Objective To explore the current situation and influencing factors of self-management behavior in patients with primary glaucoma, so as to provide a theoretical basis for formulating intervention strategies to improve patients’ self-management ability. Methods Using convenient sampling method, 400 patients with primary glaucoma visiting the Outpatient Department of Ophthalmology, West China Hospital of Sichuan University between September 2019 and March 2020 were selected. Their current situation of self-management behavior was investigated by self-management behavior questionnaire, and the influencing factors of self-management behavior were analyzed. Results A total of 381 valid questionnaires were recovered. The total score of self-management behavior of patients with primary glaucoma was 51.11±6.22, and the mean scores of life debugging dimension, functional health care dimension, and medical management dimension were 2.66±0.67, 3.02±0.81, and 3.13±0.60, respectively. The results of multiple linear regression analysis showed that age [40-59 vs. <40 years old: unstandardized partial regression coefficient (b)=–2.830, 95% confidence interval (CI) (–4.813, –0.847), P=0.005; ≥60 vs. <40 years old: b=–2.660, 95%CI (–4.820, –0.498), P=0.016], occupation [in-service vs. farmers: b=2.639, 95%CI (0.303, 4.976), P=0.027; unemployed or retired vs. farmers: b=2.913, 95%CI (0.995, 4.831), P=0.003], smoking [smoking vs. non-smoking: b=–3.135, 95%CI (–5.196, –1.075), P=0.003], disease type [primary open-angle glaucoma vs. primary angle-closure glaucoma: b=–2.119, 95%CI (–3.317, –0.921), P=0.001], number of follow-up visits [≤2 vs. >2: b=–1.071, 95%CI (–2.118, –0.024), P=0.045], whether fixed doctor follow-up [unfixed vs. fixed: b=–2.619, 95%CI (–3.632, –1.605), P<0.001] were correlated with the total score of self-management behavior of patients with primary glaucoma. Conclusions The self-management behavior of patients with primary glaucoma is in the middle level. The main factors affecting the self-management behavior level of primary glaucoma patients include age, occupation, smoking, disease type, follow-up times, and fixed doctor’s follow-up. Ophthalmologists should pay attention to the current situation and influencing factors of self-management behavior and take feasible intervention measures to improve the self-management behavior of patients with primary glaucoma.
Objective To explore the influencing factors for pulmonary infection after radical resection of colon cancer. Methods A cohort study included 56 patients who underwent radical resection of colon cancer in People’s Hospital of Daye City from Oct. 2014 to Oct. 2016 were followed-up prospectively, to observe the occurrence of pulmonary infection, and collectting the related factors for pulmonary infection in addition. Results The clinical data of 53 patients were finalized and the clinical data of these patients were complete. Among them, 13 patients suffered from pulmonary infection after radical resection of colon cancer, and 40 patients had no obvious exacerbation and no complicated pulmonary infection. Results of logistic regression showed that, value of forced expiratory volume in1 second/forced vital capacity (OR=1.174, P=0.033), operative time (OR=1.638, P=0.012), levels of postoperative copeptin (OR=1.328, P=0.032), and procalcitonin (OR=1.465, P=0.042) were risk factors for pulmonary infection after radical resection of colon cancer. Receiver operating characteristic curve (ROC) showed that, operative time was 6.207-hour, postoperative copeptin level was 10.420 pmol/L, and the postoperative procalcitonin level was 3.676 ng/mL, which had the best predictive effect on predicting pulmonary infection after radical resection of colon cancer. Conclusions Value of forced expiratory volume in 1 second/forced vital capacity, operative time, levels of copeptin and procalcitonin after operation are the independent influencing factors for pulmonary infection after radical resection of colon cancer, and it has best prognostic outcome when the operative time is 6.207-hour, postoperative copeptin level is 10.420 pmol/L, and the postoperative procalcitonin level is 3.676 ng/mL.
ObjectiveTo analyze the influencing factors of ventilator-associated pneumonia (VAP) in comprehensive intensive care units (ICUs) in a certain district of Shanghai, and to provide evidence for developing targeted measures to prevent and reduce the occurrence of VAP.MethodsThe target surveillance data of 1 567 inpatients with mechanical ventilation over 48 hours in comprehensive ICUs of 5 hospitals in the district from January 2015 to December 2017 were retrospectively analyzed to determine whether VAP occurred. The data were analyzed with SPSS 21.0 software to describe the occurrence of VAP in patients and to screen the influencing factors of VAP.ResultsThere were 133 cases of VAP in the 1 567 patients, with the incidence of 8.49% and the daily incidence of 6.01‰; the incidence of VAP decreased year by year from 2015 to 2017 (χ2trend=11.111, P=0.001). The mortality rate was 12.78% in VAP patients while was 7.25% in non-VAP patients; the difference was significant (χ2=5.223, P=0.022). A total of 203 pathogenic bacteria were detected in patients with VAP, mainly Gram-negative bacteria (153 strains, accounting for 75.37%). The most common pathogen was Pseudomonas aeruginosa. The single factor analysis showed that gender, age, Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score, the length of ICU stay, and the length of mechanical ventilation were the influencing factors of VAP (χ2=9.572, 5.237, 34.759, 48.558, 44.960, P<0.05). Multiple logistic regression analysis found that women [odds ratio (OR)=1.608, 95% confidence interval (CI) (1.104, 2.340), P=0.013], APACHE Ⅱ score >15 [OR=4.704, 95%CI (2.655, 8.335), P<0.001], the length of ICU stay >14 days [OR=2.012, 95%CI (1.188, 3.407), P=0.009], and the length of mechanical ventilation >7 days [OR=2.646, 95%CI (1.439, 4.863), P=0.002] were independent risk factors of VAP.ConclusionsNosocomial infection caused by mechanical ventilation in this area has a downward trend, and the mortality rate of patients with VAP is higher. For the patients treated with mechanical ventilation in ICU, we should actively treat the primary disease, shorten the length of ICU stay and the length of mechanical ventilation, and strictly control the indication of withdrawal, thereby reduce the occurrence of VAP.
Objective To investigate the prevalence and related factors of diabetic retinopathy (DR) among residents with type 2 diabetes mellitus (T2DM) in Culai Town of Tai'an City in Shandong Province. Methods According to the DM management file database for community, 785 patients with T2DM were randomly selected by cluster sampling method. The questionnaires, routine general examinations, visual and fundus-free fluoroscopy were performed on all the patients. DR diagnosis and classification was according to the guidelines for clinical diagnosis and treatment of DR in China (2014). Both monocular and binocular DR were selected as DR patients, and the worse eye for binocular DR were treated as the DR classification of the patient. The patients were grouped by presence or absence of DR. GraphPad Prism 6, SigmaPlot 12.5, SPSS 20.0 and Excel were used to achieve data analysis. Also, SPSS 20.0 was used for multi-factor logistic regression analysis. Results A total of 699 patients (89.04%) were actually recorded. There were 122 eyes of 63 patients (9.01%) with DR (DR group), 1272 eyes of 636 patients (90.99%) without DR (NDR group). Among the 122 eyes of DR, there were 19 (15.57%), 17 (13.93%), 70 (57.38%), 10 (8.20%), 6 (4.92%) eyes in stage Ⅰ, Ⅱ, Ⅲ, Ⅳ, Ⅴ, respectively. The differences of mean age (t=15 290, P=0.002), DM duration (t=9075, P＜0.000) and diastolic blood pressure (t=15 810, P=0.006) between the two groups were statistically significant. There were 23 (36.51%) and 394 (61.95%) patients with hypertension history in the DR group and the NDR group, with the significant difference ( χ2=15.42, OR=0.35, 95%CI 0.21-0.60). There were 57 (90.48%) and 500 (78.62%) patients with fasting blood glucose larger than 6.11 mmol/L in the DR group and the NDR group, with the significant difference (OR=2.51, 95%CI 1.06-5.95, P=0.031). Logistic regression analysis showed that the age, fasting blood glucose and DM duration were influencing factors for DR (OR=1.039, 0.864, 0.898; P=0.021, ＜0.000, ＜0.000). Conclusion The prevalence of DR in patients with T2DM in Culai Town of Tai'an City is 9.01%. Age, DM duration, fasting blood glucose are associated to DR. Those with a history of hypertension may have a lower risk of DR than those without a history of hypertension.
ObjectiveTo investigate the health literacy level and its influencing factors among follow-up patients with chronic kidney disease (CKD).MethodsFrom March to August 2018, 248 patients from the CKD Follow-up Management Center, West China Hospital, Sichuan University were included. Basic information questionnaire and chronic diseases health literacy scale were used. Analysis of variance and t test were used in univariate analysis, and multiple linear stepwise regression was used in multivariate analysis, to explore the influencing factors of health literacy score.ResultsThe average health literacy score of the 248 CKD patients (97.24±12.22) were in medium to low level. Listed from high to low, the score of each dimension was: ability to obtain information (4.24±0.50), willingness to improve health (4.17±0.66), competence to communicate and interact with others (3.95±0.59), and willingness to support financially (3.41±1.10). The result of multiple linear stepwise regression showed that whether followed up on time, families’ monthly income per capita, and the patients’ age were independent influencing factors of health literacy score (P<0.05).ConclusionsThe health literacy level of follow-up patients with CKD remains to be improved. Medical personnel should pay attention to whether patients with CKD are followed up on time, make targeted intervention, and improve the self-management of patients so as to delay the disease progress of CKD.
ObjectiveTo systematically evaluate the related factors of constipation in patients with stroke. MethodsCochrane Library, PubMed, Web of Science, Embase, CNKI, VIP, Wanfang and China Biomedical Literature Database were searched by computer, and the retrieval time was set to May 2022. Case-control studies, cohort studies and cross-sectional studies on stroke and constipation were selected. Meta-analysis was performed using RevMan 5.3 software. ResultsA total of 13 studies involving 2 834 patients were included. Meta-analysis showed that age [odds ratio (OR) =2.54, 95% confidence interval (CI) (1.36, 3.73), P<0.001], lesion location [OR=1.98, 95%CI (1.27, 3.11), P=0.003], National Institutes of HealthStroke Scale score [OR=0.40, 95%CI (0.10, 0.70), P=0.010], hemiplegia [OR=4.31, 95%CI (2.59, 7.17), P<0.001], dysphagia [OR=2.32, 95%CI (1.27, 4.25), P=0.006], antidepressants [OR=2.33, 95%CI (1.62, 3.34), P<0.001], BI score [OR=−17.08, 95%CI (−33.07, −1.08), P=0.04], eating pattern [OR=4.18, 95%CI (1.16, 15.09), P=0.030], drinking water volume ≥800 mL [OR=0.30, 95%CI (0.19, 0.46), P<0.001] might be the influencing factors of constipation in patients after stroke. The results of sensitivity analysis showed that age, education level, diabetes, smoking, stroke type, lesion location, diuretic and BI score might be the influencing factors of constipation after stroke (P<0.05). The results of bias analysis suggest that publication bias is less likely. Conclusions There are many risk factors for constipation in patients with stroke. Current evidence shows that age, diabetes, smoking and other 11 factors may be risk factors for stroke constipation, while high education level and drinking water ≥800 mL may be protective factors, and the other influencing factors have not been determined and need further study.
Objective To explore the current status of preoperative hope level and its influencing factors in scoliosis patients, focusing on the role of medical coping, social support and self-care ability on the hope level, and to provide a basis for optimising perioperative psychological interventions. Methods Preoperative scoliosis patients at West China Hospital of Sichuan University between January 2024 and January 2025 were selected. Patients were included in the survey using a general information questionnaire, Herth Hope Index (HHI), Medical Coping Questionnaire, Social Support Rating Scale (SSRS), and Daily Living Ability Scale. Multiple linear regression analyses were performed and influential factors were explored with HHI score as the dependent variable. Results A total of 156 patients were investigated. Among them, there were 104 females (66.67%); The average HHI score was (36.88±4.04) points; 41.03% (64 cases) of patients were at a low to moderate hope level (HHI≤35 points). There were statistically significant differences in HHI scores among patients with different marital statuses and disease durations (P<0.05). The correlation analysis results showed that social support was positively correlated with HHI (r=0.207, P=0.010); Medical coping (r=−0.015, P=0.852) and self-care ability (r=0.010, P=0.903) were not correlated with HHI. The results of multiple linear regression analysis showed that the total SSRS score affected the HHI score of preoperative scoliosis patients (P=0.040). Conclusion Multidisciplinary interventions should be implemented for patients with low levels of hope, focusing on married patients with a disease duration of 1-5 years, and improving their level of hope by strengthening the social support network.
ObjectiveTo investigate the risk factors of postoperative portal vein thrombosis (PVT) after devascu-larization in patients with cirrhotic portal hypertension. MethodsThe clinical data of 40 patients with cirrhotic portal hypertension treated with splenectomy and gastric pericardial devascularization were retrospectively analyzed to investigate the related risk factors. ResultsA total of 12 of the 40 patients suffered from PVT (30.00%). The results of multivariate analysis showed that portal vein diameter, postoperative portal vein velocity, platelet count at 2 weeks postoperatively, and postoperative portal vein pressure were the factors influencing the incidence of PVT after devascularization. Patients with the greater portal vein diameter and platelet count at 2 weeks postoperatively, the lower postoperative portal vein velocity and postoperative portal vein pressure, had higher ratio of PVT (P < 0.05). ConclusionPortal vein diameter, portal vein blood flow velocity, platelet count, and postoperative portal vein pressure were the main risk factors for PVT after surgery in patients with cirrhotic portal hypertension.
ObjectiveTo investigate the status of quality of life and influencing factors among newly diagnosed epilepsy patients with co-morbid anxiety and depression. MethodsA total of 180 newly diagnosed epilepsy patients from June 2022 to December 2022 in a district of Shanghai were selected as the study subjects. The Quality of Life in Epilepsy-31 (QOLIE-31), Hamilton Depression Rating Scale (HAMD-24), Hamilton Anxiety Rating Scale (HAMA), and Epilepsy Self-Management Scale (ESMS) were used to assess patients' quality of life, depression levels, anxiety levels, and self-management abilities, respectively. Patients were divided into the co-morbid depression group (HAMA≥14 and HAMD>17) and the control group (HAMA<14 and HAMD≤17), and their general characteristics and scale scores were compared. Spearman correlation, Pearson correlation, and multiple linear regression analysis were used to identify influencing factors of quality of life in epilepsy patients with co-morbid depression. ResultsCompared to the control group, the anxiety comorbid with depression group of older adults had a higher proportion, higher unemployment rate, lower personal and family annual income in the past year, higher frequency of epileptic seizures, and lower medication adherence (P<0.05). The correlational analysis revealed a negative correlation between the quality of life abilities of epilepsy patients with comorbid anxiety and depression and the severity of anxiety and depression. (r=−0.589, −0.620, P<0.05). The results of multiple linear regression analysis showed that the frequency of seizures in the past year (β=−1.379, P<0.05), severity of anxiety (β=−0.279, P<0.05), and severity of depression (β=−0.361, P<0.05) have an impact on the ability to quality of life in epilepsy patients with co-morbid anxiety and depression. These factors account for 44.1% of the total variability in quality of life (R2=0.4411, P<0.05). ConclusionThe frequency of seizures in the past year, as well as the severity of anxiety and depression, are important factors that influence the ability to quality of life in epilepsy patients with comorbid anxiety and depression. For these patients, it is crucial to take into account these factors and provide appropriate support and interventions.
Objective To broaden the current understanding of the usage willingness about artificial intelligence (AI) robots and relevant influence factors for elderly patients. Methods The elderly patients in the inpatient ward, outpatient department and physical examination of the Department of Geriatrics, West China Hospital of Sichuan University were selected by convenient sampling for investigation between February and April 2020, to explore the willingness of elderly patients to use AI robots and related influencing factors. Results A total of 446 elderly patients were included. There were 244 males and 202 females. The willingness to use AI robots was (14.40±3.62) points. There were statistically significant differences among the elderly patients with different ages, marital status, living conditions, educational level, current health status, current vision status, current hearing status, self-care ability and family support in their willingness to use AI robots (P<0.05). Multiple linear regression analysis showed that age, education level and family support were the influencing factors of use intention (P<0.05). Among the elderly patients, 60.76% had heard of AI robots, but only 28.03% knew the medical application of AI robots, and only 13.90% had used AI robot services. Most elderly patients (>60%) thought that some adverse factors may reduce their usage willingness, like “the price is too expensive” and “the use is complex, or I don’t know how to use”. Conclusions Elderly patients’ cognition of AI robots is still at a low level, and their willingness to use AI robots is mainly affected by age, education level and family support. It is suggested to consider the personalized needs of the elderly in terms of different ages, education levels and family support, and promote the cheap and user-friendly AI robots, so as to improve the use of AI robots by elderly patients.