Comparative Analysis of the Risk of Severe Bacterial Infection and Septicemia in Adolescents and Young Adults with Treatment-Resistant Depression and Treatment- Responsive Depression - A Nationwide Cohort Study in Taiwan

Comparative Analysis of the Risk of Severe Bacterial Infection and Septicemia in Adolescents and Young Adults with Treatment-Resistant Depression and Treatment- Responsive Depression - A Nationwide Cohort Study in Taiwan | 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 Comparative Analysis of the Risk of Severe Bacterial Infection and Septicemia in Adolescents and Young Adults with Treatment-Resistant Depression and Treatment- Responsive Depression - A Nationwide Cohort Study in Taiwan Jia-Ru Li, Yu-Chen Kao, Shih-Jen Tsai, Ya-Mei Bai, Tung-Ping Su, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4614090/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 08 Mar, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted 12 You are reading this latest preprint version Abstract Background Previous studies have shown an association between depression and susceptibility to infection in adults. However, few studies have investigated the association between treatment-resistant depression (TRD) and severe infections in adolescents and young adults. Methods This study included adolescents (12–19 years of age) and young adults (20–29 years of age) who were diagnosed with major depressive disorder (MDD, including 6958 cases of TRD and 27832 cases of antidepressant-responsive depression [ARPD]), from the Taiwan National Health Insurance Research Database (NHIRD), from 2001 to 2010. The TRD and ARPD groups were further matched (4:1) by chronological age, age at diagnosis of depression, sex, residence, and family income. The primary outcomes were severe bacterial infections (SBI) and septicemia. Cox regression analysis was conducted to identify the risk of hospitalization due to SBI or septicemia during the follow-up period. Results Compared with controls, the ARPD group had increased risks of SBI (hazard ratio [HR] with 95% confidence interval [CI]: 3.90, 2.73–5.57) and septicemia (HR, 95% CI: 2.56, 1.34–4.91). Notably, the risks of SBI and septicemia appeared to be further elevated in the TRD group. The TRD group exhibited higher incidences of SBI (HR, 95% CI: 6.99, 4.73–10.34) and septicemia (HR, 95% CI: 2.85, 1.28–6.36) than the control group. Conclusions Adolescents and young adults with TRD had 6.99-fold and 3.90-fold increased risks of SBI and septicemia compared to individuals without MDD, respectively. Therefore, healthcare providers need to be vigilant when monitoring and implementing preventive measures in this population. Figures Figure 1 Introduction Major depressive disorder is a significant mental health concern and a leading cause of disability. It typically begins in adolescence and contributes significantly to the disease burden among young individuals. Studies have estimated the prevalence of major depressive disorder (MDD) to be approximately 4–6% among adolescents. Moreover, the incidence of depressive symptoms and MDD increases sharply during adolescence [ 1 – 3 ]. The onset of MDD during adolescence is associated with increased illness severity in adulthood, increased psychiatric morbidity, and poor physical health outcomes [ 4 , 5 ]. Additionally, adolescents and young adults with MDD tend to experience significant social and educational difficulties, thus, increasing the risk of long-term psychosocial impairment in adulthood [ 6 – 9 ]. Among adolescents with MDD, up to 23% show poor response to initial antidepressant treatment, and approximately 2% meet the criteria for treatment- resistant depression (TRD) [ 10 ]. The strict criteria for TRD typically signify an inadequate response to at least two trials of antidepressants prescribed at sufficient doses for an appropriate duration [ 11 , 12 ]. Resistance to antidepressants in adolescents with MDD is associated with comorbidities, such as anxiety disorders, substance use disorders, and attention deficit hyperactivity disorder [ 10 , 13 ]. Consequently, increasing outpatient healthcare resource utilization, inpatient days, and higher all-cause mortality. Moreover, previous studies have indicated that TRD may be associated with diminished health-related quality of life, general medical condition exacerbations, and increased healthcare costs [ 14 , 15 ]. Adolescents and young adults undergo various transitional stages that potentially render them more susceptible to infection. This increased vulnerability can be attributed to various factors, such as hormonal changes, heightened social interactions, and higher engagement in risk-taking behaviors during this developmental phase. [ 16 , 17 ]. A study revealed a higher incidence of severe bacterial infections (SBI) (Odds Ratio [OR], 95% CI: 1.8, 1.6–2.0) and sepsis (OR, 95% CI: 2.3, 1.1–5.0) among adolescents compared to children, resulting in more frequent hospital admissions [ 18 ]. Septicemia, characterized by the occurrence of sepsis accompanied by the presence of pathogenic microorganisms within the bloodstream, is associated with significant negative consequences, such as organ dysfunction, long-term impairment, and high mortality rates [ 19 ]. Hence, addressing infections in global public health is of significant importance. Indeed, a Japanese study observed a 25% overall mortality from sepsis in adolescents in intensive care units. Moreover, an alarming estimate of more than 10 million sepsis-related deaths annually highlights the substantial contribution of infections to over 20% of global mortality [ 20 , 21 ]. Despite the encouraging decrease in the age-standardized incidence of sepsis by 37.0% (95% uncertainty interval [UI] 11.8–54.5) and mortality by 52.8% (47.7–57.5) from 1990 to 2017, addressing the burden of severe bacterial infections (SBI) and septicemia remains a crucial priority [ 21 ]. Clinical data suggest a potential link between depression and an increased risk of infection [ 22 , 23 ]. For example, a previous study identified a potential link between major MDD and an increased risk of herpes zoster in older adults [ 24 ]. Another study associated depression with an increased risk of a wide range of infections [ 23 ]. Moreover, data from the UK Biobank links the genetic risk score for MDD with a higher likelihood of intestinal E.coli infections (OR 3.24, 95% CI 1.74–6.02) [ 25 ]. Furthermore, previous studies have found that adults with a history of depression are more susceptible to various infections than those without a history of depression [ 23 ]. Additionally, cross-sectional studies have demonstrated a correlation between depressive and anxiety symptoms and the risk of mortality due to infectious diseases [ 26 ]. However, limited research has been conducted on the relationship between TRD and SBI among adolescents and young adults. In the current study, using longitudinal data from a large sample population drawn from the Taiwan National Health Insurance Research Database (NHIRD), we investigated the risk of developing SBI and septicemia in adolescents and young adults with MDD., especially TRD We hypothesized that adolescents and young adults with TRD have a higher risk of SBI and septicemia in later stages of life relative to adolescents and young adults with antidepressant-responsive depression (ARPD), and those without depression. Methods Data source. The Taiwan NHIRD is audited and released by the National Health Research Institute (NHRI) for scientific and study purposes upon the formal application. In the current study, we linked two datasets of the NHIRD, namely, the specialized dataset of mental disorders and the longitudinal health insurance database, for analysis. The specialized dataset of mental disorders included all medical records of all insured individuals with mental disorders, and thus, was used for identifying participants of the study group in the current study. The longitudinal health insurance database includes all medical records of 3,000,000 insured individuals randomly selected from the entire Taiwanese population (approximately 28,000,000) and was used to identify participants of the control group. The diagnostic codes used were based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM). The NHIRD has been extensively used in many epidemiological studies in Taiwan [ 27 – 30 ]. This study was approved by the Institutional Review Board of the Taipei Veterans General Hospital. The Taipei Veterans General Hospital Institutional Review Board approved the study protocol and waived the requirement for informed consent because this investigation used de-identified data and no human subject contact was required. Study protocol. Adolescents (aged 12–19 years), and young adults (aged 20–29 years), who were diagnosed with MDD (ICD-9-CM codes: 296.2, 296.3) by board-certified psychiatrists and had no prior history of SBI between 2001 and 2010 were included in this study. To specifically identify SBI and improve our diagnostic validity, only the diagnostic codes of bacterial infections in the inpatient dataset were included in the present study. Septicemia was defined using the ICD-9-CM code 038 in the inpatient dataset. In Taiwan, to reduce and control the risk of developing antibiotic-resistant bacteria, hospital infectionists supervise the use of antibiotics in infectious diseases, and cultures of infectious origins are required in clinical practice. These clinical procedures aim to ensure the diagnostic validity of infections and their origins. Patients with MDD were classified into two groups (ARPD and TRD) based on their antidepressant treatment response during 1 year of follow-up following diagnosis [ 10 , 31 ]. An adequate trial of antidepressant treatment was defined as the use of an antidepressant within its therapeutic dosage range (e.g., fluoxetine ≥ 20 mg/day) for ≥ 60 consecutive days [ 10 , 13 ]. Patients who remained on a single antidepressant were assigned to the ARPD group, and those who changed the antidepressant treatment regimen two or more times were assigned to the TRD group. The ARPD and TRD groups were further matched (4:1) by chronological age, age at the time of depression diagnosis, sex, residence, and family income. For the control group, participants were also age-, sex-, family income-, and residence-matched (1:4), after eliminating participants that were potential study cases, namely, those who had any diagnostic code for severe mental disorders (ICD-9-CM codes: 295, 296, 300.3, 300.4, and 311) in the database, and those who had been diagnosed with SBI before enrollment. SBI were identified in the inpatient dataset from enrollment until the end of 2011. Additionally, Charlson Comorbidity Index (CCI) and all-cause clinical visits were provided for the study and control cohorts. CCI consisting of 22 physical conditions was also assessed to determine the systemic health conditions of all enrolled individuals [ 32 ]. CCI includes myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatologic disease, peptic ulcer disease, liver disease, diabetes, hemiplegia, paraplegia, renal disease, malignancy, leukemia, lymphoma, and AIDS [ 32 ]. In order to avoid the bias from the confounding effect of other infection-related physical comorbidities, we additionally assessed asthma, thyroid disorders, anemia, and congenital anomalies in the present study. Income level (levels 1–3 per month: ≤ 19,000 NTD (New Taiwanese Dollars), 19,001–42,000 NTD, and ≥ 42,001 NTD) and urbanization level of residence (levels 1–5, most to least urbanized) were regarded as the proxies for healthcare availability in Taiwan [ 33 ]. Statistical analysis. For between-group comparisons, the F-test was used for continuous variables and Pearson's X 2 test was used for nominal variables, where appropriate. Cox regression models with adjustments for age, sex, level of urbanization, income, and CCI scores were used to investigate the HR with a 95% confidence interval (CI) of SBI and septicemia during the follow-up between groups. Finally, given the hypothesis that depressed patients who responded to antidepressant treatment were less likely to be affected by the inflammatory and immunological dysfunction [ 34 , 35 ], we investigated the likelihoods of severe bacterial infection and septicemia between patients with TRD and the combined group of patients with non-TRD and non-depressed control individuals. A 2-tailed P -value of less than 0.05 was considered statistically significant. All data processing and statistical analyses were performed using the Statistical Package for Social Science, version 17 (SPSS; SPSS Inc., Armonk, NY, USA) and Statistical Analysis Software version 9.1 (SAS; SAS Institute, Cary, NC). Data Availability Statement. The NHIRD was released and audited by the Department of Health and the Bureau of the NHI Program for Scientific Research (https://nhird.nhri.org.tw/). The NHIRD can be obtained through a formal application regulated by the Department of Health and the Bureau of the NHI Program. Results In total, 62,622 adolescents and young adults were included in this study, including 6,958 adolescents and young adults with TRD, 27,832 adolescents and young adults with ARPD, and 27,832 controls (Table 1 ). The mean age is approximately 22.8 years, with a female predominance of 52.6% of the population (Table 1 ). Additionally, adolescents and young adults with TRD were more likely to have higher CCI scores and other physical comorbidities than those in the other two groups (P < 0.001) (Table 1 ). Table 1 Demographic characteristics between adolescents and young adults with treatment-resistant and antidepressant-responsive depression A. Adolescents and young adults with treatment-resistant depression (n = 6958) B. Adolescents and young adults with antidepressant-responsive depression (n = 27,832) C. Control group (n = 27,832) p-value Post-hoc Age at depression diagnosis or enrollment (years, SD) 22.84 (4.04) 22.80 (4.01) 22.83 (4.05) 0.646 Male (n, %) 3301 (47.4) 13,204 (47.4) 13,204 (47.4) > 0.999 Level of urbanization (n, %) > 0.999 1 (most urbanized) 1948 (28.0) 7792 (28.0) 7792 (28.0) 2 2343 (33.7) 9372 (33.7) 9372 (33.7) 3 908 (13.0) 3632 (13.0) 3632 (13.0) 4 631 (9.1) 2524 (9.1) 2524 (9.1) 5 (most rural) 1128 (16.2) 4512 (16.2) 4512 (16.2) Income-related insured amount (n, %) > 0.999 ≤ 19,100 NTD/month 1290 (18.5) 5160 (18.5) 5160 (18.5) 19,001 ~ 42,000 NTD/month 2370 (34.1) 9480 (34.1) 9480 (34.1) > 42,000 NTD/month 3298 (47.4) 13,192 (47.4) 13,192 (47.4) CCI score (SD) 0.97 (1.16) 0.80 (1.03) 0.45 (0.77) B > C Other physical comorbidities (n, %) Thyroid disorders 327 (4.7) 953 (3.4) 466 (1.7) B > C Anemia 197 (2.8) 677 (2.4) 398 (1.4) B > C Asthma 435 (6.3) 1389 (5.0) 672 (2.4) B > C Congenital anomalies 90 (1.3) 253 (0.9) 135 (0.5) B > C SD: standard deviation; NTD: New Taiwan dollar; CCI: Charlson Comorbidity Index. During the follow-up duration of 12 years, the incidence of SBI was highest in the TRD group (1.3%), followed by the ARPD group (0.6%) and the control groups (0.1%) (P < 0.001) (Table 2 ). The incidence of septicemia was also highest in the TRD group (0.2%), followed by the ARPD group (0.1%) and the control group (0.0%) (P < 0.001) (Table 2 ). The age at diagnosis of septicemia was significantly different for the three groups (24.00 ± 3.53 in the TRD group, 24.87 ± 3.88 in the ARPD group, and 31.97 ± 4.05 in the control group [P < 0.001]) (Table 2 ). Table 2 Incidence of severe bacterial infection and septicemia between adolescents and young adults with treatment-resistant and antidepressant-responsive depression A. Adolescents and young adults with treatment-resistant depression (n = 6958) B. Adolescents and young adults with antidepressant-responsive depression (n = 27,832) C. Control group (n = 27,832) p-value Post-hoc Incidence of severe bacterial infection (n, %) 122 (1.3) 280 (0.6) 63 (0.1) B > C Incidence of septicemia (n, %) 13 (0.2) 40 (0.1) 12 (0.0) B > C Age at diagnosis (years, SD) 24.00 (3.53) 24.87 (3.88) 31.97 (4.05) < 0.001 A ~ B < C Origins of bacteria Streptococcus 2 (0.0) 7 (0.0) 5 (0.0) 0.739 Klebsiella 1 (0.0) 3 (0.0) 5 (0.0) 0.191 Pseudomonas 1 (0.0) 0 (0.0) 0 (0.0) 0.018 Hemophilus 1 (0.0) 1 (0.0) 1 (0.0) 0.472 Staphylococcus 4 (0.1) 14 (0.1) 2 (0.0) 0.008 A ~ B > C Mycoplasma 2 (0.0) 4 (0.0) 0 (0.0) 0.050 A > B > C Chlamydia 0 (0.0) 1 (0.0) 0 (0.0) 0.535 Meningococcus 0 (0.0) 0 (0.0) 0 (0.0) n.a. Escherichia 8 (0.1) 18 (0.1) 4 (0.0) 0.001 A > B > C Tuberculosis 5 (0.1) 10 (0.0) 2 (0.0) 0.007 A > B > C Zoonotic bacterial diseases 0 (0.0) 0 (0.0) 0 (0.0) n.a. Actinomycotic infections 0 (0.0) 0 (0.0) 0 (0.0) n.a. Rickettsioses 0 (0.0) 4 (0.0) 2 (0.0) 0.472 Syphilis 2 (0.0) 2 (0.0) 0 (0.0) 0.027 A ~ B > C Gonococcus 0 (0.0) 0 (0.0) 0 (0.0) n.a. Trichomoniasis 1 (0.0) 4 (0.0) 0 (0.0) 0.135 SD: standard deviation; n.a.: not available. Adolescents and young adults with TRD had a 6.99 times higher risk (HR, 95% CI: 6.99, 4.73–10.34), and those with ARPD had a 3.90 times higher risk (HR, 95% CI: 3.90, 2.73–5.57) of developing SBI in later life compared to the control group (Table 3 ). Both the TRD (HR, 95% CI: 2.85, 1.28–6.36) and ARPD groups (HR, 95% CI: 2.56, 1.34–4.91) had an increased risk of septicemia later in life compared with the control group (Table 3 ). Table 3 Risks of developing severe bacterial infection and septicemia between adolescents and young adults with treatment-resistant and antidepressant-responsive depression* HR, 95% CI Severe bacterial infection Septicemia Control group 1 (ref) 1 (ref) Antidepressant-responsive depression group 3.90 (2.73–5.57) 2.56 (1.34–4.91) Treatment-resistant depression group 6.99 (4.73–10.34) 2.85 (1.28–6.36) Control and antidepressant-responsive depression group 1 (ref) 1 (ref) Treatment-resistant depression group 2.61 (2.03–3.37) 1.48 (0.80–2.75) HR: hazard ratio; CI: confidence interval; CCI: Charlson Comorbidity Index. *: adjusting for demographic characteristics, CCI, and other physical comorbidities. Bold type indicates statistical significance. Fig. 1 shows the Kaplan-Meier curves of SBI and septicemia in the TRD, ARPD, and control groups. The cumulative SBI and septicemia rates during the maximum 12-year follow-up revealed a statistically significant difference among the three groups. Discussion Our research findings suggest that adolescents and young adults with TRD and ARPD have significantly high risk of SBI and septicaemia compared to the control group. In particular, the risk for SBI was 6.99.-fold and 3.90-fold higher for those with TRD and ARPD, respectively. Furthermore, the risk for septicaemia was 2.85-fold and 2.56-fold higher, respectively. Importantly, the response to antidepressant treatment emerged as an independent factor influencing the development of SBI and septicemia in adolescents and adults with MDD. We found that adolescents and young adults with TRD had a higher incidence of SBI and septicemia than those with ARPD and healthy controls. This finding is consistent with those of previous studies. An analysis of a combined dataset consisting of 130,652 participants from the UK Biobank and additional data from Finnish replication cohorts comprising 109,781 participants revealed a link between depression and an increased susceptibility to bacterial infections requiring hospitalization (HR 2.52; 95% CI, 1.99–3.19) [ 36 ]. Andersson et al. suggested a correlation between depression and escalated susceptibility to a range of infections, particularly sepsis, which showed the highest risk at approximately 2.39 times higher [ 23 ]. Adams et al . further revealed that college students, aged 18–24 years, who reported not experiencing depression, anxiety, or exhaustion were consistently associated with a lower probability of infectious diseases [ 37 ]. Moreover, Hamer et al . demonstrate a correlation between the levels of depression and anxiety distress symptoms and the risk of mortality due to infectious diseases [ 26 ]. Previous research has suggested the possibility of a dose-response relationship between the number of depressive episodes and the occurrence of infections, as well as the severity of symptoms associated with infectious disease mortality. [ 23 , 26 ]. Additionally, even during antidepressant treatment, individuals with depression may be at the highest risk of adverse infection-related outcomes [ 38 ]. The results of the current study are consistent with those of previous studies. Our findings demonstrated that depression correlated positively with the incidence of SBI and septicemia [ 23 , 38 , 39 ]. Furthermore, our study demonstrated that adolescents and young adults with TRD had a 6.99 times higher risk of developing SBI later in life than the control group, which was significantly higher than that in the ARPD group (3.90 times higher). A previous study suggested that the TRD group may manifest characteristics indicative of more severe depression, as well as more medical comorbidities [ 40 ]. The coexistence of TRD and infectious conditions may be influenced by various factors, such as socioeconomic status (SES), shared environmental risk factors, or shared genetic elements [ 41 , 42 ]. Low SES is independently associated with depression and susceptibility to infections [ 41 , 43 , 44 ]. Our study matched the assessed population based on the level of urbanization of residency, serving as an approximate means to control for potential confounding variables related to SES. Poor personal hygiene can potentially increase vulnerability to infection among adolescents and young adults with TRD. Patients with TRD who neglect self-care could also be at risk of common infections that progress to severe SBI and septicemia. Additionally, heightened instances of risk-taking behaviors, such as injuries, are associated with TRD, which may potentially elevate the risk of open wounds and contribute to the development of SBI and septicemia. [ 45 , 46 ]. Moreover, nonadherence to medication may contribute to both TRD and antibiotic resistance, thereby worsening the prognosis and increasing the risk of SBI and septicemia. Several mechanisms may influence the relationship between TRD and SBI development in adolescents and young adults. First, the association between depression and the risk of infection may be mediated through depression-related immunological changes. Individuals with elevated levels of proinflammatory cytokines may have a greater propensity to exhibit resistance to antidepressant medications, thus, potentially heightening their vulnerability to infections and sepsis [ 34 , 47 ]. Depression has been linked to the upregulation of inflammatory cytokines and acute-phase reactants, such as interleukin 6, tumor necrosis factor alpha, and C-reactive protein, which are strongly associated with infection [ 34 , 48 , 49 ]. Second, in patients with depression, abnormalities in the hypothalamic-pituitary-adrenal (HPA) axis have been observed. The abnormalities were associated with the development of depression and antidepressant resistance [ 50 , 51 ]. Additionally, dysregulation of the HPA contributes to the development of systemic bacterial infection and sepsis [ 52 , 53 ]. Third, the gut microbial community is associated with the development and progression of various infectious and inflammatory diseases [ 54 ]. Increasing evidence supports the bidirectional relationship between depression and the gut microbiome. Previous studies have suggested that antidepressant use can influence the composition and function of the gut microbiome, potentially affecting the responses [ 55 – 57 ]. However, the exact mechanisms underlying the effects of antidepressants on gut microbiome remain unclear. Additionally, a Genome-Wide Association Studies (GWAS) study suggested a link between genetically predicted major depressive disorder and an increased risk of sepsis. This finding supports the hypothesis that these two conditions may share common genetic factors [ 58 ]. The results of this study provide further evidence of the role of TRD in infectious diseases among adolescents and young adults. The strengths of our study include a large sample size and, a database-based longitudinal follow-up. This study also has some limitations. First, the data used in this study were extracted from the NHIRD registries from 2000 to 2011. Thus, it may not fully reflect recent developments in healthcare. Second, TRD data captured in the NHIRD registries are based on diagnoses made in psychiatric treatment settings, which can lead to underreporting of depression. Therefore, despite the nationwide population-based design of this study, there is a possibility of selection bias. Third, the incidence of septicemia in our sample was low. Consequently, despite significant HR, the actual risks remained remarkably low in each of the three groups. Furthermore, the strata for certain bacteria were not fully represented due to limited sample sizes. Fourth, SBI do not commonly occur in adolescents and young adults, except in those with severe physical diseases, such as severe autoimmune diseases. In the present study, we only adjusted for the CCI, which included 22 severe physical conditions, as specific types of comorbidities to account for infection-related confounding factors in our regression model. Therefore, several unmeasured biases, such as minor physical diseases, may have influenced our study. Conclusions This study found that individuals with TRD have a higher incidence of SBI and septicemia than those with ARPD and controls. Our findings highlight the need for clinicians to remain vigilant regarding adolescents and young adults with TRD, as they are at an increased risk of developing SBI and septicemia later in life. These results underscore the need for appropriate monitoring and prevention of severe infections in this population. Further research is needed to examine the link between TRD, risk of SBI, and septicemia. Declarations Conflicts of interest No conflict of interest. Ethics approval This study protocol was reviewed and accepted by the Institutional Review Board of Taipei Veterans General Hospital (approval number: TPEVGH-IRB-2018-07-016AC). The requirement for patient consent was waived because the data used in this study were anonymized and derived wholly from a sizeable national database. Informed consent Not Applicable. Funding The study was supported by grant from Taipei Veterans General Hospital (V111C-010, V111C-040, V111C-029), Yen Tjing Ling Medical Foundation (CI-109-21, CI-109-22, CI-110-30) and Ministry of Science and Technology, Taiwan (MOST110-2314-B-075-026, MOST110-2314-B-075-024 -MY3, MOST 109-2314-B-010-050-MY3, MOST111-2314-B-075 -014 -MY2, MOST 111-2314-B-075 -013). The funding source had no role in any process of our study. Author Contribution Drs MHC and CSL designed the study. Drs JRL, MHC, CSL wrote the draft; Drs YCK, SJT, YMB, TPS, and TJC performed the literature review and revised the manuscript; Dr MHC performed the statistical analysis; all authors have read and approved the final submitted manuscript, and agree to be accountable for the work. Data Availability The NHIRD was released and audited by the Department of Health and the Bureau of the NHI Program for Scientific Research (https://nhird.nhri.org.tw/). The NHIRD can be obtained through a formal application regulated by the Department of Health and the Bureau of the NHI Program. References Thapar A, Collishaw S, Pine DS, Thapar AK (2012) Depression in adolescence. Lancet 379(9820):1056–1067 Yorbik O, Birmaher B, Axelson D, Williamson DE, Ryan ND (2004) Clinical characteristics of depressive symptoms in children and adolescents with major depressive disorder. J Clin Psychiatry 65(12):1654–1659 quiz 1760 – 1651 Windfuhr K, While D, Hunt I, Turnbull P, Lowe R, Burns J, Swinson N, Shaw J, Appleby L, Kapur N (2008) Suicide in juveniles and adolescents in the United Kingdom. J Child Psychol Psychiatry 49(11):1155–1165 Goldstein BI, Carnethon MR, Matthews KA, McIntyre RS, Miller GE, Raghuveer G, Stoney CM, Wasiak H, McCrindle BW (2015) Major Depressive Disorder and Bipolar Disorder Predispose Youth to Accelerated Atherosclerosis and Early Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 132(10):965–986 Birmaher B, Brent D (2007) Practice Parameter for the Assessment and Treatment of Children and Adolescents With Depressive Disorders. J Am Acad Child Adolesc Psychiatry 46(11):1503–1526 Mullen S (2018) Major depressive disorder in children and adolescents. Ment Health Clin 8(6):275–283 Lewinsohn PM, Rohde P, Seeley JR (1998) Major depressive disorder in older adolescents: Prevalence, risk factors, and clinical implications. Clin Psychol Rev 18(7):765–794 Fletcher JM (2010) Adolescent depression and educational attainment: results using sibling fixed effects. Health Econ 19(7):855–871 Fergusson DM, Woodward LJ (2002) Mental Health, Educational, and Social Role Outcomes of Adolescents With Depression. Arch Gen Psychiatry 59(3):225–231 Chen LC, Chen YH, Bai YM, Chen TJ, Chen MH, Su TP (2020) Antidepressant resistance in adolescents with major depressive disorder: A nationwide longitudinal study. J Affect Disord 262:293–297 Fava M (2003) Diagnosis and definition of treatment-resistant depression. Biol Psychiatry 53(8):649–659 Rush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, Niederehe G, Thase ME, Lavori PW, Lebowitz BD et al (2006) Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry 163(11):1905–1917 Cheng CM, Chen MH, Tsai SJ, Chang WH, Tsai CF, Lin WC, Bai YM, Su TP, Chen TJ, Li CT (2024) Susceptibility to Treatment-Resistant Depression Within Families. JAMA Psychiatry Amos TB, Tandon N, Lefebvre P, Pilon D, Kamstra RL, Pivneva I, Greenberg PE (2018) Direct and Indirect Cost Burden and Change of Employment Status in Treatment-Resistant Depression: A Matched-Cohort Study Using a US Commercial Claims Database. J Clin Psychiatry 79(2) Cai Q, Sheehan JJ, Wu B, Alphs L, Connolly N, Benson C (2020) Descriptive analysis of the economic burden of treatment resistance in a major depressive episode. Curr Med Res Opin 36(2):329–335 Ramirez JM (2003) Hormones and aggression in childhood and adolescence. Aggress Violent Beh 8(6):621–644 Willoughby T, Good M, Adachi PJ, Hamza C, Tavernier R (2013) Examining the link between adolescent brain development and risk taking from a social-developmental perspective. Brain Cogn 83(3):315–323 Borensztajn D, Hagedoorn NN, Carrol E, von Both U, Dewez JE, Emonts M, van der Flier M, de Groot R, Herberg J, Kohlmaier B et al (2022) Characteristics and management of adolescents attending the ED with fever: a prospective multicentre study. BMJ Open 12(1):e053451 Angus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR (2001) Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 29(7):1303–1310 Shime N, Kawasaki T, Saito O, Akamine Y, Toda Y, Takeuchi M, Sugimura H, Sakurai Y, Iijima M, Ueta I et al (2012) Incidence and risk factors for mortality in paediatric severe sepsis: results from the national paediatric intensive care registry in Japan. Intensive Care Med 38(7):1191–1197 Rudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, Colombara DV, Ikuta KS, Kissoon N, Finfer S (2020) Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. Lancet 395(10219):200–211 Seminog OO, Goldacre MJ (2013) Risk of pneumonia and pneumococcal disease in people with severe mental illness: English record linkage studies. Thorax 68(2):171–176 Andersson NW, Goodwin RD, Okkels N, Gustafsson LN, Taha F, Cole SW, Munk-Jørgensen P (2016) Depression and the risk of severe infections: prospective analyses on a nationwide representative sample. Int J Epidemiol 45(1):131–139 Irwin MR, Levin MJ, Carrillo C, Olmstead R, Lucko A, Lang N, Caulfield MJ, Weinberg A, Chan IS, Clair J et al (2011) Major depressive disorder and immunity to varicella-zoster virus in the elderly. Brain Behav Immun 25(4):759–766 Mulugeta A, Zhou A, King C, Hyppönen E (2020) Association between major depressive disorder and multiple disease outcomes: a phenome-wide Mendelian randomisation study in the UK Biobank. Mol Psychiatry 25(7):1469–1476 Hamer M, Kivimaki M, Stamatakis E, Batty GD (2019) Psychological distress and infectious disease mortality in the general population. Brain Behav Immun 76:280–283 Chen MH, Pan TL, Li CT, Lin WC, Chen YS, Lee YC, Tsai SJ, Hsu JW, Huang KL, Tsai CF et al (2015) Risk of stroke among patients with post-traumatic stress disorder: nationwide longitudinal study. Br J psychiatry: J mental Sci 206(4):302–307 Chen MH, Su TP, Chen YS, Hsu JW, Huang KL, Chang WH, Bai YM (2013) Attention deficit hyperactivity disorder, tic disorder, and allergy: is there a link? A nationwide population-based study. J Child Psychol Psychiatry Allied Discip 54(5):545–551 Cheng CM, Chang WH, Chen MH, Tsai CF, Su TP, Li CT, Tsai SJ, Hsu JW, Huang KL, Lin WC et al (2018) Co-aggregation of major psychiatric disorders in individuals with first-degree relatives with schizophrenia: a nationwide population-based study. Mol Psychiatry 23(8):1756–1763 Liang CS, Bai YM, Hsu JW, Huang KL, Ko NY, Chu HT, Yeh TC, Tsai SJ, Chen TJ, Chen MH (2020) The Risk of Sexually Transmitted Infections Following First-Episode Schizophrenia Among Adolescents and Young Adults: A Cohort Study of 220 545 Subjects. Schizophrenia bulletin Li CT, Bai YM, Huang YL, Chen YS, Chen TJ, Cheng JY, Su TP (2012) Association between antidepressant resistance in unipolar depression and subsequent bipolar disorder: cohort study. Br J psychiatry: J mental Sci 200(1):45–51 Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373–383 Liu CY, Hung YT, Chuang YL, Chen YJ, Weng WS, Liu JS (2006) Incorporating development stratification of Taiwan townships into sampling design of large scale health interview survey. J Health Manage (Chin) 4:1–22 Miller AH, Maletic V, Raison CL (2009) Inflammation and Its Discontents: The Role of Cytokines in the Pathophysiology of Major Depression. Biol Psychiatry 65(9):732–741 Ruiz NAL, Del Ángel DS, Brizuela NO, Peraza AV, Olguín HJ, Soto MP, Guzmán DC (2022) Inflammatory Process and Immune System in Major Depressive Disorder. Int J Neuropsychopharmacol 25(1):46–53 Frank P, Batty GD, Pentti J, Jokela M, Poole L, Ervasti J, Vahtera J, Lewis G, Steptoe A, Kivimäki M (2023) Association Between Depression and Physical Conditions Requiring Hospitalization. JAMA Psychiatry 80(7):690–699 Adams TB, Wharton CM, Quilter L, Hirsch T (2008) The association between mental health and acute infectious illness among a national sample of 18- to 24-year-old college students. J Am Coll Health 56(6):657–663 Davydow DS, Ribe AR, Pedersen HS, Vestergaard M, Fenger-Grøn M (2016) The association of unipolar depression with thirty-day mortality after hospitalization for infection: A population-based cohort study in Denmark. J Psychosom Res 89:32–38 Ronaldson A, Arias de la Torre J, Sima R, Ashworth M, Armstrong D, Bakolis I, Hotopf M, Dregan A (2022) Prospective associations between depression and risk of hospitalisation for infection: Findings from the UK Biobank. Brain Behav Immun 102:292–298 Maalouf FT, Atwi M, Brent DA (2011) Treatment-resistant depression in adolescents: review and updates on clinical management. Depress Anxiety 28(11):946–954 Forrester JD, Cao S, Schaps D, Liou R, Patil A, Stave C, Sokolow SH, Leo G (2022) Influence of Socioeconomic and Environmental Determinants of Health on Human Infection and Colonization with Antibiotic-Resistant and Antibiotic-Associated Pathogens: A Scoping Review. Surg Infect (Larchmt) 23(3):209–225 Wu Y, Murray GK, Byrne EM, Sidorenko J, Visscher PM, Wray NR (2021) GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression. Nat Commun 12(1):1146 Lorant V, Deliège D, Eaton W, Robert A, Philippot P, Ansseau M (2003) Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol 157(2):98–112 Miller G, Chen E, Cole SW (2009) Health psychology: developing biologically plausible models linking the social world and physical health. Annu Rev Psychol 60:501–524 Gronemann FH, Jørgensen MB, Nordentoft M, Andersen PK, Osler M (2021) Treatment-resistant depression and risk of all-cause mortality and suicidality in Danish patients with major depression. J Psychiatr Res 135:197–202 Tørmoen AJ, Myhre M, Walby FA, Grøholt B, Rossow I (2020) Change in prevalence of self-harm from 2002 to 2018 among Norwegian adolescents. Eur J Public Health 30(4):688–692 Netea MG, van der Meer JWM, van Deuren M, Jan Kullberg B (2003) Proinflammatory cytokines and sepsis syndrome: not enough, or too much of a good thing? Trends Immunol 24(5):254–258 Colasanto M, Madigan S, Korczak DJ (2020) Depression and inflammation among children and adolescents: A meta-analysis. J Affect Disord 277:940–948 Rengasamy M, Marsland A, McClain L, Kovats T, Walko T, Pan L, Price RB (2021) Longitudinal relationships of cytokines, depression and anhedonia in depressed adolescents. Brain Behav Immun 91:74–80 Lopez-Duran NL, Kovacs M, George CJ (2009) Hypothalamic-pituitary-adrenal axis dysregulation in depressed children and adolescents: a meta-analysis. Psychoneuroendocrinology 34(9):1272–1283 Sigalas PD, Garg H, Watson S, McAllister-Williams RH, Ferrier IN (2012) Metyrapone in treatment-resistant depression. Ther Adv Psychopharmacol 2(4):139–149 Webster JI, Sternberg EM (2004) Role of the hypothalamic-pituitary-adrenal axis, glucocorticoids and glucocorticoid receptors in toxic sequelae of exposure to bacterial and viral products. J Endocrinol 181(2):207–221 Vandewalle J, Libert C (2020) Glucocorticoids in Sepsis: To Be or Not to Be. Front Immunol 11:1318 Maciel-Fiuza MF, Muller GC, Campos DMS, do, Socorro Silva Costa P, Peruzzo J, Bonamigo RR, Veit T, Vianna FSL (2023) Role of gut microbiota in infectious and inflammatory diseases. Front Microbiol 14:1098386 Dong Z, Shen X, Hao Y, Li J, Xu H, Yin L, Kuang W (2022) Gut microbiome: A potential indicator for predicting treatment outcomes in major depressive disorder. Front Neurosci 16:813075 Fontana A, Manchia M, Panebianco C, Paribello P, Arzedi C, Cossu E, Garzilli M, Montis MA, Mura A, Pisanu C et al (2020) Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants. Biomedicines 8(9) Wilkowska A, Szałach ŁP, Cubała WJ (2021) Gut Microbiota in Depression: A Focus on Ketamine. Front Behav Neurosci 15:693362 Yang R, Xiang H, Zheng T (2024) Causal associations between severe mental illness and sepsis: a Mendelian randomization study. Front Psychiatry 15:1341559 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 08 Mar, 2025 Read the published version in European Child & Adolescent Psychiatry → Version 1 posted Editorial decision: Revision requested 21 Nov, 2024 Reviews received at journal 20 Nov, 2024 Reviewers agreed at journal 10 Nov, 2024 Reviewers agreed at journal 05 Nov, 2024 Reviewers agreed at journal 05 Nov, 2024 Reviewers agreed at journal 13 Jul, 2024 Reviews received at journal 11 Jul, 2024 Reviewers agreed at journal 11 Jul, 2024 Reviewers invited by journal 11 Jul, 2024 Editor assigned by journal 20 Jun, 2024 Submission checks completed at journal 20 Jun, 2024 First submitted to journal 20 Jun, 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-4614090","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320451636,"identity":"a3fb6d9b-4b32-4900-a6c5-309681167a31","order_by":0,"name":"Jia-Ru Li","email":"","orcid":"","institution":"Far Eastern Memorial Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jia-Ru","middleName":"","lastName":"Li","suffix":""},{"id":320451637,"identity":"9fa50b9e-6836-44e7-8c28-3ab5128954da","order_by":1,"name":"Yu-Chen Kao","email":"","orcid":"","institution":"National Defense Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Yu-Chen","middleName":"","lastName":"Kao","suffix":""},{"id":320451638,"identity":"978b5d13-7834-4b8c-b182-3e4256da8145","order_by":2,"name":"Shih-Jen Tsai","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shih-Jen","middleName":"","lastName":"Tsai","suffix":""},{"id":320451639,"identity":"b4b5c921-4e6d-446e-8066-8c7b5846838f","order_by":3,"name":"Ya-Mei Bai","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ya-Mei","middleName":"","lastName":"Bai","suffix":""},{"id":320451640,"identity":"16ce51cd-1c1c-4f57-a254-8ffcbaa8d484","order_by":4,"name":"Tung-Ping Su","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tung-Ping","middleName":"","lastName":"Su","suffix":""},{"id":320451641,"identity":"85f7fcb3-7dfd-492b-8f3d-a32ac38993d8","order_by":5,"name":"Tzeng-Ji Chen","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tzeng-Ji","middleName":"","lastName":"Chen","suffix":""},{"id":320451642,"identity":"971eab0c-c7a8-4d63-b98c-0ad67fc2d61b","order_by":6,"name":"Chih-Sung Liang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYBACPhBRwWADJBkbDxClhQ1EnGFIA2lpIEnLYTCHSC3sx59JHGw7b7e2/TDQlhqbaMJaeHLMgFpuJ287kwjUciwtt4GgFgkeNumP224nmx0AamFsOEyMFnagw7adSzY7/5BoLQxAh207YGd2g2hbeHKMLQ7+S04wuwG0JYEYv/CzH39448AZO3uz8+kPH3yosSGsBQhYJIBEIlhlAhHKQYD5A5CwJ1LxKBgFo2AUjEQAAINBRq452aRLAAAAAElFTkSuQmCC","orcid":"","institution":"National Defense Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Chih-Sung","middleName":"","lastName":"Liang","suffix":""},{"id":320451643,"identity":"7d3de061-2460-45d9-9d91-5c8ffcb54422","order_by":7,"name":"Mu-Hong Chen","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mu-Hong","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-06-21 00:23:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4614090/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4614090/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00787-025-02684-y","type":"published","date":"2025-03-08T15:58:42+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60600354,"identity":"6f44e5b3-7ce2-435f-a9ae-20a181e8795c","added_by":"auto","created_at":"2024-07-18 16:01:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":135269,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4614090/v1/ddcab6f47c3c867ad50d7cd9.png"},{"id":78190912,"identity":"5952f341-3086-4bb7-937a-4af5a5cf3c76","added_by":"auto","created_at":"2025-03-10 19:51:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1199380,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4614090/v1/5b404357-c83a-44bd-b5f7-e37f1c008614.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Analysis of the Risk of Severe Bacterial Infection and Septicemia in Adolescents and Young Adults with Treatment-Resistant Depression and Treatment- Responsive Depression - A Nationwide Cohort Study in Taiwan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMajor depressive disorder is a significant mental health concern and a leading cause of disability. It typically begins in adolescence and contributes significantly to the disease burden among young individuals. Studies have estimated the prevalence of major depressive disorder (MDD) to be approximately 4\u0026ndash;6% among adolescents. Moreover, the incidence of depressive symptoms and MDD increases sharply during adolescence [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The onset of MDD during adolescence is associated with increased illness severity in adulthood, increased psychiatric morbidity, and poor physical health outcomes [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Additionally, adolescents and young adults with MDD tend to experience significant social and educational difficulties, thus, increasing the risk of long-term psychosocial impairment in adulthood [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong adolescents with MDD, up to 23% show poor response to initial antidepressant treatment, and approximately 2% meet the criteria for treatment- resistant depression (TRD) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The strict criteria for TRD typically signify an inadequate response to at least two trials of antidepressants prescribed at sufficient doses for an appropriate duration [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Resistance to antidepressants in adolescents with MDD is associated with comorbidities, such as anxiety disorders, substance use disorders, and attention deficit hyperactivity disorder [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Consequently, increasing outpatient healthcare resource utilization, inpatient days, and higher all-cause mortality. Moreover, previous studies have indicated that TRD may be associated with diminished health-related quality of life, general medical condition exacerbations, and increased healthcare costs [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdolescents and young adults undergo various transitional stages that potentially render them more susceptible to infection. This increased vulnerability can be attributed to various factors, such as hormonal changes, heightened social interactions, and higher engagement in risk-taking behaviors during this developmental phase. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A study revealed a higher incidence of severe bacterial infections (SBI) (Odds Ratio [OR], 95% CI: 1.8, 1.6\u0026ndash;2.0) and sepsis (OR, 95% CI: 2.3, 1.1\u0026ndash;5.0) among adolescents compared to children, resulting in more frequent hospital admissions [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Septicemia, characterized by the occurrence of sepsis accompanied by the presence of pathogenic microorganisms within the bloodstream, is associated with significant negative consequences, such as organ dysfunction, long-term impairment, and high mortality rates [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Hence, addressing infections in global public health is of significant importance. Indeed, a Japanese study observed a 25% overall mortality from sepsis in adolescents in intensive care units. Moreover, an alarming estimate of more than 10\u0026nbsp;million sepsis-related deaths annually highlights the substantial contribution of infections to over 20% of global mortality [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Despite the encouraging decrease in the age-standardized incidence of sepsis by 37.0% (95% uncertainty interval [UI] 11.8\u0026ndash;54.5) and mortality by 52.8% (47.7\u0026ndash;57.5) from 1990 to 2017, addressing the burden of severe bacterial infections (SBI) and septicemia remains a crucial priority [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eClinical data suggest a potential link between depression and an increased risk of infection [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. For example, a previous study identified a potential link between major MDD and an increased risk of herpes zoster in older adults [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Another study associated depression with an increased risk of a wide range of infections [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, data from the UK Biobank links the genetic risk score for MDD with a higher likelihood of intestinal \u003cem\u003eE.coli\u003c/em\u003e infections (OR 3.24, 95% CI 1.74\u0026ndash;6.02) [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Furthermore, previous studies have found that adults with a history of depression are more susceptible to various infections than those without a history of depression [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, cross-sectional studies have demonstrated a correlation between depressive and anxiety symptoms and the risk of mortality due to infectious diseases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. However, limited research has been conducted on the relationship between TRD and SBI among adolescents and young adults.\u003c/p\u003e \u003cp\u003eIn the current study, using longitudinal data from a large sample population drawn from the Taiwan National Health Insurance Research Database (NHIRD), we investigated the risk of developing SBI and septicemia in adolescents and young adults with MDD., especially TRD We hypothesized that adolescents and young adults with TRD have a higher risk of SBI and septicemia in later stages of life relative to adolescents and young adults with antidepressant-responsive depression (ARPD), and those without depression.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eData source.\u003c/b\u003e The Taiwan NHIRD is audited and released by the National Health Research Institute (NHRI) for scientific and study purposes upon the formal application. In the current study, we linked two datasets of the NHIRD, namely, the specialized dataset of mental disorders and the longitudinal health insurance database, for analysis. The specialized dataset of mental disorders included all medical records of all insured individuals with mental disorders, and thus, was used for identifying participants of the study group in the current study. The longitudinal health insurance database includes all medical records of 3,000,000 insured individuals randomly selected from the entire Taiwanese population (approximately 28,000,000) and was used to identify participants of the control group. The diagnostic codes used were based on the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM). The NHIRD has been extensively used in many epidemiological studies in Taiwan [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This study was approved by the Institutional Review Board of the Taipei Veterans General Hospital. The Taipei Veterans General Hospital Institutional Review Board approved the study protocol and waived the requirement for informed consent because this investigation used de-identified data and no human subject contact was required.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy protocol.\u003c/b\u003e Adolescents (aged 12\u0026ndash;19 years), and young adults (aged 20\u0026ndash;29 years), who were diagnosed with MDD (ICD-9-CM codes: 296.2, 296.3) by board-certified psychiatrists and had no prior history of SBI between 2001 and 2010 were included in this study. To specifically identify SBI and improve our diagnostic validity, only the diagnostic codes of bacterial infections in the inpatient dataset were included in the present study. Septicemia was defined using the ICD-9-CM code 038 in the inpatient dataset. In Taiwan, to reduce and control the risk of developing antibiotic-resistant bacteria, hospital infectionists supervise the use of antibiotics in infectious diseases, and cultures of infectious origins are required in clinical practice. These clinical procedures aim to ensure the diagnostic validity of infections and their origins. Patients with MDD were classified into two groups (ARPD and TRD) based on their antidepressant treatment response during 1 year of follow-up following diagnosis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. An adequate trial of antidepressant treatment was defined as the use of an antidepressant within its therapeutic dosage range (e.g., fluoxetine\u0026thinsp;\u0026ge;\u0026thinsp;20 mg/day) for \u0026ge;\u0026thinsp;60 consecutive days [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Patients who remained on a single antidepressant were assigned to the ARPD group, and those who changed the antidepressant treatment regimen two or more times were assigned to the TRD group. The ARPD and TRD groups were further matched (4:1) by chronological age, age at the time of depression diagnosis, sex, residence, and family income. For the control group, participants were also age-, sex-, family income-, and residence-matched (1:4), after eliminating participants that were potential study cases, namely, those who had any diagnostic code for severe mental disorders (ICD-9-CM codes: 295, 296, 300.3, 300.4, and 311) in the database, and those who had been diagnosed with SBI before enrollment. SBI were identified in the inpatient dataset from enrollment until the end of 2011. Additionally, Charlson Comorbidity Index (CCI) and all-cause clinical visits were provided for the study and control cohorts. CCI consisting of 22 physical conditions was also assessed to determine the systemic health conditions of all enrolled individuals [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. CCI includes myocardial infarction, congestive heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic pulmonary disease, rheumatologic disease, peptic ulcer disease, liver disease, diabetes, hemiplegia, paraplegia, renal disease, malignancy, leukemia, lymphoma, and AIDS [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In order to avoid the bias from the confounding effect of other infection-related physical comorbidities, we additionally assessed asthma, thyroid disorders, anemia, and congenital anomalies in the present study. Income level (levels 1\u0026ndash;3 per month: \u0026le; 19,000 NTD (New Taiwanese Dollars), 19,001\u0026ndash;42,000 NTD, and \u0026ge;\u0026thinsp;42,001 NTD) and urbanization level of residence (levels 1\u0026ndash;5, most to least urbanized) were regarded as the proxies for healthcare availability in Taiwan [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical analysis.\u003c/b\u003e For between-group comparisons, the F-test was used for continuous variables and Pearson's X\u003csup\u003e2\u003c/sup\u003e test was used for nominal variables, where appropriate. Cox regression models with adjustments for age, sex, level of urbanization, income, and CCI scores were used to investigate the HR with a 95% confidence interval (CI) of SBI and septicemia during the follow-up between groups. Finally, given the hypothesis that depressed patients who responded to antidepressant treatment were less likely to be affected by the inflammatory and immunological dysfunction [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], we investigated the likelihoods of severe bacterial infection and septicemia between patients with TRD and the combined group of patients with non-TRD and non-depressed control individuals. A 2-tailed \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 was considered statistically significant. All data processing and statistical analyses were performed using the Statistical Package for Social Science, version 17 (SPSS; SPSS Inc., Armonk, NY, USA) and Statistical Analysis Software version 9.1 (SAS; SAS Institute, Cary, NC).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Availability Statement.\u0026nbsp;\u003c/strong\u003eThe NHIRD was released and audited by the Department of Health and the Bureau of the NHI Program for Scientific Research (https://nhird.nhri.org.tw/). The NHIRD can be obtained through a formal application regulated by the Department of Health and the Bureau of the NHI Program.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003eIn total, 62,622 adolescents and young adults were included in this study, including 6,958 adolescents and young adults with TRD, 27,832 adolescents and young adults with ARPD, and 27,832 controls (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mean age is approximately 22.8 years, with a female predominance of 52.6% of the population (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, adolescents and young adults with TRD were more likely to have higher CCI scores and other physical comorbidities than those in the other two groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\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\u003eDemographic characteristics between adolescents and young adults with treatment-resistant and antidepressant-responsive depression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA. Adolescents and young adults with treatment-resistant depression (n\u0026thinsp;=\u0026thinsp;6958)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB. Adolescents and young adults with antidepressant-responsive depression (n\u0026thinsp;=\u0026thinsp;27,832)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC. Control group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;27,832)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-hoc\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at depression diagnosis or enrollment (years, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.84 (4.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.80 (4.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.83 (4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3301 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,204 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,204 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLevel of urbanization (n, %)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 (most urbanized)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1948 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7792 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7792 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2343 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9372 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9372 (33.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e908 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3632 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3632 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e631 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2524 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2524 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5 (most rural)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1128 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4512 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4512 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncome-related insured amount (n, %)\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=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le; 19,100 NTD/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1290 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5160 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5160 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19,001\u0026thinsp;~\u0026thinsp;42,000 NTD/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2370 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9480 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9480 (34.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; 42,000 NTD/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3298 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,192 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,192 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCCI score (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.97 (1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80 (1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45 (0.77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther physical comorbidities (n, %)\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e327 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e953 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e466 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e197 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e677 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e398 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e435 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1389 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e672 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCongenital anomalies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e90 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e253 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e135 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSD: standard deviation; NTD: New Taiwan dollar; CCI: Charlson Comorbidity Index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eDuring the follow-up duration of 12 years, the incidence of SBI was highest in the TRD group (1.3%), followed by the ARPD group (0.6%) and the control groups (0.1%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The incidence of septicemia was also highest in the TRD group (0.2%), followed by the ARPD group (0.1%) and the control group (0.0%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The age at diagnosis of septicemia was significantly different for the three groups (24.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.53 in the TRD group, 24.87\u0026thinsp;\u0026plusmn;\u0026thinsp;3.88 in the ARPD group, and 31.97\u0026thinsp;\u0026plusmn;\u0026thinsp;4.05 in the control group [P\u0026thinsp;\u0026lt;\u0026thinsp;0.001]) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003eIncidence of severe bacterial infection and septicemia between adolescents and young adults with treatment-resistant and antidepressant-responsive depression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA. Adolescents and young adults with treatment-resistant depression (n\u0026thinsp;=\u0026thinsp;6958)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB. Adolescents and young adults with antidepressant-responsive depression (n\u0026thinsp;=\u0026thinsp;27,832)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC. Control group\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;27,832)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-hoc\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncidence of severe bacterial infection (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e280 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e63 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncidence of septicemia (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge at diagnosis (years, SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24.00 (3.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.87 (3.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.97 (4.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;~\u0026thinsp;B\u0026thinsp;\u0026lt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOrigins of bacteria\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStreptococcus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKlebsiella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePseudomonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemophilus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaphylococcus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;~\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMycoplasma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChlamydia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeningococcus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.a.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEscherichia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;\u0026gt;\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eZoonotic bacterial diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.a.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActinomycotic infections\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.a.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRickettsioses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyphilis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eA\u0026thinsp;~\u0026thinsp;B\u0026thinsp;\u0026gt;\u0026thinsp;C\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGonococcus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.a.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrichomoniasis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eSD: standard deviation; n.a.: not available.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAdolescents and young adults with TRD had a 6.99 times higher risk (HR, 95% CI: 6.99, 4.73\u0026ndash;10.34), and those with ARPD had a 3.90 times higher risk (HR, 95% CI: 3.90, 2.73\u0026ndash;5.57) of developing SBI in later life compared to the control group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Both the TRD (HR, 95% CI: 2.85, 1.28\u0026ndash;6.36) and ARPD groups (HR, 95% CI: 2.56, 1.34\u0026ndash;4.91) had an increased risk of septicemia later in life compared with the control group (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRisks of developing severe bacterial infection and septicemia between adolescents and young adults with treatment-resistant and antidepressant-responsive depression*\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHR, 95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere bacterial infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSepticemia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntidepressant-responsive depression group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3.90 (2.73\u0026ndash;5.57)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.56 (1.34\u0026ndash;4.91)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-resistant depression group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.99 (4.73\u0026ndash;10.34)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.85 (1.28\u0026ndash;6.36)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl and antidepressant-responsive depression group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatment-resistant depression group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e2.61 (2.03\u0026ndash;3.37)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.48 (0.80\u0026ndash;2.75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eHR: hazard ratio; CI: confidence interval; CCI: Charlson Comorbidity Index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*: adjusting for demographic characteristics, CCI, and other physical comorbidities.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eBold type\u003c/b\u003e indicates statistical significance.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cp\u003eFig. 1 shows the Kaplan-Meier curves of SBI and septicemia in the TRD, ARPD, and control groups. The cumulative SBI and septicemia rates during the maximum 12-year follow-up revealed a statistically significant difference among the three groups.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur research findings suggest that adolescents and young adults with TRD and ARPD have significantly high risk of SBI and septicaemia compared to the control group. In particular, the risk for SBI was 6.99.-fold and 3.90-fold higher for those with TRD and ARPD, respectively. Furthermore, the risk for septicaemia was 2.85-fold and 2.56-fold higher, respectively. Importantly, the response to antidepressant treatment emerged as an independent factor influencing the development of SBI and septicemia in adolescents and adults with MDD.\u003c/p\u003e \u003cp\u003eWe found that adolescents and young adults with TRD had a higher incidence of SBI and septicemia than those with ARPD and healthy controls. This finding is consistent with those of previous studies. An analysis of a combined dataset consisting of 130,652 participants from the UK Biobank and additional data from Finnish replication cohorts comprising 109,781 participants revealed a link between depression and an increased susceptibility to bacterial infections requiring hospitalization (HR 2.52; 95% CI, 1.99\u0026ndash;3.19) [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Andersson \u003cem\u003eet al.\u003c/em\u003e suggested a correlation between depression and escalated susceptibility to a range of infections, particularly sepsis, which showed the highest risk at approximately 2.39 times higher [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Adams \u003cem\u003eet al\u003c/em\u003e. further revealed that college students, aged 18\u0026ndash;24 years, who reported not experiencing depression, anxiety, or exhaustion were consistently associated with a lower probability of infectious diseases [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Moreover, Hamer \u003cem\u003eet al\u003c/em\u003e. demonstrate a correlation between the levels of depression and anxiety distress symptoms and the risk of mortality due to infectious diseases [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Previous research has suggested the possibility of a dose-response relationship between the number of depressive episodes and the occurrence of infections, as well as the severity of symptoms associated with infectious disease mortality. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, even during antidepressant treatment, individuals with depression may be at the highest risk of adverse infection-related outcomes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The results of the current study are consistent with those of previous studies. Our findings demonstrated that depression correlated positively with the incidence of SBI and septicemia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Furthermore, our study demonstrated that adolescents and young adults with TRD had a 6.99 times higher risk of developing SBI later in life than the control group, which was significantly higher than that in the ARPD group (3.90 times higher).\u003c/p\u003e \u003cp\u003eA previous study suggested that the TRD group may manifest characteristics indicative of more severe depression, as well as more medical comorbidities [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The coexistence of TRD and infectious conditions may be influenced by various factors, such as socioeconomic status (SES), shared environmental risk factors, or shared genetic elements [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Low SES is independently associated with depression and susceptibility to infections [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Our study matched the assessed population based on the level of urbanization of residency, serving as an approximate means to control for potential confounding variables related to SES. Poor personal hygiene can potentially increase vulnerability to infection among adolescents and young adults with TRD. Patients with TRD who neglect self-care could also be at risk of common infections that progress to severe SBI and septicemia. Additionally, heightened instances of risk-taking behaviors, such as injuries, are associated with TRD, which may potentially elevate the risk of open wounds and contribute to the development of SBI and septicemia. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Moreover, nonadherence to medication may contribute to both TRD and antibiotic resistance, thereby worsening the prognosis and increasing the risk of SBI and septicemia.\u003c/p\u003e \u003cp\u003eSeveral mechanisms may influence the relationship between TRD and SBI development in adolescents and young adults. First, the association between depression and the risk of infection may be mediated through depression-related immunological changes. Individuals with elevated levels of proinflammatory cytokines may have a greater propensity to exhibit resistance to antidepressant medications, thus, potentially heightening their vulnerability to infections and sepsis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Depression has been linked to the upregulation of inflammatory cytokines and acute-phase reactants, such as interleukin 6, tumor necrosis factor alpha, and C-reactive protein, which are strongly associated with infection [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Second, in patients with depression, abnormalities in the hypothalamic-pituitary-adrenal (HPA) axis have been observed. The abnormalities were associated with the development of depression and antidepressant resistance [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Additionally, dysregulation of the HPA contributes to the development of systemic bacterial infection and sepsis [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Third, the gut microbial community is associated with the development and progression of various infectious and inflammatory diseases [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Increasing evidence supports the bidirectional relationship between depression and the gut microbiome. Previous studies have suggested that antidepressant use can influence the composition and function of the gut microbiome, potentially affecting the responses [\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. However, the exact mechanisms underlying the effects of antidepressants on gut microbiome remain unclear. Additionally, a Genome-Wide Association Studies (GWAS) study suggested a link between genetically predicted major depressive disorder and an increased risk of sepsis. This finding supports the hypothesis that these two conditions may share common genetic factors [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results of this study provide further evidence of the role of TRD in infectious diseases among adolescents and young adults. The strengths of our study include a large sample size and, a database-based longitudinal follow-up. This study also has some limitations. First, the data used in this study were extracted from the NHIRD registries from 2000 to 2011. Thus, it may not fully reflect recent developments in healthcare. Second, TRD data captured in the NHIRD registries are based on diagnoses made in psychiatric treatment settings, which can lead to underreporting of depression. Therefore, despite the nationwide population-based design of this study, there is a possibility of selection bias. Third, the incidence of septicemia in our sample was low. Consequently, despite significant HR, the actual risks remained remarkably low in each of the three groups. Furthermore, the strata for certain bacteria were not fully represented due to limited sample sizes. Fourth, SBI do not commonly occur in adolescents and young adults, except in those with severe physical diseases, such as severe autoimmune diseases. In the present study, we only adjusted for the CCI, which included 22 severe physical conditions, as specific types of comorbidities to account for infection-related confounding factors in our regression model. Therefore, several unmeasured biases, such as minor physical diseases, may have influenced our study.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study found that individuals with TRD have a higher incidence of SBI and septicemia than those with ARPD and controls. Our findings highlight the need for clinicians to remain vigilant regarding adolescents and young adults with TRD, as they are at an increased risk of developing SBI and septicemia later in life. These results underscore the need for appropriate monitoring and prevention of severe infections in this population. Further research is needed to examine the link between TRD, risk of SBI, and septicemia.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflicts of interest\u003c/h2\u003e \u003cp\u003eNo conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics approval\u003c/h2\u003e \u003cp\u003e This study protocol was reviewed and accepted by the Institutional Review Board of Taipei Veterans General Hospital (approval number: TPEVGH-IRB-2018-07-016AC). The requirement for patient consent was waived because the data used in this study were anonymized and derived wholly from a sizeable national database.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eInformed consent\u003c/h2\u003e \u003cp\u003eNot Applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe study was supported by grant from Taipei Veterans General Hospital (V111C-010, V111C-040, V111C-029), Yen Tjing Ling Medical Foundation (CI-109-21, CI-109-22, CI-110-30) and Ministry of Science and Technology, Taiwan (MOST110-2314-B-075-026, MOST110-2314-B-075-024 -MY3, MOST 109-2314-B-010-050-MY3, MOST111-2314-B-075 -014 -MY2, MOST 111-2314-B-075 -013). The funding source had no role in any process of our study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eDrs MHC and CSL designed the study. Drs JRL, MHC, CSL wrote the draft; Drs YCK, SJT, YMB, TPS, and TJC performed the literature review and revised the manuscript; Dr MHC performed the statistical analysis; all authors have read and approved the final submitted manuscript, and agree to be accountable for the work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe NHIRD was released and audited by the Department of Health and the Bureau of the NHI Program for Scientific Research (https://nhird.nhri.org.tw/). The NHIRD can be obtained through a formal application regulated by the Department of Health and the Bureau of the NHI Program.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThapar A, Collishaw S, Pine DS, Thapar AK (2012) Depression in adolescence. Lancet 379(9820):1056\u0026ndash;1067\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYorbik O, Birmaher B, Axelson D, Williamson DE, Ryan ND (2004) Clinical characteristics of depressive symptoms in children and adolescents with major depressive disorder. J Clin Psychiatry 65(12):1654\u0026ndash;1659 quiz 1760\u0026thinsp;\u0026ndash;\u0026thinsp;1651\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWindfuhr K, While D, Hunt I, Turnbull P, Lowe R, Burns J, Swinson N, Shaw J, Appleby L, Kapur N (2008) Suicide in juveniles and adolescents in the United Kingdom. J Child Psychol Psychiatry 49(11):1155\u0026ndash;1165\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoldstein BI, Carnethon MR, Matthews KA, McIntyre RS, Miller GE, Raghuveer G, Stoney CM, Wasiak H, McCrindle BW (2015) Major Depressive Disorder and Bipolar Disorder Predispose Youth to Accelerated Atherosclerosis and Early Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 132(10):965\u0026ndash;986\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBirmaher B, Brent D (2007) Practice Parameter for the Assessment and Treatment of Children and Adolescents With Depressive Disorders. J Am Acad Child Adolesc Psychiatry 46(11):1503\u0026ndash;1526\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMullen S (2018) Major depressive disorder in children and adolescents. Ment Health Clin 8(6):275\u0026ndash;283\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLewinsohn PM, Rohde P, Seeley JR (1998) Major depressive disorder in older adolescents: Prevalence, risk factors, and clinical implications. Clin Psychol Rev 18(7):765\u0026ndash;794\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFletcher JM (2010) Adolescent depression and educational attainment: results using sibling fixed effects. Health Econ 19(7):855\u0026ndash;871\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFergusson DM, Woodward LJ (2002) Mental Health, Educational, and Social Role Outcomes of Adolescents With Depression. Arch Gen Psychiatry 59(3):225\u0026ndash;231\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen LC, Chen YH, Bai YM, Chen TJ, Chen MH, Su TP (2020) Antidepressant resistance in adolescents with major depressive disorder: A nationwide longitudinal study. J Affect Disord 262:293\u0026ndash;297\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFava M (2003) Diagnosis and definition of treatment-resistant depression. Biol Psychiatry 53(8):649\u0026ndash;659\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRush AJ, Trivedi MH, Wisniewski SR, Nierenberg AA, Stewart JW, Warden D, Niederehe G, Thase ME, Lavori PW, Lebowitz BD et al (2006) Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. Am J Psychiatry 163(11):1905\u0026ndash;1917\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng CM, Chen MH, Tsai SJ, Chang WH, Tsai CF, Lin WC, Bai YM, Su TP, Chen TJ, Li CT (2024) Susceptibility to Treatment-Resistant Depression Within Families. JAMA Psychiatry\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmos TB, Tandon N, Lefebvre P, Pilon D, Kamstra RL, Pivneva I, Greenberg PE (2018) Direct and Indirect Cost Burden and Change of Employment Status in Treatment-Resistant Depression: A Matched-Cohort Study Using a US Commercial Claims Database. J Clin Psychiatry 79(2)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCai Q, Sheehan JJ, Wu B, Alphs L, Connolly N, Benson C (2020) Descriptive analysis of the economic burden of treatment resistance in a major depressive episode. Curr Med Res Opin 36(2):329\u0026ndash;335\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamirez JM (2003) Hormones and aggression in childhood and adolescence. Aggress Violent Beh 8(6):621\u0026ndash;644\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilloughby T, Good M, Adachi PJ, Hamza C, Tavernier R (2013) Examining the link between adolescent brain development and risk taking from a social-developmental perspective. Brain Cogn 83(3):315\u0026ndash;323\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBorensztajn D, Hagedoorn NN, Carrol E, von Both U, Dewez JE, Emonts M, van der Flier M, de Groot R, Herberg J, Kohlmaier B et al (2022) Characteristics and management of adolescents attending the ED with fever: a prospective multicentre study. BMJ Open 12(1):e053451\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAngus DC, Linde-Zwirble WT, Lidicker J, Clermont G, Carcillo J, Pinsky MR (2001) Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs of care. Crit Care Med 29(7):1303\u0026ndash;1310\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShime N, Kawasaki T, Saito O, Akamine Y, Toda Y, Takeuchi M, Sugimura H, Sakurai Y, Iijima M, Ueta I et al (2012) Incidence and risk factors for mortality in paediatric severe sepsis: results from the national paediatric intensive care registry in Japan. Intensive Care Med 38(7):1191\u0026ndash;1197\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudd KE, Johnson SC, Agesa KM, Shackelford KA, Tsoi D, Kievlan DR, Colombara DV, Ikuta KS, Kissoon N, Finfer S (2020) Global, regional, and national sepsis incidence and mortality, 1990\u0026ndash;2017: analysis for the Global Burden of Disease Study. Lancet 395(10219):200\u0026ndash;211\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeminog OO, Goldacre MJ (2013) Risk of pneumonia and pneumococcal disease in people with severe mental illness: English record linkage studies. Thorax 68(2):171\u0026ndash;176\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersson NW, Goodwin RD, Okkels N, Gustafsson LN, Taha F, Cole SW, Munk-J\u0026oslash;rgensen P (2016) Depression and the risk of severe infections: prospective analyses on a nationwide representative sample. Int J Epidemiol 45(1):131\u0026ndash;139\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIrwin MR, Levin MJ, Carrillo C, Olmstead R, Lucko A, Lang N, Caulfield MJ, Weinberg A, Chan IS, Clair J et al (2011) Major depressive disorder and immunity to varicella-zoster virus in the elderly. Brain Behav Immun 25(4):759\u0026ndash;766\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulugeta A, Zhou A, King C, Hypp\u0026ouml;nen E (2020) Association between major depressive disorder and multiple disease outcomes: a phenome-wide Mendelian randomisation study in the UK Biobank. Mol Psychiatry 25(7):1469\u0026ndash;1476\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHamer M, Kivimaki M, Stamatakis E, Batty GD (2019) Psychological distress and infectious disease mortality in the general population. Brain Behav Immun 76:280\u0026ndash;283\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen MH, Pan TL, Li CT, Lin WC, Chen YS, Lee YC, Tsai SJ, Hsu JW, Huang KL, Tsai CF et al (2015) Risk of stroke among patients with post-traumatic stress disorder: nationwide longitudinal study. Br J psychiatry: J mental Sci 206(4):302\u0026ndash;307\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen MH, Su TP, Chen YS, Hsu JW, Huang KL, Chang WH, Bai YM (2013) Attention deficit hyperactivity disorder, tic disorder, and allergy: is there a link? A nationwide population-based study. J Child Psychol Psychiatry Allied Discip 54(5):545\u0026ndash;551\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCheng CM, Chang WH, Chen MH, Tsai CF, Su TP, Li CT, Tsai SJ, Hsu JW, Huang KL, Lin WC et al (2018) Co-aggregation of major psychiatric disorders in individuals with first-degree relatives with schizophrenia: a nationwide population-based study. Mol Psychiatry 23(8):1756\u0026ndash;1763\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiang CS, Bai YM, Hsu JW, Huang KL, Ko NY, Chu HT, Yeh TC, Tsai SJ, Chen TJ, Chen MH (2020) The Risk of Sexually Transmitted Infections Following First-Episode Schizophrenia Among Adolescents and Young Adults: A Cohort Study of 220 545 Subjects. \u003cem\u003eSchizophrenia bulletin\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi CT, Bai YM, Huang YL, Chen YS, Chen TJ, Cheng JY, Su TP (2012) Association between antidepressant resistance in unipolar depression and subsequent bipolar disorder: cohort study. Br J psychiatry: J mental Sci 200(1):45\u0026ndash;51\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 40(5):373\u0026ndash;383\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu CY, Hung YT, Chuang YL, Chen YJ, Weng WS, Liu JS (2006) Incorporating development stratification of Taiwan townships into sampling design of large scale health interview survey. J Health Manage (Chin) 4:1\u0026ndash;22\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller AH, Maletic V, Raison CL (2009) Inflammation and Its Discontents: The Role of Cytokines in the Pathophysiology of Major Depression. Biol Psychiatry 65(9):732\u0026ndash;741\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuiz NAL, Del \u0026Aacute;ngel DS, Brizuela NO, Peraza AV, Olgu\u0026iacute;n HJ, Soto MP, Guzm\u0026aacute;n DC (2022) Inflammatory Process and Immune System in Major Depressive Disorder. Int J Neuropsychopharmacol 25(1):46\u0026ndash;53\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrank P, Batty GD, Pentti J, Jokela M, Poole L, Ervasti J, Vahtera J, Lewis G, Steptoe A, Kivim\u0026auml;ki M (2023) Association Between Depression and Physical Conditions Requiring Hospitalization. JAMA Psychiatry 80(7):690\u0026ndash;699\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdams TB, Wharton CM, Quilter L, Hirsch T (2008) The association between mental health and acute infectious illness among a national sample of 18- to 24-year-old college students. J Am Coll Health 56(6):657\u0026ndash;663\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavydow DS, Ribe AR, Pedersen HS, Vestergaard M, Fenger-Gr\u0026oslash;n M (2016) The association of unipolar depression with thirty-day mortality after hospitalization for infection: A population-based cohort study in Denmark. J Psychosom Res 89:32\u0026ndash;38\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRonaldson A, Arias de la Torre J, Sima R, Ashworth M, Armstrong D, Bakolis I, Hotopf M, Dregan A (2022) Prospective associations between depression and risk of hospitalisation for infection: Findings from the UK Biobank. Brain Behav Immun 102:292\u0026ndash;298\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaalouf FT, Atwi M, Brent DA (2011) Treatment-resistant depression in adolescents: review and updates on clinical management. Depress Anxiety 28(11):946\u0026ndash;954\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForrester JD, Cao S, Schaps D, Liou R, Patil A, Stave C, Sokolow SH, Leo G (2022) Influence of Socioeconomic and Environmental Determinants of Health on Human Infection and Colonization with Antibiotic-Resistant and Antibiotic-Associated Pathogens: A Scoping Review. Surg Infect (Larchmt) 23(3):209\u0026ndash;225\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Murray GK, Byrne EM, Sidorenko J, Visscher PM, Wray NR (2021) GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression. Nat Commun 12(1):1146\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLorant V, Deli\u0026egrave;ge D, Eaton W, Robert A, Philippot P, Ansseau M (2003) Socioeconomic inequalities in depression: a meta-analysis. Am J Epidemiol 157(2):98\u0026ndash;112\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller G, Chen E, Cole SW (2009) Health psychology: developing biologically plausible models linking the social world and physical health. Annu Rev Psychol 60:501\u0026ndash;524\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGronemann FH, J\u0026oslash;rgensen MB, Nordentoft M, Andersen PK, Osler M (2021) Treatment-resistant depression and risk of all-cause mortality and suicidality in Danish patients with major depression. J Psychiatr Res 135:197\u0026ndash;202\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eT\u0026oslash;rmoen AJ, Myhre M, Walby FA, Gr\u0026oslash;holt B, Rossow I (2020) Change in prevalence of self-harm from 2002 to 2018 among Norwegian adolescents. Eur J Public Health 30(4):688\u0026ndash;692\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNetea MG, van der Meer JWM, van Deuren M, Jan Kullberg B (2003) Proinflammatory cytokines and sepsis syndrome: not enough, or too much of a good thing? Trends Immunol 24(5):254\u0026ndash;258\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eColasanto M, Madigan S, Korczak DJ (2020) Depression and inflammation among children and adolescents: A meta-analysis. J Affect Disord 277:940\u0026ndash;948\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRengasamy M, Marsland A, McClain L, Kovats T, Walko T, Pan L, Price RB (2021) Longitudinal relationships of cytokines, depression and anhedonia in depressed adolescents. Brain Behav Immun 91:74\u0026ndash;80\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLopez-Duran NL, Kovacs M, George CJ (2009) Hypothalamic-pituitary-adrenal axis dysregulation in depressed children and adolescents: a meta-analysis. Psychoneuroendocrinology 34(9):1272\u0026ndash;1283\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSigalas PD, Garg H, Watson S, McAllister-Williams RH, Ferrier IN (2012) Metyrapone in treatment-resistant depression. Ther Adv Psychopharmacol 2(4):139\u0026ndash;149\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWebster JI, Sternberg EM (2004) Role of the hypothalamic-pituitary-adrenal axis, glucocorticoids and glucocorticoid receptors in toxic sequelae of exposure to bacterial and viral products. J Endocrinol 181(2):207\u0026ndash;221\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVandewalle J, Libert C (2020) Glucocorticoids in Sepsis: To Be or Not to Be. Front Immunol 11:1318\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaciel-Fiuza MF, Muller GC, Campos DMS, do, Socorro Silva Costa P, Peruzzo J, Bonamigo RR, Veit T, Vianna FSL (2023) Role of gut microbiota in infectious and inflammatory diseases. \u003cem\u003eFront Microbiol\u003c/em\u003e 14:1098386\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDong Z, Shen X, Hao Y, Li J, Xu H, Yin L, Kuang W (2022) Gut microbiome: A potential indicator for predicting treatment outcomes in major depressive disorder. Front Neurosci 16:813075\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFontana A, Manchia M, Panebianco C, Paribello P, Arzedi C, Cossu E, Garzilli M, Montis MA, Mura A, Pisanu C et al (2020) Exploring the Role of Gut Microbiota in Major Depressive Disorder and in Treatment Resistance to Antidepressants. Biomedicines 8(9)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilkowska A, Szałach ŁP, Cubała WJ (2021) Gut Microbiota in Depression: A Focus on Ketamine. Front Behav Neurosci 15:693362\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang R, Xiang H, Zheng T (2024) Causal associations between severe mental illness and sepsis: a Mendelian randomization study. Front Psychiatry 15:1341559\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":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4614090/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4614090/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePrevious studies have shown an association between depression and susceptibility to infection in adults. However, few studies have investigated the association between treatment-resistant depression (TRD) and severe infections in adolescents and young adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study included adolescents (12\u0026ndash;19 years of age) and young adults (20\u0026ndash;29 years of age) who were diagnosed with major depressive disorder (MDD, including 6958 cases of TRD and 27832 cases of antidepressant-responsive depression [ARPD]), from the Taiwan National Health Insurance Research Database (NHIRD), from 2001 to 2010. The TRD and ARPD groups were further matched (4:1) by chronological age, age at diagnosis of depression, sex, residence, and family income. The primary outcomes were severe bacterial infections (SBI) and septicemia. Cox regression analysis was conducted to identify the risk of hospitalization due to SBI or septicemia during the follow-up period.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared with controls, the ARPD group had increased risks of SBI (hazard ratio [HR] with 95% confidence interval [CI]: 3.90, 2.73\u0026ndash;5.57) and septicemia (HR, 95% CI: 2.56, 1.34\u0026ndash;4.91). Notably, the risks of SBI and septicemia appeared to be further elevated in the TRD group. The TRD group exhibited higher incidences of SBI (HR, 95% CI: 6.99, 4.73\u0026ndash;10.34) and septicemia (HR, 95% CI: 2.85, 1.28\u0026ndash;6.36) than the control group.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAdolescents and young adults with TRD had 6.99-fold and 3.90-fold increased risks of SBI and septicemia compared to individuals without MDD, respectively. Therefore, healthcare providers need to be vigilant when monitoring and implementing preventive measures in this population.\u003c/p\u003e","manuscriptTitle":"Comparative Analysis of the Risk of Severe Bacterial Infection and Septicemia in Adolescents and Young Adults with Treatment-Resistant Depression and Treatment- Responsive Depression - A Nationwide Cohort Study in Taiwan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 16:01:30","doi":"10.21203/rs.3.rs-4614090/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-21T10:23:42+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-20T23:01:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"250588134659448363711388250744473777796","date":"2024-11-10T13:10:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"72197240351943841035999249710231540699","date":"2024-11-05T13:41:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"285449235326236010838004627434883055918","date":"2024-11-05T09:44:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233278224436789963005623999571389639615","date":"2024-07-13T16:48:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-12T00:32:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196913725779225604857393572778078650485","date":"2024-07-12T00:10:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-11T15:28:25+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-21T03:45:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-21T03:45:08+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Child \u0026 Adolescent Psychiatry","date":"2024-06-21T00:11:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-child-and-adolescent-psychiatry","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ecap","sideBox":"Learn more about [European Child \u0026 Adolescent Psychiatry](http://link.springer.com/journal/787)","snPcode":"787","submissionUrl":"https://submission.nature.com/new-submission/787/3","title":"European Child \u0026 Adolescent Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"c9ee32b5-1791-43bb-b7f4-d07f39c99055","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-10T19:50:46+00:00","versionOfRecord":{"articleIdentity":"rs-4614090","link":"https://doi.org/10.1007/s00787-025-02684-y","journal":{"identity":"european-child-and-adolescent-psychiatry","isVorOnly":false,"title":"European Child \u0026 Adolescent Psychiatry"},"publishedOn":"2025-03-08 15:58:42","publishedOnDateReadable":"March 8th, 2025"},"versionCreatedAt":"2024-07-18 16:01:30","video":"","vorDoi":"10.1007/s00787-025-02684-y","vorDoiUrl":"https://doi.org/10.1007/s00787-025-02684-y","workflowStages":[]},"version":"v1","identity":"rs-4614090","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4614090","identity":"rs-4614090","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}