Predictors of disability trajectories in individuals with spinal cord injury in mainland China

doi:10.21203/rs.3.rs-3899271/v1

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Predictors of disability trajectories in individuals with spinal cord injury in mainland China

https://doi.org/10.21203/rs.3.rs-3899271/v1

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published 08 Oct, 2024

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Study Design: Observational cohort study.

Objectives: To identify classes of disability trajectories from spinal-cord injury to 6 months after discharge and to investigate whether psychosocial resources and disease factors can predict disability trajectory.

Setting: Spinal surgery in three Class III hospitals. Hospitals in China are divided into three classes (Class I, II and III). Class III hospitals are the highest-level hospitals in China.

Methods: All the participants were submitted to WHO Disability Assessment Schedule (WHO-DAS 2.0) at three times；and personal data anamnesis, hope, PTSD, social support

were recorded at first time. All the data collected by the master's students who participated in this study.

Results: Two disability trajectories were identified using the latent class growth model: the continuous high disability group (N=196, 93.3%) and the low starting point stabilization group (N=14, 6.7%). Participants with higher American Spinal Injury Association (ASIA) (β=1.26; 95% confidence interval [CI] 1.00-12.21) and more depression (β=0.249; 95% CI 1.05-1.56) in the stable condition after SCI surgery were more likely to be classified as having higher disability than those with a lower disability

trajectory. Occupation, annual family income, hope, social support, and Post-traumatic Stress Disorder (PTSD) cannot predict individuals belonging to trajectory classes.

Conclusion: These findings emphasize the importance of ASIA and depression in the early recovery stage after SCI and support the opinion that strengthening psychological nursing and rehabilitation management at an early stage after SCI will benefit individuals with a lower disability trajectory.

Health sciences/Risk factors

Biological sciences/Neuroscience/Diseases of the nervous system/Dystonia

Health sciences/Medical research/Outcomes research

In recent years, with the rapid development of the Chinese economy and the rise of the transportation and construction industries, the number of patients with spinal-cord injury (SCI) caused by traffic accidents and falls from high places has exceeded 1 million, and the number has increased by 120,000 per year.¹ Disabilities are a general term including injury, activity and limited participation.² Impairment refers to physical function and structural problems, while limitations in activity and participation are defined as difficulties in cognition, physical mobility, self-care, getting along with others, relaxation, and community activities.^3,4 Therefore, disability is a social model with multiple dimensions, reflecting the result of interactions between individuals and the environment, and this is ultimately manifested as limited activity and participation, thus negatively predicting quality of life. Most patients with SCI have difficulty adjusting their disability over the short term, resulting in higher levels of anxiety (27%) and depression (22%) compared to the general population anxiety (3%) and depression (7%), ⁵ and this seriously affects the quality of life of patients. Disability is not only the result of the interaction between humans and the environment, but also a dynamic evolutionary process and this view has become the consensus view for researchers in the field of disability worldwide. ⁶ Therefore, Identifying early predicators of poor disability outcomes in patients with SCI will guide practitioners in treatment, offering specifics points of intervention.

Current research on disabilities in patients with SCI tends to focus on participation limitations and cognitive impairments, which is narrow view of disability. Talamonti ⁷ investigated disability at 6, 18 and 30 months after SCI and found that 76% of the patients with SCI had secondary health conditions (such as pain, constipation, and urinary tract infection) related to the disability level within 6 months that gradually worsened over time. Karcz ⁸ conducted a five-year longitudinal follow-up in Switzerland and found that the employment rate can be divided into four different tracks according to its characteristics: higher weekly workload (15%), same-weekly workload (57%), lower weekly workload (16%) and dropout track (12%). Gray matter and white matter of the brain gradually atrophy with time after SCI, and gray matter atrophy accelerates atrophy 1.5 years after injury,⁹ Therefore, it is speculated that the cognitive function of patients with SCI will gradually decline with time.¹⁰ Furthermore, Tulsky ¹¹ conducted a longitudinal study on the recovery of body function in 479 patients with SCI in the United States, and found that there were great differences in activity limitation between the acute and rehabilitation stages of SCI due to individual differences and environmental factors. Overall, previous studies have shown that patients with SCI present different developmental trajectories of disability; however the present study authors have not seen the trajectory and potential category of an individual feature in the first 6 months after SCI, while taking into account the heterogeneity of the population. There is insufficient evidence for disability management in the early stages of SCI to change the disability trajectory.

Therefore, this study aimed to (a) investigate the degree of disability in acute phase patients with SCI, 3 months after discharge, and 6 months after discharge, using the WHO Disability Assessment Schedule (WHO-DAS 2.0)¹² to determine the category of disability development trajectory of patients with SCI, and (b) analyze whether disease factors and psychosocial factors (depression, Post-traumatic Stress Disorder [PTSD], hope level, and social support) can predict the disability trajectory attributes. It is considered that participants with positive psychosocial factors will be more likely fit better trajectory of disability (i.e, less disability).

Participants

This multicenter longitudinal cohort study was conducted between January 2021 and February 2022. The subjects (N=211) were from three Class III hospitals in Anhui Province, China. The inclusion criteria were clinical diagnosis of SCI, age ≥ 18 years, clear consciousness, and the ability to communicate in Chinese without barriers. Exclusion criteria were the following: premorbid clinical diagnosis of severe psychiatric disorder¹³ , neurocognitive disorders ¹³ (such as Alzheimer's disease and dementia), stroke¹⁴, spinal malignant tumor , and other diseases that may have caused limited patient activity at or before the evaluation.

Measures

Outcome for disability trajectories: degree of disability

Degree of disability was assessed with WHO-DAS 2.0 that contains 36 items across six domains: Cognition, Mobility, Self-care, Getting along with people, Life activities and Participation. Items asked responders to evaluate their degree of difficulty on a 5-point Likert scale (0=no difficulty, 4=extreme/cannot), with total score ranging from 0 (No disability) to 144 (maximum disability). Higher scores indicate a higher degree of disability.¹⁵ The scale has been widely used in various populations,¹⁶ including patients with SCI,¹⁷ and has good reliability and validity. The degree of disability was evaluated at three time points: T1-T3 (T1= stable condition after SCI; T2 =3 months after SCI; and T3= 6 months after SCI).

Predictors for disability trajectories: The role of psychological resources

The Hamilton Depression Rating Scale (HAMD) has been used to assess depression in patients with SCI and has good reliability and validity.^18,19 It has 17 items in total, and most of them adopt a 5-level scoring method of 0-4, where ＞ 24 is severe depression; 18-24 is moderate depression; 7-17 is mild and < 7 is normal. The Post-Traumatic Stress Disorder Checklist-Civilian (PCL-C) was used to assess symptoms related to post-traumatic stress disorder.²⁰ The reliability and validity of the PCL-C were good in patients with SCI.²¹ It includes three dimensions: intrusion, avoidance and alertness, as expressed by a five-point Likert scale (1=not at all, 5=extreme). The Herth Hope Index (HHI) has been used to evaluate the hope level of patients²², and its validity has been validated in a population with SCI.²³ In this 12-item measure, Respondents are asked to rate their level of agreement using a 1 (Strongly Disagree) to 4 (Strongly Agree) scale. items 3 and 6 were reverse scored. The total score for hope was the sum of all items. The higher score for hope, which means the greater hope. Social Support Rating Scale (SSRS) has been used to assess the level of social support with SCI ²⁴, and has good reliability and validity in patients with SCI. ²⁵It contains 10 items across three domains: objective support, subjective support and utilization of social support. The higher the score, the better the family functioning and social support. The internal consistency and reliability of all questionnaires was good (WHO-DAS 2.0 α=0.995; depression α=0.978; PTSD α=0.968; HHI α=0.946; Social support α=0.859).

Self-designed general data were used to collect the demographic and disease characteristics of the patients, including age, sex, education level, occupation, residence, injury segment (cervical/thoracic/lumbosacral), reason for injury, injury degree, and number of basic diseases.

All data were collected by the authors, who received uniform professional training prior to data collection. General data, disease data, and HAMD, PCL-C, HHI, SSRS, WHO-DAS 2.0（T1）questionnaires were collected face-to-face. When collecting the questionnaires of the WHO-DAS 2.0 (T2, T3), data were collected face-to-face for hospitalized patients, whilst data were collected through telephone follow-ups of patients who were not hospitalized.

Statistical analysis

Statistical analysis was performed using SPSS (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp) and Mplus (Muthén, L.K. and Muthén, B.O. (1998-2015). Mplus User's Guide. Version 8.3. Los Angeles, CA: Muthén & Muthén). The measurement data conforming to a normal distribution are described as mean and standard deviation, and the measurement data not conforming to a normal distribution are described as median and interquartile spacing. Counting data are described using frequencies and percentages. Mplus 8.3 software was used to explore the developmental trajectory of disability in patients with SCI. First, process the missing data and outliers and test the normality of the distribution of quantitative data. Variables with statistical differences in the univariate analysis (P<0.1，statistically significant to avoid omission) were included in the logistic regression model to analyze the main influencing factors of the development trajectories of different types of disability. Using a bilateral test, a difference was considered statistically significant with P ＜ 0.05.

Potential category analysis is a model-based method to deal with group heterogeneity, which can both describe the growth trend and consider group heterogeneity.²⁶ Latent Category Growth Model (LCGM) can predict factors of disability in patients with SCI. The potential predictors of disability trajectories were examined in two steps. First, based on the post-validation probability, each participant was assigned at trajectory of disability. Secondary, in SPSS25.0, logistic regression was used to determine whether psychosocial resources can predict different disability trajectories of individuals.

Participant characteristics

As shown in Table 1, the majority of patients with SCI were male (82.4%), and the most common causes of SCI were traffic accidents (34.3%), falls (32.4%), and falls from a height (16.7%). The most common SCI type was at the cervical level (78.1%). The degree of SCI was grade C (33.3%) and D (31%) in more than of half cases. More than half (66.7%) of the households have an annual income of less than RMB 50,000.

Table 1

Basic characteristics of the research objects
Variables	Classify	210 Patients Requiring Follow-up		176 Patients Requiring Follow-up		34 Lost Patients
		frequency	ratio	frequency	ratio	frequency	ratio
Age	<20	3	1.4	3	1.7	0	0
	20–30	5	2.4	5	2.8	0	0
	31–40	14	6.7	13	7.4	1	2.9
	41–50	29	13.8	25	14.2	4	11.8
	51–60	77	36.7	63	35.8	14	41.2
	61–70	51	24.3	40	22.7	11	32.4
	>70	31	14.8	27	15.3	4	11.8
Gender	Male	173	82.4	141	80.1	32	94.1
	Female	37	17.6	35	19.9	2	5.9
Occupation	Farmer	110	52.4	91	51.7	19	55.9
	Worker	59	28.1	49	27.8	10	29.4
	Student	3	1.4	3	1.7	0	0
	Civil servant	1	0.5	0	0	1	2.9
	Self-employed	9	4.3	8	4.5	1	2.9
	Staff	8	3.8	8	4.5	0	0
	Retired	8	3.8	7	4	1	2.9
	Others	12	5.7	10	5.7	2	5.9
Education	Primary	113	53.8	95	54	18	52.9
Level	Junior middle	60	28.6	50	28.4	10	29.4
	Senior middle	28	13.3	24	13.6	4	11.8
	College or above	9	4.3	7	4	2	5.9
Chronic	0 type	118	56.2	102	58	16	47.1
Disease	1 type	45	21.4	38	21.6	7	20.6
Type	2 types	22	10.5	18	10.2	4	11.8
	≥ 3 types	25	11.9	18	10.2	7	20.6
Damaged Part	Neck	164	78.1	134	76.1	30	88.2
	Chest	27	12.9	23	13.1	4	11.8
	Lumbosacral	19	9	19	10.8	0	0
ASIA grade	A	28	13.3	21	11.9	7	20.6
	B	35	16.7	24	13.6	11	32.4
	C	70	33.3	59	33.5	11	32.4
	D	65	31	61	34.7	4	11.8
	E	12	5.7	11	6.3	1	2.9
Injury	Traffic accident	72	34.3	59	33.5	13	38.2
Reason	Fall over	68	32.4	58	33	10	29.4
	Falling from height	35	16.7	33	18.8	2	5.9
	Heavy objects injuries	12	5.7	11	6.3	1	2.9
	Violent injury	2	1	2	1.1	0	0
	Others	21	10	13	7.4	8	23.5
Annual	<50000 yuan	140	66.7	114	64.8	26	76.5
Household	50000–100000 yuan	60	28.6	54	30.7	6	17.6
Income	>100000 yuan	10	4.8	8	4.5	2	5.9

Category of disability development track

When using the LCGM in Mplus 8.3 for data analysis, the full-information maximum likelihood method (FIML) was used to process the missing data. The fitting indices of the LCGM for Categories 1–5 are shown in Table 2.

As shown in Table 2, the two disability development trajectories based on the best model (Category 2) fitting index were class1: high starting point continuous decline group (N = 196, 93.3%) and class2: low starting point stable group (N = 14, 6.7%). The posterior classification results showed that all trajectories had good accuracy. The developmental tracks of individual disabilities are shown in Fig. 1.

Table 2

Fitting index of LCGM model with 1 ~ 5 classes
classes	k	AIC	BIC	aBIC	Entropy	LMR	BLRT	Sample proportion in each category
								1	2	3	4	5
1	5	5344.03	5360.76	5344.92				1
2	8	5331.00	5357.78	5332.43	0.84	0.016	0.001	93.3	6.70
3	11	5331.40	5368.22	5333.36	0.75	0.348	0.150	29.52	65.71	4.76
4	14	5304.72	5351.57	5307.22	0.73	0.259	0.667	3.81	45.24	10.00	40.95
5	17	5310.72	5367.62	5313.75	0.63	0.507	1.000	11.43	42.38	3.81	0.00	42.38
Note: k:Free parameter; AIC:Akaike Information Criterion; BIC:Bayesian Information Criterion; BLRT:Bootstrapped Likelihood Ratio Test; LMR:Lo-Mendell-Rubin Likelihood Ratio Test

Univariate analysis

As shown in Table 3, according to the two trajectories identified by the LCGM, general data, disease data, depression, PTSD, hope, and social support were included in the univariate analysis. The results showed that there were significant differences in occupation, depression, PTSD, hope and social support, but no significant differences in age, sex, education leve, cause of injury and family income.

Table 3
Characteristics	Continuous high disability group	Low starting point stabilization group	statistics	P
Age(Group)			8.21*	0.16*
<20	2(1%)	1(7.1%)
20–30	5(2.6%)	0(0%)
31–40	14(7.1%)	0(0%)
41–50	25(12.8%)	4(28.6%)
51–60	71(36.2%)	6(42.9%)
61–70	48(24.5%)	3(21.4%)
>70	31(15.8%)	0(0%)
Gender			1.13	0.47
Male	160(81.6%)	13(92.9%)
Female	36(18.4%)	1(7.1%)
Occupation			14.80*	0.02*
Farmer	102(52.0%)	8(57.1%)
Worker	58(29.6%)	1(7.1%)
Student	2(1.0%)	1(7.1%)
Self-employed	7(3.6%)	3(21.4%)
Staff	8(4.1%)	0(0.0%)
Retired	7(3.6%)	1(7.1%)
Others	12(6.1%)	0(0.0%)
Education level			3.10*	0.32*
primary school	108(55.1%)	5(35.7%)
Junior middle	54(27.6%)	6(42.9%)
Senior middle	25(12.8%)	3(21.4%)
College or above	9(4.6%)	0(0%)
ASIA grade			26.28*	<0.05
A	28(14.3%)	0(0.0%)
B	35(17.9%)	0(0.0%)
C	70(35.7%)	0(0.0%)
D	51(26.0%)	14(100%)
E	12(6.1%)	0(0.0%)
Cause of injury			5.14*	0.36*
Traffic accident	68(34.7%)	4(28.6%)
Fall over	64(32.7%)	4(28.6%)
Falling from height	33(16.8%)	2(14.3%)
Heavy objects injuries	12(6.1%)	0(0.0%)
Violent injury	2(1%)	0(0.0%)
Others	17(8.7%)	4(28.6%)
Annual household income			5.34*	0.06*
<50000 yuan	134(68.4%)	6(42.9%)
50000–100000 yuan	54(27.6%)	6(42.9%)
>100000 yuan	8(4.1%)	2(14.3%)
Depression	11.97 ± 6.93	3.64 ± 2.82	19.91	<0.05
PTSD	29.91 ± 14.83	17.71 ± 1.73	9.43	<0.05
Hope	35.04 ± 5.67	35.04 ± 5.67	14.73	<0.05
Social support	38.30 ± 6.57	42.21 ± 7.34	4.57	<0.05
Note: * refers to Fisher exact probability method

Predictors of disability trajectories

As shown in Table 4, variables with P<0.1 in univariate analysis were included in multivariate logistic regression analysis. The ASIA grade and depression were strong predictors of disability. Patients with high ASIA grade (OR = 3.51; 95%CI: 1.00-12.21; P = 0.04) and depression (OR = 1.28; 95%CI: 1.05–1.56; P = 0.013) were more likely to develop a high starting point continuous decline group trajectory than a low starting point stable group trajectory.

Table 4

Low starting point stabilization group^a
Predictor Variables	β	SE	Wald	OR	95%CI	P
Occupation	-0.07	0.17	0.18	0.93	0.68–1.29	0.67
Annual household income	0.86	0.56	2.39	2.36	0.79-7.00	0.12
ASIA grade	1.26	0.64	3.89	3.51	1.00-12.21	0.04
Hope	-0.03	0.09	0.09	0.97	0.82–1.16	0.76
Depression	0.249	0.11	6.13	1.28	1.05–1.56	0.013
Social support	0.16	0.05	0.08	1.02	0.91–1.13	0.77
PTSD	-0.09	0.12	0.58	0.91	0.72–1.16	0.45
Note: a: Take the low starting point stable group as the reference group

This study aimed to explore the disability changes in patients with SCI and was conducted by enrolling patients from the spinal surgery wards of three Class III hospitals in Hefei, Anhui Province, China. Two variant trajectories were identified with significant.

Two variant trajectories were identified with significant disability differences at 6 months after SCI, with 93.3% and 6.7% of the participants belonging to the high, and low trajectories, respectively. These findings indicates that disability is the main factor in the early rehabilitation of most individuals after SCI. Some factors closely related to disease (e.g, ASIA grade), and psychosocial factors such as depression, are associated with the level and change rate of the disability track.

Previous studies have compared changes in disability over time, involving only one area of disability, such as self-care ability,²⁷ cognition,²⁸ or social participation.²⁹ This study incorporated some fields into a composite concept of disability that really reflects the ability of patients to take care of themselves, get along with others, entertain and participate socially.^3,4 It was found that compared to the higher trajectories, which included more than 90% of the participants, individuals assigned to lower trajectories have occupational differences. Research by Schwegler ³⁰ showed that it is difficult for patients with SCI to continue their original work, especially physical activity. In contrast, in a Swiss cohort it was found that cognitive-oriented work can assist with returning to work.

The disability trajectories found in our study were similar to those in other populations and revealed some interesting features. The relationship between occupation and disability remains inconclusive. In this present study, ASIA classification grade, annual family income, hope, depression, social support, and PTSD were included in the regression model, and the relationship between the two was no longer significant. This may be because,in this present study, only the occupations of patients before injury were collected, while an Australian study showed that individuals returning to work after SCI not only need to have knowledge, skills, and interests that match their jobs, but also need the government to provide corresponding support, such as skill training.³¹ However, the patient cohort in this present study was from Anhui, China. The participants were mainly farmers and workers engaged in heavy manual labor (80.5%). On the one hand, it is difficult to fully recover limb function to the level before the injury in a short time (6 months). Also, there is no professional skill training and relevant policy support for SCI at present in China. In terms of annual income, low-income patients are more likely to be assigned to the track of continuous high disability, and this is consistent with a result of the cohort study on income level from the United States and the United Kingdom.³² The disability rate of low-income individuals (48%) is significantly higher than high-income individuals (17%), and this may be because income level affects the disease affordability of individuals.

Consistent with this study, a positive correlation was found in the higher ASIA with SCI and disability which has been previously reported.³³ A cross-sectional study from Vietnam, shows that the Activities of Daily Living (ADL) scored higher with a ASIA-D compared to someone of ASIA-B.³⁴ This may be because a more severe injury can cause a higher disability level. Therefore, a better understanding of the degree of injury plays an important role in reducing the degree of disability in patients. ASIA grade functional independence, motor function, and getting along with others have been described in previous studies with SCI. Higher grade ASIA patients with SCI may experience more spasms,³⁵ and secondary health conditions such as neurogenic rectum, neurogenic bladder. Also, neuropathic pain influences their physical independence, activity limitation and participation limitation compared to the patients with incomplete SCI.³⁶ Therefore, there is a need to provide continuous and better rehabilitation services for incomplete SCI, including mobile assistive devices such as exoskeleton robots, and continuous home care services to reduce the speed of developing disability.

Positive psychosocial determinants such as hope and social support are relevant to disability of individuals. In a study in pain trajectories after SCI, Braunwalder found that individuals with more optimism, higher levels of social support, and less anxiety were more likely to report pain relief 1 month after the onset of SCI.³⁷ However, given that psychosocial resources and early disability trajectories after SCI have not been researched before, previous research on SCI is limited. Previous studies on disability showed that high levels of hope,³⁸ and social support³⁹ can reduce disability, and this can be explained by the fact that individuals with high hope levels and social support tend to adopt a positive attitude to adapt to changes in their physical condition and participate in social activities to alleviate levels of disability.⁴⁰ In this present study, positive psychosocial factors seem to have no connection with better disability trajectories in the final logistic regression model. The differences between this present study and previous studies could be attributed to social and cultural differences: clinical workers, patients, and family members tend to pay more attention to the treatment effect on physical function, while ignoring the impact of positive psychological factors on disability during the period of stable condition after SCI to 6 months after discharge in China.

Depression and PTSD, being negative psychosocial determinants, are persistently strong risk factors linked to disability after SCI. Data from this present study also reveal that a significant association between high depression and worse disability trajectories is supported by a meta-analysis of longitudinal studies looking at disability and post-stroke depression.⁴¹ Bonanno revealed that the depression trajectory after SCI was chronically elevated and fluctuated greatly within 1 year after SCI, and this further verifies the results of this present study in connection with between depression and the disability trajectory.⁴² As for PTSD, the association with disability trajectories lost significance in the final logistic regression model, most likely because of the high correlation between PTSD and the ability to make new social connections.

Clinical implications

This study showed that disability trajectories have different developmental trends over time. ASIA grade and depression level have a strong predictive function for disability 6 months after discharge. In the early screening of patients with SCI, psychosocial (depression) and disease factors (ASIA grade) might provide significant information about these patients experiencing trouble in daily life in the long term. It may give the entire rehabilitation team a target for intervention by identifying individuals with long to high disability trajectories. This early intervention may positively affect adjustment outcomes, such as depression severity.

Limitations of study

First, although a large number of participants were included in the LCGM, some data were still lost during follow-up. Although FIML was used to process missing data, there is still a possibility of bias. Second, participants were primarily farmers and workers (80.4%). They may be poorer than the general population, so findings of this present study may apply only to developing countries with relatively poor economies. As the participants change, the link between disability trajectories and their underlying factors may also change. Third, this study only explored disability trajectories from the stable stage after SCI surgery to six months after discharge. However, the length of follow-up may have affected the results. There are some measures to control for the loss to follow-up bias: First, select a relatively stable population to facilitate follow-up; Second, this study will continue to investigate the outcomes of individuals who were lost to follow-up in the future and compare them with those who completed follow-up to speculate on the impact of loss to follow-up. A multicenter, large-sample, long-term follow-up study should be conducted in the future to verify the results of this study.

This study emphasized the disease characteristics of SCI and their important role in the early disability track after SCI providing a meaningful basis for disability intervention after SCI. Specifically, higher ASIA grade and depression level have high disability trajectories with a stable stage after SCI and 6 months after discharge that can provide specific intervention targets for patients in future disability management intervention research during the stable conditions after SCI.

Data availability statement

Lun-lan Li:Conceptualization, Methodology, Validation, Writing-Review, Supervision,and funding acquisition.

Hui Huang:Methodology, and writing - original draft.

Pei-Pei Ding: Formal analysis, and investigation.

Lin-Sheng Feng: Formal analysis, and investigation.

Xiao-Xiao Xia: Formal analysis,Software,and Validation.

Dai Qing:Conceptualization, Methodology,Modify, Supervision.

Ethics statement

This study was approved by the Ethics Committee of The Second Hospital of Anhui Medical University (Ethics Number: PJ2020-08-07).

Conflict of interest

No potential competing interest was reported by the authors.

Acknowledgments

We thank three hospitals in Anhui Province for their support in allowing us to visit individuals. We are also very grateful to all the people who are willing to spend time and energy to respond to these questions, and to all the members of the research group for their efforts in collecting data ,They are: Chenxia Liao, Jing Wang ,(The First Affiliated Hospital of Anhui Medical University 1926,Hefei), We also appreciate Jie Cao 's revision of this article.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

Clinical Resources

International Spinal Cord Society. https://www.iscos.org.uk/
United Spinal Association—Spinal Cord Resource Centre. https://askus-resource-center. unitedspinal.org/index.php?pg=kb.printer.friendly&id=71

Wang Y, Zhao X, Xie H. Quality of life and its predictors in people with traumatic spinal cord injury in mainland China. Spinal Cord 2019;57:739-46.
Tomandl J, Heinmuller S, Selb M, et al. Laying the foundation for a core set of the international classification of functioning, disability and health for community-dwelling older adults in primary care: relevant categories of their functioning from the research perspective, a scoping review. BMJ Open 2021;11:e37333.
World report on disability 2011.Geneva: World Health Organization; 2011. Available at: [https://www.sciencedirect.com/science/article/pii/S1875067211000290]
Li X, Yang L, Yin J, et al. Validation study of the chinese version of addenbrooke's cognitive examination III for diagnosing mild cognitive impairment and mild dementia. J Clin Neurol 2019;15:313-20.
Van Diemen T, Tran Y, Stolwijk-Swuste JM, et al. Trajectories of self-efficacy, depressed mood, and anxiety from admission to spinal cord injury rehabilitation to 1 year after discharge. Arch Phys Med Rehabil 2021;102:1939-46.
Jimenez BM, Gonzalez DP, Martin MJ. International classification of functioning, disability and health (ICF) 2001. Rev Esp Salud Publica 2002;76:271-79.
Talamonti G, Ligarotti GK, Bramerio M, et al. Unusual behaviour of a pineal germinoma mimicking neurosarcoidosis and metastasising along the endoscopic route. BMJ Case Rep. 2013;2013:bcr2013200278.
Karcz K, Ehrmann C, Finger ME, et al.Predicting change in labour market participation of people with spinal cord injury (SCI): longitudinal evidence from the Swiss SCI community survey. Spinal Cord 2022;60:996-1005.
David G, Pfyffer D, Vallotton K, et al. Longitudinal changes of spinal cord grey and white matter following spinal cord injury. J Neurol Neurosurg Psychiatry 2021;92:1222-30.
Wang J, Li LL, Liao CX, et al. Research progress in cognitive impairment and neuroimaging in patients with spinal cord injury magnetic resonance imaging (in Chinese) 2022;13:134-37.
Tulsky DS, Boulton AJ, Kisala PA, et al. Physical function recovery trajectories after spinal cord injury. Arch Phys Med Rehabil 2022;103:215-23.
WHO disability adjustment schedule II (WHODAS II). Available at: [http://www.who.int/icidh/whodas/index.htm]
Battle DE: Diagnostic and statistical manual of mental disorders (DSM). Codas 2013;25:191-192.
Diagnostic points of various cerebrovascular diseases [J]. Chinese Journal of Neurology (in Chinese) 1996; 06:60-61. Available at: [https://kns.cnki.net/kcms2/article/abstract?v=3uoqIhG8C44YLTlOAiTRKjkpgKvIT9NkZNmQNo4kSVpez3eMlQjjSuhePpDVcZomml_wHmEXcq2tNtJPdzfbB6U0dNMgq-lH&uniplatform=NZKPT]
Andrews G, Kemp A, Sunderland M, et al. Normative data for the 12 item WHO Disability Assessment Schedule 2.0. PLoS One 2009;4:e8343.
Federici S, Bracalenti M, Meloni F, et al. World Health Organization disability assessment schedule 2.0: An international systematic review. Disabil Rehabil 2017;39:2347-80.
Richardson A, Samaranayaka A, Sullivan M, et al. Secondary health conditions and disability among people with spinal cord injury: A prospective cohort study. J Spinal Cord Med 2021;44:19-28.
Hamilton M. A rating scale for depression. J Neurology, Neurosurgery, Psychiatry 1960;23:56–62.
Craig A, Tran Y, Guest R, et al. Trajectories of self-efficacy and depressed mood and their relationship in the first 12 months following spinal cord injury. Arch Phys Med Rehabil 2019;100:441-47.
Weathers F W, Litz B T, Herman D S, et al. The PTSD Checklist (PCL): Reliability, validity, and diagnostic utility[C]//annual convention of the international society for traumatic stress studies, San Antonio, TX. 1993, 462.
Li J, Reinhardt JD, Feng X. Physical function, post-traumatic stress disorder, and quality of life in persons with spinal cord injury caused by the Wenchuan earthquake versus nondisaster trauma: a cross-sectional modeling study. Spinal Cord 2020;58:616-25.
Chan KS, Li HC, Chan SW, et al. Herth hope index: Psychometric testing of the Chinese version. J Adv Nurs. 2012;68:2079-85.
Simpson GK, Anderson MI, Daher M, et al. Testing a model of resilience in family members of relatives with traumatic brain injury vs spinal cord injury: multigroup analysis. Arch Phys Med Rehabil 2021;102:2325-34.
Xiao SY. Social Support Rating Scale [J]. China Journal of Mental Health. 1993 ;02:13-42
Liao CX, Li LL, Dai Q, et al. Analysis of influencing factors of cognitive function in patients with spinal cord injury Chinese Journal of Nursing(in Chinese) 2021;56:1015-22.
Van Leeuwen CM, Hoekstra T, Van Koppenhagen CF, et al.Trajectories and predictors of the course of mental health after spinal cord injury. Arch Phys Med Rehabil 2012; 93:2170-2176.
Hodel J, Ehrmann C, Scheel-Sailer A, et al. Identification of classes of functioning trajectories and their predictors in individuals with spinal cord injury attending initial rehabilitation in switzerland. Arch Rehabil Res Clin Transl 2021;3:100121.
David G, Pfyffer D, Vallotton K, et al. Longitudinal changes of spinal cord grey and white matter following spinal cord injury. J Neurol Neurosurg Psychiatry 2021;92:1222-30.
Mercier HW, Hamner JW, Torous J,et al. Digital phenotyping to quantify psychosocial well-being trajectories after spinal cord injury. Am J Phys Med Rehabil 2020;99:1138-44.
Schwegler U, Nutzi M, Marti A, et al. Pre- and post-injury job type distributions of individuals with SCI in relation to structural changes in the labor market: A comparative analysis based on findings from the Swiss Spinal Cord Injury Cohort Study. J Spinal Cord Med 2021;44:77-88.
Dorstyn DS, Chur-Hansen A, Mansell E, et al. Facilitators and barriers to employment for persons with chronic spinal cord injury or disorder: A qualitative study framed by the person-environment-occupation model. J Spinal Cord Med 2023;46:246-255.
Makaroun LK, Brown RT, Diaz-Ramirez LG, et al. Wealth-Associated Disparities in Death and Disability in the United States and England. JAMA Intern Med 2017;177:1745-53.
Kader M, Perera N, Sohrab HM, et al. Socio-demographic and injury-related factors contributing to activity limitations and participation restrictions in people with spinal cord injury in Bangladesh. Spinal Cord 2018;56:239-46.
Tien NLB, Thanh VV, Hanh KTH, et al. Quality of life and activities of daily living among patients with complete cervical spinal cord injury and surgical treatment in vietnam. Int J Environ Res Public Health 2021;18.
Skold C, Levi R, Seiger A. Spasticity after traumatic spinal cord injury: nature, severity, and location. Arch Phys Med Rehabil 1999;80:1548-57.
Jorgensen S, Iwarsson S, Lexell J. Secondary health conditions, activity limitations, and life satisfaction in older adults with long-term spinal cord injury. PM R 2017;9:356-66.
Braunwalder C, Ehrmann C, Hodel J, et al. Pain trajectories during initial rehabilitation after spinal cord injury: Do psychosocial resources and mental health predict trajectories? Arch Phys Med Rehabil 2022;103:1294-1302.
Wu XL, Li L, Xu L. Study on the status quo and influencing factors of social participation of burn patients after discharge Chinese nursing management (in Chinese) 2017;17:1663-68.
Li J, Lv YM, Zhou YQ,et al.Study on disability status and influencing factors of stroke inpatients in Daqing, Chinese Journal of Rehabilitation Medicine (in Chinese) 2017;32:1376-81.
Li L, Wu XL, Xu L. Factors affecting self-perceived participation and autonomy among patients with burns: A follow-up study. Burns 2018;44:2064-73.
Blochl M, Meissner S, Nestler S. Does depression after stroke negatively influence physical disability? A systematic review and meta-analysis of longitudinal studies. J Affect Disord 2019;247:45-56.
Bonanno GA, Kennedy P, Galatzer-Levy IR, et al.Trajectories of resilience, depression, and anxiety following spinal cord injury. Rehabil Psychol 2012;57:236-247.

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Predictors of disability trajectories in individuals with spinal cord injury in mainland China

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Introduction

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Participant characteristics

Category of disability development track

Univariate analysis

Predictors of disability trajectories

Discussion

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Conclusions

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