The decrease in sleep quality leads to an increased risk of cardiovascular disease and is closely related to the prognosis of various diseases. However, the relationship between preoperative sleep quality and postoperative clinical outcomes in patients with acute aortic dissection is still unclear. We aimed to assess the relationship between sleep quality and the clinical outcomes of acute aortic dissection. We assessed participants' sleep quality and the clinical outcomes of acute aortic dissection, which included prolonged mechanical ventilation, postoperative delirium, in-hospital death, continuous renal replacement therapy, intensive care unit stay time, and length of stay. Patients were divided into good sleep quality group (n = 103) and poor sleep quality group (n = 113). Postoperative delirium, in-hospital death, prolonged mechanical ventilation and intensive care unit stay time were significantly increased in the poor sleep quality group when compared with the good sleep quality group (p < 0.05). Multivariate regression analysis showed that the poorer sleep quality, the greater the risk of in-hospital death (odds ratio = 3.451, 95% confidence interval 1.19-10.004) and prolonged mechanical ventilation (odds ratio = 6.302, 95% confidence interval 3.105-12.791), and the longer intensive care unit stay time (β = 62.37, 95% confidence interval 22.411-102.329). In addition, the higher the incidence of smoking history (odds ratio = 7.417, 95% confidence interval 2.425-22.684), poor sleep quality (odds ratio = 11.59, 95% confidence interval 3.844-34.942) and postoperative delirium (odds ratio = 5.1, 95% confidence interval 1.793-14.504), the greater the risk of prolonged mechanical ventilation. Our findings revealed that poor sleep quality may be a risk factor for adverse clinical outcomes of acute aortic dissection. Rapid assessment of self-reported sleep quality may be a simple and effective way to identify patients with acute aortic dissection who are at high risk for prolonged mechanical ventilation.

To systematically investigate the efficacy of aromatherapy in patients with acute coronary syndrome (ACS).

We conducted a comprehensive search for papers published until November 2023 using the following databases: PubMed, Embase, and Cochrane Library. This study was conducted following the PRISMA and Cochrane Guidelines. The inclusion criteria were randomized controlled trials (RCTs) performed to assess the comparative effectiveness of inhalation aromatherapy versus controls in individuals diagnosed with ACS. The Jadad rating method was used to assess the quality of the included studies, and a meta-analysis was performed using the RevMan 5.4 software. Heterogeneity was quantified using the Higgins I2 (%) test.

A total of 12 RCTs with 476 patients with ACS were included. Aromatherapy has been shown to reduce anxiety scores significantly (standard mean difference [SMD]: -1.18, 95 % confidence interval [CI]: -1.33 to -1.03; P < 0.00001) along with reduction in systolic blood pressure (MD = -8.78, 95 % CI [-13.92, -3.65], P = 0.008); diastolic blood pressure (MD = -7.76, 95 % CI [-11.39, -4.12], P < 0.001); mean artery pressure MD = -9.68, 95 % CI [-13.93.-5.44]; P < 0.0001). However, no significant effects were reported on the heart rate (MD = -6.98, 95 % CI [-15.46, 1.50], P = 0.11) and respiratory rate (MD = -0.67, 95 % CI [-2.52, 1.19], P = 0.48). A greater frequency of aromatherapy was associated greater anxiety -1.80 incidence, with 95 % CI [-2.04, -1.56]. Citrus essential oils exhibited the strongest effect (SMD = -1.97, 95 % CI [-3.34, -0.60], P = 0.005) in reducing anxiety levels.

Aromatherapy appears to be an effective non-pharmacological intervention for reducing blood pressure and anxiety in individuals with ACS. This suggests that aromatherapy more than twice a day is effective in reducing anxiety levels. However, aromatherapy had no statistically significant impact on the heart or respiratory rates. Moreover, additional high-quality RCTs should be conducted to verify these results and explore the efficacy and mechanism of aromatherapy in patients with ACS.

The aim of this study was to evaluate the effects of vitamin D and/or calcium supplementation on sleep quality in individuals with prediabetes.

A 24-week randomized controlled trial (RCT) was conducted in a 212 Chinese population with prediabetes. Participants were randomly assigned to four groups: vitamin D + calcium group (1600 IU/day + 500 mg/day, n = 53), vitamin D group (1600 IU/day, n = 54), calcium group (500 mg/day, n = 51), and control group (placebo, n = 54). The Pittsburgh Sleep Quality Index (PSQI) was used as the primary outcome to assess sleep quality. Questionnaires and fasting blood samples were collected at baseline and post-intervention for demographic assessment and correlation index analysis.

After a 24-week intervention, a significant difference was observed in serum 25(OH)D concentration among the four groups (P < 0.05), and the total PSQI score in vitamin D + calcium group was lower compared to the preintervention levels. Subgroup analyses revealed improved sleep quality with calcium supplementation (P < 0.05) for specific groups, including women, individuals with a low baseline 25(OH)D level (< 30 ng/mL), and individuals in menopause. Moreover, correlation analysis revealed a negative correlation between the extent of change in sleep efficiency scores before and after the calcium intervention and the degree of change in insulin efficiency scores (r = - 0.264, P = 0.007), as well as the magnitude of change in islet beta cell function (r = - 0.304, P = 0.002).

The combined intervention of vitamin D and calcium, as well as calcium interventions alone, exhibits substantial potential for improving sleep quality in individuals with prediabetes.

The trial was registered in August 2019 as ChiCTR190002487.

Loneliness is prevalent in patients with coronary heart disease (CHD). It has a serious impact on the physical and mental health and the quality of life of patients with CHD. However, what factors contribute to loneliness and the mechanism of action still need to be explored.

To explore the chain mediating effect among self-disclosure, social support, sense of coherence and loneliness in patients with CHD through a chain mediating model.

This cross-sectional study included 248 patients with CHD from three tertiary hospitals in Shiyan, Hubei Province, China. Self-reported scales were used to assess feelings of loneliness, self-disclosure, social support and sense of coherence. The Amos 26.0 software was used to construct the chain mediating effect.

Self-disclosure cannot directly affect patients' loneliness (β = -0.60, P>0.05). Social support and sense of coherence play a significant complete mediating role between self-disclosure and loneliness, with an overall mediating effect value of -0.479.

Self-disclosure in CHD patients indirectly affect loneliness through social support and sense of coherence (β = -0.479, P = 0.001). Improving patient self-disclosure and modulation of social support and sense of coherence help reduce in loneliness.

This study examined the potential relationship between sleep, exercise, and depression with coronary heart disease (CHD) using the 2020 Behavioral Risk Factor Surveillance System (BRFSS) (n = 391 750) during the COVID-19 pandemic. CHD was defined as the presence of self-reported CHD or myocardial infarction (MI). Descriptive statistics were used to report variable frequencies and percentages. Logistic regression models were used to assess potential relationships between lifestyle behaviors (individually and for effect modification) and CHD, with additional sensitivity analysis comparing depressed subjects with non-depressed subjects. Sleep and exercise were assessed in the model for potential effect modification. Those with insufficient sleep and those who did not exercise were more likely to report CHD (sleep OR = 1.09; 95% CI: 1.06, 1.12); (exercise OR = 2.00; 95% CI: 1.95, 2.05), though the interaction term was non-significant. Those with self-reported depression were found to be associated with CHD (OR = 1.34; 95% CI: 1.30, 1.38). Among depressed individuals, insufficient sleep and no exercise exhibited a stronger association (sleep OR = 1.19; 95% CI: 1.13,1.25); (exercise OR = 2.13; 95% CI = 2.03, 2.23). Results support an association between sleep, exercise, and self-report of CHD, and this association is potentially magnified among depressed individuals, which may be further exacerbated by the COVID-19 pandemic.

To determine the effectiveness of non-pharmacological interventions on sleep outcomes among patients with coronary artery disease and recognize pertinent characteristics that potentially affect the effectiveness of such interventions.

Relevant studies conducted before 27 April 2022 were identified through four core electronic databases using terms related to coronary artery disease, sleep outcomes, and randomized controlled trials. Two authors independently conducted study selection, data extraction, and risk-of-bias assessment. Meta-analysis, sub-group analysis, publication bias analysis, and sensitivity analysis were conducted using R version 4.2.2. Of the 4755 retrieved articles, 42 studies were selected for systematic review and 30 studies were included in the meta-analysis. The findings of this study revealed that non-pharmacological interventions significantly improved self-reported sleep quality (standardized mean difference = -0.85, 95% confidence interval -1.08, -0.63), but had no effects on objectively measured sleep efficiency and duration. Regarding the types of interventions involved, environmental control was the most effective in improving self-reported sleep quality, followed by relaxation, self-care behaviour management, and relaxation and cognitive/psychological complex interventions. Through subgroup analysis, we did not find any covariates that were significantly related to self-reported sleep quality.

Non-pharmacological interventions have been shown to play beneficial roles in improving self-reported sleep quality among patients with coronary artery disease. Additional studies are required to elucidate the effect of non-pharmacological interventions on objectively measured sleep outcomes and to characterize their optimal frequencies and durations.

PROSPERO CRD42022366851.

Studies have shown that sleep disorders are closely related to anxiety and depression, and the quality of life (QoL) of patients with sleep disorders is generally poor.

To examine the occurrence of sleep disorders in people with coronary heart disease (CHD) and their relationships with QoL, depression, and anxiety.

As per the sleep condition, 240 CHD individuals were separated into two groups: non-sleep disorder group (n = 128) and sleep disorder group (n = 112). The self-rating anxiety scale (SAS), self-rating depression scale (SDS), and World Health Organization criteria for the Quality of Life Brief scale (WHOQOL-BREF) scores of the two groups were compared. Logistic regression method was used to analyze the independent risk factors of CHD patients with sleep disorders. Multivariate logistic regression analysis was employed to develop the risk prediction model. The association among the Pittsburgh Sleep Quality Index, SAS, and SDS was examined using Spearman's correlation analysis.

The incidence of sleep disorder was 46.67% in 240 patients. The scores of SAS and SDS in the sleep disorder group were higher than those in the non-sleep disorder group, and the WHOQOL-BREF scores were lower than those in the non-sleep disorder group (P < 0.05). The risk prediction model of sleep disturbances in CHD patients was constructed using the outcomes of multivariate logistic regression analysis, P = 1/[1 + e (-2.160 + 0.989 × (female) + 0.001 × (new rural cooperative medical insurance) + 2.219 × (anxiety) + 2.157 × depression)]. The results of a Spearman's correlation study revealed that sleep quality was strongly adversely connected with the physiological field, psychological field, and social relation scores in QoL, and was considerably positively correlated with SAS and SDS (P < 0.05).

A multivariate logistic regression model can better predict the occurrence of sleep disorders in CHD patients. Sleep disorders in CHD patients are significantly correlated with QoL, depression, and anxiety.

Type A behavior pattern (TABP) is a personality type characterized by rapid speech, impatience, competition, and hostility. Asymptomatic cerebral small vessel disease (CSVD) is often endemic in older adults. Individuals with TABP commonly experience suboptimal sleep quality, and a correlation exists between sleep disturbances and CSVD. We investigated the relationship between TABP and CSVD markers and further explored the mediating role of sleep quality in the relationship between TABP and CSVD.

A cross-sectional survey included 764 community-dwelling adults aged 55-85 years. The TABP Scale and the Pittsburgh Sleep Quality Index (PSQI) were used to assess personality and sleep quality, respectively. Linear and logistic regression analyses were used to examine relationships between variables of interest. In addition, mediation analyses with bootstrapping were used to test whether sleep quality mediated the relationship between TABP and CSVD.

Of the 764 participants [median age 65 (61-69) years, 59.9% female], the population with type A personality accounted for 44.8%. After adjusting for covariates, TABP scores (p = 0.03) and PSQI scores (p < 0.001) were significantly correlated with CSVD. In addition, sleep quality partially mediated the association between type A behavior and CSVD, and the mediating effect was 10.67%.

This study showed that type A behavior was a risk factor for CSVD among older community-dwelling adults and that sleep quality mediated the relationship between type A behavior and CSVD. Changing type A behavior may help improve sleep quality, which may in turn reduce the prevalence of CSVD.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a group of chronic conscious fatigue that is not easily relieved by rest and is accompanied by corresponding physiological dysfunction and psychological symptoms. However, due to the insufficient understanding of the pathogenesis of ME/CFS, there is currently a lack of effective treatment methods. In addition, there are few surveys on the current status of ME/CFS in the central region of China, and the data on ME/CFS among university students in the central region are lacking. This group conducted a survey on university students in Wuhan, Hubei Province in 2022 to collect and analyze the current status of ME/CFS among university students in central China for the first time, aiming to understand the current development of ME/CFS among university students, investigate the influencing factors of its prevalence, fill the data gaps, and provide a reliable basis for developing interventions for chronic fatigue syndrome among university students.

A cross-sectional study was conducted among university students in a university in Hubei province. Data were collected via online questionnaire surveys. The contents included demographic characteristics, lifestyles, disease history, depression, anxiety, sleep, ME/CFS and other associated factors. SAS 9.4 statistical software was used to analyze and estimate the effect of associated factors on ME/CFS.

A total of 1826 subjects were included in the final analysis. The results showed that the prevalence of ME/CFS in university students was 6.25%. Univariate analysis showed that exercise, alcohol consumption, study, overnights, diet, anxiety, depression, and sleep quality were associated with ME/CFS (P < 0.05). Multivariate analysis showed that overnights, overeating, anxiety, and sleep quality were independent risk factors, while learning was a protective factor.

College students should pay enough attention to ME/CFS, improve their understanding of ME/CFS, and improve people's ability to understand ME/CFS.

Patients with coronary heart disease (CHD) experience stress and suffer from the risk of recurrence and death. Comprehensive nursing intervention based on self-disclosure (CNISD) is an interdisciplinary service and an effective approach to care that improves quality of life and alleviates suffering for patients with CHD. The purpose of this study was to analyze the effects of CNISD on alexithymia in patients with CHD.

A total of 1088 patients with CHD were recruited and received CNISD (n = 540) and usual care (n = 548). The quality of life, alexithymia, four statutory health insurance funds, recurrence, mortality, and satisfaction was compared in patients with CHD between CNISD and usual care group.

Outcomes showed that CNISD improved sleep quality and quality of life, increased physical activity, reduced the hospital anxiety and depression scale in patients with CHD compared to usual care. Recurrence and mortality of patients with CHD were markedly improved by CNISD compared to patients with CHD in usual care group.

In conclusion, data in this study indicate that CNISD presents benefits in improving quality of life, physical activity, anxiety, depression, recurrence, and mortality for patients with CHD.

Depression is associated with an increased risk of death in patients with coronary heart disease (CHD). This study aimed to explore the factors influencing depression in elderly patients with CHD and to construct a prediction model for early identification of depression in this patient population.

We used propensity-score matching to identify 1,065 CHD patients aged ≥65 years from four hospitals in Chongqing between January 2015 and December 2021. The patients were divided into a training set (n = 880) and an external validation set (n = 185). Univariate logistic regression, multivariate logistic regression, and least absolute shrinkage and selection operator regression were used to determine the factors influencing depression. A nomogram based on the multivariate logistic regression model was constructed using the selected influencing factors. The discrimination, calibration, and clinical utility of the nomogram were assessed by the area under the curve (AUC) of the receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) and clinical impact curve (CIC), respectively.

The predictive factors in the multivariate model included the lymphocyte percentage and the blood urea nitrogen and low-density lipoprotein cholesterol levels. The AUC values of the nomogram in the training and external validation sets were 0.762 (95% CI = 0.722-0.803) and 0.679 (95% CI = 0.572-0.786), respectively. The calibration curves indicated that the nomogram had strong calibration. DCA and CIC indicated that the nomogram can be used as an effective tool in clinical practice. For the convenience of clinicians, we used the nomogram to develop a web-based calculator tool (https://cytjt007.shinyapps.io/dynnomapp_depression/).

Reductions in the lymphocyte percentage and blood urea nitrogen and low-density lipoprotein cholesterol levels were reliable predictors of depression in elderly patients with CHD. The nomogram that we developed can help clinicians assess the risk of depression in elderly patients with CHD.