To analyze the developmental trajectory and influencing factors of PTSD symptoms in ICU patients with mechanical ventilation based on latent category growth: A longitudinal examination

To analyze the developmental trajectory and influencing factors of PTSD symptoms in ICU patients with mechanical ventilation based on latent category growth: A longitudinal examination | 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 Article To analyze the developmental trajectory and influencing factors of PTSD symptoms in ICU patients with mechanical ventilation based on latent category growth: A longitudinal examination Yunting Li, Jiabi Zhang, Chen Wei, Mi Liu, Yang Xiong, Xiaoli Yuan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7220761/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Background： ICU patients exhibit a high incidence of post-traumatic stress disorder (PTSD). During treatment, procedural pain (e.g., suctioning, ventilator asynchrony) and communication barriers can trigger significant stress responses, exacerbating feelings of fear and helplessness, ultimately contributing to PTSD post-extubation. Current research predominantly relies on cross-sectional studies, failing to capture the dynamic progression of PTSD. As recovery evolves, patients' psychological and physical states continuously change, necessitating adaptive intervention strategies. There is an urgent need for longitudinal studies to elucidate PTSD development trajectories, clinical characteristics, and risk factors. However, research on the psychological recovery pathways of post-ICU patients remains scarce. Objective: This study aimed to identify the heterogeneous developmental trajectories of PTSD in ICU patients receiving mechanical ventilation within 6 months post-extubation and to analyze influencing factors across trajectory subgroups. Methods: From July 2023 to June 2024, a purposive sampling method was employed to select mechanically ventilated patients admitted to the ICU of a tertiary hospital in Zunyi, China. At 7 days post-extubation (T0), baseline assessments were conducted using the following instruments: a general information questionnaire, the Impact of Event Scale-Revised (IES-R), the Hospital Anxiety and Depression Scale (HADS), the Simplified Coping Style Questionnaire (SCSQ), the short-form Chinese version of the Eysenck Personality Questionnaire-Revised (EPQ-RSC), and the Perceived Social Support Scale (PSSS). Follow-up assessments were performed at 1 month (T1), 3 months (T2), and 6 months (T3) post-extubation using the IES-R. Data were analyzed using Mplus 8.3 and SPSS 29.0. Design: Prospective longitudinal study. Results: Among 204 completed cases (89.1% retention), four trajectories emerged: high-risk deterioration (6.9%), high-risk improvement (27.2%), medium-risk maintenance (14.3%), and low-risk improvement (51.6%). Lower education, prolonged hospitalization, delayed ICU discharge post-extubation, and baseline anxiety independently predicted adverse trajectories ( P <0.05). Conclusion: PTSD trajectories in mechanically ventilated ICU patients exhibit significant heterogeneity. Clinicians should prioritize screening high-risk subgroups (e.g., less-educated patients, extended hospitalization) for early PTSD intervention to enhance recovery outcomes. Clinical Implications: Targeted PTSD monitoring and psychological support are recommended for at-risk populations to mitigate long-term mental health burdens. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Risk factors Respiration Artificial PTSD Trajectory Latent class growth model Influencing factors Nursing Figures Figure 1 Introduction Thanks to the development of critical care medicine, the success rate and transfer rate of patients in Intensive Care Units (ICUs) have significantly improved(Mikkelsen et al., 2020 ). With the increase in patient survival rates, their physical and mental health and quality of life have received more and more attention(Griffith et al., 2018 ). Post-traumatic stress disorder (PTSD) is a common mental and psychological disorder among ICU patients, with an incidence rate of 19.83%(Righy et al., 2019 ). It refers to a delayed or persistent mental disorder that occurs in individuals after experiencing or witnessing a major traumatic event(N., Tobias, Ilan, H., & H., 2023). Mechanical ventilation, a common life support method in ICUs, has saved countless lives. According to statistics, approximately 310 of every 100,000 adults receive invasive ventilation treatment for non-surgical reasons(Mehta, Syeda, Wiener, & Walkey, 2015 ). ICU patients on mechanical ventilation experience a lot of hidden pain during treatment, such as tracheal intubation, suctioning, and human-machine conflict, all of which can cause stress in the body. These factors increase patients' feelings of helplessness and fear, leading to PTSD after extubation and weaning(Yan, 2022 ; Yanjie, Qiongqiong, & Yanhui, 2019 ). The core manifestations of PTSD include intrusive memories, avoidance reactions, and arousal reactions(Bisson & Olff, 2021 ). Its impact on patients can last several years or even longer, reducing their social adaptability and increasing medical and nursing costs(Lane-Fall, Kuza, Fakhry, & Kaplan, 2019 ). At present, most of the studies on PTSD in ICU mechanically ventilated patients are cross-sectional surveys, with few longitudinal studies reported, neglecting that PTSD is a complex and dynamic process. However, assisting patients in adjusting their mindset and integrating into the changes in social functions is often challenging. As the rehabilitation process progresses, the physical and mental states of patients constantly change, and their intervention measures need to be adapted to the situation and individualized. In addition, the chronic disease trajectory theory model indicates that the disease development trajectory not only varies among individuals but may also differ at the group level, that is, the disease development trajectory of patients has group heterogeneity(Jian, Linglong, & Ya, 2020 ). Given this, this study tracked the PTSD symptom levels of ICU mechanically ventilated patients, identified their potential subgroups based on the latent class growth model (LCGM), and analyzed the influencing factors of each subgroup, to provide a basis for the clinical formulation of precise psychological intervention measures. Methods Respondents This investigation recruited mechanically ventilated ICU patients at a Grade III Level A hospital in Zunyi, China during the period from August 2023 to July 2024. Inclusion criteria: ① Invasive mechanical ventilation time ≥ 48 hours; ② Age ≥ 18 years old; ③ No other major stress events within one year before admission; ④ Conscious and with normal communication ability; ⑤ Patients and their families gave informed consent and voluntarily participated. Exclusion criteria: ① Those with a history of mental illness or currently taking psychotropic drugs; ② Those who were re-admitted to the ICU and intubated during the investigation period. Dropout criteria: ① Patients who died or had their condition worsen during the investigation period; ② Patients who voluntarily withdrew or did not cooperate; ③ Failure to contact the patient for three consecutive days. The sample size was calculated based on the sample size requirements of the latent class growth model. A total of 23 variables were included in this study, and the sample size was taken as 5 to 10 times the number of variables(Ping, Jingli, & Na, 2010 ). Considering a 20% loss to follow-up rate, the required sample size was 138 to 276 cases. According to research, when the Bayesian information criterion (BIC) is used as the primary indicator for model selection, the sample size should be ≥ 200(Mengcheng, Qiaowen, & Xiangyang, 2017 ). Ultimately, 229 questionnaires were distributed. This study has been approved by the hospital's ethics committee (KLLY-2023-055), and all subjects gave informed consent and voluntarily participated. Survey tools General Information Questionnaire Designed by the researchers themselves, The data included gender, age, marital status, education level, residence, occupational status, swallowing, drinking, hospitalization expenses, payment method of medical expenses, APACHE Ⅱ score, duration of mechanical ventilation, the total length of hospital stay, length of ICU stay, length of extubation to ICU discharge, whether complicated with hypertension, whether complicated with diabetes, whether complicated with coronary heart disease and the number of chronic diseases, a total of 19 items. Demographic data were filled in by patients or their family members, and disease data were derived from the hospital’s electronic medical record system or obtained by consulting doctors. Impact of Event Scale-Revised (IES-R) Compiled by Weiss et al in 1997, and sinicized by Huang Guoping et al.(Guoping, Yalin, Hui, & Yunfei, 2006 ) in 2006, it included 3 dimensions and 22 items, which are intrusive thinking symptoms (8 items), avoidance symptoms (8 items), and high arousal symptoms (6 items). Likert 5 scale is used to count 0–4 points from "never" to "always". The total score ranges from 0 to 88. The subject scored each item according to the impact of a traumatic event in the past 7 days. The cut-off value was 22 points, and the total score >22 points was positive PTSD symptoms, while scores ≤ 22 indicated negative PTSD symptoms. The total Cronbach's α of the scale was 0.89, and the Cronbach's α coefficients of the three dimensions were 0.77, 0.83, and 0.76, respectively. Eysenck Personality Questionnaire-Revised, Short Scale for Chinese (ERQ-RSC) Developed by British psychologist Eysenck et al.(Mingyi, City, Rongchun, & Xin, 2000 ), The Chinese version was revised and introduced by Qianming-yi et al. It includes four subscales, P (psychoticism scale), E (extraversion scale), N (neuroticism scale), and L (Lie scale). Each subscale contains 12 items, and the score is 0–12, the higher the score, the stronger the personality trait. The Cronbach's α coefficients of the E, N, and L subscales of the EPQ-RSC ranged from 0.74 to 0.78, and the Cronbach's α coefficients of the P scale ranged from 0.54 to 0.60. Two personality traits, E and N, were analyzed in this study. Simplified Coping Style Questionnaire (SCSQ) Xie Yaning(Yanin, 1998 ) compiled the Coping style Scale on the basis of the foreign coping style scale and combined it with the characteristics of the Chinese population, and it is widely used in the field of psychology in China. A total of 20 items were included, including positive coping style (items 1–12) and negative coping style (items 13–20). The Likert T4 scale was used to calculate 0–3 points from "don't take" to "often take". The results were positive coping style scores and negative coping style scores. The Cronbach's α coefficient of the whole scale was 0.9, the Cronbach's α coefficient of the positive coping scale was 0.89, and the Cronbach's α coefficient of the negative coping scale was 0.78. Perceived Social Support Scale (PSSS) It was compiled by Zimet(Zimet, Dahlem, Zimet, & Farley, 1988 ) in 1988 and translated into Chinese by Jiang Qianjin et al. in 2001. It included 3 dimensions of family support, other support (leaders, relatives, colleagues), and friend support, and 12 items. Likert7 scale was used to calculate 1–7 points from "strongly agree" to "strongly agree". The total score reflects the degree of social support, which can be divided into low, medium, and high support levels. They were 12–36 points, 37–60 points, and 61–84 points, respectively. The total score was positively proportional to the degree of social support. The total Cronbach's α of the scale was 0.92, and the Cronbach's α coefficients of the three subscales were 0.91, 0.89, and 0.81, respectively. Hospital Anxiety and Depression Scale (HADS) Developed by Zigmond and Snaith(Zigmond & Snaith, 1983 ) in 1983, it is composed of two subscales: Anxiety (A) and Depression (D), each with 7 items. The Likert T4 scale is used (0–3 points), and the total score of each dimension is 0–21 points, which is divided into 8 points. They were positive for anxiety or depression. Zheng Leilei et al.(Leilei, Yeling, & Huichun, 2003 ) showed that Cronbach's α coefficients of anxiety subscale and depression subscale were 0.806 and 0.791, respectively, indicating that the scale had good reliability and validity. Methods of data collection and quality control The researchers screened the subjects strictly according to the inclusion and exclusion criteria, fully explained the purpose, significance, and questionnaire-filling requirements of the study, and obtained their informed consent to collect their basic information within 7 days after being transferred from the ICU. At the same time, the researchers made an appointment with the subjects for the next follow-up, and data were collected through face-to-face follow-up, telephone interviews, and WeChat. The PTSD symptom levels of the patients were assessed using the IES-R at 7 days (T 0 ), 1 month (T 1 ), 3 months (T 2 ), and 6 months (T 3 ) after extubation. If patients had any questions during the filling process, a unified statement was used to answer them. If the patient had difficulty reading and writing, the questions were retold in a neutral tone and checked with the investigator after obtaining the patient's consent. All the questionnaires were collected on the spot and entered and checked by two members of the research team to check for missing items and eliminate the regularly answered questionnaires. Statistical methods Mplus8.3 was used to build the latent category growth model. Starting from a single-category model, the number of categories was gradually increased, and the best-fitting model was selected according to the model fit index and clinical significance. The model adaptation indicators mainly include the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted BIC (aBIC), the smaller the statistical value, the better the model fitting effect. Lo-Mendell-Rubin likelihood ratio test (LMR), and Bootstrap likelihood ratio text test (BLRT), when the test statistic value was P < 0.05, The results showed that the k classification model had a better fitting degree than the K-1 classification model. The entropy index is used to evaluate the accuracy of classification. The value ranges from 0 to 1, and the closer the value is to 1, the more accurate the classification is. When Entropy is ≥ 0.8, the accuracy of classification is ≥ 90%(Mengcheng et al., 2017 ). SPSS29.0 was used for data analysis. The count data were described by frequency and percentage, and the χ2 test was used for comparison between groups. Measurement data following normal distribution were described by \(\:\stackrel{-}{x}\) ±s . One-way analysis of variance was used for comparison between groups. Multiple groups of influencing factors were analyzed by unordered multinomial Logistic regression analysis. P < 0.05 was considered statistically significant. Ethical Approval and Consent to Participate This study protocol was reviewed and approved by the Ethics Committee of the Affiliated Hospital of Zunyi Medical University (Ethical Approval No.: KLLY-2023-055). Written informed consent was obtained from all participants. All study procedures were conducted in accordance with the principles of the Declaration of Helsinki and the relevant guidelines and regulations of the Ethics Committee of the Affiliated Hospital of Zunyi Medical University. Results General Information A total of 229 questionnaires were distributed in this study, and 25 patients were excluded for loss of follow-up. A total of 204 valid questionnaires were obtained, with an effective recovery rate of 89.1%. The average age of mechanical ventilation patients in ICU was (56.23±1.02) years old. There were 125 males (61.30%) and 79 females (38.7%). Most of them (140, 68.6%) lived in rural areas. The most common marital status was married (178, 87.3%). The education level was low, 93 (45.6%) were in primary school or below. Most of the occupational statuses were freelance and unemployed, accounting for 30.9% and 30.4% respectively. Most of the medical payment methods were medical insurance for urban residents, accounting for 72.5%. Not drinking is more than drinking; There were more non-smokers than smokers. Most of the patients had one or less chronic diseases. The duration of mechanical ventilation was (150.76±7.52) hours; The total length of hospital stay was (24.59±0.89) days. The length of ICU stay was (220.74±8.85) hours; The duration from extubation to ICU discharge was (95.62±5.79) hours. APACHE Ⅱ score was (21.59±0.34) points; The hospitalization cost was (88257.68±4157.62) yuan. Descriptive analysis of social psychology scale scores of patients with tracheal intubation in ICU at T 0 The score of positive coping dimension of SCSQ in ICU patients with tracheal intubation at T 0 was (21.01±5.02), and the score of negative coping dimension was (10.89±3.55). The score of the extraversion dimension of ERQ-RSC was (8.87±3.10). The score of neuroticism was (4.34±2.95); The total score of PSSS was (60.39±10.35), the score of family support dimension was (24.01±3.15), the score of friend support dimension was (14.48±6.44) and the score of other support dimension was (21.90±3.54). The anxiety dimension score of HADS was (9.06±4.06), and the depression dimension score was (7.77±4.14). Latent class growth model analysis of the change trajectory of PTSD in ICU patients with tracheal intubation Potential category models were fitted based on IES-R scale scores of ICU mechanical ventilation patients, and a total of 5 potential profile models were fitted starting from the initial model, as shown in Table 1. With the increase in the number of categories, AIC, BIC and aBIC gradually decreased, and the information entropy was all greater than 0.85. When the number of model categories was 4, the decreasing trend of AIC, BIC, and aBIC tended to be stable, and the LMRT and BLRT tests all reached significant levels ( P <0.05). Considering the fitting indexes and practical significance of the model, model 4 was selected as the optimal fitting model for patients with mechanical ventilation in the ICU in this study, and discriminant analysis was used to verify the accuracy of the optimal model, with a posterior probability of 98 and high discriminating power. Based on model 4, the mean scores of each category on the IES-R scale are shown in Figure 1. According to the fluctuation of the mean line chart of each item in the potential profile, the characteristic attributes of four potential PTSD subtypes are analyzed and named as follows. The trajectory of the C1 group had the highest IES-R score at the T 0 stage. Combined with the mean intercept and slope of the curve, they were 39.40 ( P <0.001) and 9.99 ( P <0.05), respectively, and the slope was positive, indicating that the IES-R score of patients showed an increasing trend during the follow-up period, so they were named as the "high-risk worsening group". There were 14 in this category, accounting for 6.9%. In the T 0 phase, the IES-R score level of the C2 locus was second only to the C1 locus, but this locus showed a significant downward trend, and its mean curve intercept and slope were 37.73 ( P <0.001) and -43.90 ( P <0.05), respectively. During the T 1 -T 3 follow-up period, the mean IES-R score was ≤22, showing a large improvement, so the C2 category was named the "high-risk improvement group". There were 57 students in this category, accounting for 27.2%. In the T 0 period, the IES-R score level of the C3 category was in the middle of the four tracks, the mean intercept rate was 35.99 ( P <0.001) and the mean slope was -13.10 ( P 22 points. Therefore, this category is named the "Medium-Risk Retention Group". There were 27 students in this category, accounting for 14.3%. In the four follow-up periods, the level of IES-R score of the C4 category was low, and the overall trend was downward and tended to be flat. Combined with the mean intercept and slope of the curve, which were 17.66 ( P <0.001) and -18.34 ( P <0.05), the C4 category was named "low-risk improvement group". There were 106 students in this category, accounting for 51.6%. Single-factor analysis of social psychology of various groups of patients The results of the univariate analysis showed that the scores of SCSQ positive coping dimension, ERQ-RSC neurotic dimension, anxiety dimension, and depression dimension were statistically significant in the 4 groups of patients ( P <0.05), as shown in Table 2. Single-factor analysis of social psychology of various groups of patients The scores of ERQ-RSC, SCSQ, PSSS, and HADS scales at T 0 were used to conduct a univariate analysis of personality characteristics, coping styles, social support, anxiety, and depression. The results showed that the scores of SCSQ positive coping dimension, ERQ-RSC neurotic dimension, anxiety dimension, and depression dimension were statistically significant in the 4 groups of patients ( P <0.05), as shown in Table 3. Multiple Logistics Regression Analysis In the construction of the regression model, the trajectory category was used as the dependent variable, and the significant indicators in the univariate analysis were used as the independent variables. The continuous numerical variables were directly included in the regression equation with their original values for calculation, and the assignment of categorical variables was shown in Table 4. Taking the "low-risk improvement group", "medium-risk maintenance group" and "high-risk improvement group" as the reference group, multivariate Logistic regression analysis showed that education level, the total length of hospital stay, duration from extubation to transfer from ICU, and anxiety were independent predictors of PTSD development trajectory in ICU patients with tracheal intubation. Education level and anxiety were the most influential factors for the high-risk deterioration group compared with the low-risk improvement group. The influencing factors of the "high-risk improvement group" were the total length of hospital stay and anxiety; The influencing factor of the "medium-risk maintenance group" was anxiety. Compared with the "medium-risk maintenance group", the influencing factor of the "high-risk deterioration group" was the duration from extubation to ICU discharge. See Table 5 for details. The Omnibus test （ =130.759, df =45, P <0.001) showed that the model fitted well and could truly and reliably reflect the relationship between the original variables. Discussion There is heterogeneity in the development trajectory of PTSD in patients with tracheal intubation in ICU The population of patients with endotracheal intubation in ICU is heterogeneous. In this study, we fitted the potential categories of PTSD change trajectory of patients with endotracheal intubation in ICU based on LCGM, and finally determined four potential categories of PTSD (high risk of deterioration, high risk of improvement, medium risk of maintaining, and low risk of improvement). Galatzer et al.(Galatzer-Levy, Huang, & Bonanno, 2018 ) reviewed related articles on PTSD trajectory and found that the most consistent trajectory change categories observed by patients after traumatic experience were four trajectory categories: maintenance group, recovery group, chronic group, and delayed onset group, which were similar to the results of this study. Among the four trajectories, the low-risk improvement group accounted for the highest proportion (51.6%), indicating that most ICU mechanical ventilation patients could better adjust their mentality and adapt to changes in social function after extubation and weaning. The initial IES-R scores were higher (> 22) in the intermediate-risk maintenance group, high-risk improvement group, and high-risk deterioration group, but the slope changes were different. Patients in the moderate-risk maintenance group maintained moderately severe PTSD symptoms at all time points, and although the developmental trajectory showed a downward trend over time, their nadir IES-R scores were higher than 22. Without intervention, PTSD symptoms in such groups may persist longer. Therefore, the focus of intervention in such patients should be on the full cycle. For the patients in the high-risk improvement group, although the PTSD symptoms were at a high level in the initial stage, the severity of PTSD showed a significant downward trend with time. At T2-T3, the mean IES-R score was ≤ 22, and the PTSD symptoms were greatly improved. An in-depth exploration of the factors affecting the psychological status of such patients may provide a valuable reference for the formulation of future intervention strategies. Patients in the high-risk deterioration group had the highest initial IES-R scores and their IES-R scores gradually increased over time. It is suggested that the PTSD symptoms of these patients gradually worsen over time, which poses a serious threat to their mental health and delays the recovery process of patients. We should pay more attention to the high-risk group. Patients in the high-risk deterioration group have higher symptom scores and lower identification difficulty in the early stage of extubation and weaning. Medical staff should provide full-cycle psychological counseling for such patients, establish follow-up files, and pay close attention to changes in mental health status. Influencing factors of PTSD development trajectory in ICU patients with tracheal intubation Univariate and multivariate analysis showed that education level, total length of hospital stay, duration from extubation to ICU discharge, and anxiety were independent influencing factors of PTSD development trajectory in ICU patients with tracheal extubation. Previous studies have pointed out that gender(Girard et al., 2007 ; Shuo, Wanling, Rongfang, & Li, 2016 ), age(Meihong, 2019 ; Rattray, Johnston, & Wildsmith, 2005 ), mechanical ventilation(Wade et al., 2012 ; Yan, 2022 ), APACHE Ⅱ score(Meihong, 2019 ; Yan, 2022 ), and so on are the influencing factors of PTSD in ICU patients. The heterogeneity of study results may result from differences in sample characteristics. Although the subjects were all mechanically ventilated patients in the ICU, the conclusions of different studies are different due to the diversity of clinical characteristics such as disease types and severity. In addition, the number of PTSD-positive samples in this study was small, and multi-center studies with large samples can be carried out in the future to analyze its influencing factors in depth. The mental health problems of ICU patients have been widely discussed by scholars at home and abroad, and it is urgent to formulate precise intervention measures in clinical practice. The results of this study showed that compared with the low-risk improvement group, the high-risk deterioration group had lower education levels and higher anxiety dimension scores. Compared with the intermediate-risk maintenance group, the high-risk deterioration group had a longer time from extubation to ICU discharge. These patients are more likely to develop PTSD, and their PTSD symptoms are more likely to aggravate over time. Therefore, we should pay more attention to preventing and treating these patients. Studies have found that psychological disorders in patients transferred from the ICU are often not isolated, and the comorbidity rate of anxiety, depression, and PTSD is as high as 65%(Bryant, 2019 ; Hatch et al., 2018 ; Navarra-Ventura et al., 2024 ). The present study found that the more severe the anxiety, the more likely it was to induce PTSD, which was the same as the results of previous studies(Ronghua, 2019 ; Xin & Qiang, 2020 ). In the state of anxiety, the neurotransmitter activity of patients is more active, which can acutely capture the discomfort of the body(Carpenter, Bragdon, & Pineles, 2022 ). Such discomfort may lead to the aggravation of the psychological burden of patients and increase the risk of PTSD. In this study, no significant difference in depression was found among different types, and the reason may be that the HADS questionnaire was collected within 7 days after extubation, and patients in this period have a high level of social support, more concern about disease progression, high compliance, and a strong desire to express, so the incidence of depression is low. In the future, it can be further verified by reassessing the anxiety and depression when assessing the PTSD level of patients. In addition, patients with a lower level of education are more likely to be assigned to the high-risk deterioration group, which is similar to the findings of Li Zhuqing et al.(Li et al., 2023 ). Low cognition is a risk factor for PTSD, and education is highly correlated with cognition, thus education is negatively associated with the risk of PTSD(Myhren, Ekeberg, Tøien, Karlsson, & Stokland, 2010 ; Sayed, Iacoviello, & Charney, 2015 ). However, some studies have pointed out that there is no correlation between education level and PTSD(Bienvenu et al., 2013 ), or that patients with higher education levels are more likely to develop PTSD(Ronghua, Jingye, Xiaoqing, Ying, & Yimin, 2020 ). The differences in the results of the studies may be affected by the sample size and the subjects. Whether a low education level is a risk factor for PTSD needs to be further explored. Studies have shown that the delay in discharge will delay the time of patients' discharge, and increase the cost of treatment, mortality, and readmission rate(Diwan, Mentz, Romano, & Engoren, 2023 ; Edenharter et al., 2019 ; Ofoma et al., 2020 ). The study by Bagshaw et al.(Bagshaw et al., 2020 ) showed that 20%-50% of ICU patients have a delay in transfer. ICU delay refers to the phenomenon that the patient's condition has improved and meets the requirements for discharge, but it is not necessary to stay in the ICU for treatment(Chaoping, Junxi, Benjin, Hongyan, & Xiaoli, 2023 ). Chick et al. put forward the transition theory in 1986, which refers to the transformation of people from one life state to another(Chick & Meleis, 1986 ; Meleis, 2010 ). Extubation is a transition for patients with tracheal intubation in ICU. Based on this, this study included "the time from extubation to ICU discharge" for influencing factors analysis. The results of this study show that the time from extubation to transfer is one of the influencing factors of PTSD in ICU patients with tracheal intubation. The longer the time from extubation to transfer, the more likely the patients are to develop PTSD. The reason may be that after extubation, patients have clear consciousness, and the delay in discharge aggravates the patient's illness uncertainty(Everall et al., 2019 ). At the same time, high treatment costs and psychological needs such as family company cause great burden to patients and increase the risk of PTSD. Based on this, medical personnel should pay attention to the mental health status of patients at an early stage, conduct a key assessment of anxiety, and formulate targeted intervention measures based on understanding the psychological status of patients, to reduce the risk of PTSD while reducing anxiety. At the same time, for patients with a low education level and a long time from extubation to ICU transfer, it is suggested that medical staff can help patients establish a positive attitude, increase positive feelings, release psychological pressure, and reduce the incidence of PTSD through psychosocial interventions such as disease knowledge education, positive self-disclosure, and mindfulness-based stress reduction therapy. The shorter the time from extubation to discharge and the severe the anxiety level, the patients with tracheal intubation in ICU are more likely to belong to the medium-risk maintenance group Some patients with PTSD show that one or more symptoms persist for a lifetime, which seriously affects the quality of life of patients(Girgenti et al., 2021 ). In this study, patients in the moderate-risk maintenance group had persistent PTSD symptoms during the investigation period, and the risk of PTSD in this group was only second to the high-risk worsening group. Early intervention for such patients may change the outcome of patients. The results of multivariate analysis showed that compared with the low-risk improvement group, the patients in the medium-risk maintenance group had more severe anxiety; Compared with the high-risk deterioration group, the moderate-risk maintenance group had a shorter time from extubation to ICU discharge, indicating that patients with shorter time from extubation to ICU discharge and more severe anxiety were more likely to be classified into this group. This suggests that it is important for medical staff to assess the anxiety level of patients with tracheal intubation in the ICU. If the patients have severe anxiety symptoms, even those with a short time from extubation to discharge cannot relax their vigilance. The mental health level of such patients should be dynamically evaluated in the whole process, and individualized intervention measures should be carried out according to the assessment results, to improve the level of PTSD symptoms and accelerate the rehabilitation process of patients. Compared with the low-risk improvement group, the longer the total length of hospital stay and the more severe the anxiety level of ICU patients with tracheal intubation are more likely to belong to the high-risk improvement group Although the risk of PTSD in the high-risk improvement group was higher in the early stage, the level of PTSD symptoms decreased significantly over time, and most of the patients had no PTSD symptoms (IES-R score ≤ 22) at the T2 stage. Such patients are characterized by a longer total length of hospital stay and higher levels of anxiety. The reason for this result may be that patients with a longer total length of hospital stay have a stronger readiness for hospital discharge, and they are better able to cope with physical and psychological changes and make timely adjustments after discharge. Readiness for hospital discharge is not only the patient's self-feeling of readiness for discharge but also the prediction and evaluation of rehabilitation ability and discharge adaptability by medical staff after comprehensive consideration of the patient's physical, psychological, and social health status(Galvin, Wills, & Coffey, 2017 ). Discharge readiness is an important link linking in-hospital treatment and self-management of patients after discharge. Good discharge readiness can significantly promote the disease process of patients, reduce the length of hospital stay, and help patients integrate into social life as soon as possible(Kucharczuk et al., 2022 ; Plotnikoff et al., 2021 ; Xiaojing, Yunan, & Yue, 2024 ). It is suggested that medical staff should strengthen the discharge readiness assessment of ICU patients with mechanical ventilation, to accelerate their disease recovery process. The higher severity of early PTSD symptoms in the intermediate-risk maintenance group may be related to the higher level of anxiety symptoms. With the systematic and scientific treatment, the patient's uncertainty in illness was relieved, and the accompanying family members reduced his psychological burden, thus relieving his PTSD symptoms. This suggests that although some patients show higher levels of PTSD symptoms in the early stage, it is still possible for patients to significantly improve their psychological status or even return to normal levels under certain conditions. However, in this study, no significant protective factors were found when analyzing the influencing factors of this type of patient. Future research can deeply analyze the protective factors of PTSD risk in this type of patient, to provide a reference for the construction of feasible intervention strategies. Strengths and Limitations This study delineates the trajectory of PTSD symptom severity among ICU patients during the 6-month period following extubation. A multidimensional analysis incorporating sociodemographic, clinical, and psychosocial factors provides an evidence-based foundation for early identification, prevention, and personalized intervention strategies. However, as a single-center study, the generalizability of findings may be somewhat constrained. Future multicenter studies with larger sample sizes are recommended to enhance the representativeness and external validity of the results. Conclusion In this study, ICU patients with tracheal intubation were followed up for PTSD at 7 days, 1 month, 3 months, and 6 months after extubation and weaning. Heterogeneity analysis was performed by LCGM, and four categories were identified: high-risk deterioration group, high-risk improvement group, medium-risk maintenance group, and low-risk improvement group. Through univariate and multivariate analysis, the study showed that education level, total length of hospital stay, duration from extubation to transfer from ICU, and anxiety were independent risk factors for the development trajectory of PTSD in ICU patients with tracheal intubation. However, since this study was a single-center study, the sample representativeness was limited. It is suggested that the sample size should be further expanded and multi-center surveys with large samples should be carried out in the future to increase the representativeness of the samples. Declarations Author Contributions Statement : Li Yunting Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing – Original Draft, Visualization. Zhang Jiabi Methodology, Validation, Resources, Writing – Review, Supervision. Chen Wei Writing – Review, Methodology, Methodology. Liu Mi Software, Investigation, Data curation, Visualization. Xiong Yan Validation, Data Curation. Yuan Xiaoli (Corresponding Author) Conceptualization, Resources, Writing – Review, Supervision, Project administration, Funding acquisition. Declaration of Interests All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest Funding Acknowledgements: This research was supported by the Zunyi Science and Technology Program Project [Zunyi Science and Technology Cooperation Document No. HZ (2022) 278]. Author Contribution Li Yunting: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing – Original Draft, Visualization.Zhang Jiabi: Methodology, Validation, Resources, Writing – Review, Supervision.Chen Wei: Writing – Review, Methodology, Methodology.Liu Mi: Software, Investigation, Data curation, Visualization.Xiong Yan: Validation, Data Curation.Yuan Xiaoli (Corresponding Author) : Conceptualization, Resources, Writing – Review , Supervision, Project administration, Funding acquisition.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript. Acknowledgments The authors gratefully acknowledge all contributors to this research endeavor. Data Availability The datasets generated or analyzed during the current study are available from the corresponding author on reasonable request. References Bagshaw, S. M. et al. Assessment of costs of avoidable delays in intensive care unit discharge. JAMA Netw. Open. 3 (8), e2013913–e2013913 (2020). Bienvenu, O. J. et al. Post-traumatic stress disorder symptoms after acute lung injury: a 2-year prospective longitudinal study. Psychol. Med. 43 (12), 2657–2671 (2013). Bisson, J. I. & Olff, M. Prevention and treatment of PTSD: the current evidence base. Eur. J. Psychotraumatol . 12 (1), 1824381 (2021). Bryant, R. A. Post-traumatic stress disorder: a state‐of‐the‐art review of evidence and challenges. World psychiatry . 18 (3), 259–269 (2019). Carpenter, J. K., Bragdon, L. & Pineles, S. L. Conditioned physiological reactivity and PTSD symptoms across the menstrual cycle: Anxiety sensitivity as a moderator. Psychol. Trauma: Theory Res. Pract. Policy . 14 (3), 453 (2022). Chaoping, W., Junxi, C., Benjin, W., Hongyan, C. & Xiaoli, Y. Research progress on non-clinical causes of delayed transfer out of ICU patients and intervention strategies. Chin. J. Acute Crit. Care . 4 (11), 1006–1010 (2023). Chick, N. & Meleis, A. I. Transitions: A nursing concern. PL Chinn (Ed.), Nursing research methodology: Issues and implementation , 237–257. (1986). Diwan, M., Mentz, G., Romano, M. & Engoren, M. Delayed discharge from the intensive care unit is associated with longer hospital lengths of stay. J. Cardiothorac. Vasc. Anesth. 37 (2), 232–236 (2023). Edenharter, G. et al. Delay of transfer from the intensive care unit: a prospective observational analysis on economic effects of delayed in-house transfer. Eur. J. Med. Res. 24 , 1–5 (2019). Everall, A. C. et al. Patient and caregiver experience with delayed discharge from a hospital setting: a scoping review. Health Expect. 22 (5), 863–873 (2019). Galatzer-Levy, I. R., Huang, S. H. & Bonanno, G. A. Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluation. Clin. Psychol. Rev. 63 , 41–55 (2018). Galvin, E. C., Wills, T. & Coffey, A. Readiness for hospital discharge: A concept analysis. J. Adv. Nurs. 73 (11), 2547–2557 (2017). Girard, T. D. et al. Risk factors for post-traumatic stress disorder symptoms following critical illness requiring mechanical ventilation: a prospective cohort study. Crit. Care . 11 (1), R8 (2007). Girgenti, M. J. et al. Transcriptomic organization of the human brain in post-traumatic stress disorder. Nat. Neurosci. 24 (1), 24–33 (2021). Griffith, D. M. et al. Determinants of Health-Related Quality of Life After ICU: Importance of Patient Demographics, Previous Comorbidity, and Severity of Illness. Crit. Care Med. 46 (4), 594–601. 10.1097/ccm.0000000000002952 (2018). Guoping, H., Yalin, Z., Hui, X. & Yunfei, Z. Reliability and validity analysis of the Event Impact Scale-Revised (IES-R) in female prisoners. Chin. J. Mental Health . 20 (1), 28–31 (2006). Hatch, R. et al. Anxiety, Depression and Post Traumatic Stress Disorder after critical illness: a UK-wide prospective cohort study. Crit. Care . 22 (1), 310 (2018). Jian, X., Linglong, Y. & Ya, F. Progress in the application of growth mix model in health trajectory research. Chin. Health Stat. , 37 (4). (2020). Kucharczuk, C. et al. Standardized discharge planning tool leads to earlier discharges and fewer readmissions. J. Nurs. Care Qual. 37 (1), 54–60 (2022). Lane-Fall, M. B., Kuza, C. M., Fakhry, S. & Kaplan, L. J. The Lifetime Effects of Injury: Postintensive Care Syndrome and Posttraumatic Stress Disorder. Anesthesiol Clin. 37 (1), 135–150 (2019). Leilei, Z., Yeling, W. & Huichun, L. Application of hospital anxiety and depression scale in general hospital. Shanghai Psychiatry . 15 (5), 264–266 (2003). Li, Z. et al. A cross-sectional study on the mental health of patients with COVID-19 1 year after discharge in Huanggang, China. Eur. Arch. Psychiatry Clin. NeuroSci. 273 (2), 301–310 (2023). Mehta, A. B., Syeda, S. N., Wiener, R. S. & Walkey, A. J. Epidemiological trends in invasive mechanical ventilation in the United States: A population-based study. J. Crit. Care . 30 (6), 1217–1221 (2015). Meihong, Y. Status and influencing factors of post-traumatic stress disorder in patients with mechanical ventilation in ICU. Zhejiang Trauma. Surg. Department , 24 . (2019). Meleis, A. Middle-Range and situatoin-specific theories in nursing research and practice. Transitions Theory , 1–11. (2010). Mengcheng, W., Qiaowen, D. & Xiangyang, B. Bayesian method for latent variable modeling. Adv. Psychol. Sci. 25 (10), 1682–1695 (2017). Mikkelsen, M. E. et al. Society of Critical Care Medicine's International Consensus Conference on Prediction and Identification of Long-Term Impairments After Critical Illness. Crit Care Med, 48 (11), 1670–1679. (2020). Mingyi, Q., City, W., Rongchun, Z. & Xin, Z. Revision of the Chinese version of the Eysenck Personality Questionnaire (EPQ-RSC). Acta Physiol. Sinica . 32 (3), 317–323 (2000). Myhren, H., Ekeberg, Ø., Tøien, K., Karlsson, S. & Stokland, O. Posttraumatic stress, anxiety and depression symptoms in patients during the first year post intensive care unit discharge. Crit. Care . 14 , 1–10 (2010). Tobias, N. M. A., Ilan, S. & H.-R., H., K. J., & H., P. R Post-traumatic Stress Disorder. Med. Clin. North Am. 107 (1), 85–99 (2023). Navarra-Ventura, G. et al. Occurrence, co-occurrence and persistence of symptoms of depression and post-traumatic stress disorder in survivors of COVID-19 critical illness. Eur. J. Psychotraumatol . 15 (1), 2363654 (2024). Ofoma, U. R. et al. Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality. J. Crit. Care . 58 , 48–55 (2020). Ping, N., Jingli, C. & Na, L. Sample size estimation for quantitative studies in nursing research. Chin. J. Nurs. 45 (4), 378–380 (2010). Plotnikoff, K. M. et al. Patient discharge from intensive care: an updated scoping review to identify tools and practices to inform high-quality care. Crit. Care . 25 , 1–13 (2021). Rattray, J. E., Johnston, M. & Wildsmith, J. Predictors of emotional outcomes of intensive care. Anaesthesia 60 (11), 1085–1092 (2005). Righy, C. et al. Prevalence of post-traumatic stress disorder symptoms in adult critical care survivors: a systematic review and meta-analysis. Crit. Care . 23 (1), 213. 10.1186/s13054-019-2489-3 (2019). Ronghua, L. Study on post-ICU syndrome of mechanical ventilation survivors and their family members in Guangzhou. (PhD). (2019). Ronghua, L., Jingye, H., Xiaoqing, L., Ying, Z. & Yimin, L. Longitudinal study on mental function of mechanical ventilation survivors in ICU at different periods. J. Practical Med. , 36. (2020). Sayed, S., Iacoviello, B. M. & Charney, D. S. Risk Factors for the Development of Psychopathology Following Trauma. Curr. Psychiatry Rep. 17 (10), 80 (2015). Shuo, W., Wanling, H., Rongfang, H. & Li, H. Meta-analysis of risk factors for post-traumatic stress disorder in ICU patients. Chin. J. Nurs. , 51. (2016). Wade, D. M. et al. Investigating risk factors for psychological morbidity three months after intensive care: a prospective cohort study. Crit. Care . 16 (5), 1–16 (2012). Xiaojing, Z., Yunan, C. & Yue, T. Investigation on discharge readiness of patients with chronic diseases and its influencing factors and discussion on nursing strategies. Chin. J. Practical Nurs. 40 (4), 296–302 (2024). Xin, X. & Qiang, S. Analysis of risk factors of post-traumatic stress disorder in critical emergency patients with mechanical ventilation off-line. Int. J. Psychiatry , 47 (6). (2020). Yan, L. Analysis of risk factors for post-traumatic stress disorder after mechanical ventilation in emergency patients with severe illness. J. Math. Med. Pharmacol. 35 (01), 150–153 (2022). Yanin, X. A preliminary study on the reliability and validity of the simple coping style Scale. J. Clin. Psychol. (2), 114–115. (1998). Yanjie, S., Qiongqiong, H. & Yanhui, C. Study on occurrence and influencing factors of post-traumatic stress disorder in ICU patients. China Med. Rev. 8 (16). (2019). Zigmond, A. S. & Snaith, R. P. The hospital anxiety and depression scale. Acta Psychiatry. Scand. 67 (6), 361–370 (1983). Zimet, G. D., Dahlem, N. W., Zimet, S. G. & Farley, G. K. The multidimensional scale of perceived social support. J. Pers. Assess. 52 (1), 30–41. 10.1207/s15327752jpa5201-2 (1988). Tables Table 1 Potential category model fitting information for PTSD development trajectory of tracheal intubation patients in ICU (n=204) Model AIC BIC aBIC P 值 Entropy Class probability（%） LMRT BLRT 1 6010.254 6043.435 6011.752 - - - 100 2 6041.572 6081.389 6043.370 ＜0.001 ＜0.001 0.963 98.3/0.17 3 5906.231 5956.003 5908.479 0.0418 0.0487 0.894 16.2/30.4/ 53.4 4 5814.745 5874.472 5817.442 0.0297 0.0353 0.907 6.9/ 27.2/ 51.6/ 14.3 5 5787.082 5856.762 5790.228 0.2840 0.2968 0.910 26.0/2.9/14.2/7.8/ 49.1 Note: AIC is Akike information criterion; BIC is the Bayesian information criterion; aBIC is the Bayesian information criterion for sample correction. The LMRT is the Roi-Mondel-Ruben-corrected likelihood ratio test; BLRT is a likelihood ratio test based on Bootstrap. "-" indicates no meaning. Table 2 Results of univariate analysis of general information of patients with PTSD development trajectory in each group (n=204) item high-risk deterioration group (n=14) high-risk improvement group (n=57) medium-risk maintenance group (n=27) low-risk improvement group (n=106) Test statistic P Level of education 16.743 1 ） 0.034 Primary school degree and below 4（28.6%） 27（47.4%） 19（70.4%） 41（38.7%） Junior high school degree 4（28.6%） 23（40.4%） 5（18.5%） 42（39.6%） High school and technical secondary school degree 6（42.8%） 5（8.8%） 3（11.1%） 17（16%） College degree or above 0（0%） 2（3.5%） 0（0%） 6（5.7%） Medical payment methods 17.936 1 ） 0.016 Urban residents 6（42.9%） 46（80.7%） 17（63%） 79（74.5%） Urban workers 2（14.3%） 6（10.5%） 3（11.1%） 18（17%） All expenses paid 5（35.7%） 4（7%） 6（22.2%） 8（7.5%） Other (Business, industrial injury Medical) 1（7.1%） 1（1.8%） 1（3.7%） 1（1%） Total hospitalization days(Day, ) 30.21±14.44 27.28±12.16 28.82±17.60 21.32±10.45 14.767 2 ） 0.002 Duration from extubation to ICU discharge （ h ， ） 155.81±124.65 95.17±84.07 71.57±52.19 85.07±64.01 17.376 2 ） 0.001 Hospitalization fee （ Yuan ， ） 119466.02± 71849.60 93234.50± 43149.12 103766.81± 65691.79 77509.17± 61603.82 8.565 2 ） 0.036 Note: Only statistically significant data are presented in Table 6:1)Fisher's exact test; 2)H value Table 3 Results of univariate analysis of social psychology in patients with PTSD developmental trajectories in various groups (n=204) item high-risk deterioration group（n=14） high-risk improvement group (n=57) medium-risk maintenance group (n=27) low-risk improvement group (n=106) H P ERQ-RSC score（points， ） Extroversion 8.57±3.65 8.60±3.23 8.33±3.10 9.20±2.95 3.156 0.368 Neurotic 5.57±2.85 5.05±3.04 5.52±2.93 3.49±2.67 19.004 ＜0.001 SCSQ score （points， ） Positive response 20.64±5.02 19.46±5.33 20.00±5.00 22.15±4.63 10.899 0.012 Negative response 11.86±3.42 11.12±3.96 11.41±3.84 10.51±3.25 2.900 0.407 PSSS score （points， ） Family support 24.07±3.15 23.51±3.44 23.41±3.13 24.42±2.97 4.038 0.257 Friend support 13.43±5.53 13.60±6.17 13.81±6.85 15.26±6.56 3.068 0.381 Other support 22.07±3.73 21.88±3.44 28.98±3.80 22.15±3.50 2.517 0.472 HADS score （points， ） HADS-A 11.00±4.21 11.00±3.47 12.19±3.63 6.96±3.23 61.888 ＜0.001 HADS-D 8.57±4.78 9.51±3.37 10.07±4.20 6.15±3.76 34.957 ＜0.001 Table 4 Variable assignment methods Variables assignment Trajectory class high-risk deterioration group=1 high-risk improvement group =2 medium-risk maintenance group =3 low-risk improvement group=4 Level of education Primary school degree and below=1 Junior high school degree=2 High school and technical secondary school degree=3 College degree or above =4 Medical payment methods Urban residents=1 Urban workers=2 All expenses paid=3 Other (Business, industrial injury Medical)=4 Table 5 Results of multivariate logistic regression analysis of patients with PTSD developmental trajectory in various groups (n=204) Item β Standard error Wald X 2 P OR 95% CI Lower limit Upper limit C1 vs C2 1) HADS-A score 0.364 0.106 11.674 0.001 1.291 1.168 1.772 C1 vs C3 1) Total hospitalization days 0.042 0.020 4.394 0.036 1.043 1.003 1.085 HADS-A score 0.301 0.081 13.704 ＜0.001 1.351 1.152 1.583 C1 vs C4 1) HADS-A score 0.318 0.140 5.181 0.023 1.374 1.045 1.807 Level of education （Primary school degree and below） 17.383 0.925 353.007 ＜0.001 - - - Level of education （Junior high school degree） 17.157 0.890 371.353 ＜0.001 - - - C2 vs C4 2) Duration from extubation to ICU discharge 0.015 0.005 7.832 0.005 1.015 1.004 1.025 Note: C1 refers to low-risk improvement; C2 was medium risk maintenance group; C3 was the high-risk improvement group; C4 was defined as high risk deterioration group; 1) C4 was used as the reference group; 2) C2 was used as the reference group; "-" represents a higher value. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 06 Nov, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 10 Sep, 2025 Reviews received at journal 09 Sep, 2025 Reviewers agreed at journal 08 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviewers agreed at journal 04 Sep, 2025 Reviews received at journal 01 Sep, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers invited by journal 21 Aug, 2025 Editor assigned by journal 21 Aug, 2025 Editor invited by journal 12 Aug, 2025 Submission checks completed at journal 05 Aug, 2025 First submitted to journal 05 Aug, 2025 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. 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With the increase in patient survival rates, their physical and mental health and quality of life have received more and more attention(Griffith et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Post-traumatic stress disorder (PTSD) is a common mental and psychological disorder among ICU patients, with an incidence rate of 19.83%(Righy et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It refers to a delayed or persistent mental disorder that occurs in individuals after experiencing or witnessing a major traumatic event(N., Tobias, Ilan, H., \u0026amp; H., 2023). Mechanical ventilation, a common life support method in ICUs, has saved countless lives. According to statistics, approximately 310 of every 100,000 adults receive invasive ventilation treatment for non-surgical reasons(Mehta, Syeda, Wiener, \u0026amp; Walkey, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). ICU patients on mechanical ventilation experience a lot of hidden pain during treatment, such as tracheal intubation, suctioning, and human-machine conflict, all of which can cause stress in the body. These factors increase patients' feelings of helplessness and fear, leading to PTSD after extubation and weaning(Yan, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yanjie, Qiongqiong, \u0026amp; Yanhui, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The core manifestations of PTSD include intrusive memories, avoidance reactions, and arousal reactions(Bisson \u0026amp; Olff, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Its impact on patients can last several years or even longer, reducing their social adaptability and increasing medical and nursing costs(Lane-Fall, Kuza, Fakhry, \u0026amp; Kaplan, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAt present, most of the studies on PTSD in ICU mechanically ventilated patients are cross-sectional surveys, with few longitudinal studies reported, neglecting that PTSD is a complex and dynamic process. However, assisting patients in adjusting their mindset and integrating into the changes in social functions is often challenging. As the rehabilitation process progresses, the physical and mental states of patients constantly change, and their intervention measures need to be adapted to the situation and individualized. In addition, the chronic disease trajectory theory model indicates that the disease development trajectory not only varies among individuals but may also differ at the group level, that is, the disease development trajectory of patients has group heterogeneity(Jian, Linglong, \u0026amp; Ya, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given this, this study tracked the PTSD symptom levels of ICU mechanically ventilated patients, identified their potential subgroups based on the latent class growth model (LCGM), and analyzed the influencing factors of each subgroup, to provide a basis for the clinical formulation of precise psychological intervention measures.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cb\u003eRespondents\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis investigation recruited mechanically ventilated ICU patients at a Grade III Level A hospital in Zunyi, China during the period from August 2023 to July 2024. Inclusion criteria: ① Invasive mechanical ventilation time ≥ 48 hours; ② Age ≥ 18 years old; ③ No other major stress events within one year before admission; ④ Conscious and with normal communication ability; ⑤ Patients and their families gave informed consent and voluntarily participated. Exclusion criteria: ① Those with a history of mental illness or currently taking psychotropic drugs; ② Those who were re-admitted to the ICU and intubated during the investigation period. Dropout criteria: ① Patients who died or had their condition worsen during the investigation period; ② Patients who voluntarily withdrew or did not cooperate; ③ Failure to contact the patient for three consecutive days. The sample size was calculated based on the sample size requirements of the latent class growth model. A total of 23 variables were included in this study, and the sample size was taken as 5 to 10 times the number of variables(Ping, Jingli, \u0026amp; Na, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Considering a 20% loss to follow-up rate, the required sample size was 138 to 276 cases. According to research, when the Bayesian information criterion (BIC) is used as the primary indicator for model selection, the sample size should be ≥ 200(Mengcheng, Qiaowen, \u0026amp; Xiangyang, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Ultimately, 229 questionnaires were distributed. This study has been approved by the hospital's ethics committee (KLLY-2023-055), and all subjects gave informed consent and voluntarily participated.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSurvey tools\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGeneral Information Questionnaire\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDesigned by the researchers themselves, The data included gender, age, marital status, education level, residence, occupational status, swallowing, drinking, hospitalization expenses, payment method of medical expenses, APACHE Ⅱ score, duration of mechanical ventilation, the total length of hospital stay, length of ICU stay, length of extubation to ICU discharge, whether complicated with hypertension, whether complicated with diabetes, whether complicated with coronary heart disease and the number of chronic diseases, a total of 19 items. Demographic data were filled in by patients or their family members, and disease data were derived from the hospital’s electronic medical record system or obtained by consulting doctors.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImpact of Event Scale-Revised (IES-R)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCompiled by Weiss et al in 1997, and sinicized by Huang Guoping et al.(Guoping, Yalin, Hui, \u0026amp; Yunfei, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) in 2006, it included 3 dimensions and 22 items, which are intrusive thinking symptoms (8 items), avoidance symptoms (8 items), and high arousal symptoms (6 items). Likert 5 scale is used to count 0–4 points from \"never\" to \"always\". The total score ranges from 0 to 88. The subject scored each item according to the impact of a traumatic event in the past 7 days. The cut-off value was 22 points, and the total score \u0026gt;22 points was positive PTSD symptoms, while scores ≤ 22 indicated negative PTSD symptoms. The total Cronbach's α of the scale was 0.89, and the Cronbach's α coefficients of the three dimensions were 0.77, 0.83, and 0.76, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEysenck Personality Questionnaire-Revised, Short Scale for Chinese (ERQ-RSC)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDeveloped by British psychologist Eysenck et al.(Mingyi, City, Rongchun, \u0026amp; Xin, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), The Chinese version was revised and introduced by Qianming-yi et al. It includes four subscales, P (psychoticism scale), E (extraversion scale), N (neuroticism scale), and L (Lie scale). Each subscale contains 12 items, and the score is 0–12, the higher the score, the stronger the personality trait. The Cronbach's α coefficients of the E, N, and L subscales of the EPQ-RSC ranged from 0.74 to 0.78, and the Cronbach's α coefficients of the P scale ranged from 0.54 to 0.60. Two personality traits, E and N, were analyzed in this study.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSimplified Coping Style Questionnaire (SCSQ)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eXie Yaning(Yanin, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1998\u003c/span\u003e) compiled the Coping style Scale on the basis of the foreign coping style scale and combined it with the characteristics of the Chinese population, and it is widely used in the field of psychology in China. A total of 20 items were included, including positive coping style (items 1–12) and negative coping style (items 13–20). The Likert T4 scale was used to calculate 0–3 points from \"don't take\" to \"often take\". The results were positive coping style scores and negative coping style scores. The Cronbach's α coefficient of the whole scale was 0.9, the Cronbach's α coefficient of the positive coping scale was 0.89, and the Cronbach's α coefficient of the negative coping scale was 0.78.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePerceived Social Support Scale (PSSS)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIt was compiled by Zimet(Zimet, Dahlem, Zimet, \u0026amp; Farley, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1988\u003c/span\u003e) in 1988 and translated into Chinese by Jiang Qianjin et al. in 2001. It included 3 dimensions of family support, other support (leaders, relatives, colleagues), and friend support, and 12 items. Likert7 scale was used to calculate 1–7 points from \"strongly agree\" to \"strongly agree\". The total score reflects the degree of social support, which can be divided into low, medium, and high support levels. They were 12–36 points, 37–60 points, and 61–84 points, respectively. The total score was positively proportional to the degree of social support. The total Cronbach's α of the scale was 0.92, and the Cronbach's α coefficients of the three subscales were 0.91, 0.89, and 0.81, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHospital Anxiety and Depression Scale (HADS)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDeveloped by Zigmond and Snaith(Zigmond \u0026amp; Snaith, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1983\u003c/span\u003e) in 1983, it is composed of two subscales: Anxiety (A) and Depression (D), each with 7 items. The Likert T4 scale is used (0–3 points), and the total score of each dimension is 0–21 points, which is divided into 8 points. They were positive for anxiety or depression. Zheng Leilei et al.(Leilei, Yeling, \u0026amp; Huichun, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) showed that Cronbach's α coefficients of anxiety subscale and depression subscale were 0.806 and 0.791, respectively, indicating that the scale had good reliability and validity.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods of data collection and quality control\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe researchers screened the subjects strictly according to the inclusion and exclusion criteria, fully explained the purpose, significance, and questionnaire-filling requirements of the study, and obtained their informed consent to collect their basic information within 7 days after being transferred from the ICU. At the same time, the researchers made an appointment with the subjects for the next follow-up, and data were collected through face-to-face follow-up, telephone interviews, and WeChat. The PTSD symptom levels of the patients were assessed using the IES-R at 7 days (T\u003csub\u003e0\u003c/sub\u003e), 1 month (T\u003csub\u003e1\u003c/sub\u003e), 3 months (T\u003csub\u003e2\u003c/sub\u003e), and 6 months (T\u003csub\u003e3\u003c/sub\u003e) after extubation. If patients had any questions during the filling process, a unified statement was used to answer them. If the patient had difficulty reading and writing, the questions were retold in a neutral tone and checked with the investigator after obtaining the patient's consent. All the questionnaires were collected on the spot and entered and checked by two members of the research team to check for missing items and eliminate the regularly answered questionnaires.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStatistical methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMplus8.3 was used to build the latent category growth model. Starting from a single-category model, the number of categories was gradually increased, and the best-fitting model was selected according to the model fit index and clinical significance. The model adaptation indicators mainly include the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted BIC (aBIC), the smaller the statistical value, the better the model fitting effect. Lo-Mendell-Rubin likelihood ratio test (LMR), and Bootstrap likelihood ratio text test (BLRT), when the test statistic value was \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, The results showed that the k classification model had a better fitting degree than the K-1 classification model. The entropy index is used to evaluate the accuracy of classification. The value ranges from 0 to 1, and the closer the value is to 1, the more accurate the classification is. When Entropy is ≥ 0.8, the accuracy of classification is ≥ 90%(Mengcheng et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). SPSS29.0 was used for data analysis. The count data were described by frequency and percentage, and the χ2 test was used for comparison between groups. Measurement data following normal distribution were described by \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\stackrel{-}{x}\\)\u003c/span\u003e\u003c/span\u003e\u003cem\u003e±s\u003c/em\u003e. One-way analysis of variance was used for comparison between groups. Multiple groups of influencing factors were analyzed by unordered multinomial Logistic regression analysis. \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 was considered statistically significant.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study protocol was reviewed and approved by the Ethics Committee of the Affiliated Hospital of Zunyi Medical University (Ethical Approval No.: KLLY-2023-055). Written informed consent was obtained from all participants. All study procedures were conducted in accordance with the principles of the Declaration of Helsinki and the relevant guidelines and regulations of the Ethics Committee of the Affiliated Hospital of Zunyi Medical University.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eGeneral Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 229 questionnaires were distributed in this study, and 25 patients were excluded for loss of follow-up. A total of 204 valid questionnaires were obtained, with an effective recovery rate of 89.1%. The average age of mechanical ventilation patients in ICU was (56.23\u0026plusmn;1.02) years old. There were 125 males (61.30%) and 79 females (38.7%). Most of them (140, 68.6%) lived in rural areas. The most common marital status was married (178, 87.3%). The education level was low, 93 (45.6%) were in primary school or below. Most of the occupational statuses were freelance and unemployed, accounting for 30.9% and 30.4% respectively. Most of the medical payment methods were medical insurance for urban residents, accounting for 72.5%. Not drinking is more than drinking; There were more non-smokers than smokers. Most of the patients had one or less chronic diseases. The duration of mechanical ventilation was (150.76\u0026plusmn;7.52) hours; The total length of hospital stay was (24.59\u0026plusmn;0.89) days. The length of ICU stay was (220.74\u0026plusmn;8.85) hours; The duration from extubation to ICU discharge was (95.62\u0026plusmn;5.79) hours. APACHE\u0026nbsp;Ⅱ\u0026nbsp;score was (21.59\u0026plusmn;0.34) points; The hospitalization cost was (88257.68\u0026plusmn;4157.62) yuan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive analysis of social psychology scale scores of patients with tracheal intubation in ICU at T\u003csub\u003e0\u003c/sub\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe score of positive coping dimension of SCSQ in ICU patients with tracheal intubation at T\u003csub\u003e0\u003c/sub\u003e was (21.01\u0026plusmn;5.02), and the score of negative coping dimension was (10.89\u0026plusmn;3.55). The score of the extraversion dimension of ERQ-RSC was (8.87\u0026plusmn;3.10). The score of neuroticism was (4.34\u0026plusmn;2.95); The total score of PSSS was (60.39\u0026plusmn;10.35), the score of family support dimension was (24.01\u0026plusmn;3.15), the score of friend support dimension was (14.48\u0026plusmn;6.44) and the score of other support dimension was (21.90\u0026plusmn;3.54). The anxiety dimension score of HADS was (9.06\u0026plusmn;4.06), and the depression dimension score was (7.77\u0026plusmn;4.14).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLatent\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eclass growth model\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;analysis of the change trajectory of PTSD in ICU patients with tracheal intubation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePotential category models were fitted based on IES-R scale scores of ICU mechanical ventilation patients, and a total of 5 potential profile models were fitted starting from the initial model, as shown in Table 1. With the increase in the number of categories, AIC, BIC and aBIC gradually decreased, and the information entropy was all greater than 0.85. When the number of model categories was 4, the decreasing trend of AIC, BIC, and aBIC tended to be stable, and the LMRT and BLRT tests all reached significant levels (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Considering the fitting indexes and practical significance of the model, model 4 was selected as the optimal fitting model for patients with mechanical ventilation in the ICU in this study, and discriminant analysis was used to verify the accuracy of the optimal model, with a posterior probability of 98 and high discriminating power.\u003c/p\u003e\n\u003cp\u003eBased on model 4, the mean scores of each category on the IES-R scale are shown in Figure 1. According to the fluctuation of the mean line chart of each item in the potential profile, the characteristic attributes of four potential PTSD subtypes are analyzed and named as follows.\u003c/p\u003e\n\u003cp\u003eThe trajectory of the C1 group had the highest IES-R score at the T\u003csub\u003e0\u003c/sub\u003e stage. Combined with the mean intercept and slope of the curve, they were 39.40 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and 9.99 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), respectively, and the slope was positive, indicating that the IES-R score of patients showed an increasing trend during the follow-up period, so they were named as the \u0026quot;high-risk worsening group\u0026quot;. There were 14 in this category, accounting for 6.9%.\u003c/p\u003e\n\u003cp\u003eIn the T\u003csub\u003e0\u003c/sub\u003e phase, the IES-R score level of the C2 locus was second only to the C1 locus, but this locus showed a significant downward trend, and its mean curve intercept and slope were 37.73 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and -43.90 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), respectively. During the T\u003csub\u003e1\u003c/sub\u003e-T\u003csub\u003e3\u003c/sub\u003e follow-up period, the mean IES-R score was \u0026le;22, showing a large improvement, so the C2 category was named the \u0026quot;high-risk improvement group\u0026quot;. There were 57 students in this category, accounting for 27.2%.\u003c/p\u003e\n\u003cp\u003eIn the T\u003csub\u003e0\u003c/sub\u003e period, the IES-R score level of the C3 category was in the middle of the four tracks, the mean intercept rate was 35.99 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and the mean slope was -13.10 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). Although the overall trend was downward, the mean IES-R score at the four points was \u0026gt;22 points. Therefore, this category is named the \u0026quot;Medium-Risk Retention Group\u0026quot;. There were 27 students in this category, accounting for 14.3%.\u003c/p\u003e\n\u003cp\u003eIn the four follow-up periods, the level of IES-R score of the C4 category was low, and the overall trend was downward and tended to be flat. Combined with the mean intercept and slope of the curve, which were 17.66 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) and -18.34 (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), the C4 category was named \u0026quot;low-risk improvement group\u0026quot;. There were 106 students in this category, accounting for 51.6%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-factor analysis of social psychology of various groups of patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the univariate analysis showed that the scores of SCSQ positive coping dimension, ERQ-RSC neurotic dimension, anxiety dimension, and depression dimension were statistically significant in the 4 groups of patients (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), as shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle-factor analysis of social psychology of various groups of patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe scores of ERQ-RSC, SCSQ, PSSS, and HADS scales at T\u003csub\u003e0\u003c/sub\u003e were used to conduct a univariate analysis of personality characteristics, coping styles, social support, anxiety, and depression. The results showed that the scores of SCSQ positive coping dimension, ERQ-RSC neurotic dimension, anxiety dimension, and depression dimension were statistically significant in the 4 groups of patients (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05), as shown in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Logistics Regression Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the construction of the regression model, the trajectory category was used as the dependent variable, and the significant indicators in the univariate analysis were used as the independent variables. The continuous numerical variables were directly included in the regression equation with their original values for calculation, and the assignment of categorical variables was shown in Table 4.\u003c/p\u003e\n\u003cp\u003eTaking the \u0026quot;low-risk improvement group\u0026quot;, \u0026quot;medium-risk maintenance group\u0026quot; and \u0026quot;high-risk improvement group\u0026quot; as the reference group, multivariate Logistic regression analysis showed that education level, the total length of hospital stay, duration from extubation to transfer from ICU, and anxiety were independent predictors of PTSD development trajectory in ICU patients with tracheal intubation. Education level and anxiety were the most influential factors for the high-risk deterioration group compared with the low-risk improvement group. The influencing factors of the \u0026quot;high-risk improvement group\u0026quot; were the total length of hospital stay and anxiety; The influencing factor of the \u0026quot;medium-risk maintenance group\u0026quot; was anxiety. Compared with the \u0026quot;medium-risk maintenance group\u0026quot;, the influencing factor of the \u0026quot;high-risk deterioration group\u0026quot; was the duration from extubation to ICU discharge. See Table 5 for details. The Omnibus test （\u003cimg width=\"17\" height=\"19\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1756478236.gif\" alt=\"image\"\u003e=130.759, \u003cem\u003edf\u003c/em\u003e=45, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001) showed that the model fitted well and could truly and reliably reflect the relationship between the original variables.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cb\u003eThere is heterogeneity in the development trajectory of PTSD in patients with tracheal intubation in ICU\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe population of patients with endotracheal intubation in ICU is heterogeneous. In this study, we fitted the potential categories of PTSD change trajectory of patients with endotracheal intubation in ICU based on LCGM, and finally determined four potential categories of PTSD (high risk of deterioration, high risk of improvement, medium risk of maintaining, and low risk of improvement). Galatzer et al.(Galatzer-Levy, Huang, \u0026amp; Bonanno, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reviewed related articles on PTSD trajectory and found that the most consistent trajectory change categories observed by patients after traumatic experience were four trajectory categories: maintenance group, recovery group, chronic group, and delayed onset group, which were similar to the results of this study. Among the four trajectories, the low-risk improvement group accounted for the highest proportion (51.6%), indicating that most ICU mechanical ventilation patients could better adjust their mentality and adapt to changes in social function after extubation and weaning. The initial IES-R scores were higher (\u0026gt;\u0026thinsp;22) in the intermediate-risk maintenance group, high-risk improvement group, and high-risk deterioration group, but the slope changes were different. Patients in the moderate-risk maintenance group maintained moderately severe PTSD symptoms at all time points, and although the developmental trajectory showed a downward trend over time, their nadir IES-R scores were higher than 22. Without intervention, PTSD symptoms in such groups may persist longer. Therefore, the focus of intervention in such patients should be on the full cycle. For the patients in the high-risk improvement group, although the PTSD symptoms were at a high level in the initial stage, the severity of PTSD showed a significant downward trend with time. At T2-T3, the mean IES-R score was \u0026le;\u0026thinsp;22, and the PTSD symptoms were greatly improved. An in-depth exploration of the factors affecting the psychological status of such patients may provide a valuable reference for the formulation of future intervention strategies. Patients in the high-risk deterioration group had the highest initial IES-R scores and their IES-R scores gradually increased over time. It is suggested that the PTSD symptoms of these patients gradually worsen over time, which poses a serious threat to their mental health and delays the recovery process of patients. We should pay more attention to the high-risk group. Patients in the high-risk deterioration group have higher symptom scores and lower identification difficulty in the early stage of extubation and weaning. Medical staff should provide full-cycle psychological counseling for such patients, establish follow-up files, and pay close attention to changes in mental health status.\u003c/p\u003e\u003cp\u003e\u003cb\u003eInfluencing factors of PTSD development trajectory in ICU patients with tracheal intubation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUnivariate and multivariate analysis showed that education level, total length of hospital stay, duration from extubation to ICU discharge, and anxiety were independent influencing factors of PTSD development trajectory in ICU patients with tracheal extubation. Previous studies have pointed out that gender(Girard et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Shuo, Wanling, Rongfang, \u0026amp; Li, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), age(Meihong, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rattray, Johnston, \u0026amp; Wildsmith, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), mechanical ventilation(Wade et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Yan, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), APACHE Ⅱ score(Meihong, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Yan, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and so on are the influencing factors of PTSD in ICU patients. The heterogeneity of study results may result from differences in sample characteristics. Although the subjects were all mechanically ventilated patients in the ICU, the conclusions of different studies are different due to the diversity of clinical characteristics such as disease types and severity. In addition, the number of PTSD-positive samples in this study was small, and multi-center studies with large samples can be carried out in the future to analyze its influencing factors in depth.\u003c/p\u003e\u003cp\u003eThe mental health problems of ICU patients have been widely discussed by scholars at home and abroad, and it is urgent to formulate precise intervention measures in clinical practice. The results of this study showed that compared with the low-risk improvement group, the high-risk deterioration group had lower education levels and higher anxiety dimension scores. Compared with the intermediate-risk maintenance group, the high-risk deterioration group had a longer time from extubation to ICU discharge. These patients are more likely to develop PTSD, and their PTSD symptoms are more likely to aggravate over time. Therefore, we should pay more attention to preventing and treating these patients.\u003c/p\u003e\u003cp\u003eStudies have found that psychological disorders in patients transferred from the ICU are often not isolated, and the comorbidity rate of anxiety, depression, and PTSD is as high as 65%(Bryant, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hatch et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Navarra-Ventura et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The present study found that the more severe the anxiety, the more likely it was to induce PTSD, which was the same as the results of previous studies(Ronghua, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Xin \u0026amp; Qiang, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In the state of anxiety, the neurotransmitter activity of patients is more active, which can acutely capture the discomfort of the body(Carpenter, Bragdon, \u0026amp; Pineles, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Such discomfort may lead to the aggravation of the psychological burden of patients and increase the risk of PTSD. In this study, no significant difference in depression was found among different types, and the reason may be that the HADS questionnaire was collected within 7 days after extubation, and patients in this period have a high level of social support, more concern about disease progression, high compliance, and a strong desire to express, so the incidence of depression is low. In the future, it can be further verified by reassessing the anxiety and depression when assessing the PTSD level of patients. In addition, patients with a lower level of education are more likely to be assigned to the high-risk deterioration group, which is similar to the findings of Li Zhuqing et al.(Li et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Low cognition is a risk factor for PTSD, and education is highly correlated with cognition, thus education is negatively associated with the risk of PTSD(Myhren, Ekeberg, T\u0026oslash;ien, Karlsson, \u0026amp; Stokland, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sayed, Iacoviello, \u0026amp; Charney, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). However, some studies have pointed out that there is no correlation between education level and PTSD(Bienvenu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), or that patients with higher education levels are more likely to develop PTSD(Ronghua, Jingye, Xiaoqing, Ying, \u0026amp; Yimin, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The differences in the results of the studies may be affected by the sample size and the subjects. Whether a low education level is a risk factor for PTSD needs to be further explored. Studies have shown that the delay in discharge will delay the time of patients' discharge, and increase the cost of treatment, mortality, and readmission rate(Diwan, Mentz, Romano, \u0026amp; Engoren, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Edenharter et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ofoma et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The study by Bagshaw et al.(Bagshaw et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) showed that 20%-50% of ICU patients have a delay in transfer. ICU delay refers to the phenomenon that the patient's condition has improved and meets the requirements for discharge, but it is not necessary to stay in the ICU for treatment(Chaoping, Junxi, Benjin, Hongyan, \u0026amp; Xiaoli, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Chick et al. put forward the transition theory in 1986, which refers to the transformation of people from one life state to another(Chick \u0026amp; Meleis, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1986\u003c/span\u003e; Meleis, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Extubation is a transition for patients with tracheal intubation in ICU. Based on this, this study included \"the time from extubation to ICU discharge\" for influencing factors analysis. The results of this study show that the time from extubation to transfer is one of the influencing factors of PTSD in ICU patients with tracheal intubation. The longer the time from extubation to transfer, the more likely the patients are to develop PTSD. The reason may be that after extubation, patients have clear consciousness, and the delay in discharge aggravates the patient's illness uncertainty(Everall et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). At the same time, high treatment costs and psychological needs such as family company cause great burden to patients and increase the risk of PTSD.\u003c/p\u003e\u003cp\u003eBased on this, medical personnel should pay attention to the mental health status of patients at an early stage, conduct a key assessment of anxiety, and formulate targeted intervention measures based on understanding the psychological status of patients, to reduce the risk of PTSD while reducing anxiety. At the same time, for patients with a low education level and a long time from extubation to ICU transfer, it is suggested that medical staff can help patients establish a positive attitude, increase positive feelings, release psychological pressure, and reduce the incidence of PTSD through psychosocial interventions such as disease knowledge education, positive self-disclosure, and mindfulness-based stress reduction therapy.\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe shorter the time from extubation to discharge and the severe the anxiety level, the patients with tracheal intubation in ICU are more likely to belong to the medium-risk maintenance group\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSome patients with PTSD show that one or more symptoms persist for a lifetime, which seriously affects the quality of life of patients(Girgenti et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, patients in the moderate-risk maintenance group had persistent PTSD symptoms during the investigation period, and the risk of PTSD in this group was only second to the high-risk worsening group. Early intervention for such patients may change the outcome of patients. The results of multivariate analysis showed that compared with the low-risk improvement group, the patients in the medium-risk maintenance group had more severe anxiety; Compared with the high-risk deterioration group, the moderate-risk maintenance group had a shorter time from extubation to ICU discharge, indicating that patients with shorter time from extubation to ICU discharge and more severe anxiety were more likely to be classified into this group. This suggests that it is important for medical staff to assess the anxiety level of patients with tracheal intubation in the ICU. If the patients have severe anxiety symptoms, even those with a short time from extubation to discharge cannot relax their vigilance. The mental health level of such patients should be dynamically evaluated in the whole process, and individualized intervention measures should be carried out according to the assessment results, to improve the level of PTSD symptoms and accelerate the rehabilitation process of patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCompared with the low-risk improvement group, the longer the total length of hospital stay and the more severe the anxiety level of ICU patients with tracheal intubation are more likely to belong to the high-risk improvement group\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAlthough the risk of PTSD in the high-risk improvement group was higher in the early stage, the level of PTSD symptoms decreased significantly over time, and most of the patients had no PTSD symptoms (IES-R score\u0026thinsp;\u0026le;\u0026thinsp;22) at the T2 stage. Such patients are characterized by a longer total length of hospital stay and higher levels of anxiety. The reason for this result may be that patients with a longer total length of hospital stay have a stronger readiness for hospital discharge, and they are better able to cope with physical and psychological changes and make timely adjustments after discharge. Readiness for hospital discharge is not only the patient's self-feeling of readiness for discharge but also the prediction and evaluation of rehabilitation ability and discharge adaptability by medical staff after comprehensive consideration of the patient's physical, psychological, and social health status(Galvin, Wills, \u0026amp; Coffey, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Discharge readiness is an important link linking in-hospital treatment and self-management of patients after discharge. Good discharge readiness can significantly promote the disease process of patients, reduce the length of hospital stay, and help patients integrate into social life as soon as possible(Kucharczuk et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Plotnikoff et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xiaojing, Yunan, \u0026amp; Yue, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It is suggested that medical staff should strengthen the discharge readiness assessment of ICU patients with mechanical ventilation, to accelerate their disease recovery process. The higher severity of early PTSD symptoms in the intermediate-risk maintenance group may be related to the higher level of anxiety symptoms. With the systematic and scientific treatment, the patient's uncertainty in illness was relieved, and the accompanying family members reduced his psychological burden, thus relieving his PTSD symptoms. This suggests that although some patients show higher levels of PTSD symptoms in the early stage, it is still possible for patients to significantly improve their psychological status or even return to normal levels under certain conditions. However, in this study, no significant protective factors were found when analyzing the influencing factors of this type of patient. Future research can deeply analyze the protective factors of PTSD risk in this type of patient, to provide a reference for the construction of feasible intervention strategies.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStrengths and Limitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study delineates the trajectory of PTSD symptom severity among ICU patients during the 6-month period following extubation. A multidimensional analysis incorporating sociodemographic, clinical, and psychosocial factors provides an evidence-based foundation for early identification, prevention, and personalized intervention strategies. However, as a single-center study, the generalizability of findings may be somewhat constrained. Future multicenter studies with larger sample sizes are recommended to enhance the representativeness and external validity of the results.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, ICU patients with tracheal intubation were followed up for PTSD at 7 days, 1 month, 3 months, and 6 months after extubation and weaning. Heterogeneity analysis was performed by LCGM, and four categories were identified: high-risk deterioration group, high-risk improvement group, medium-risk maintenance group, and low-risk improvement group. Through univariate and multivariate analysis, the study showed that education level, total length of hospital stay, duration from extubation to transfer from ICU, and anxiety were independent risk factors for the development trajectory of PTSD in ICU patients with tracheal intubation. However, since this study was a single-center study, the sample representativeness was limited. It is suggested that the sample size should be further expanded and multi-center surveys with large samples should be carried out in the future to increase the representativeness of the samples.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cb\u003eAuthor Contributions Statement\u003c/b\u003e:\u003c/h2\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eLi Yunting\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eConceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing \u0026ndash; Original Draft, Visualization.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eZhang Jiabi\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eMethodology, Validation, Resources, Writing \u0026ndash; Review, Supervision.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eChen Wei\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eWriting \u0026ndash; Review, Methodology, Methodology.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eLiu Mi\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eSoftware, Investigation, Data curation, Visualization.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eXiong Yan\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eValidation, Data Curation.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e\u003cb\u003eYuan Xiaoli (Corresponding Author)\u003c/b\u003e\u003c/strong\u003e\u003cp\u003eConceptualization, Resources, Writing \u0026ndash; Review, Supervision, Project administration, Funding acquisition.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eDeclaration of Interests\u003c/h2\u003e\u003cp\u003eAll authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eAcknowledgements: This research was supported by the Zunyi Science and Technology Program Project [Zunyi Science and Technology Cooperation Document No. HZ (2022) 278].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eLi Yunting: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Writing \u0026ndash; Original Draft, Visualization.Zhang Jiabi: Methodology, Validation, Resources, Writing \u0026ndash; Review, Supervision.Chen Wei: Writing \u0026ndash; Review, Methodology, Methodology.Liu Mi: Software, Investigation, Data curation, Visualization.Xiong Yan: Validation, Data Curation.Yuan Xiaoli (Corresponding Author) : Conceptualization, Resources, Writing \u0026ndash; Review , Supervision, Project administration, Funding acquisition.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. This research received no specific grant from funding agencies in the public, commercial, or not-for-profit sectors. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers' bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e\u003cp\u003eThe authors gratefully acknowledge all contributors to this research endeavor.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBagshaw, S. M. et al. Assessment of costs of avoidable delays in intensive care unit discharge. \u003cem\u003eJAMA Netw. Open.\u003c/em\u003e \u003cb\u003e3\u003c/b\u003e (8), e2013913\u0026ndash;e2013913 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBienvenu, O. J. et al. Post-traumatic stress disorder symptoms after acute lung injury: a 2-year prospective longitudinal study. \u003cem\u003ePsychol. Med.\u003c/em\u003e \u003cb\u003e43\u003c/b\u003e (12), 2657\u0026ndash;2671 (2013).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBisson, J. I. \u0026amp; Olff, M. Prevention and treatment of PTSD: the current evidence base. \u003cem\u003eEur. J. Psychotraumatol\u003c/em\u003e. \u003cb\u003e12\u003c/b\u003e (1), 1824381 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBryant, R. A. Post-traumatic stress disorder: a state‐of‐the‐art review of evidence and challenges. \u003cem\u003eWorld psychiatry\u003c/em\u003e. \u003cb\u003e18\u003c/b\u003e (3), 259\u0026ndash;269 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCarpenter, J. K., Bragdon, L. \u0026amp; Pineles, S. L. Conditioned physiological reactivity and PTSD symptoms across the menstrual cycle: Anxiety sensitivity as a moderator. \u003cem\u003ePsychol. Trauma: Theory Res. Pract. Policy\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (3), 453 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChaoping, W., Junxi, C., Benjin, W., Hongyan, C. \u0026amp; Xiaoli, Y. Research progress on non-clinical causes of delayed transfer out of ICU patients and intervention strategies. \u003cem\u003eChin. J. Acute Crit. Care\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e (11), 1006\u0026ndash;1010 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChick, N. \u0026amp; Meleis, A. I. Transitions: A nursing concern. \u003cem\u003ePL Chinn (Ed.), Nursing research methodology: Issues and implementation\u003c/em\u003e, 237\u0026ndash;257. (1986).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDiwan, M., Mentz, G., Romano, M. \u0026amp; Engoren, M. Delayed discharge from the intensive care unit is associated with longer hospital lengths of stay. \u003cem\u003eJ. Cardiothorac. Vasc. Anesth.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (2), 232\u0026ndash;236 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEdenharter, G. et al. Delay of transfer from the intensive care unit: a prospective observational analysis on economic effects of delayed in-house transfer. \u003cem\u003eEur. J. Med. Res.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e, 1\u0026ndash;5 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEverall, A. C. et al. Patient and caregiver experience with delayed discharge from a hospital setting: a scoping review. \u003cem\u003eHealth Expect.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (5), 863\u0026ndash;873 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalatzer-Levy, I. R., Huang, S. H. \u0026amp; Bonanno, G. A. Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluation. \u003cem\u003eClin. Psychol. Rev.\u003c/em\u003e \u003cb\u003e63\u003c/b\u003e, 41\u0026ndash;55 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGalvin, E. C., Wills, T. \u0026amp; Coffey, A. Readiness for hospital discharge: A concept analysis. \u003cem\u003eJ. Adv. Nurs.\u003c/em\u003e \u003cb\u003e73\u003c/b\u003e (11), 2547\u0026ndash;2557 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGirard, T. D. et al. Risk factors for post-traumatic stress disorder symptoms following critical illness requiring mechanical ventilation: a prospective cohort study. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e11\u003c/b\u003e (1), R8 (2007).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGirgenti, M. J. et al. Transcriptomic organization of the human brain in post-traumatic stress disorder. \u003cem\u003eNat. Neurosci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (1), 24\u0026ndash;33 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGriffith, D. M. et al. Determinants of Health-Related Quality of Life After ICU: Importance of Patient Demographics, Previous Comorbidity, and Severity of Illness. \u003cem\u003eCrit. Care Med.\u003c/em\u003e \u003cb\u003e46\u003c/b\u003e (4), 594\u0026ndash;601. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/ccm.0000000000002952\u003c/span\u003e\u003cspan address=\"10.1097/ccm.0000000000002952\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGuoping, H., Yalin, Z., Hui, X. \u0026amp; Yunfei, Z. Reliability and validity analysis of the Event Impact Scale-Revised (IES-R) in female prisoners. \u003cem\u003eChin. J. Mental Health\u003c/em\u003e. \u003cb\u003e20\u003c/b\u003e (1), 28\u0026ndash;31 (2006).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHatch, R. et al. Anxiety, Depression and Post Traumatic Stress Disorder after critical illness: a UK-wide prospective cohort study. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e22\u003c/b\u003e (1), 310 (2018).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJian, X., Linglong, Y. \u0026amp; Ya, F. Progress in the application of growth mix model in health trajectory research. \u003cem\u003eChin. Health Stat.\u003c/em\u003e, \u003cb\u003e37\u003c/b\u003e(4). (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKucharczuk, C. et al. Standardized discharge planning tool leads to earlier discharges and fewer readmissions. \u003cem\u003eJ. Nurs. Care Qual.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (1), 54\u0026ndash;60 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLane-Fall, M. B., Kuza, C. M., Fakhry, S. \u0026amp; Kaplan, L. J. The Lifetime Effects of Injury: Postintensive Care Syndrome and Posttraumatic Stress Disorder. \u003cem\u003eAnesthesiol Clin.\u003c/em\u003e \u003cb\u003e37\u003c/b\u003e (1), 135\u0026ndash;150 (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLeilei, Z., Yeling, W. \u0026amp; Huichun, L. Application of hospital anxiety and depression scale in general hospital. \u003cem\u003eShanghai Psychiatry\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e (5), 264\u0026ndash;266 (2003).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi, Z. et al. A cross-sectional study on the mental health of patients with COVID-19 1 year after discharge in Huanggang, China. \u003cem\u003eEur. Arch. Psychiatry Clin. NeuroSci.\u003c/em\u003e \u003cb\u003e273\u003c/b\u003e (2), 301\u0026ndash;310 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMehta, A. B., Syeda, S. N., Wiener, R. S. \u0026amp; Walkey, A. J. Epidemiological trends in invasive mechanical ventilation in the United States: A population-based study. \u003cem\u003eJ. Crit. Care\u003c/em\u003e. \u003cb\u003e30\u003c/b\u003e (6), 1217\u0026ndash;1221 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeihong, Y. Status and influencing factors of post-traumatic stress disorder in patients with mechanical ventilation in ICU. \u003cem\u003eZhejiang Trauma. Surg. Department\u003c/em\u003e, \u003cb\u003e24\u003c/b\u003e. (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeleis, A. Middle-Range and situatoin-specific theories in nursing research and practice. \u003cem\u003eTransitions Theory\u003c/em\u003e, 1\u0026ndash;11. (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMengcheng, W., Qiaowen, D. \u0026amp; Xiangyang, B. Bayesian method for latent variable modeling. \u003cem\u003eAdv. Psychol. Sci.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e (10), 1682\u0026ndash;1695 (2017).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMikkelsen, M. E. et al. Society of Critical Care Medicine's International Consensus Conference on Prediction and Identification of Long-Term Impairments After Critical Illness. \u003cem\u003eCrit Care Med, 48\u003c/em\u003e(11), 1670\u0026ndash;1679. (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMingyi, Q., City, W., Rongchun, Z. \u0026amp; Xin, Z. Revision of the Chinese version of the Eysenck Personality Questionnaire (EPQ-RSC). \u003cem\u003eActa Physiol. Sinica\u003c/em\u003e. \u003cb\u003e32\u003c/b\u003e (3), 317\u0026ndash;323 (2000).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMyhren, H., Ekeberg, \u0026Oslash;., T\u0026oslash;ien, K., Karlsson, S. \u0026amp; Stokland, O. Posttraumatic stress, anxiety and depression symptoms in patients during the first year post intensive care unit discharge. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e, 1\u0026ndash;10 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTobias, N. M. A., Ilan, S. \u0026amp; H.-R., H., K. J., \u0026amp; H., P. R Post-traumatic Stress Disorder. \u003cem\u003eMed. Clin. North Am.\u003c/em\u003e \u003cb\u003e107\u003c/b\u003e (1), 85\u0026ndash;99 (2023).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNavarra-Ventura, G. et al. Occurrence, co-occurrence and persistence of symptoms of depression and post-traumatic stress disorder in survivors of COVID-19 critical illness. \u003cem\u003eEur. J. Psychotraumatol\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e (1), 2363654 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOfoma, U. R. et al. Associations between hospital occupancy, intensive care unit transfer delay and hospital mortality. \u003cem\u003eJ. Crit. Care\u003c/em\u003e. \u003cb\u003e58\u003c/b\u003e, 48\u0026ndash;55 (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePing, N., Jingli, C. \u0026amp; Na, L. Sample size estimation for quantitative studies in nursing research. \u003cem\u003eChin. J. Nurs.\u003c/em\u003e \u003cb\u003e45\u003c/b\u003e (4), 378\u0026ndash;380 (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePlotnikoff, K. M. et al. Patient discharge from intensive care: an updated scoping review to identify tools and practices to inform high-quality care. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e25\u003c/b\u003e, 1\u0026ndash;13 (2021).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRattray, J. E., Johnston, M. \u0026amp; Wildsmith, J. Predictors of emotional outcomes of intensive care. \u003cem\u003eAnaesthesia\u003c/em\u003e \u003cb\u003e60\u003c/b\u003e (11), 1085\u0026ndash;1092 (2005).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRighy, C. et al. Prevalence of post-traumatic stress disorder symptoms in adult critical care survivors: a systematic review and meta-analysis. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e23\u003c/b\u003e (1), 213. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13054-019-2489-3\u003c/span\u003e\u003cspan address=\"10.1186/s13054-019-2489-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRonghua, L. Study on post-ICU syndrome of mechanical ventilation survivors and their family members in Guangzhou. (PhD). (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRonghua, L., Jingye, H., Xiaoqing, L., Ying, Z. \u0026amp; Yimin, L. Longitudinal study on mental function of mechanical ventilation survivors in ICU at different periods. \u003cem\u003eJ. Practical Med.\u003c/em\u003e, 36. (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSayed, S., Iacoviello, B. M. \u0026amp; Charney, D. S. Risk Factors for the Development of Psychopathology Following Trauma. \u003cem\u003eCurr. Psychiatry Rep.\u003c/em\u003e \u003cb\u003e17\u003c/b\u003e (10), 80 (2015).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShuo, W., Wanling, H., Rongfang, H. \u0026amp; Li, H. Meta-analysis of risk factors for post-traumatic stress disorder in ICU patients. \u003cem\u003eChin. J. Nurs.\u003c/em\u003e, 51. (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWade, D. M. et al. Investigating risk factors for psychological morbidity three months after intensive care: a prospective cohort study. \u003cem\u003eCrit. Care\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e (5), 1\u0026ndash;16 (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXiaojing, Z., Yunan, C. \u0026amp; Yue, T. Investigation on discharge readiness of patients with chronic diseases and its influencing factors and discussion on nursing strategies. \u003cem\u003eChin. J. Practical Nurs.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e (4), 296\u0026ndash;302 (2024).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eXin, X. \u0026amp; Qiang, S. Analysis of risk factors of post-traumatic stress disorder in critical emergency patients with mechanical ventilation off-line. \u003cem\u003eInt. J. Psychiatry\u003c/em\u003e, \u003cb\u003e47\u003c/b\u003e(6). (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYan, L. Analysis of risk factors for post-traumatic stress disorder after mechanical ventilation in emergency patients with severe illness. \u003cem\u003eJ. Math. Med. Pharmacol.\u003c/em\u003e \u003cb\u003e35\u003c/b\u003e (01), 150\u0026ndash;153 (2022).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYanin, X. A preliminary study on the reliability and validity of the simple coping style Scale. \u003cem\u003eJ. Clin. Psychol.\u003c/em\u003e (2), 114\u0026ndash;115. (1998).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eYanjie, S., Qiongqiong, H. \u0026amp; Yanhui, C. Study on occurrence and influencing factors of post-traumatic stress disorder in ICU patients. \u003cem\u003eChina Med. Rev.\u003c/em\u003e \u003cb\u003e8\u003c/b\u003e(16). (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZigmond, A. S. \u0026amp; Snaith, R. P. The hospital anxiety and depression scale. \u003cem\u003eActa Psychiatry. Scand.\u003c/em\u003e \u003cb\u003e67\u003c/b\u003e (6), 361\u0026ndash;370 (1983).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZimet, G. D., Dahlem, N. W., Zimet, S. G. \u0026amp; Farley, G. K. The multidimensional scale of perceived social support. \u003cem\u003eJ. Pers. Assess.\u003c/em\u003e \u003cb\u003e52\u003c/b\u003e (1), 30\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1207/s15327752jpa5201-2\u003c/span\u003e\u003cspan address=\"10.1207/s15327752jpa5201-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1988).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Potential category model fitting information for PTSD development trajectory of tracheal intubation patients in ICU (n=204)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 51px;\"\u003e\n \u003cp\u003eModel\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 76px;\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 81px;\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eaBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e值\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 69px;\"\u003e\n \u003cp\u003eEntropy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 128px;\"\u003e\n \u003cp\u003eClass probability（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003eLMRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003eBLRT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e6010.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6043.435\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e6011.752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e6041.572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e6081.389\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e6043.370\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.963\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e98.3/0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5906.231\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5956.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e5908.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.0418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.0487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.894\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e16.2/30.4/\u0026nbsp;53.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5814.745\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5874.472\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5817.442\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0297\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0353\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.907\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.9/\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e27.2/\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e51.6/\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e14.3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e5787.082\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e5856.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e5790.228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e0.2840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.2968\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e0.910\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e26.0/2.9/14.2/7.8/\u0026nbsp;49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: AIC is Akike information criterion; BIC is the Bayesian information criterion; aBIC is the Bayesian information criterion for sample correction. The LMRT is the Roi-Mondel-Ruben-corrected likelihood ratio test; BLRT is a likelihood ratio test based on Bootstrap. \u0026quot;-\u0026quot; indicates no meaning.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Results of univariate analysis of general information of patients with PTSD development trajectory in each group (n=204)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"729\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eitem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003ehigh-risk deterioration group (n=14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003ehigh-risk improvement group (n=57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003emedium-risk maintenance group (n=27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003elow-risk improvement group (n=106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eTest statistic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel of education\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e16.743\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e）\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003ePrimary school degree and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e4（28.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e27（47.4%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e19（70.4%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e41（38.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eJunior high school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e4（28.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e23（40.4%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e5（18.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e42（39.6%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eHigh school and technical secondary school degree\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e6（42.8%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e5（8.8%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e3（11.1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e17（16%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eCollege degree or above\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e0（0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e2（3.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e0（0%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e6（5.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical payment methods\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e17.936\u003csup\u003e1\u003c/sup\u003e\u003csup\u003e）\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eUrban residents\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e6（42.9%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e46（80.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e17（63%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e79（74.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eUrban workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2（14.3%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e6（10.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e3（11.1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e18（17%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eAll expenses paid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e5（35.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e4（7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e6（22.2%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e8（7.5%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003cp\u003e(Business, industrial injury Medical)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e1（7.1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e1（1.8%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e1（3.7%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e1（1%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal hospitalization days(Day,\u003c/strong\u003e\u003cstrong\u003e\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img175647827686.png\" alt=\"image\"\u003e)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e30.21\u0026plusmn;14.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e27.28\u0026plusmn;12.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e28.82\u0026plusmn;17.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e21.32\u0026plusmn;10.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e14.767\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e）\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration from extubation to ICU discharge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eh\u003c/strong\u003e\u003cstrong\u003e，\u003c/strong\u003e\u003cstrong\u003e\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1756478277.png\" alt=\"image\"\u003e\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e155.81\u0026plusmn;124.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e95.17\u0026plusmn;84.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e71.57\u0026plusmn;52.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e85.07\u0026plusmn;64.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e17.376\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e）\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospitalization fee\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eYuan\u003c/strong\u003e\u003cstrong\u003e，\u003c/strong\u003e\u003cstrong\u003e\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img1756478276.png\" alt=\"image\"\u003e\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e119466.02\u0026plusmn;\u003c/p\u003e\n \u003cp\u003e71849.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 98px;\"\u003e\n \u003cp\u003e93234.50\u0026plusmn;\u003c/p\u003e\n \u003cp\u003e43149.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101px;\"\u003e\n \u003cp\u003e103766.81\u0026plusmn;\u003c/p\u003e\n \u003cp\u003e65691.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e77509.17\u0026plusmn;\u003c/p\u003e\n \u003cp\u003e61603.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e8.565\u003csup\u003e2\u003c/sup\u003e\u003csup\u003e）\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Only statistically significant data are presented in Table 6:1)Fisher\u0026apos;s exact test; 2)H value\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Results of univariate analysis of social psychology in patients with PTSD developmental trajectories in various groups (n=204)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"697\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 209px;\"\u003e\n \u003cp\u003eitem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003ehigh-risk deterioration group（n=14）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003ehigh-risk improvement group (n=57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003emedium-risk maintenance group (n=27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003elow-risk improvement group (n=106)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 125px;\"\u003e\n \u003cp\u003eERQ-RSC score（points，\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img175647827798.png\" alt=\"image\"\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eExtroversion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e8.57\u0026plusmn;3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8.60\u0026plusmn;3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e8.33\u0026plusmn;3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e9.20\u0026plusmn;2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e3.156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.368\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNeurotic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e5.57\u0026plusmn;2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e5.05\u0026plusmn;3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e5.52\u0026plusmn;2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e3.49\u0026plusmn;2.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e19.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSCSQ score\u003c/p\u003e\n \u003cp\u003e（points，\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img175647827763.png\" alt=\"image\"\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003ePositive response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e20.64\u0026plusmn;5.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e19.46\u0026plusmn;5.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e20.00\u0026plusmn;5.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e22.15\u0026plusmn;4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e10.899\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eNegative response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e11.86\u0026plusmn;3.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e11.12\u0026plusmn;3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e11.41\u0026plusmn;3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e10.51\u0026plusmn;3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e2.900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 125px;\"\u003e\n \u003cp\u003ePSSS score\u003c/p\u003e\n \u003cp\u003e（points，\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img175647827755.png\" alt=\"image\"\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eFamily support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e24.07\u0026plusmn;3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e23.51\u0026plusmn;3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e23.41\u0026plusmn;3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e24.42\u0026plusmn;2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e4.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.257\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eFriend support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e13.43\u0026plusmn;5.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e13.60\u0026plusmn;6.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e13.81\u0026plusmn;6.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e15.26\u0026plusmn;6.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e3.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eOther support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e22.07\u0026plusmn;3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e21.88\u0026plusmn;3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e28.98\u0026plusmn;3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e22.15\u0026plusmn;3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e2.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.472\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHADS score\u003c/p\u003e\n \u003cp\u003e（points，\u003cimg width=\"34\" height=\"22\" src=\"https://myfiles.space/user_files/127393_c7e80a1c9bb65875/127393_custom_files/img175647827768.png\" alt=\"image\"\u003e）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eHADS-A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e11.00\u0026plusmn;4.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e11.00\u0026plusmn;3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e12.19\u0026plusmn;3.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e6.96\u0026plusmn;3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e61.888\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eHADS-D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e8.57\u0026plusmn;4.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.51\u0026plusmn;3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e10.07\u0026plusmn;4.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 89px;\"\u003e\n \u003cp\u003e6.15\u0026plusmn;3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e34.957\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4 Variable assignment methods\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"717\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 580px;\"\u003e\n \u003cp\u003eassignment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eTrajectory class\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003ehigh-risk deterioration group=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ehigh-risk improvement group\u0026nbsp;=2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003emedium-risk maintenance group\u0026nbsp;=3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003elow-risk improvement group=4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003ePrimary school degree and below=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eJunior high school degree=2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eHigh school and technical secondary school degree=3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eCollege degree or above\u0026nbsp;=4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eMedical payment methods\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003eUrban residents=1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eUrban workers=2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eAll expenses paid=3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 153px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003cp\u003e(Business, industrial injury Medical)=4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5 Results of multivariate logistic regression analysis of patients with PTSD developmental trajectory in various groups (n=204)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"550\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026beta;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 64px;\"\u003e\n \u003cp\u003eStandard error\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cem\u003eWald X\u003csup\u003e2\u003c/sup\u003e\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 123px;\"\u003e\n \u003cp\u003e95%\u003cem\u003eCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eLower limit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eUpper limit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC1 vs C2\u003csup\u003e1)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eHADS-A score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e11.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.772\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC1 vs C3\u003csup\u003e1)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eTotal hospitalization days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e4.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.085\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eHADS-A score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e13.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.351\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.583\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC1 vs C4\u003csup\u003e1)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eHADS-A score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e5.181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.374\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.807\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003cp\u003e（Primary school degree and below）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e17.383\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e353.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eLevel of education\u003c/p\u003e\n \u003cp\u003e（Junior high school degree）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e17.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e371.353\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC2 vs C4\u003csup\u003e2)\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eDuration from extubation to ICU discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e7.832\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003e1.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e1.025\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: C1 refers to low-risk improvement; C2 was medium risk maintenance group; C3 was the high-risk improvement group; C4 was defined as high risk deterioration group; 1) C4 was used as the reference group; 2) C2 was used as the reference group; \u0026quot;-\u0026quot; represents a higher value.\u003c/p\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Respiration, Artificial; PTSD; Trajectory, Latent class growth model, Influencing factors, Nursing","lastPublishedDoi":"10.21203/rs.3.rs-7220761/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7220761/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground：\u003c/strong\u003eICU patients exhibit a high incidence of post-traumatic stress disorder (PTSD). During treatment, procedural pain (e.g., suctioning, ventilator asynchrony) and communication barriers can trigger significant stress responses, exacerbating feelings of fear and helplessness, ultimately contributing to PTSD post-extubation. Current research predominantly relies on cross-sectional studies, failing to capture the dynamic progression of PTSD. As recovery evolves, patients' psychological and physical states continuously change, necessitating adaptive intervention strategies. There is an urgent need for longitudinal studies to elucidate PTSD development trajectories, clinical characteristics, and risk factors. However, research on the psychological recovery pathways of post-ICU patients remains scarce.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e This study aimed to identify the heterogeneous developmental trajectories of PTSD in ICU patients receiving mechanical ventilation within 6 months post-extubation and to analyze influencing factors across trajectory subgroups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFrom July 2023 to June 2024, a purposive sampling method was employed to select mechanically ventilated patients admitted to the ICU of a tertiary hospital in Zunyi, China. At 7 days post-extubation (T0), baseline assessments were conducted using the following instruments: a general information questionnaire, the Impact of Event Scale-Revised (IES-R), the Hospital Anxiety and Depression Scale (HADS), the Simplified Coping Style Questionnaire (SCSQ), the short-form Chinese version of the Eysenck Personality Questionnaire-Revised (EPQ-RSC), and the Perceived Social Support Scale (PSSS). Follow-up assessments were performed at 1 month (T1), 3 months (T2), and 6 months (T3) post-extubation using the IES-R. Data were analyzed using Mplus 8.3 and SPSS 29.0.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDesign:\u003c/strong\u003eProspective longitudinal study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among 204 completed cases (89.1% retention), four trajectories emerged: high-risk deterioration (6.9%), high-risk improvement (27.2%), medium-risk maintenance (14.3%), and low-risk improvement (51.6%). Lower education, prolonged hospitalization, delayed ICU discharge post-extubation, and baseline anxiety independently predicted adverse trajectories (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e PTSD trajectories in mechanically ventilated ICU patients exhibit significant heterogeneity. Clinicians should prioritize screening high-risk subgroups (e.g., less-educated patients, extended hospitalization) for early PTSD intervention to enhance recovery outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Implications:\u003c/strong\u003e Targeted PTSD monitoring and psychological support are recommended for at-risk populations to mitigate long-term mental health burdens.\u003c/p\u003e","manuscriptTitle":"To analyze the developmental trajectory and influencing factors of PTSD symptoms in ICU patients with mechanical ventilation based on latent category growth: A longitudinal examination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-01 10:09:36","doi":"10.21203/rs.3.rs-7220761/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-10T06:35:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-09T06:59:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41724100327338232887202969489469633092","date":"2025-09-08T20:37:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60947720163589054457617757709903851504","date":"2025-09-04T09:19:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"191285872702127989474451075341089799373","date":"2025-09-04T05:29:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T09:43:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"222609199594904609313864252982115477381","date":"2025-08-27T13:10:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-21T14:40:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-21T14:29:28+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-12T16:01:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-05T06:21:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-05T06:13:38+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"85cf8ff6-764e-4c03-baba-1968388d15b2","owner":[],"postedDate":"September 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":53835883,"name":"Health sciences/Diseases"},{"id":53835884,"name":"Health sciences/Health care"},{"id":53835885,"name":"Health sciences/Medical research"},{"id":53835886,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2025-11-10T16:06:13+00:00","versionOfRecord":{"articleIdentity":"rs-7220761","link":"https://doi.org/10.1038/s41598-025-22646-3","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-06 15:56:53","publishedOnDateReadable":"November 6th, 2025"},"versionCreatedAt":"2025-09-01 10:09:36","video":"","vorDoi":"10.1038/s41598-025-22646-3","vorDoiUrl":"https://doi.org/10.1038/s41598-025-22646-3","workflowStages":[]},"version":"v1","identity":"rs-7220761","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7220761","identity":"rs-7220761","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}