Objective To screen the independent influencing factors for gastrointestinal bleeding(GIB)in hospitalized patients with coronary heart disease(CHD)and to construct and validate a no-mogram prediction model.Methods A total of 440 CHD patients who developed GIB during hospi-talization were selected as GIB group,and another 320 CHD patients hospitalized in the department of cardiovascular medicine were randomly selected as non-GIB group.The clinical data of the two groups were analyzed and compared.Multivariate logistic regression analysis was used to screen the indepen-dentinfluencing factors for GIB.Based on these factors,a nomogram prediction model for the risk of GIB in hospitalized CHD patients was constructed.The entire dataset was randomly divided into train-ing set(n=532)and validation set(n=228)in a 7∶3 ratio.The performance of the nomogram model was evaluated using the receiver operating characteristic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results Multivariate logistic regression analysis showed that body mass index(BMI),history of digestive system diseases,CHD classification,albumin,white blood cell count,monocyte-to-lymphocyte ratio(MLR),and low-density lipoprotein were all independent influencing factors for GIB in CHD patients(P＜0.05).ROC curve analysis indicated that the nomo-gram model(excluding low-density lipoprotein)constructed based on independent influencing factors exhibited good discrimination in both the training set(area under the curve:0.839,95％CI,0.805 to 0.873)and the validation set(area under the curve:0.810,95％CI,0.751 to 0.868).Calibration curve analysis demonstrated good consistency between the predicted probabilities and the observed incidence of GIB in hospitalized CHD patients in both the training and validation sets.DCA results revealed that the nomogram model had a good clinical net benefit.Conclusion The nomogram model constructed based on independent influencing factors has good predictive performance for the risk of GIB in hospitalized CHD patients and can provide a basis for clinicians to promptly identify GIB and adjust medication regimens.

Objective:To conduct a scope review on the application of ICU diaries in critically ill patients, laying the foundation for further exploration and construction of ICU diary patterns and frameworks that were in line with the national conditions and tailored to different regions and cultural backgrounds.Methods:The Joanna Briggs Institute Reviewer′s Manual was used as the methodological framework, and a computer search was conducted in nine domestic and international databases, including China National Knowledge Infrastructure, Wanfang Database, China Biomedical Literature Database, Cochrane Library, PubMed, and Embase, etc. The search period was from the inception of the databases until March 13, 2023. The included literature was screened, summarized, and analyzed.Results:A total of 19 articles were included. ICU diaries were commonly recorded using a combination of text and visuals, with the involvement of both healthcare professionals and family members. Most patients received ICU diaries approximately one month after their transfer from the ICU. Out of the 15 studies, ICU diaries were found to be effective, while 4 studies indicated no significant improvement in patients′ psychological issues. However, ICU diaries were still considered acceptable by patients and their families.Conclusions:The application of ICU diaries has shown positive significance in critically ill patients, but further research and exploration are needed to investigate its impact on issues such as post-traumatic stress disorder, anxiety, depression, and quality of life. In the future, a combination of multiple forms and high-quality research designs with large samples, long periods, and structured approaches should be employed to explore its application effects and long-term outcomes on psychological problems.

Background::Polycystic ovarian syndrome (PCOS) is a heterogeneous and complex reproductive endocrinological disease that could lead to infertility. There were many attempts to classify PCOS but it remains unclear whether there is a specific subgroup of PCOS that is associated with the best or worst reproductive outcomes of assisted reproductive techniques (ART).Methods::Infertile PCOS patients who underwent their first cycle of in vitro fertilization (IVF) in West China Second University Hospital, Sichuan University from January 2019 to December 2021 were included. Basic clinical and laboratory information of each individual were extracted. Unsupervised cluster analysis was performed. Controlled ovarian stimulation parameters and reproductive outcomes were collected and compared between the different clusters of PCOS. Results::Our analysis clustered women with PCOS into "reproductive", "metabolic", and "balanced" clusters based on nine traits. Reproductive group was characterized by high levels of testosterone (T), sex hormone-binding globulin (SHBG), follicular stimulation hormone (FSH), luteinizing hormone (LH), and anti-Müllerian hormone (AMH). Metabolic group was characterized by high levels of body mass index (BMI), fasting insulin, and fasting glucose. Balanced group was characterized by low levels of the aforementioned reproductive and metabolic parameters, except for SHBG. Compared with PCOS patients in reproductive and balanced clusters, those in metabolic cluster had lower rates of good quality day 3 embryo and blastocyst formation. Moreover, PCOS patients in the reproductive cluster had greater fresh embryo transfer (ET) cancelation rate and clinical pregnancy rate after fresh ET than metabolic cluster (odds ratio [OR] = 3.37, 95% confidence interval [CI]: 1.77-6.44, and OR = 6.19, 95% CI: 1.58-24.24, respectively). And compared with PCOS of metabolic cluster, PCOS of balanced cluster also had higher chance for fresh ET cancelation (OR = 2.83, 95% CI: 1.26-6.35).Conclusion::Our study suggested that PCOS patients in metabolic cluster may be associated with adverse reproductive outcomes and might need individualized treatment and careful monitoring before and during ART.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

Objective: Primary spinal cord glioblastoma (PSCGBM) is a rare malignancy with a poor prognosis. To date, no prognostic nomogram for this rare disease was established. Hence, we aimed to develop a nomogram to predict overall survival (OS) of PSCGBM. Methods: Clinical data of patients with PSCGBM was retrospectively collected from the neurosurgery department of Soochow University Affiliated Second Hospital and the Surveillance Epidemiology and End Results database. Information including age, sex, race, tumor extension, extent of resection, adjuvant treatment, marital status, income, year of diagnosis and months from diagnosis to treatment were recorded. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for PSCGBM. A nomogram was constructed to predict 1-year, 1.5-year, and 2-year OS of PSCGBM. Results: A total of 132 patients were included. The 1-year, 1.5-year, and 2-year OS were 45.5%, 29.5%, and 18.9%, respectively. Four variables: age groups, tumor extension, extent of resection, and adjuvant therapy, were identified as independent prognostic factors. The nomogram showed robust discrimination with a C-index value for the prediction of 1-year OS, 1.5-year OS, and 2-year of 0.71 (95% confidence interval [CI], 0.61–0.70), 0.72 (95% CI, 0.62–0.70), and 0.70 (95% CI, 0.61–0.70), respectively. The calibration curves exhibited high consistencies between the predicted and observed survival probability in this cohort. Conclusion We have developed and internally validated a nomogram for predicting the survival outcome of PSCGBM for the first time. The nomogram has the potential to assist clinicians in making individualized predictions of survival outcome of PSCGBM.

At present ICU transition management in China is still in the exploration stage, and the existing research results are difficult to be promoted in the clinic, and the management plan lacks unified and feasible standards. This paper introduces the concept and model of ICU transition management, and provides an overview of the current situation of ICU transition management for patients transferred out of ICU, adverse outcomes for patients transferred out of ICU, and the content of ICU transition management for patients transferred out of ICU, aiming to provide a reference for the formation of a unified and standardized ICU transition management scheme.

Purpose: This study compared the clinical parameters and histological findings according to the benzalkonium chloride concentration (BAC; 0.05%, 0.1%, and 0.2%) for inducing experimental dry eye (EDE) in a rabbit model. Methods: Rabbits were divided into four groups according to the BAC concentration: untreated group, 0.05%, 0.1%, and 0.2% BAC. BAC was instilled topically in both eyes of the rabbits twice daily until they were euthanized after 14 days. Tear volume, tear break-up time (TBUT), and corneal fluorescein staining score (CFS) were measured 0, 3, 5, 7, and 14 days after treatment. After excising tissues on day 14, the conjunctival goblet cell density and corneal epithelial apoptosis were quantified. Results: The tear volume and TBUT were lower and the CFS was higher than baseline values after 14, 10, and 5 days in the 0.05, 0.1, and 0.2% BAC groups, respectively (all p < 0.05). At 14 days, the 0.2% BAC group showed more significant aggravation of all clinical parameters, and the 0.1% BAC group had a lower CFS (all p < 0.05) than the 0.05% BAC group. In all BAC groups, the conjunctival goblet cell density was lower and corneal epithelial apoptosis was significantly higher than in the untreated group (all p < 0.01). The conjunctival goblet cell density was lower in the 0.2% BAC group than in the 0.05% BAC group. Between-group differences in corneal epithelial apoptosis were observed in all experimental groups (all p < 0.01). Conclusions Instilling BAC for 14 days induced EDE in the 0.05, 0.1, and 0.2% BAC groups. Although 0.2% BAC cannot be used for a severe EDE model, it is useful for inducing EDE in a rabbit model in a short time.