visually inspected to confirm the absence of systematic patterns or remaining autocorrelation. In addition, the Ljung–Box test was applied to assess residual autocorrelation, and a p value ≥ 0.05 was considered indicative that the residuals approximated white noise. Results Time-Series Trends in Hypnotics, Antipsychotics, and Delirium Incidence Based on ARIMA Models A total of 79,555 patients were included in this study. In the time-series analysis of prescription rates for hypnotics, a significant downward trend in the proportion of BZRAs use was observed over the six-year period (drift = − 0.103, 95% CI − 0.165 to − 0.041; p < 0.01; Fig. 1 ). A similar significant downward trend was observed for Z-drugs (drift = − 0.072, 95% CI − 0.118 to − 0.026; p < 0.01). In contrast, the proportion of DORAs use showed a significant increasing trend over the same period (drift = 0.274, 95% CI 0.097 to 0.452; p < 0.01). No significant differences were observed in MRA prescriptions. Across all study periods, the incidence of delirium among hospitalized patients ranged from approximately 0.6% to 2.9%, with no statistically significant differences (Fig. 2 ). Similarly, for the four antipsychotic agents examined in this study, the prescription rate of at least one agent ranged from approximately 2.1% to 4.6%, with no statistically significant differences (Fig. 3 ). For individual antipsychotic agents, quetiapine and haloperidol use showed a significant negative coefficient for MA1, whereas the drift term was not statistically significant. No significant differences were observed in risperidone prescriptions. In contrast, perospirone use showed a significant positive drift, along with a significant negative MA1 (Fig. 4 ). Evaluation of ARIMA Model Fit Based on Residuals and the Ljung–Box Test Residual diagnostics demonstrated a generally adequate model fit across all ARIMA models. For all series, the residuals fluctuated randomly over time, and no systematic patterns were observed in the PACF or residual distributions (Supplementary Figures S1 –S10). The Ljung–Box test indicated no significant residual autocorrelation in most models (p ≥ 0.05). A significant result was observed only for haloperidol (p = 0.03), which was modeled using an ARIMA (4,1,1) specification without a drift term. This model showed a small number of minor spikes in the residual ACF; however, no clear temporal structure was evident in the residual plots, and the absence of a drift term indicated that long-term trend estimation was not affected. Discussion This retrospective analysis of 79,555 hospitalized patients over six years demonstrated a clear institutional shift in prescribing patterns for insomnia, with significant declines in BZRAs and Z-drugs and a marked increase in DORAs. These findings mirror the Japanese expert consensus that increasingly prioritizes newer hypnotics—particularly DORAs—over traditional agents, reflecting the accumulating evidence on safety and tolerability profiles. ( 3 ) Despite the substantial change in hypnotic use, the overall incidence of delirium remained stable across periods (approximately 0.6%–2.9%), and the proportion of patients receiving at least one antipsychotic hovered between 2.1% and 4.6%, without significant differences between cohorts. In contrast, there were shifts within the antipsychotic category: quetiapine and haloperidol prescriptions decreased, whereas perospirone prescriptions increased significantly. Informed by the Japanese expert consensus, our institution established formulary standards for insomnia pharmacotherapy in 2023, prioritizing DORAs. However, our findings indicate that the transition in hypnotic prescriptions had already begun before this policy change. In Japan, the Guidelines for Medical Treatment and its Safety in the Elderly 2015 and subsequent reports documented declines in BZRAs following their dissemination. ( 16 , 17 ) In addition to this guideline-driven shift, growing awareness of safety concerns associated with traditional hypnotics and accumulating evidence favoring the tolerability of DORAs likely accelerated their uptake in routine care. Notwithstanding the observed evolution in insomnia pharmacotherapy, the incidence of delirium did not change materially over the same period. Several factors may account for this null finding. First, the proportion of inpatients exposed to hypnotics was modest; even at the peak of DORA uptake, the exposure was approximately 20%, limiting the capacity to influence hospital-wide rates. Although insomnia is more prevalent among older adults, this study encompassed a broad age range of hospitalized patients, which may have reduced the proportion of patients receiving hypnotic therapy. ( 18 , 19 ) Moreover, delirium is driven by a diverse set of predisposing and precipitating factors, and modifying hypnotic choice alone may be insufficient to shift the aggregate incidence. ( 10 ) Second, reimbursement changes implemented in Japan in 2020 likely increased awareness among clinical staff and prompted more psychiatry consultations for suspected delirium, potentially offsetting any reductions attributable to changes in hypnotic use. Taken together, the stability of delirium incidence despite marked changes in hypnotic prescription, including decreased use of BZRAs and increased use of DORAs, likely reflects limited patient exposure and greater linkage to psychiatric consultation rather than a true absence of pharmacologic effect. Further research, particularly in cohorts with high hypnotic exposure, such as older adults, would help clarify whether these prescribing trends translate into clinically meaningful differences in delirium risk. We hypothesized that the increased use of DORAs, which have been associated with a reduced risk of delirium, might be accompanied by a decrease in the overall antipsychotic prescription. However, no significant changes in total antipsychotic use was observed in this study. One possible explanation is that the study population included hospitalized patients without delirium and, although psychiatric wards were excluded, they likely encompassed individuals with other psychiatric conditions, which may have contributed to stable antipsychotic utilization. When individual antipsychotic agents were examined, a significant increasing trend was observed only for perospirone, whereas no significant long-term trends were detected for the other agents. Perospirone is considered to have relatively weaker sedative effects than other antipsychotics. ( 20 ) Although causal inferences cannot be drawn, this finding may suggest a subtle shift in antipsychotic selection rather than a reduction in overall use. DORAs are characterized by a unique mechanism of action and minimal residual effects. ( 21 ) Their increasing availability may allow clinicians to manage sleep disturbances and delirium-related symptoms without increasing their reliance on strongly sedating antipsychotics. This study has several strengths. It leverages a large, multiyear hospital population, enabling a robust description of the temporal trends in hypnotic drug prescription. It classifies hypnotics based on their mechanism of action, allowing for the clear quantification of the shift from traditional agents to DORAs. However, the limitations of this study warrant caution. First, the retrospective design constrains causal inference, and susceptibility to unmeasured confounding remains. Delirium arises from a complex interplay of predisposing and precipitating factors, making the adjustment for confounders essential; however, this study primarily focused on prescribing patterns rather than comprehensive risk factor control. Second, the choice of antipsychotic agents may vary according to individual physicians’ discretion, and the observed changes may not be solely attributable to shifts in insomnia treatment practices. However, during the study period, the physicians involved in the psychiatric liaison team were trained within the same department, which may have minimized this influence. Finally, case ascertainment may have attenuated detectable differences: our analysis counted only psychiatrist‑diagnosed delirium, and episodes managed by primary teams without psychiatric consultation may have been missed in our analysis. Future prospective studies incorporating comprehensive adjustments for confounders and standardized delirium assessments are warranted to confirm these findings and clarify causal relationships. Conclusions This study documents a pronounced and guideline‑concordant shift in inpatient insomnia pharmacotherapy from BZRAs and Z‑drugs toward DORAs yet finds no corresponding reduction in overall delirium incidence or aggregate antipsychotic use. These results underscore that while optimizing hypnotic selection is a foundational safety step, improving delirium outcomes at the population level requires multifaceted, system‑wide prevention strategies and patient‑level precision in exposure assessment and confounder control. Integrating pharmacologic prudence with comprehensive non‑pharmacologic bundles and focusing on high‑risk cohorts offers a pragmatic path toward realizing the anticipated benefits of contemporary insomnia management on delirium‑related outcomes. Abbreviations ACF autocorrelation function AICc Akaike’s bias-corrected information criterion ARIMA autoregressive integrated moving average BZRA benzodiazepine receptor agonist CI confidence interval DORA dual orexin receptor antagonist MA1 first order moving-average term MRA melatonin receptor agonist PACF partial autocorrelation function Z-drug non-benzodiazepine hypnotic Declarations Ethics approval and consent to participate: This retrospective study was approved by the Institutional Review Board of Saga University Hospital (Approval No. 2025-02-05). Informed consent was obtained via opt-out on the hospital website. Consent for publication: Not applicable. Competing interests: Not applicable. Authors' information: Not applicable. Funding: This study was supported by JSPS KAKENHI (grant nos. 25K19084) from the Japanese Ministry of Education, Culture, Sports, Science and Technology. Author Contribution MW, RS, and YN collected and analyzed the data. MW, RS, and CS designed the study and contributed to manuscript writing. YN, TM-H, TS, HT, YM, and AM supervised the research process and reviewed and edited the manuscript. MW and RS reviewed and edited the manuscript. All authors read and approved the final manuscript. Acknowledgments: Not applicable. Data Availability The datasets used and analyzed during this study are available from the corresponding author upon reasonable request. References Sateia MJ, Buysse DJ, Krystal AD, Heald JL. Clinical Practice Guideline for the Pharmacologic Treatment of Chronic Insomnia in Adults: An American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2017;13:307–49. Riemann D, Espie CA, Altena E, Arnardottir ES, Baglioni C, Bassetti CLA, et al. The European Insomnia Guideline: An update on the diagnosis and treatment of insomnia 2023. J Sleep Res. 2023;32:e14035. Takaesu Y, Sakurai H, Aoki Y, Takeshima M, Ie K, Matsui K, et al. 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Hatta K, Kishi Y, Wada K, Takeuchi T, Hashimoto N, Suda K, et al. Real-World Effectiveness of Ramelteon and Suvorexant for Delirium Prevention in 948 Patients With Delirium Risk Factors. J Clin Psychiatry. 2019;81:19m12865. Akishita M. [Guidelines for medical treatment and its safety in the elderly]. Nihon Ronen Igakkai Zasshi. 2007;44:31–4. Japanese. Okui T, Park J, Hirata A, Nakashima N. Trends in the Prescription of Benzodiazepine Receptor Agonists from 2009 to 2020: A Retrospective Study Using Electronic Healthcare Record Data of a University Hospital in Japan. Healthc (Basel). 2021;9:1724. Morin CM, Jarrin DC. Epidemiology of Insomnia: Prevalence, Course, Risk Factors, and Public Health Burden. Sleep Med Clin. 2022;17:173–91. León-Barriera R, Chaplin MM, Kaur J, Modesto-Lowe V. Insomnia in older adults: A review of treatment options. Cleve Clin J Med. 2025;92:43–50. Valencia Carlo YE, Saracco-Alvarez RA, Valencia Carlo VA, Vázquez Vega D, Natera Rey G, Escamilla Orozco RI. Adverse effects of antipsychotics on sleep in patients with schizophrenia. Systematic review and meta-analysis. Front Psychiatry. 2023;14:1189768. Gotter AL, Winrow CJ, Brunner J, Garson SL, Fox SV, Binns J, et al. The duration of sleep promoting efficacy by dual orexin receptor antagonists is dependent upon receptor occupancy threshold. BMC Neurosci. 2013;14:90. Additional Declarations No competing interests reported. Supplementary Files SuppFig.pptx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8673561","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":581735286,"identity":"47351994-f31a-4966-adcf-13846657c051","order_by":0,"name":"Mao Washida","email":"","orcid":"","institution":"Saga University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mao","middleName":"","lastName":"Washida","suffix":""},{"id":581735287,"identity":"fb4ee3af-df75-429a-877c-1f3be487cf15","order_by":1,"name":"Rintaro 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hypnotic\u003c/p\u003e","description":"","filename":"Slide1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/475444a29b04abafb79c350a.jpg"},{"id":101436876,"identity":"21c081b5-d869-443d-800b-c4ba4d4e55c8","added_by":"auto","created_at":"2026-01-29 16:26:39","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":61129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTime-series trends in delirium incidence from 2019 to 2024\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Slide2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/87224fdacdc429c42b1ab2fb.jpg"},{"id":101436958,"identity":"aba11c80-2b3c-4d95-b7b3-70f258642322","added_by":"auto","created_at":"2026-01-29 16:26:56","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":62583,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTime-series trends in overall antipsychotic prescription rates from 2019 to 2024\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Slide3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/183f47dd905191c9ff3de4ed.jpg"},{"id":101436881,"identity":"f11f06a2-7a94-4778-a3fd-03e866767470","added_by":"auto","created_at":"2026-01-29 16:26:41","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":142502,"visible":true,"origin":"","legend":"\u003cp\u003eLegend not included with this version.\u003cstrong\u003eTime-series trends in individual antipsychotic prescription rates from 2019 to 2024\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Slide4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/85f9d1e7a3c6cac5c3e249f7.jpg"},{"id":102832299,"identity":"e2c8c602-e265-4471-905e-2ea2afdda5d2","added_by":"auto","created_at":"2026-02-17 10:12:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1109230,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/03419db2-4d06-492b-ada1-dc94c919bd98.pdf"},{"id":101436879,"identity":"af96c566-daf8-4276-a133-22b42600de3b","added_by":"auto","created_at":"2026-01-29 16:26:40","extension":"pptx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":2169367,"visible":true,"origin":"","legend":"","description":"","filename":"SuppFig.pptx","url":"https://assets-eu.researchsquare.com/files/rs-8673561/v1/856fdd5ca2f9c27aac0eba5f.pptx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trends and Associations of Insomnia Medications with Delirium: A Single- Center Cohort Retrospective Study","fulltext":[{"header":"Background","content":"\u003cp\u003eInsomnia treatment includes several classes of medications, such as benzodiazepine receptor agonists (BZRAs), non-benzodiazepines (Z-drugs), melatonin receptor agonists (MRAs), and dual orexin receptor antagonists (DORAs). In recent years, relatively new hypnotic agents have been increasingly recommended, and several clinical guidelines now include DORAs among the preferred options. \u003csup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/sup\u003e According to expert consensus guidelines for primary care physicians in Japan, orexin receptor antagonists are recommended as the first-line treatment for both sleep onset and sleep maintenance insomnia. \u003csup\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/sup\u003e In addition to their efficacy, DORAs have been reported to have no apparent association with an increased risk of falls and fractures, which is a major safety concern related to traditional hypnotics. \u003csup\u003e(\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/sup\u003e Conversely, BZRAs, which have traditionally been used, are now considered less favorable because of safety concerns. \u003csup\u003e(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/sup\u003e These developments indicate that the appropriate use of hypnotics is at a turning point.\u003c/p\u003e \u003cp\u003eDelirium is an acute state of confusion characterized by disorientation, incoherent speech, and behavioral changes such as agitation, hallucinations, or delusions. The onset of delirium is clinically significant because it is associated with increased mortality and long-term cognitive decline. \u003csup\u003e(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/sup\u003e Delirium is considered a multifactorial condition, and its contributing factors are commonly categorized as predisposing, precipitating, and direct, with medications classified as direct factors. \u003csup\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/sup\u003e Among these, BZRAs are recognized as representative drugs associated with delirium risk. \u003csup\u003e(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/sup\u003e In contrast, recent reports suggest that specific agents, such as MRAs and DORAs, may help reduce delirium risk. \u003csup\u003e(\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/sup\u003e Therefore, many insomnia medications are key drugs that can either increase or decrease the risk of delirium.\u003c/p\u003e \u003cp\u003eWe hypothesized that if prescribing trends have shifted, such as a decrease in BZRA use and an increase in MRA or DORA prescriptions, these changes might lead to a reduction in delirium incidence or a decrease in antipsychotic use for delirium treatment. Thus, this study aimed to clarify the impact of changes in prescribing patterns for insomnia medications on delirium. These findings support ongoing efforts to optimize the use of insomnia medications.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThis study included patients hospitalized at our institution between January 1, 2019, and December 31, 2024. Patients admitted to the Department of Psychiatry and Neurology were excluded from the study. All data were anonymized to ensure patient confidentiality. This study was approved by the Institutional Review Board of Saga University Hospital (Approval No. 2025-02-05). Informed consent was obtained through an opt-out process on the hospital\u0026rsquo;s website.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eIn this study, we assessed the monthly drug utilization rates and incidence of delirium. For each month, the number of patients who received the drug and the number of patients who developed delirium were divided by the total number of hospitalized patients to calculate the respective proportions. The medications of interest included hypnotics and antipsychotic agents. Hypnotics were categorized into four classes: BZRAs (brotizolam, estazolam, etizolam, flunitrazepam, lormetazepam, nitrazepam, quazepam, rilmazafone, and triazolam), Z-drugs (eszopiclone, zopiclone, and zolpidem), MRA (ramelteon), and DORAs (lemborexant and suvorexant). The antipsychotic agents included haloperidol, perospirone, quetiapine, and risperidone. Delirium was defined as a diagnosis confirmed through liaison consultation with the Department of Psychiatry and Neurology, excluding cases related to alcohol consumption.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo evaluate temporal trends in the use of insomnia medications (BZRAs, Z-drugs, DORAs, MRAs, and Antipsychotics) and the incidence of delirium among hospitalized patients, time-series analyses were performed using autoregressive integrated moving average (ARIMA) models. The analyzed series consisted of monthly aggregated proportions of prescriptions for each drug class and monthly delirium incidence rates. All analyses were conducted using R (version 4.4.2; R Core Team, Vienna, Austria; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org/\u003c/span\u003e\u003cspan address=\"https://www.R-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and SAS software (version 9.4; SAS Institute Inc., Cary, NC, USA). Initial model identification was performed in R using the \u003cem\u003eforecast\u003c/em\u003e package and the auto.arima function, with stepwise search and approximation disabled. Candidate models were compared using Akaike\u0026rsquo;s bias-corrected information criterion (AICc). The final ARIMA models were fitted and evaluated in SAS version 9.4 using PROC ARIMA. All figures were generated using R. An ARIMA (p, d, q) model with a drift term is defined for the d-times differenced series as follows (Eq.\u0026nbsp;1):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:{\\nabla\\:}^{d}{y}^{t}=c+\\sum\\:_{i=1}^{p}{\\phi\\:}_{i}{\\nabla\\:}^{d}{y}_{t-1}+{\\epsilon\\:}_{t}+\\sum\\:_{j=1}^{q}{\\theta\\:}_{j}{\\epsilon\\:}_{t-j}\\:\\:\\:\\left(1\\right)$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{y}^{t}\\)\u003c/span\u003e\u003c/span\u003e denotes the observed value at time \u003cem\u003et\u003c/em\u003e, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\nabla\\:}^{d}\\)\u003c/span\u003e\u003c/span\u003e represents the d-order differencing operator, \u003cem\u003ec\u003c/em\u003e is the drift term, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\phi\\:}_{i}\\)\u003c/span\u003e\u003c/span\u003e are autoregressive coefficients, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\theta\\:}_{j}\\)\u003c/span\u003e\u003c/span\u003e are moving-average coefficients, and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\epsilon\\:}_{t}\\)\u003c/span\u003e\u003c/span\u003e is a random error term with mean 0 and constant variance. Linear trends were assessed using the drift term \u003cem\u003ec\u003c/em\u003e in Eq.\u0026nbsp;(1). Estimates of the drift and first order moving-average term (MA1), together with their 95% confidence intervals (CIs) and p values, are reported. Statistical significance was defined as a two-sided p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Model adequacy was evaluated using residual diagnostics. Specifically, residuals over time, the autocorrelation function (ACF) of the residuals, the partial autocorrelation function (PACF) of the residuals, and histograms of the residuals were visually inspected to confirm the absence of systematic patterns or remaining autocorrelation. In addition, the Ljung\u0026ndash;Box test was applied to assess residual autocorrelation, and a p value\u0026thinsp;\u0026ge;\u0026thinsp;0.05 was considered indicative that the residuals approximated white noise.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eTime-Series Trends in Hypnotics, Antipsychotics, and Delirium Incidence Based on ARIMA Models\u003c/h2\u003e \u003cp\u003eA total of 79,555 patients were included in this study. In the time-series analysis of prescription rates for hypnotics, a significant downward trend in the proportion of BZRAs use was observed over the six-year period (drift\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.103, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;0.165 to \u0026minus;\u0026thinsp;0.041; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A similar significant downward trend was observed for Z-drugs (drift\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.072, 95% CI\u0026thinsp;\u0026minus;\u0026thinsp;0.118 to \u0026minus;\u0026thinsp;0.026; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). In contrast, the proportion of DORAs use showed a significant increasing trend over the same period (drift\u0026thinsp;=\u0026thinsp;0.274, 95% CI 0.097 to 0.452; p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). No significant differences were observed in MRA prescriptions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAcross all study periods, the incidence of delirium among hospitalized patients ranged from approximately 0.6% to 2.9%, with no statistically significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similarly, for the four antipsychotic agents examined in this study, the prescription rate of at least one agent ranged from approximately 2.1% to 4.6%, with no statistically significant differences (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For individual antipsychotic agents, quetiapine and haloperidol use showed a significant negative coefficient for MA1, whereas the drift term was not statistically significant. No significant differences were observed in risperidone prescriptions. In contrast, perospirone use showed a significant positive drift, along with a significant negative MA1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of ARIMA Model Fit Based on Residuals and the Ljung\u0026ndash;Box Test\u003c/h2\u003e \u003cp\u003eResidual diagnostics demonstrated a generally adequate model fit across all ARIMA models. For all series, the residuals fluctuated randomly over time, and no systematic patterns were observed in the PACF or residual distributions (Supplementary Figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u0026ndash;S10).\u003c/p\u003e \u003cp\u003eThe Ljung\u0026ndash;Box test indicated no significant residual autocorrelation in most models (p\u0026thinsp;\u0026ge;\u0026thinsp;0.05). A significant result was observed only for haloperidol (p\u0026thinsp;=\u0026thinsp;0.03), which was modeled using an ARIMA (4,1,1) specification without a drift term. This model showed a small number of minor spikes in the residual ACF; however, no clear temporal structure was evident in the residual plots, and the absence of a drift term indicated that long-term trend estimation was not affected.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis retrospective analysis of 79,555 hospitalized patients over six years demonstrated a clear institutional shift in prescribing patterns for insomnia, with significant declines in BZRAs and Z-drugs and a marked increase in DORAs. These findings mirror the Japanese expert consensus that increasingly prioritizes newer hypnotics\u0026mdash;particularly DORAs\u0026mdash;over traditional agents, reflecting the accumulating evidence on safety and tolerability profiles. \u003csup\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/sup\u003e Despite the substantial change in hypnotic use, the overall incidence of delirium remained stable across periods (approximately 0.6%\u0026ndash;2.9%), and the proportion of patients receiving at least one antipsychotic hovered between 2.1% and 4.6%, without significant differences between cohorts. In contrast, there were shifts within the antipsychotic category: quetiapine and haloperidol prescriptions decreased, whereas perospirone prescriptions increased significantly.\u003c/p\u003e \u003cp\u003eInformed by the Japanese expert consensus, our institution established formulary standards for insomnia pharmacotherapy in 2023, prioritizing DORAs. However, our findings indicate that the transition in hypnotic prescriptions had already begun before this policy change. In Japan, the Guidelines for Medical Treatment and its Safety in the Elderly 2015 and subsequent reports documented declines in BZRAs following their dissemination. \u003csup\u003e(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/sup\u003e In addition to this guideline-driven shift, growing awareness of safety concerns associated with traditional hypnotics and accumulating evidence favoring the tolerability of DORAs likely accelerated their uptake in routine care.\u003c/p\u003e \u003cp\u003eNotwithstanding the observed evolution in insomnia pharmacotherapy, the incidence of delirium did not change materially over the same period. Several factors may account for this null finding. First, the proportion of inpatients exposed to hypnotics was modest; even at the peak of DORA uptake, the exposure was approximately 20%, limiting the capacity to influence hospital-wide rates. Although insomnia is more prevalent among older adults, this study encompassed a broad age range of hospitalized patients, which may have reduced the proportion of patients receiving hypnotic therapy. \u003csup\u003e(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/sup\u003e Moreover, delirium is driven by a diverse set of predisposing and precipitating factors, and modifying hypnotic choice alone may be insufficient to shift the aggregate incidence. \u003csup\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/sup\u003e Second, reimbursement changes implemented in Japan in 2020 likely increased awareness among clinical staff and prompted more psychiatry consultations for suspected delirium, potentially offsetting any reductions attributable to changes in hypnotic use. Taken together, the stability of delirium incidence despite marked changes in hypnotic prescription, including decreased use of BZRAs and increased use of DORAs, likely reflects limited patient exposure and greater linkage to psychiatric consultation rather than a true absence of pharmacologic effect. Further research, particularly in cohorts with high hypnotic exposure, such as older adults, would help clarify whether these prescribing trends translate into clinically meaningful differences in delirium risk.\u003c/p\u003e \u003cp\u003eWe hypothesized that the increased use of DORAs, which have been associated with a reduced risk of delirium, might be accompanied by a decrease in the overall antipsychotic prescription. However, no significant changes in total antipsychotic use was observed in this study. One possible explanation is that the study population included hospitalized patients without delirium and, although psychiatric wards were excluded, they likely encompassed individuals with other psychiatric conditions, which may have contributed to stable antipsychotic utilization. When individual antipsychotic agents were examined, a significant increasing trend was observed only for perospirone, whereas no significant long-term trends were detected for the other agents. Perospirone is considered to have relatively weaker sedative effects than other antipsychotics. \u003csup\u003e(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/sup\u003e Although causal inferences cannot be drawn, this finding may suggest a subtle shift in antipsychotic selection rather than a reduction in overall use. DORAs are characterized by a unique mechanism of action and minimal residual effects. \u003csup\u003e(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/sup\u003e Their increasing availability may allow clinicians to manage sleep disturbances and delirium-related symptoms without increasing their reliance on strongly sedating antipsychotics.\u003c/p\u003e \u003cp\u003eThis study has several strengths. It leverages a large, multiyear hospital population, enabling a robust description of the temporal trends in hypnotic drug prescription. It classifies hypnotics based on their mechanism of action, allowing for the clear quantification of the shift from traditional agents to DORAs. However, the limitations of this study warrant caution. First, the retrospective design constrains causal inference, and susceptibility to unmeasured confounding remains. Delirium arises from a complex interplay of predisposing and precipitating factors, making the adjustment for confounders essential; however, this study primarily focused on prescribing patterns rather than comprehensive risk factor control. Second, the choice of antipsychotic agents may vary according to individual physicians\u0026rsquo; discretion, and the observed changes may not be solely attributable to shifts in insomnia treatment practices. However, during the study period, the physicians involved in the psychiatric liaison team were trained within the same department, which may have minimized this influence. Finally, case ascertainment may have attenuated detectable differences: our analysis counted only psychiatrist‑diagnosed delirium, and episodes managed by primary teams without psychiatric consultation may have been missed in our analysis. Future prospective studies incorporating comprehensive adjustments for confounders and standardized delirium assessments are warranted to confirm these findings and clarify causal relationships.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e This study documents a pronounced and guideline‑concordant shift in inpatient insomnia pharmacotherapy from BZRAs and Z‑drugs toward DORAs yet finds no corresponding reduction in overall delirium incidence or aggregate antipsychotic use. These results underscore that while optimizing hypnotic selection is a foundational safety step, improving delirium outcomes at the population level requires multifaceted, system‑wide prevention strategies and patient‑level precision in exposure assessment and confounder control. Integrating pharmacologic prudence with comprehensive non‑pharmacologic bundles and focusing on high‑risk cohorts offers a pragmatic path toward realizing the anticipated benefits of contemporary insomnia management on delirium‑related outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eautocorrelation function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAICc\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAkaike\u0026rsquo;s bias-corrected information criterion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARIMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eautoregressive integrated moving average\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBZRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebenzodiazepine receptor agonist\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDORA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edual orexin receptor antagonist\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMA1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efirst order moving-average term\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emelatonin receptor agonist\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePACF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epartial autocorrelation function\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eZ-drug\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enon-benzodiazepine hypnotic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e \u003cp\u003e This retrospective study was approved by the Institutional Review Board of Saga University Hospital (Approval No. 2025-02-05). Informed consent was obtained via opt-out on the hospital website.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication:\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eAuthors' information:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis study was supported by JSPS KAKENHI (grant nos. 25K19084) from the Japanese Ministry of Education, Culture, Sports, Science and Technology.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMW, RS, and YN collected and analyzed the data. MW, RS, and CS designed the study and contributed to manuscript writing. YN, TM-H, TS, HT, YM, and AM supervised the research process and reviewed and edited the manuscript. MW and RS reviewed and edited the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSateia MJ, Buysse DJ, Krystal AD, Heald JL. Clinical Practice Guideline for the Pharmacologic Treatment of Chronic Insomnia in Adults: An American Academy of Sleep Medicine Clinical Practice Guideline. J Clin Sleep Med. 2017;13:307\u0026ndash;49.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiemann D, Espie CA, Altena E, Arnardottir ES, Baglioni C, Bassetti CLA, et al. The European Insomnia Guideline: An update on the diagnosis and treatment of insomnia 2023. J Sleep Res. 2023;32:e14035.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTakaesu Y, Sakurai H, Aoki Y, Takeshima M, Ie K, Matsui K, et al. Treatment strategy for insomnia disorder: Japanese expert consensus. Front Psychiatry. 2023;14:1168100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePan G, Ni L, Yan H, Yao L. Association between the use of orexin receptor antagonists and falls or fractures: A meta-analysis. J Psychiatr Res. 2024;176:393\u0026ndash;402.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSogawa R, Emoto A, Monji A, Miyamoto Y, Yukawa M, Murakawa-Hirachi T, et al. Association of orexin receptor antagonists with falls during hospitalization. J Clin Pharm Ther. 2022;47:809\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHirata R, Katsuki NE, Shimada H, Nakatani E, Shikino K, Saito C, et al. The Administration of Lemborexant at Admission is Not Associated with Inpatient Falls: A Multicenter Retrospective Observational Study. Int J Gen Med. 2024;17:1139\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarkota M, Rummans TA, Bostwick JM, Lapid MI. Benzodiazepine Use in Older Adults: Dangers, Management, and Alternative Therapies. Mayo Clin Proc. 2016;91:1632-9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLin SM, Liu CY, Wang CH, Lin HC, Huang CD, Huang PY, et al. The impact of delirium on the survival of mechanically ventilated patients. Crit Care Med. 2004;32:2254\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePandharipande PP, Girard TD, Jackson JC, Morandi A, Thompson JL, Pun BT, et al. Long-term cognitive impairment after critical illness. N Engl J Med. 2013;369:1306\u0026ndash;16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipowski ZJ. Delirium: Acute Confusional States. Oxford University Press; 1990.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClegg A, Young JB. Which medications to avoid in people at risk of delirium: a systematic review. Age Ageing. 2011;40:23\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKassie GM, Nguyen TA, Kalisch Ellett LM, Pratt NL, Roughead EE. Preoperative medication use and postoperative delirium: a systematic review. BMC Geriatr 29. 2017;17:298.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHatta K, Kishi Y, Wada K, Takeuchi T, Odawara T, Usui C, et al. Preventive effects of ramelteon on delirium: a randomized placebo-controlled trial. JAMA Psychiatry. 2014;71:397\u0026ndash;403.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHatta K, Kishi Y, Wada K, Takeuchi T, Ito S, Kurata A, et al. Preventive Effects of Suvorexant on Delirium: A Randomized Placebo-Controlled Trial. J Clin Psychiatry. 2017;78:e970\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHatta K, Kishi Y, Wada K, Takeuchi T, Hashimoto N, Suda K, et al. Real-World Effectiveness of Ramelteon and Suvorexant for Delirium Prevention in 948 Patients With Delirium Risk Factors. J Clin Psychiatry. 2019;81:19m12865.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkishita M. [Guidelines for medical treatment and its safety in the elderly]. Nihon Ronen Igakkai Zasshi. 2007;44:31\u0026ndash;4. Japanese.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkui T, Park J, Hirata A, Nakashima N. Trends in the Prescription of Benzodiazepine Receptor Agonists from 2009 to 2020: A Retrospective Study Using Electronic Healthcare Record Data of a University Hospital in Japan. Healthc (Basel). 2021;9:1724.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorin CM, Jarrin DC. Epidemiology of Insomnia: Prevalence, Course, Risk Factors, and Public Health Burden. Sleep Med Clin. 2022;17:173\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe\u0026oacute;n-Barriera R, Chaplin MM, Kaur J, Modesto-Lowe V. Insomnia in older adults: A review of treatment options. Cleve Clin J Med. 2025;92:43\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eValencia Carlo YE, Saracco-Alvarez RA, Valencia Carlo VA, V\u0026aacute;zquez Vega D, Natera Rey G, Escamilla Orozco RI. Adverse effects of antipsychotics on sleep in patients with schizophrenia. Systematic review and meta-analysis. Front Psychiatry. 2023;14:1189768.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGotter AL, Winrow CJ, Brunner J, Garson SL, Fox SV, Binns J, et al. The duration of sleep promoting efficacy by dual orexin receptor antagonists is dependent upon receptor occupancy threshold. BMC Neurosci. 2013;14:90.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"delirium, hypnotic, benzodiazepine receptor agonist, dual orexin receptor antagonist, antipsychotic","lastPublishedDoi":"10.21203/rs.3.rs-8673561/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8673561/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e Clinical guidelines increasingly recommend dual orexin receptor antagonists (DORAs) over benzodiazepine receptor agonists (BZRAs) and non-benzodiazepines (Z-drugs) for insomnia treatment because of their improved safety profiles. Whether these changes in prescribing influence the incidence of delirium or antipsychotic use in hospitalized patients remain unclear, particularly given the multifactorial nature of delirium.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrospectively analyzed 79,555 inpatients admitted between 2019 and 2024, excluding those in the psychiatry and neurology wards. The monthly proportions of hypnotic use BZRAs, Z-drugs, melatonin receptor agonists (MRA), and DORAs, antipsychotic use, and psychiatrist-confirmed delirium incidence were evaluated using autoregressive integrated moving average (ARIMA) models.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eARIMA-based time-series analyses showed significantly decreasing trends in monthly BZRAs and Z-drug use and a significantly increasing trend in DORAs use, while MRA prescriptions remained stable. The incidence of delirium did not show any significant temporal changes over the study period. Overall antipsychotic use remained stable; however, agent-specific analyses revealed distinct time-series patterns, including significant first order moving average components for quetiapine and haloperidol and a positive drift for perospirone.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eA substantial shift toward DORAs occurred without a corresponding reduction in delirium or overall antipsychotic use in older adults. Further research in high-risk cohorts, such as older adults with frequent hypnotic exposure, will help clarify the potential patient-level benefits.\u003c/p\u003e","manuscriptTitle":"Trends and Associations of Insomnia Medications with Delirium: A Single- Center Cohort Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 16:26:15","doi":"10.21203/rs.3.rs-8673561/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7ea0ad9f-c3ab-44ca-9e1e-b7598a425b9f","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-17T10:10:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 16:26:15","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8673561","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8673561","identity":"rs-8673561","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}