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Background: Thromboelastography (TEG) can objectively reflect the formation, development and rupture process of thrombosis in patients, but there are limited data on whether TEG can be used as a predictive tool for recurrence in patients with acute ischemic stroke. Objective: To explore the TEG risk of recurrence in patients with acute ischemic stroke predictive value. Methods: A total of 441 patients with acute ischemic stroke who met the research criteria in the First Affiliated Hospital of Henan University of Traditional Chinese Medicine from January 2020 to December 2021 were selected as the research objects. TEG was measured in all patients, and the main parameters of TEG (R value, indicating coagulation reaction time; K value and Angle, the rate of blood clot formation; MA value, indicating the maximum amplitude). The primary outcome of this study was ischemic stroke recurrence. Recurrent events included cerebral infarction, cerebral hemorrhage, TIA, and were determined by combining imaging events and clinical events. Logistic regression analysis was used to explore the influencing factors of recurrence in patients with acute ischemic stroke. Results: Fifty-six patients (12.7%) had recurrence. Multivariate Logistic regression analysis showed that: Age [OR = 1.078, 95%CI(1.024, 1.135)], triglyceride [OR = 1.541, 95%CI(1.033, 2.298)], glycosylated hemoglobin [OR = 1.401, 95%CI(1.097, 1.790)], history of hypertension [OR = 16.046, p < 0.05], 95%CI(4.726, 54.489), R value [OR = 0.533, 95%CI(0.351, 0.809)], MA value [OR = 1.399, 95%CI(1.004, 1.949)] were independent influencing factors for hemorrhagic transformation in patients with acute ischemic stroke. Conclusion: TEG has some value in predicting recurrence in patients with acute ischemic stroke, and the MA value in TEG [AUC = 0.806 (95%CI:0.747-0.867), with a sensitivity of 78.6% and a specificity of 70.4%], predicted the most significant efficiency of AIS recurrence.

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Objective: This research investigates the role of human factors of all hierarchical levels in radiotherapy safety incidents and examines their interconnections. Methods: Utilizing the human factor analysis and classification system (HFACS) and Bayesian network (BN) methodologies, we created a BN-HFACS model to comprehensively analyze human factors, integrating the hierarchical structure. We examined 81 radiotherapy incidents from the radiation oncology incident learning system (RO-ILS), conducting a qualitative analysis using HFACS. Subsequently, parametric learning was applied to the derived data, and the prior probabilities of human factors were calculated at each BN-HFACS model level. Finally, a sensitivity analysis was conducted to identify the human factors with the greatest influence on unsafe acts. Results: The majority of safety incidents reported on RO-ILS were traced back to the treatment planning phase, with skill errors and habitual violations being the primary unsafe acts causing these incidents. The sensitivity analysis highlighted that the condition of the operators, personnel factors, and environmental factors significantly influenced the occurrence of incidents. Additionally, it underscored the importance of organizational climate and organizational process in triggering unsafe acts. Conclusion: Our findings suggest a strong association between upper-level human factors and unsafe acts among radiotherapy incidents in RO-ILS. To enhance radiation therapy safety and reduce incidents, interventions targeting these key factors are recommended.

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Aim: To evaluate the existing level of emergency capabilities among shared nurses and analyze the factors influencing these capabilities. Methods: An descriptive cross-sectional survey was conducted from September to October 2023, a purposive sampling method was employed to select 340 shared nurses as the subjects for investigation in Nanchang and Ganzhou cities of Jiangxi Province, as well as Wenzhou city in Zhejiang Province. A self - designed questionnaire on the emergency capabilities of shared nurses was utilized for data collection. Results: This investigation encompassed the collection of 340 valid questionnaires, assessing the overall emergency response proficiency of shared nurses. The cumulative score amounted to (170.81±24.62), averaging (4.27±0.62). It is noteworthy that the dimension scoring the highest was preparedness (4.33±0.68), whereas the recovery capability dimension received the lowest score (4.17±0.75). Through multiple linear regression analysis, it was determined that marital status, participation in emergency capability training, and experience in home nursing services significantly influenced the emergency capabilities of shared nurses (P<0.05). Conclusion: Shared nurses in China demonstrate a moderately high level of emergency response capability. The marital status, participation in emergency capacity training, and on-site nursing service experience are pivotal factors influencing the emergency capabilities of shared nurses. Nursing administrators should prioritize the development of emergency capacity training and team building for shared nurses, establishing a scientifically standardized mechanism for training, assessment, and management. The implementation of performance evaluation mechanisms for shared nurses is crucial to enhance professional awareness within the workforce.

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Freight truck-related crashes in urban contexts have caused significant economic losses and casualties, making it increasingly essential to understand the spatial patterns of such crashes. Limitations regarding data availability have greatly undermined the generalizability and applicability of certain prior research findings. This study explores the potential of emerging geospatial data to delve deeply into the determinants of these incidents with a more generalizable research design. By synergizing high-resolution satellite imagery with refined GIS map data and geospatial tabular data, a rich tapestry of the road environment and freight truck operations emerges. To navigate the challenges of zero-inflated issues of the crash datasets, the Tweedie Gradient Boosting model is adopted. Results reveal a pronounced spatial heterogeneity between highway and urban non-highway road networks in crash determinants. Factors such as freight truck activity, intricate road network patterns, and vehicular densities rise to prominence, albeit with varying degrees of influence across highways and urban non-highway terrains. Results emphasize the need for context-specific interventions for policymakers, encompassing optimized urban planning, infrastructural overhauls, and refined traffic management protocols. This endeavor may not only elevate the academic discourse around freight truck-related crashes but also champion a data-driven approach towards safer road ecosystems for all.

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Construction safety is of significance since construction accidents can result in loss of property and large numbers of casualties. This research aims to identify the critical causes of construction accidents by introducing a hybrid approach. The hybrid approach is developed to identify the critical causes of construction accidents by combining the human factors analysis and classification system (HFACS) model with complex network (CN) theory. A total of 863 construction accident cases were collected, and 46 causal factors were identified. Subsequently, the accident causal network was established, and six critical causal factors were extracted. The hybrid analysis approach is demonstrated with a real construction accident case, and the results demonstrate that the hybrid approach could better identify the critical causal factors. Consequently, this research enables the enhancement of understanding the HFACS framework and CN theory, as well as a contribution to safety management in the construction industry at different levels.

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AIMS: To investigate the level of spiritual health in older patients with chronic obstructive pulmonary disease (COPD) from the core dimensions and to explore its associated factors. DESIGN: A cross-sectional study. METHODS: Participants were recruited from four hospitals between September 2020 and June 2021, using a convenience sampling. Older patients with COPD (n = 162) completed the demographic and disease-related information questionnaires, Function Assessment of Chronic Illness Therapy Spiritual Scale, 10-item Connor-Davidson Resilience Scale, General Self-efficacy Scale, Social Support Rating Scale, COPD Assessment Test, 15-item Geriatric Depression Scale and modified Medical Research Council Dyspnea Scale. Descriptive statistics, Pearson and Spearman correlation analyses, t-tests, one-way ANOVA and multiple linear regression models were used. RESULTS: Older patients with COPD have a moderate level of spiritual health. The multiple linear regression analysis showed that psychological resilience, general self-efficacy, social support, symptom burden and monthly income were associated with the core dimensions of spiritual health. CONCLUSION: Chinese older patients with COPD have a moderate level of spiritual health. Psychological resilience, general self-efficacy, social support, monthly income and symptom burden were associated with the core dimensions of spiritual health. IMPACT: This study is the first to investigate the level of spiritual health in older patients with COPD from the core dimensions and to explore its associated factors, providing a basis for developing spiritual intervention programs. Our findings can help us realize that intervention strategies of psychological resilience, general self-efficacy and social support can all be used to enhance spiritual health. Nurses should focus on the spiritual health of older COPD patients with high symptom burden and low monthly income. PATIENT OR PUBLIC CONTRIBUTION: Although we did not directly involve patients and the public because of the COVID-19 pandemic, the results of the study will be disseminated to patients and the public through WeChat and seminars.

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ObjectiveTo investigate the epidemic characteristics and influencing factors of acute conjunctivitis caused by human adenovirus（HAdv）in Yantian District of Shenzhen City， Guangdong Province from 2014 to 2022， and to provide evidence for formulating effective prevention and control measures. MethodsDescriptive epidemiology was used to analyze the epidemiological characteristics of acute hemorrhagic conjunctivitis （AHC） cases reported from the Chinese disease prevention and control information system. Etiological characteristics of laboratory-confirmed cases were analyzed， and a case-control study method of test-negative design （TND） was conducted as well. According to the result of HAdv detection， analysis was used to identify the influencing factors of morbidity. ResultsA total of 1 005 AHC cases were reported in Yantian District， Shenzhen City from 2014 to 2022， with an average annual incidence rate of 49.49/105. The incidence rate ranged from 4.67/105 to 117.28/105. The peak incidence occurred from July to October each year， with a male-to-female ratio of 1.42∶1. The median （P25，P75） age of onset was 29（12，40） years. A total of 716 eye swabs were collected for etiological detection from 2014 to 2022. HAdv positive detection rate was 36.45% （263/716）， Cox 24v positive detection rate was 0.28% （2/716）， while EV70 was not detected. The longest viral shedding time in eye swabs was 10 days， with a median of 2 days. The highest HAdv positive detection rate （47.47%） was observed when the sampling-to-onset interval was 4‒5 days， and the difference was statistically significant （P<0.05）， with a trend of first increasing and then decreasing. Multivariate logistic regressing analysis showed that aged 18‒ years， and average temperature higher than 24.90 ℃ 3 days before onset （P<0.05） were the risk factors for acute HAdv conjunctivitis. ConclusionAHC in Yantian District， Shenzhen City showed a low level of prevalence from 2014 to 2022， with HAdv being the predominant pathogen. The peak period of viral shedding occurred on the 4th to 5th day after symptom onset， suggesting the importance of adherence to strict home isolation for infected persons. Aged18‒ years and average temperature increased 3 days before onset are associated with an increased risk of adenoviral conjunctivitis. It is recommended to strengthen personal protection and keep doing a good job of AHC surveillance and early warning， so as to timely prevent the outbreaks of AHC.

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ObjectiveTo investigate the general situation of defect of vertebral column among primary and middle school students in Minhang District of Shanghai and analyze the related factors， to provide a scientific basis for prevention and treatment. MethodsFrom September to October 2022， a total of 5 715 students were selected from two primary schools， two middle schools， and two high schools in Minhang District for physical examinations and screening for defect of vertebral column. ResultsTotally 219 students had defect of vertebral column， accounting for 3.83% of the sampled population. Anteroposterior spinal abnormalities were found in 4 individuals， accounting for 0.07%， and 218 students had scoliosis， accounting for 3.81%. The detection rate of defect of vertebral column was higher in girls （6.27%） than that in boys （1.51%）， and higher in high school students （10.74%） than in primary school students （1.31%） and middle school students （10.97%）. Students who are mildly underweight （5.95%） and who are moderately to severely underweight （7.46%） had a higher detection rate of defect of vertebral column than those with normal weight （4.54%）， overweight （2.83%）， and obesity （1.60%）. The detection rate among students with poor vision （4.32%） was significantly higher than those with normal vision （2.24%）， with all differences statistically significant （all P<0.05）. ConclusionThe positive rate of defect of vertebral column in primary and middle school students in Minhang District， Shanghai is nearly 4%， with most cases being scoliosis. Factors such as being female， increasing age， being underweight， and poor vision are associated with a higher probability of detecting defect of vertebral column.

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Since China joined the WTO, its economy has experienced rapidly growth, resulting in significantly increase in fossil fuel consumption and corresponding rise in CO2 emissions. Currently, China is the world's largest emitter of CO2, the regional distribution is also extremely uneven. so, it is important to identify the factors influence CO2 emissions in the three regions and predict future trends based on these factors. This paper proposes 14 carbon emission factors and uses the random forest feature ranking algorithm to rank the importance of these factors in three regions. The main factors affecting CO2 emissions in each region are identified. Additionally, an ARIMA + LSTM carbon emission predict model based on the inverse error combination method is developed to address the linear and nonlinear relationships of carbon emission data. The findings suggest that the ARIMA + LSTM is more accurate in predicting the trend of CO2 emissions in China. Moreover, the ARIMA + LSTM is employed to forecast the future CO2 emission trends in China's east, central, and west regions, which can serve as a foundation for China's CO2 emission reduction initiatives.

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BACKGROUND: Crimean-Congo haemorrhagic fever (CCHF) is caused by an orthonairovirus transmitted by bites from infected ticks or by direct contact with blood or tissues of infected ticks, viraemic patients or viraemic livestock. OBJECTIVE: It was implemented to access the seropositivity and associated factors with CCHF in sheep in two provinces in Burkina Faso. METHODS: Three hundred and sixty-four sheep sera have been taken from 73 herds in four municipalities and two provinces. The double-antigen sandwich ELISA test was used to test for antibodies against CCHF virus (CCHFV). Data have also been collected using questionnaire to assess factors associated with CCHF seropositivity. RESULTS: Fifty-four (54 out to 364 sheep were seropositive given an overall seropositivity of 14.8% (95% confidence interval [CI]: 10.9%-19.8%) with an adjusted seropositivity of 13.1%. The study showed that 15.6% (95% CI: 10.2-21.0) and 14.1% (95% CI: 9.2-19.1) of sheep in the provinces of Mouhoun and Kénédougou, respectively, had antibodies against CCHFV. The highest seropositivity was found in Dédougou municipality (24.4%). The study showed that sheep from the municipalities of Dédougou (AOR = 8.4; 95% CI: 2.2-31.8), N'dorola (AOR = 14.7; 95% CI: 3.8-56.8), Sindou (AOR = 4.9; 95% CI: 1.2-20.7), sheep aged between 27 and 36 months (AOR = 6.4; 95% CI: 2.3-17.3) and sheep with ticks (AOR = 24.8; 95% CI: 7.7-80.1) were more likely to be seropositive to CCHF. CONCLUSIONS: The study revealed that sheep in Burkina Faso experienced contacts with CCHFV and suggests the importance of implementing control action in the country.

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Human factors have increasingly been the leading cause of aircraft accidents. In most cases, human factors are not working alone, instead they are coupled with complex environment, mechanical factors, physiological and psychological factors of pilots, and organizational management, all of which form a complex aviation safety system. It is vital to investigate the coupling impact of human errors to avoid the occurrence of aviation accidents. In view that the Human Factors Analysis and Classification System (HFACS) provides a hierarchical classification principle of human errors in aviation accidents, and the System Dynamics (SD) approach is helpful to describe the risk evolution process, this paper establishes a hybrid HFACS-SD model by employing the HFACS and the SD approach to reveal the aviation human factors risk evolution mechanism, in which the HFACS is first used to capture the causal factors of human errors risk, and a coupling SD model is then built to describe the evolution of aviation human factors risk supported by historical data. The eigenvalue elasticity analysis is taken to identify critical loops and parameters that have a substantial impact on the system structural behavior, and the influence of parameters and loops is assessed. Simulation results show that the evolution trend of the accident rate can be replicated by the proposed HFACS-SD model, and the structural dominance analysis can efficiently identify critical loops and parameters. Simulation results further show that, with the recommended safety enhancement measures, the stability of the aviation system is increased, and thus lowering the overall accident rate.

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Chitin deacetylase (CDA), a prominent member of the carbohydrate esterase enzyme family 4 (CE4), is found ubiquitously in bacteria, fungi, insects, and crustaceans. This metalloenzyme plays a pivotal role in recognizing and selectively removing acetyl groups from chitin, thus offering an environmentally friendly and biologically-driven preparation method for chitosan with immense industrial potential. Due to its diverse origins, CDAs sourced from different organisms exhibit unique functions, optimal pH ranges, and temperature preferences. Furthermore, certain organic reagents can induce structural changes in CDAs, influencing their catalytic activity. Leveraging CDA's capabilities extends beyond chitosan biocatalysis, as it demonstrates promising application value in agricultural pest control. In this paper, the source, reaction mechanism, influencing factors, the fermentation methods and applications of CDA are reviewed, which provides theoretical help for the research and application of CDA.

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Medical institutions worldwide strive to avoid adverse medical events, including adverse medication-related events. However, studies on the comprehensive analysis of medication-related adverse events are limited. Therefore, we aimed to identify the error factors contributing to medication-related adverse events using the Human Factors Analysis and Classification System (HFACS) and to develop error models through logistic regression. These models calculate the probability of a medication-related adverse event when a healthcare system defect occurs. Seven experts with at least 12 years of work experience (four nurses and three pharmacists) were recruited to analyze thirty-seven medication-related adverse events. The findings indicate that decision errors, physical/mental limitations, failure to correct problems, and organizational processes were the four factors that most frequently contributed to errors at the four levels of the HFACS. Seven error models of two types (error occurrence and error analysis pathways) were established using logistic regression models, and the relative probabilities of failure factor occurrences were calculated. Based on our results, medical staff can use the error models as a new analytical approach to improve and prevent adverse medication events, thereby improving patient safety.

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In 2020, the domestic (Chinese native) 2v human papillomavirus (HPV) vaccine was approved for use in females. At present, there are obvious differences in demand for different HPV vaccines. We aimed to investigate knowledge level of cervical cancer and HPV vaccine and its influencing factors among the eligible female recipients in Shenzhen, China, and to analyze the factors influencing choice of 2vHPV vaccine (domestic or imported) would be selected. A self-administered questionnaire was carried out on this investigation, and respondents were selected by random sampling method conducted by vaccination doctors. A total of 1197 valid questionnaires were collected, of which 729 (60.9%) were vaccinated with domestic vaccines and 468 (39.1%) were vaccinated with imported. Four hundred and fifty (61.7%) and 306 (65.4%) got a passing grade, respectively (χ2 = 1.637, P = .201). Logistic regression analysis showed that age (P = .002), ethnicity (P < .001), duration of residence in Shenzhen (P < .001), educational level (P < .001) and occupation (P < .001) were significant. It also showed that the manufacturers (P < .001), efficacy (P < .001), safety (P < .001), cognitive approach (P < .001), public opinion (P < .001), convenient acquisition (P < .001) and knowledge reserve (P = .035) were statistically significant. While price (P = .371) and doctor's suggestion (P = .114) were not. In conclusion, eligible female recipients had a high degree of knowledge regarding cervical cancer and HPV vaccine, education level and occupation were the most important factors for scores. Domestic 2vHPV vaccine was more widely utilized than imported, manufacturer, efficacy, safety, cognitive approach, public opinion, convenient acquisition, and knowledge reserve had an impact on selection for recipients, while price and doctor's suggestion did not.

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Rapid urbanization has reduced the capacity of cities to mitigate and withstand disasters. Strengthening urban ecological resilience (ER) is important for improving urban self-organization. Geographical characteristics and developmental status of different cities lead to a more complex relationship between urbanization and ER. Using the three major urban agglomerations in China, we constructed a new framework for assessing the ER from a landscape and ecological processes perspective, and analyzed the driving heterogeneity of urbanization on ER. The results indicated that the ER of Yangtze River Delta (YRD) and Pearl River Delta (PRD) decreased continuously from 2000 to 2018, while the ER of Beijing-Tianjin-Hebei (BTH) decreased from 2000 to 2010, and then increased from 2010 to 2018. The resilience level of PRD was significantly lower than those of BTH and YRD. The urbanization process had a negative impact on ER, and the contribution of urbanization factors to ER varied significantly across cities, and population factors have the most direct influence. Curve fitting analysis further deepened our understanding of heterogeneity, investigating from the perspective of landscape and driving factors, and suggesting improvement measures. This study can deepen the understanding of the impact of urbanization on resilience and provide scientific guidance for achieving regional sustainability.

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Introduction: In the aviation industry, safety management has moved away from capturing frontline failures toward the management of systemic conditions through organizational safety management systems (SMS). However, subjective differences can influence the classification of active failures and their associated systemic precursors. With levels of professional experience known to influence safety attitudes, the present research examines whether experience levels among airline pilots had an impact on the classification of causal factors using the Human Factors Analysis and Classification System (HFACS). Differences in the paths of association between categories were evaluated in an open-system context. Method: Pilots working in a large, international airline were categorized into high (≥10,000 total flight hours) and low (<10,000 h) experience groups and asked to classify aircraft accident causal factors using the HFACS framework. One-way ANOVA tests were carried out to determine experience effects on the utilization of the HFACS categories, and chi-squared analyses were used to assess the strength of association between different categories within the framework. Results: Results from 144 valid responses revealed differences in the attribution of human factors conditions. The high experience group was more inclined to attribute deficiencies to high-level precursors and found fewer paths of associations between different categories. In contrast, the low experience group presented a greater number of associations and was comparatively more affected by stress and uncertainty conditions. Discussion: The results confirm that the classification of safety factors can be influenced by professional experience, with hierarchical power distance impacting the attribution of failures to higher-level organizational faults. Different paths of association between the two groups also suggest that safety interventions can be targeted through different entry points. Where multiple latent conditions are associated, the selection of safety interventions should be made with consideration of the concerns, influences, and actions across the entire system. Higher-level anthropological interventions can change the interactive interfaces affecting concerns, influences, and actions across all levels, whereas frontline-level functional interventions are more efficient for failures linked to many precursor categories.

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Objectives. General aviation (GA) safety has become a key issue worldwide and pilot errors have grown to be the primary cause of GA accidents. However, fewer empirical studies have examined the contribution of management and organizational factors for these unsafe acts. Flawed decisions at the organizational level have played key roles in the performance of pilots. This study provides an in-depth understanding of the management and organizational factors involved in GA accident reports. Methods. A total of 109 GA accidents in China between 1996 and 2021 were analysed. Among these reports, pilot-related accidents were analysed using the human factors analysis and classification system (HFACS) framework. Results. The significant effects of managerial and organizational factors and the failure pathways on GA accidents have been identified. Furthermore, unlike traditional HFACS-based analyses, the statistically significant relationships between failures at the organizational level and the sub-standard acts of the pilots in GA accidents were revealed. Conclusions. Such findings support that the GA accident prevention strategy that attempts to reduce the number of unsafe acts of pilots should be directed to the crucial causal categories at HFACS organizational levels: resource management, organizational process, failure to correct a known problem, inadequate supervision and supervisory violations.

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PURPOSE: Contrast-induced encephalopathy (CIE) was defined as new onset of neurological deficits after exposure to contrast media, which could be observed after the endovascular treatment for intracranial aneurysms. METHODS: We enrolled a consecutive cohort of patients who underwent endovascular treatment for unruptured intracranial aneurysms. CIE was defined as a reversible neuropathic syndrome that occurred after interventional therapy, accompanied by imaging abnormalities and excluding other diseases. Multivariable Poisson regression analysis was performed to show risk factors by incidence rate ratio (IRR) and a clinical strategy was proposed. RESULTS: Among the 579 patients who underwent interventional therapy for intracranial aneurysms, the crude incidence rate of CIE was 2.4% (95% CI, 1.2-3.6%) at our center. Headache, hemiplegia, and disorientation could be initial symptoms, and cortical blindness was the most common localized deficit. Cerebral edema and sulci effacement on CT were observed, and re-revaluation after treatments on CT/MRI showed absent lesions. The risk factors were history of stroke (IRR, 7.752; P = 0.007), history of hypertension (IRR, 1.064; P = 0.042), posterior circulation aneurysms (IRR, 9.412; P = 0.004) and higher dosage of contrast agents (IRR, 1.018; P = 0.007). After the strategy of accelerating excretion of contrast agents, reduction of intracranial pressure and anti-inflammation/vasospasm therapy, the prognosis was favorable with most patients fully recovered within 72 h. CONCLUSION: History of stroke and posterior circulation aneurysms were main risk factors for CIE. A higher dosage of contrast agents might induce CIE, and the history of hypertension should be considered as well.

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Gaining a deeper understanding of factors that influence changes in phytoplankton community has significant implications for shallow lake management. The present study examined changes in the algae community of three shallow eutrophic lakes of the Taoge water system between 2008 and 2018 and the related factors influencing these changes. The composition of the algal community varied significantly during this period with the relative diatom biomass in lakes Changdanghu and Gehu increasing between 2014 and 2016 and again decreasing after 2017. However, relative cyanobacteria biomass initially decreased and later increased; meanwhile, the proportion of biomass of other phyla decreased continuously in the study period. Lake Zhushanhu showed similar trends, although it eventually returned to its initial state with absolute Microcystis dominance. Furthermore, the analysis of driving factors revealed that the concentrations of total nitrogen (TN), nitrate (NO3), and orthophosphate (PO4) were significantly associated with a significant increase in Microcystis biomass. Meteorological conditions also influenced changes in total algal and diatom biomasses, which were inversely related to the daily mean and daily maximum wind speeds. Monthly cumulative precipitation was only significantly associated with diatom biomass. Meanwhile, rainfall primarily affected the algal community structure between 2013 and 2017; an increase in the relative biomass of diatoms coincided with increased precipitation. Coordinating nitrogen and phosphorous use within the Taoge water system should improve lake habitat management; a broader perspective in attempts to control global and regional climate change may be needed.

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Objective:To explore the potential categories of post-operative supportive care demand trajectory for patients with non-small cell lung cancer (NSCLC), analyze the influencing factors, and propose targeted interventions.Methods:This was a prospective observational study. A convenient sampling method was used to select 177 NSCLC patients who received surgical treatment in Shanghai Lung Hospital Affiliated to Tongji University from January 2021 to February 2022. The Supportive Care Demand Scale for cancer patients was used to investigate the level of patients′supportive care demand 1 day before operation, 3 days after operation, 1 day before discharge, 1 week after discharge, 1 month after discharge, and 3 months after discharge, and the potential growth model was used to identify the trajectory category and multi category Logistic regression analysis was used to explore the influencing factors.Results:Three supportive care demand trajectories were fitted out in this study, which were the continuous high demand group (46.33%), the slowly decreasing demand group (30.51%), and the low decreasing demand group (23.16%). With the potential category group 3, low demand reduction group as the reference category, Logistic regression analysis showed that high psychological distress, low social support, high disease stage, high comorbidities were more likely to enter the continuous high demand group ( OR = 0.826 to 18.526, all P<0.05), and high education level (college education and above and high school) were more likely to enter the slowly decreasing demand group ( OR = 6.076, 4.199, both P<0.05). Conclusions:The demand track of NSCLC patients for supportive care after surgery has population heterogeneity. Clinical medical staff should provide personalized social support and emotional support for patients with high disease stage, more complications and low education level in the early postoperative period.