ECT and Psychiatric Rehospitalization Rates: A Retrospective Study

ECT and Psychiatric Rehospitalization Rates: A 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article ECT and Psychiatric Rehospitalization Rates: A Retrospective Study Aneesh Rahangdale, Joshua Wasdin, Jeffrey Ferraro This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4510944/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2024 Read the published version in BMC Psychiatry → Version 1 posted 12 You are reading this latest preprint version Abstract Background Electroconvulsive therapy (ECT) induces a generalized seizure under anesthesia with an electrical current for treatment-resistant patients and may be underutilized. To our knowledge, no large-scale, American, nationwide hospital system retrospective study has examined how ECT affects psychiatric rehospitalization chances. Methods We analyzed initial inpatient encounters for adults aged > 18 years at HCA Healthcare Behavioral Health Units from 2016–2021 with diagnoses of major depressive disorder with/without psychosis, bipolar disorder with/without psychosis, schizoaffective disorder, and schizophrenia. Excluding pregnancy and incarceration cases, we compared psychiatric rehospitalization rates within 365 days for patients receiving ECT versus those with the same diagnoses not receiving ECT. Subgroup analyses were conducted by diagnosis, length of stay, sex, and race. Detailed statistical analyses included bivariate analyses with Fisher's Exact Test and Wilcoxon Rank Sum Test. Results We analyzed 38,109 distinct patients, 637 of which received ECT. The readmission rate was 37.52% for ECT recipients versus 20.71% for non-ECT patients (p < 0.0001). ECT was associated with higher readmission rates, particularly for severe diagnoses like psychosis (87.28%), schizoaffective disorder (3.77%), and schizophrenia (6.59%). ECT patients had significantly longer readmission lengths of stay (mean 14.53 days vs 6.54 days for non-ECT, p < 0.0001). White patients received ECT more frequently. Females received ECT more often, while males had higher readmission rates. Conclusions ECT was associated with higher psychiatric rehospitalization rates and longer lengths of stay. This suggests ECT is more commonly used for complex, severe cases which may contribute to higher rehospitalization. Stronger social support and hospital and geographic ties among ECT patients may also play a role. Electroconvulsive therapy (ECT) psychiatric rehospitalization length of stay readmission Figures Figure 1 Figure 2 Figure 3 Background Electroconvulsive therapy (ECT) induces a generalized seizure under anesthesia with an electrical current for treatment-resistant patients with severe depression, bipolar disorder, schizophrenia, schizoaffective disorder, catatonia, and neuroleptic malignant syndrome. 1 , 2 Evidence suggests ECT is underutilized as a treatment modality. 3 One naturalistic retrospective cohort study in Singapore found that outpatient continuation/maintenance electroconvulsive therapy (CM-ECT) after an acute inpatient course of ECT was associated with significantly lower risks of psychiatric readmission (adjusted hazard ratio of 0.68) and lower total direct healthcare costs compared to not receiving CM-ECT, especially for patients with mood disorders. 4 Another Chinese study found that ECT lowered readmission for patients with schizophrenia within 3 months (11.37% vs 18.79%) and 6 months (17.94% vs 29.36%) compared to patients who did not receive ECT, especially for patients who received 9 or more ECT treatments had the lowest readmission rates. 5 In that study, male sex, older age, being married, lower income, shorter inpatient stay increased readmission risk. To our knowledge, no large-scale, American, nationwide hospital system retrospective study has examined how ECT affects psychiatric rehospitalization chances. This may bolster arguments for employing ECT earlier in the treatment course for severe, persistent mental illness and provide insights regarding larger demographic trends in the American healthcare system. Methods We analyzed initial encounters for adult patients (> 18 years) hospitalized at HCA Healthcare Behavioral Health Units from 2016–2021 for major depressive disorder with/without psychosis, bipolar disorder with/without psychosis, schizoaffective disorder, and schizophrenia diagnoses (F codes F 33.2, F 33.3, F 31.2, F 31.4, F 31.13, F 31.5, F 31.63, F 31.64, F25, F20). Excluding pregnancy and incarceration cases, we investigated psychiatric rehospitalization rates within 365 days for patients receiving ECT (procedure codes GZB 0–4) versus those with the same diagnoses not receiving ECT from January 2016 – December 2021. Subgroup analyses were conducted for diagnoses, length of stay for readmission, sex, and race. Detailed statistical analyses (bivariate analyses with Fisher’s Exact Test, Wilcoxon Rank Sum Test) were done. Results We analyzed 39392 initial encounters for adult patients (> 18 years old) who have been hospitalized at an HCA Healthcare Behavioral Health Unit for major depressive disorder with and without psychosis, bipolar disorder with and without psychosis, schizoaffective disorder, and schizophrenia from 1 January 2016 to 31 December 2021. We investigated psychiatric rehospitalization rates for patients getting ECT compared to patients with the same diagnostic codes from 01-01-2016 through 12-31-2021 to allow for a full year of readmission data. Thus, the total time frame was 2016 through the end of 2022. Of these patients, 1283 were excluded for pregnancy or discharge to or from prison. Of the 38109 distinct patients analyzed, 637 patients were treated with Electroconvulsive Therapy (ECT). The mean age of the total population was 44.27 years (SD = 18.24), with ECT patients averaging 59.48 years (SD = 17.10) and readmitted patients averaging 45.49 years (SD = 16.21). Gender distribution for the total population was 50.11% female and 49.89% male, whereas the ECT population had a higher percentage of females (60.13%) compared to males (39.87%). Racial demographics showed that the majority of the total population was White (71.38%), followed by Black (20.35%) and Other races (8.27%). Among ECT patients, 85.56% were White, 7.69% were Black, and 6.75% were of other races. Most ECT patients had major depressive disorder with psychotic features (55%) (Fig. 1 ). Diagnosis distribution indicated that 3.65% of the total population were diagnosed with Major Depressive Disorder (MDD) without psychosis, with this rate higher among ECT patients (9.42%). For MDD with psychosis, 55.55% of the total population were diagnosed, with a significantly higher percentage among ECT patients (87.28%). Bipolar Disorder with psychosis was diagnosed in 0.44% of the total population, with ECT patients showing a higher rate (1.10%). Schizoaffective Disorder was diagnosed in 2.58% of the total population, with ECT patients having a slightly higher incidence (3.77%). Schizophrenia was present in 3.80% of the total population, with ECT patients showing a higher rate (6.59%). The readmission rate was 37.52% for ECT recipients versus 20.71% for non-ECT patients (p < 0.0001) (Table 1 ). There was a significant overall association between ECT and readmission (p < 0.0001), but no significant directional associations based on coefficients (Table 2 ). The readmission rate within one year for the overall population was 20.99% (95% CI: 20.58–21.40%), with a significantly higher rate for ECT patients at 37.52% (95% CI: 33.76–41.28%) compared to non-ECT patients at 20.71%. The mean length of stay (LOS) for readmissions was significantly longer for ECT patients, with a mean of 14.53 days (SD = 15.94, 95% CI: 12.51–16.55), compared to the total population’s average LOS of 6.54 days (SD = 7.21, 95% CI: 6.38–6.70). Chi-Square and Wilcoxon Rank Sum Tests confirmed statistically significant associations between ECT and higher readmission rates (p < 0.0001) and in average psychiatric ward readmission LOS between ECT and non-ECT patients (Z = 15.5648, p < 0.0001). Table 1 Comparison of ECT and Non-ECT Patients on Key Variables. This table presents demographic characteristics, diagnosis distributions, readmission rates within 1 year, and length of stay for psychiatric readmissions, comparing patients who underwent electroconvulsive therapy (ECT) to those who did not receive ECT. Data is from an initial sample of 38,109 distinct patient encounters after excluding pregnancies and prison transfers. ECT patients were older on average (mean age 59.5 vs 44.3 for total population). 60.1% of ECT patients were female compared to 50.1% in the total population. ECT patients had higher rates of major depressive disorder with psychosis (87.3% vs 55.6%). 37.5% of ECT patients were readmitted within 1 year, compared to only 20.7% of non-ECT patients. For readmitted patients, mean length of stay was 14.5 days for the ECT group versus 6.5 days for the total population. Demographic Variable Total Population ECT Patients Non-ECT Patients Readmitted Patients Sample Size 38,109 637 37,472 8,000 Mean Age (years) 44.27 (SD = 18.24) 59.48 (SD = 17.10) - 45.49 (SD = 16.21) Gender Distribution - Female (%) 50.11 60.13 - - - Male (%) 49.89 39.87 - - Racial Distribution - White (%) 71.38 85.56 - - - Black (%) 20.35 7.69 - - - Other (%) 8.27 6.75 - - Readmission Rate (%) 20.99 (95% CI: 20.58–21.40) 37.52 (95% CI: 33.76–41.28) 20.71 - Diagnosis Distribution - MDD without Psychosis (%) 3.65 9.42 - - - MDD with Psychosis (%) 55.55 87.28 - - - Bipolar Disorder with Psychosis (%) 0.44 1.10 - - - Schizoaffective Disorder (%) 2.58 3.77 - - - Schizophrenia (%) 3.80 6.59 - - Length of Stay (LOS) for Readmissions (days) 6.54 (SD = 7.21, 95% CI: 6.38–6.70) 14.53 (SD = 15.94, 95% CI: 12.51–16.55) - - Table 2 With a sample size of 38109, there was a significant overall association between ECT and Readmission (p-value < 0.0001) at the 95% (α = .05) confidence limit. There was a significant difference in the proportion of patients who had a readmission after cross-tabbing by ECT. Based on analyses by Phi Coefficients, Cramer's V, and Contingency Coefficients, there was a weak strength of association between these two variables. Statistics for Cross Sectional Analysis of ECT by Readmission (n = 38109) DF Value Probability Chi-Square 1 106.6910 < 0.0001 Likelihood Ratio Chi-Square 1 92.5509 < 0.0001 Continuity Adjusted Chi-Square 1 105.6800 < 0.0001 Mantel-Haenszel Chi-Square 1 106.6882 < 0.0001 Phi Coefficient 0.0529 Contingency Coefficient 0.0528 Cramer’s V 0.0529 Over 90% of psychiatric inpatients stayed < 20 days, while a right skew showed some very long stays (Fig. 2 ). ECT patients had a significantly longer average readmission length of stay (Z = 15.5648, p < 0.0001) (Fig. 3 ). No significant age differences existed between ECT/non-ECT or readmitted/non-readmitted groups when adjusted for diagnoses. White patients received ECT more frequently. Men were readmitted more often, while women received ECT more frequently. Subgroup analyses by diagnoses yielded similar findings. Overall, the data demonstrate that ECT was associated with higher readmission rates, even when accounting for individual diagnoses. ECT patients also experienced significantly longer readmission lengths of stay compared to non-ECT patients. Discussion In summary, patients who received ECT were generally older, more likely to be female, and predominantly white. They also had higher rates of severe psychiatric diagnoses such as MDD with psychosis, bipolar disorder with psychosis, schizoaffective disorder, and schizophrenia. ECT is associated with higher readmission rates and longer lengths of stay, particularly among patients diagnoses such as Bipolar Disorder with psychosis, Schizoaffective Disorder, and Schizophrenia. These findings suggest that ECT is more commonly used in patients with more severe and complex psychiatric conditions, which may contribute to the higher readmission rates observed in this group. There was a significant association between ECT and increased rehospitalization (p < 0.0001), potentially because ECT patients are higher utilizers of inpatient psychiatric services and/or more likely to follow up and re-hospitalize at the same hospital if their mental health worsens compared to non-ECT patients with the same diagnosis. Robust social support systems and geographic roots may make ECT patients more likely to re-admit to the same hospital. ECT patients had significantly longer readmission lengths of stay (p < 0.0001), possibly because they have higher illness acuity requiring more time to stabilize, even with the same diagnostic code as non-ECT patients. For example, a patient with severe major depressive disorder may have had more instances of rehospitalization and failed medication trials if they get ECT than another patient with severe major depressive disorder. As such, with rehospitalization, they are more likely to need a longer amount of time to stabilize. Moreover, the measures of association (Phi Coefficient, Contingency Coefficient, and Cramer’s V) suggest that the strength of the association between ECT and readmission rates is very weak. The measures of association (Phi, Contingency Coefficient, and Cramer’s V) indicate the strength of the relationship is very low. With a large sample size (n = 38,109), even very small effects can become statistically significant and not practically significant. The large sample size increases the power of the statistical tests, making it easier to detect trivial associations. In summary, clinically significant differences may or may not exist between ECT and non-ECT patients hospitalized under the same diagnostic code. Nonetheless, ECT may enhance care continuity within hospital systems. Future research comparing pre- and post-ECT lengths of stay could better control for confounding variables. Conclusions Target Population for ECT The study indicates that ECT is predominantly used for patients with severe and persistent mental illnesses. Clinicians should consider ECT as a viable treatment option for complex cases, especially when multiple medication trials have failed. Rehospitalization Rates ECT was associated with significantly higher psychiatric rehospitalization rates (37.52%) compared to non-ECT patients (20.71%). This suggests that patients receiving ECT may have more severe or treatment-resistant conditions, necessitating closer follow-up and more intensive post-discharge care plans to manage their ongoing mental health needs. Length of Stay The mean length of stay for readmissions was significantly longer for ECT patients (14.53 days) compared to non-ECT patients (6.54 days). This highlights the need for healthcare providers to allocate adequate resources and support for ECT patients during readmissions for their stabilization. Demographic Considerations The study found that ECT patients were generally older, more likely to be female, and predominantly white. This demographic information may help clinicians identify bias in patient selection for ECT and tailor their treatment approaches accordingly. Utilization and Underutilization Despite its efficacy, ECT appears to be underutilized, with only 1.67% of analyzed psychiatrically hospitalized patients receiving the treatment. The study's findings support the argument for considering ECT earlier in the treatment course for severe psychiatric conditions, potentially improving patient outcomes and reducing the burden of prolonged illness. Social Support and Continuity of Care The higher rehospitalization rates among ECT patients may reflect stronger social support systems, geographic ties, and healthcare system fidelity. As such, patients may be more likely to return to the same hospital for care. This underscores the importance of integrated care models that facilitate continuity of care and robust support networks for treatment-resistant patients. Future Research Directions Further research is needed to explore the pre- and post-ECT lengths of stay and other confounding variables that might influence rehospitalization rates. Additionally, studies focusing on the long-term outcomes of ECT patients and the development of strategies to reduce rehospitalization rates are warranted. Abbreviations ECT: Electroconvulsive Therapy, LOS: Length of Stay, MDD: Major Depressive Disorder, SD: Standard Deviation, CI: Confidence Interval, p: p-value (probability value), Z: Z-score (standard score), HCA: Hospital Corporation of America, F: ICD-10 codes for mental and behavioral disorders, GZB: Procedure codes for ECT, Phi: Phi Coefficient (measure of association), Cramer’s V: Measure of association strength, N: Sample size Declarations Funding: HCA Healthcare and/or affiliated entities did not financially support this research work. There are no funders to report for this submission. Conflicts of Interest: Authors have no conflicts of interest or competing interests to disclose. Author Contribution AR – Conceptualization, Methodology, Software, Validations, Formal Analysis, Investigation, Data Curation, Writing Original Draft, Review and Editing; JW – Conceptualization, Review and Editing; JF – Conceptualization, Review and Editing, Supervision Data Availability The datasets used and/or analyzed during the current study are from the HCA Healthcare national database and available from the corresponding author on reasonable request. References Espinoza RT, Kellner CH. Electroconvulsive Therapy. N Engl J Med. 2022;386(7):667–72. Tor PC, Tan XW, Martin D, Loo C. Comparative outcomes in electroconvulsive therapy (ECT): A naturalistic comparison between outcomes in psychosis, mania, depression, psychotic depression and catatonia. Eur Neuropsychopharmacol. 2021;51:43–54. Sackeim HA. Modern Electroconvulsive Therapy. JAMA Psychiatry. 2017;74(8):779. Azriel HK, Tan XW, Tor PC, Chatterton ML, Martin DM, Loo CK. The association between outpatient continuation/maintenance electroconvulsive therapy, readmission risk and total direct cost in patients with depressive, bipolar and psychotic disorders: A naturalistic retrospective cohort study. J Affect Disord. 2023;338:289–98. 10.1016/j.jad.2023.06.016 . Ying YB, Jia LN, Wang ZY, Jiang W, Zhang J, Wang H, et al. Electroconvulsive therapy is associated with lower readmission rates in patients with schizophrenia. Brain Stimul. 2021 Jul-Aug;14(4):913–21. 10.1016/j.brs.2021.05.010 . Epub 2021 May 24. PMID: 34044182. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2024 Read the published version in BMC Psychiatry → Version 1 posted Editorial decision: Revision requested 20 Aug, 2024 Reviews received at journal 18 Aug, 2024 Reviews received at journal 14 Aug, 2024 Reviews received at journal 14 Aug, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers agreed at journal 29 Jul, 2024 Reviewers agreed at journal 24 Jul, 2024 Reviewers invited by journal 22 Jul, 2024 Editor assigned by journal 26 Jun, 2024 Submission checks completed at journal 26 Jun, 2024 First submitted to journal 31 May, 2024 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. 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Also discoverable on Platform About In Review Editorial Policies 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-4510944","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":328055588,"identity":"543dc3f8-bac3-45e8-b093-4c4e497c1074","order_by":0,"name":"Aneesh Rahangdale","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYHCCxIcfeP7x8ANZHxgYmInS8thYQuaAjGQDA+MMIrUwPhPgsTlgY3CAWC38s5vTGCRy7vAY30h+2MBQYZ3YQEiLxJ1jaQ8KzjzjMbuRZtjAcCadsBaGGznpBpI9zEAtOewPGNsOE9YifyP/mwTvP2Ye4xk5jA2M/4jQYnAjIU2Ch+cwj4EESEsDEVoMbyQkG0vwpPFInHlm2JBwLN2YoBa5GwmgqLSx528HhtiHGmtZglpQQQJpykfBKBgFo2AU4AIAv3ZBvldkkNsAAAAASUVORK5CYII=","orcid":"","institution":"HCA Florida Capital Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Aneesh","middleName":"","lastName":"Rahangdale","suffix":""},{"id":328055589,"identity":"f3818123-1c1b-433a-a991-b395caa7e228","order_by":1,"name":"Joshua Wasdin","email":"","orcid":"","institution":"HCA Florida Capital Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Wasdin","suffix":""},{"id":328055590,"identity":"f82dafdd-a91e-4fdf-89b0-01eeec199bc9","order_by":2,"name":"Jeffrey Ferraro","email":"","orcid":"","institution":"HCA Florida Capital Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jeffrey","middleName":"","lastName":"Ferraro","suffix":""}],"badges":[],"createdAt":"2024-05-31 20:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4510944/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4510944/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12888-024-06211-2","type":"published","date":"2024-10-30T15:56:53+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60706534,"identity":"eb4a29af-ff61-4079-9096-5cffb5490ff5","added_by":"auto","created_at":"2024-07-19 19:29:19","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95357,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA majority of the patients treated had the diagnosis of major depressive disorder with psychotic features.\u003c/strong\u003e 55% of patients had MDD with psychotic features, 4% had MDD, 3% had schizoaffective disorder, 4% had schizophrenia, less than a percent had bipolar psychosis, and the remaining 34% had another diagnosis, such as bipolar without psychotic features or psychosis unspecified.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4510944/v1/ab48fadc046e07054793657f.png"},{"id":60706537,"identity":"d03f70fa-1bcd-47a1-a093-efe244fb64d3","added_by":"auto","created_at":"2024-07-19 19:29:19","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102794,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThere is a right skew for length of stay of psychiatric inpatient patients.\u003c/strong\u003e Over 90% of psychiatric patients stay fewer than 20 days, while 5 patients stayed over 80 days.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4510944/v1/dd98716e3c25f65e1508bb78.jpeg"},{"id":60706536,"identity":"155fc641-9f70-459f-a2c4-c0b0da556601","added_by":"auto","created_at":"2024-07-19 19:29:19","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":119012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThere was a significant difference in the Average Psych Ward Readmission Length of Stay (per patient) between patients who had ECT compared to patients that did not have ECT (Z=15.5648, p\u0026lt;.0001). \u003c/strong\u003eThis graph shows the distribution of Wilcoxon scores for psychiatric hospitalization length of stay, comparing patients who received electroconvulsive therapy (ECT) and those who did not (No ECT). The ECT group has a narrower distribution with higher scores, indicating longer lengths of stay compared to the No ECT group. The p-values (Pr \u0026gt; Z and Pr \u0026gt; |Z|) are both less than 0.0001, indicating a statistically significant difference between the two groups.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4510944/v1/35cbfc68542b2dc7c3ea1156.jpeg"},{"id":68206334,"identity":"fbd7a17d-d75c-48bf-951a-0582fd7f8972","added_by":"auto","created_at":"2024-11-04 16:31:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":894012,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4510944/v1/a9181bfb-902c-4bb7-a836-b632e45be28f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"ECT and Psychiatric Rehospitalization Rates: A Retrospective Study","fulltext":[{"header":"Background","content":"\u003cp\u003eElectroconvulsive therapy (ECT) induces a generalized seizure under anesthesia with an electrical current for treatment-resistant patients with severe depression, bipolar disorder, schizophrenia, schizoaffective disorder, catatonia, and neuroleptic malignant syndrome.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Evidence suggests ECT is underutilized as a treatment modality.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e One naturalistic retrospective cohort study in Singapore found that outpatient continuation/maintenance electroconvulsive therapy (CM-ECT) after an acute inpatient course of ECT was associated with significantly lower risks of psychiatric readmission (adjusted hazard ratio of 0.68) and lower total direct healthcare costs compared to not receiving CM-ECT, especially for patients with mood disorders.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Another Chinese study found that ECT lowered readmission for patients with schizophrenia within 3 months (11.37% vs 18.79%) and 6 months (17.94% vs 29.36%) compared to patients who did not receive ECT, especially for patients who received 9 or more ECT treatments had the lowest readmission rates.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e In that study, male sex, older age, being married, lower income, shorter inpatient stay increased readmission risk. To our knowledge, no large-scale, American, nationwide hospital system retrospective study has examined how ECT affects psychiatric rehospitalization chances. This may bolster arguments for employing ECT earlier in the treatment course for severe, persistent mental illness and provide insights regarding larger demographic trends in the American healthcare system.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe analyzed initial encounters for adult patients (\u0026gt;\u0026thinsp;18 years) hospitalized at HCA Healthcare Behavioral Health Units from 2016\u0026ndash;2021 for major depressive disorder with/without psychosis, bipolar disorder with/without psychosis, schizoaffective disorder, and schizophrenia diagnoses (F codes F 33.2, F 33.3, F 31.2, F 31.4, F 31.13, F 31.5, F 31.63, F 31.64, F25, F20). Excluding pregnancy and incarceration cases, we investigated psychiatric rehospitalization rates within 365 days for patients receiving ECT (procedure codes GZB 0\u0026ndash;4) versus those with the same diagnoses not receiving ECT from January 2016 \u0026ndash; December 2021.\u003c/p\u003e \u003cp\u003eSubgroup analyses were conducted for diagnoses, length of stay for readmission, sex, and race. Detailed statistical analyses (bivariate analyses with Fisher\u0026rsquo;s Exact Test, Wilcoxon Rank Sum Test) were done.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe analyzed 39392 initial encounters for adult patients (\u0026gt;\u0026thinsp;18 years old) who have been hospitalized at an HCA Healthcare Behavioral Health Unit for major depressive disorder with and without psychosis, bipolar disorder with and without psychosis, schizoaffective disorder, and schizophrenia from 1 January 2016 to 31 December 2021. We investigated psychiatric rehospitalization rates for patients getting ECT compared to patients with the same diagnostic codes from 01-01-2016 through 12-31-2021 to allow for a full year of readmission data. Thus, the total time frame was 2016 through the end of 2022. Of these patients, 1283 were excluded for pregnancy or discharge to or from prison. Of the 38109 distinct patients analyzed, 637 patients were treated with Electroconvulsive Therapy (ECT). The mean age of the total population was 44.27 years (SD\u0026thinsp;=\u0026thinsp;18.24), with ECT patients averaging 59.48 years (SD\u0026thinsp;=\u0026thinsp;17.10) and readmitted patients averaging 45.49 years (SD\u0026thinsp;=\u0026thinsp;16.21). Gender distribution for the total population was 50.11% female and 49.89% male, whereas the ECT population had a higher percentage of females (60.13%) compared to males (39.87%). Racial demographics showed that the majority of the total population was White (71.38%), followed by Black (20.35%) and Other races (8.27%). Among ECT patients, 85.56% were White, 7.69% were Black, and 6.75% were of other races.\u003c/p\u003e \u003cp\u003eMost ECT patients had major depressive disorder with psychotic features (55%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Diagnosis distribution indicated that 3.65% of the total population were diagnosed with Major Depressive Disorder (MDD) without psychosis, with this rate higher among ECT patients (9.42%). For MDD with psychosis, 55.55% of the total population were diagnosed, with a significantly higher percentage among ECT patients (87.28%). Bipolar Disorder with psychosis was diagnosed in 0.44% of the total population, with ECT patients showing a higher rate (1.10%). Schizoaffective Disorder was diagnosed in 2.58% of the total population, with ECT patients having a slightly higher incidence (3.77%). Schizophrenia was present in 3.80% of the total population, with ECT patients showing a higher rate (6.59%).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe readmission rate was 37.52% for ECT recipients versus 20.71% for non-ECT patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was a significant overall association between ECT and readmission (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), but no significant directional associations based on coefficients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The readmission rate within one year for the overall population was 20.99% (95% CI: 20.58\u0026ndash;21.40%), with a significantly higher rate for ECT patients at 37.52% (95% CI: 33.76\u0026ndash;41.28%) compared to non-ECT patients at 20.71%. The mean length of stay (LOS) for readmissions was significantly longer for ECT patients, with a mean of 14.53 days (SD\u0026thinsp;=\u0026thinsp;15.94, 95% CI: 12.51\u0026ndash;16.55), compared to the total population\u0026rsquo;s average LOS of 6.54 days (SD\u0026thinsp;=\u0026thinsp;7.21, 95% CI: 6.38\u0026ndash;6.70). Chi-Square and Wilcoxon Rank Sum Tests confirmed statistically significant associations between ECT and higher readmission rates (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and in average psychiatric ward readmission LOS between ECT and non-ECT patients (Z\u0026thinsp;=\u0026thinsp;15.5648, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eComparison of ECT and Non-ECT Patients on Key Variables.\u003c/b\u003e This table presents demographic characteristics, diagnosis distributions, readmission rates within 1 year, and length of stay for psychiatric readmissions, comparing patients who underwent electroconvulsive therapy (ECT) to those who did not receive ECT. Data is from an initial sample of 38,109 distinct patient encounters after excluding pregnancies and prison transfers. ECT patients were older on average (mean age 59.5 vs 44.3 for total population). 60.1% of ECT patients were female compared to 50.1% in the total population. ECT patients had higher rates of major depressive disorder with psychosis (87.3% vs 55.6%). 37.5% of ECT patients were readmitted within 1 year, compared to only 20.7% of non-ECT patients. For readmitted patients, mean length of stay was 14.5 days for the ECT group versus 6.5 days for the total population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDemographic Variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Population\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eECT Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon-ECT Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReadmitted Patients\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSample Size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38,109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37,472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean Age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.27 (SD\u0026thinsp;=\u0026thinsp;18.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.48 (SD\u0026thinsp;=\u0026thinsp;17.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.49 (SD\u0026thinsp;=\u0026thinsp;16.21)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender Distribution\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Female (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Male (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRacial Distribution\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- White (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Black (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Other (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReadmission Rate (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.99 (95% CI: 20.58\u0026ndash;21.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.52 (95% CI: 33.76\u0026ndash;41.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis Distribution\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- MDD without Psychosis (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- MDD with Psychosis (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Bipolar Disorder with Psychosis (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Schizoaffective Disorder (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- Schizophrenia (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLength of Stay (LOS) for Readmissions (days)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.54 (SD\u0026thinsp;=\u0026thinsp;7.21, 95% CI: 6.38\u0026ndash;6.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.53 (SD\u0026thinsp;=\u0026thinsp;15.94, 95% CI: 12.51\u0026ndash;16.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eWith a sample size of 38109, there was a significant overall association between ECT and Readmission (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) at the 95% (α\u0026thinsp;=\u0026thinsp;.05) confidence limit.\u003c/b\u003e There was a significant difference in the proportion of patients who had a readmission after cross-tabbing by ECT. Based on analyses by Phi Coefficients, Cramer's V, and Contingency Coefficients, there was a weak strength of association between these two variables.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eStatistics for Cross Sectional Analysis of ECT by Readmission (n\u0026thinsp;=\u0026thinsp;38109)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChi-Square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106.6910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLikelihood Ratio Chi-Square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92.5509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eContinuity Adjusted Chi-Square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e105.6800\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMantel-Haenszel Chi-Square\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e106.6882\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhi Coefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eContingency Coefficient\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCramer\u0026rsquo;s V\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOver 90% of psychiatric inpatients stayed\u0026thinsp;\u0026lt;\u0026thinsp;20 days, while a right skew showed some very long stays (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). ECT patients had a significantly longer average readmission length of stay (Z\u0026thinsp;=\u0026thinsp;15.5648, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNo significant age differences existed between ECT/non-ECT or readmitted/non-readmitted groups when adjusted for diagnoses. White patients received ECT more frequently. Men were readmitted more often, while women received ECT more frequently. Subgroup analyses by diagnoses yielded similar findings.\u003c/p\u003e \u003cp\u003eOverall, the data demonstrate that ECT was associated with higher readmission rates, even when accounting for individual diagnoses. ECT patients also experienced significantly longer readmission lengths of stay compared to non-ECT patients.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn summary, patients who received ECT were generally older, more likely to be female, and predominantly white. They also had higher rates of severe psychiatric diagnoses such as MDD with psychosis, bipolar disorder with psychosis, schizoaffective disorder, and schizophrenia. ECT is associated with higher readmission rates and longer lengths of stay, particularly among patients diagnoses such as Bipolar Disorder with psychosis, Schizoaffective Disorder, and Schizophrenia. These findings suggest that ECT is more commonly used in patients with more severe and complex psychiatric conditions, which may contribute to the higher readmission rates observed in this group.\u003c/p\u003e \u003cp\u003eThere was a significant association between ECT and increased rehospitalization (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), potentially because ECT patients are higher utilizers of inpatient psychiatric services and/or more likely to follow up and re-hospitalize at the same hospital if their mental health worsens compared to non-ECT patients with the same diagnosis. Robust social support systems and geographic roots may make ECT patients more likely to re-admit to the same hospital.\u003c/p\u003e \u003cp\u003eECT patients had significantly longer readmission lengths of stay (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), possibly because they have higher illness acuity requiring more time to stabilize, even with the same diagnostic code as non-ECT patients. For example, a patient with severe major depressive disorder may have had more instances of rehospitalization and failed medication trials if they get ECT than another patient with severe major depressive disorder. As such, with rehospitalization, they are more likely to need a longer amount of time to stabilize.\u003c/p\u003e \u003cp\u003eMoreover, the measures of association (Phi Coefficient, Contingency Coefficient, and Cramer\u0026rsquo;s V) suggest that the strength of the association between ECT and readmission rates is very weak. The measures of association (Phi, Contingency Coefficient, and Cramer\u0026rsquo;s V) indicate the strength of the relationship is very low. With a large sample size (n\u0026thinsp;=\u0026thinsp;38,109), even very small effects can become statistically significant and not practically significant. The large sample size increases the power of the statistical tests, making it easier to detect trivial associations.\u003c/p\u003e \u003cp\u003eIn summary, clinically significant differences may or may not exist between ECT and non-ECT patients hospitalized under the same diagnostic code. Nonetheless, ECT may enhance care continuity within hospital systems. Future research comparing pre- and post-ECT lengths of stay could better control for confounding variables.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cstrong\u003eTarget Population for ECT\u003c/strong\u003e \u003cp\u003eThe study indicates that ECT is predominantly used for patients with severe and persistent mental illnesses. Clinicians should consider ECT as a viable treatment option for complex cases, especially when multiple medication trials have failed.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eRehospitalization Rates\u003c/strong\u003e \u003cp\u003eECT was associated with significantly higher psychiatric rehospitalization rates (37.52%) compared to non-ECT patients (20.71%). This suggests that patients receiving ECT may have more severe or treatment-resistant conditions, necessitating closer follow-up and more intensive post-discharge care plans to manage their ongoing mental health needs.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLength of Stay\u003c/strong\u003e \u003cp\u003eThe mean length of stay for readmissions was significantly longer for ECT patients (14.53 days) compared to non-ECT patients (6.54 days). This highlights the need for healthcare providers to allocate adequate resources and support for ECT patients during readmissions for their stabilization.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDemographic Considerations\u003c/strong\u003e \u003cp\u003eThe study found that ECT patients were generally older, more likely to be female, and predominantly white. This demographic information may help clinicians identify bias in patient selection for ECT and tailor their treatment approaches accordingly.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUtilization and Underutilization\u003c/strong\u003e \u003cp\u003eDespite its efficacy, ECT appears to be underutilized, with only 1.67% of analyzed psychiatrically hospitalized patients receiving the treatment. The study's findings support the argument for considering ECT earlier in the treatment course for severe psychiatric conditions, potentially improving patient outcomes and reducing the burden of prolonged illness.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSocial Support and Continuity of Care\u003c/strong\u003e \u003cp\u003eThe higher rehospitalization rates among ECT patients may reflect stronger social support systems, geographic ties, and healthcare system fidelity. As such, patients may be more likely to return to the same hospital for care. This underscores the importance of integrated care models that facilitate continuity of care and robust support networks for treatment-resistant patients.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFuture Research Directions\u003c/strong\u003e \u003cp\u003eFurther research is needed to explore the pre- and post-ECT lengths of stay and other confounding variables that might influence rehospitalization rates. Additionally, studies focusing on the long-term outcomes of ECT patients and the development of strategies to reduce rehospitalization rates are warranted.\u003c/p\u003e \u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eECT: Electroconvulsive Therapy, LOS: Length of Stay, MDD: Major Depressive Disorder, SD: Standard Deviation, CI: Confidence Interval, p: p-value (probability value), Z: Z-score (standard score), HCA: Hospital Corporation of America, F: ICD-10 codes for mental and behavioral disorders, GZB: Procedure codes for ECT, Phi: Phi Coefficient (measure of association), Cramer\u0026rsquo;s V: Measure of association strength, N: Sample size\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eHCA Healthcare and/or affiliated entities did not financially support this research work. There are no funders to report for this submission.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e \u003cp\u003eAuthors have no conflicts of interest or competing interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAR \u0026ndash; Conceptualization, Methodology, Software, Validations, Formal Analysis, Investigation, Data Curation, Writing Original Draft, Review and Editing; JW \u0026ndash; Conceptualization, Review and Editing; JF \u0026ndash; Conceptualization, Review and Editing, Supervision\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are from the HCA Healthcare national database and available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eEspinoza RT, Kellner CH. Electroconvulsive Therapy. N Engl J Med. 2022;386(7):667\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTor PC, Tan XW, Martin D, Loo C. Comparative outcomes in electroconvulsive therapy (ECT): A naturalistic comparison between outcomes in psychosis, mania, depression, psychotic depression and catatonia. Eur Neuropsychopharmacol. 2021;51:43\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSackeim HA. Modern Electroconvulsive Therapy. JAMA Psychiatry. 2017;74(8):779.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAzriel HK, Tan XW, Tor PC, Chatterton ML, Martin DM, Loo CK. The association between outpatient continuation/maintenance electroconvulsive therapy, readmission risk and total direct cost in patients with depressive, bipolar and psychotic disorders: A naturalistic retrospective cohort study. J Affect Disord. 2023;338:289\u0026ndash;98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jad.2023.06.016\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2023.06.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYing YB, Jia LN, Wang ZY, Jiang W, Zhang J, Wang H, et al. Electroconvulsive therapy is associated with lower readmission rates in patients with schizophrenia. Brain Stimul. 2021 Jul-Aug;14(4):913\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.brs.2021.05.010\u003c/span\u003e\u003cspan address=\"10.1016/j.brs.2021.05.010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2021 May 24. PMID: 34044182.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Electroconvulsive therapy (ECT), psychiatric rehospitalization, length of stay, readmission","lastPublishedDoi":"10.21203/rs.3.rs-4510944/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4510944/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eElectroconvulsive therapy (ECT) induces a generalized seizure under anesthesia with an electrical current for treatment-resistant patients and may be underutilized. To our knowledge, no large-scale, American, nationwide hospital system retrospective study has examined how ECT affects psychiatric rehospitalization chances.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed initial inpatient encounters for adults aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years at HCA Healthcare Behavioral Health Units from 2016\u0026ndash;2021 with diagnoses of major depressive disorder with/without psychosis, bipolar disorder with/without psychosis, schizoaffective disorder, and schizophrenia. Excluding pregnancy and incarceration cases, we compared psychiatric rehospitalization rates within 365 days for patients receiving ECT versus those with the same diagnoses not receiving ECT. Subgroup analyses were conducted by diagnosis, length of stay, sex, and race. Detailed statistical analyses included bivariate analyses with Fisher's Exact Test and Wilcoxon Rank Sum Test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe analyzed 38,109 distinct patients, 637 of which received ECT. The readmission rate was 37.52% for ECT recipients versus 20.71% for non-ECT patients (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). ECT was associated with higher readmission rates, particularly for severe diagnoses like psychosis (87.28%), schizoaffective disorder (3.77%), and schizophrenia (6.59%). ECT patients had significantly longer readmission lengths of stay (mean 14.53 days vs 6.54 days for non-ECT, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). White patients received ECT more frequently. Females received ECT more often, while males had higher readmission rates.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eECT was associated with higher psychiatric rehospitalization rates and longer lengths of stay. This suggests ECT is more commonly used for complex, severe cases which may contribute to higher rehospitalization. Stronger social support and hospital and geographic ties among ECT patients may also play a role.\u003c/p\u003e","manuscriptTitle":"ECT and Psychiatric Rehospitalization Rates: A Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-19 19:29:14","doi":"10.21203/rs.3.rs-4510944/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-20T05:39:49+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-18T09:08:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-14T09:19:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-14T08:32:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"164153077745374008124795930036034038568","date":"2024-08-07T13:05:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"171468400706044303818028509134375967334","date":"2024-08-07T10:46:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112820742524975856570909825690349617929","date":"2024-07-29T19:53:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68011814139994069712749239404439183481","date":"2024-07-24T08:58:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-22T08:56:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-27T02:07:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-27T02:07:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Psychiatry","date":"2024-05-31T20:11:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bpsy","sideBox":"Learn more about [BMC Psychiatry](http://bmcpsychiatry.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bpsy/default.aspx","title":"BMC Psychiatry","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0d1a10a3-f74f-43db-8a70-2ece976c096b","owner":[],"postedDate":"July 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-11-04T16:21:10+00:00","versionOfRecord":{"articleIdentity":"rs-4510944","link":"https://doi.org/10.1186/s12888-024-06211-2","journal":{"identity":"bmc-psychiatry","isVorOnly":false,"title":"BMC Psychiatry"},"publishedOn":"2024-10-30 15:56:53","publishedOnDateReadable":"October 30th, 2024"},"versionCreatedAt":"2024-07-19 19:29:14","video":"","vorDoi":"10.1186/s12888-024-06211-2","vorDoiUrl":"https://doi.org/10.1186/s12888-024-06211-2","workflowStages":[]},"version":"v1","identity":"rs-4510944","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4510944","identity":"rs-4510944","version":["v1"]},"buildId":"re_ckhLnmML6MCF96OHNJ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}