Analysis of the Point Prevalence and Influencing Factors of Acute Stress Disorder in Elderly Patients with Osteoporotic Fractures

Influencing factors and early predictive model of acute stress disorder in traumatic patients: A clinical comparative cohort study

OBJECTIVE

To analyze the main influencing factors of ASD (Acute Stress Disorder) in inpatients, and provide some evidence for early clinical identification and intervention of ASD.

METHODS

In this study, 489 inpatients were selected from 3 general hospitals in Zunyi City from September 2020 to August 2021. The patients were followed up with questionnaires. Mann Whitney U test, Logistic Regression analysis and Generalized Estimation Equation were used for difference comparison and influencing factor analyses.

RESULTS

Multivariate logistic regression showed that trauma exposure, psychological burden, fear and pain degree were risk factors of ASD in all inpatients. The sensitivity and specificity of combined using of "trauma, psychological burden, fear and pain" in predicting ASD reached 89.40 % and 79.20 %, respectively; and the area under ROC could reach 0.897.

CONCLUSION

Based on the different risk factors, an early effective model could be built for ASD prediction in both traumatic and nontraumatic patients.

Identification of potential cell death-related biomarkers for diagnosis and treatment of osteoporosis

BACKGROUND

This study aimed to identify potential biomarkers for the diagnosis and treatment of osteoporosis (OP).

METHODS

Data sets were downloaded from the Gene Expression Omnibus database, and differentially programmed cell death-related genes were screened. Functional analyses were performed to predict the biological processes associated with these genes. Least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), and random forest (RF) machine learning algorithms were used to screen for characteristic genes, and receiver operating characteristics were used to evaluate the diagnosis of disease characteristic gene values. Gene set enrichment analysis (GSEA) and single-sample GSEA were conducted to analyze the correlation between characteristic genes and immune infiltrates. Cytoscape and the Drug Gene Interaction Database (DGIdb) were used to construct the mitochondrial RNA-mRNA-transcription factor network and explore small-molecule drugs. Reverse transcription real-time quantitative PCR (RT-qPCR) analysis was performed to evaluate the expression of biomarker genes in clinical samples.

RESULTS

In total, 25 differential cell death genes were identified. Among these, two genes were screened using the LASSO, SVM, and RF algorithms as characteristic genes, including BRSK2 and VPS35. In GSE56815, the area under the receiver operating characteristic curve of BRSK2 was 0.761 and that of VPS35 was 0.789. In addition, immune cell infiltration analysis showed that BRSK2 positively correlated with CD56dim natural killer cells and negatively correlated with central memory CD4 + T cells. Based on the data from DGIdb, hesperadin was associated with BRSK2, and melagatran was associated with VPS35. BRSK2 and VPS35 were expectably upregulated in OP group compared with controls (all p < 0.05).

CONCLUSIONS

BRSK2 and VPS35 may be important diagnostic biomarkers of OP.

Non-adaptive cognitive emotion regulation mediates the relationship between disease uncertainty and acute stress disorder in patients with ischaemic stroke

Background

During epidemic outbreaks, hospitalized patients, especially those with cerebrovascular disease, were identified as a vulnerable group suffering from acute stress disorder (ASD) and consequent psychological distress. For stroke patients, not only will they suffer from physical illness, but the uncertainty of illness caused by sudden illness may also cause patients to experience different degrees of ASD. Relevant studies have shown that the impact of ASD on individuals may vary according to age, gender, disease characteristics, individual personality, treatment methods, income level, family support, cognitive psychology and other factors. However, non-adaptive cognitive emotion regulation plays a crucial role in influencing individual psychological states. At present, the risk factors of ASD after stroke and the mechanism between illness uncertainty and cognitive emotion regulation are not fully understood. Therefore, we focus on exploring the predictive effects of general demographic and disease-related characteristics, maladaptive cognitive emotion regulation, and illness uncertainty on ASD after stroke, and make hypotheses. When a disease acts on the body, the patient will have the corresponding cognition of the disease, and ASD will appear at the same time. Then the maladaptive cognitive emotion regulation as an important mediating variable can aggravate the level of acute stress disorder and be verified.

Methods

We used a cross-sectional design, which can be used to investigate the distribution of a disease or health condition and its related factors in a specific population at a specific time, so as to describe the distribution of the disease or health condition and its relationship with related factors. A total of 256 hospitalized patients with ischemic stroke were enrolled, including 145 males and 111 females, aged from 26 to 90 years, with a mean age of (64.71 ± 12.20) years. All patients completed and returned a self-report questionnaire that included demographic information, illness uncertainty, cognitive emotion regulation, and ASD. We then compared the differences in general demographic data, illness uncertainty, and maladaptive cognitive emotion regulation in acute stress disorders.

Results

The majority of hospitalized stroke patients (67.6%) developed ASD due to the COVID-19 pandemic and were therefore at risk for PTSD. More than one third (39.1%) of stroke survivors also suffered from severe psychological distress. More specifically, younger stroke patients are more likely to experience ASD than older patients. Although higher illness uncertainty scores indicate more severe ASD, adaptive cognitive emotion regulation was a protective factor.

Conclusion

Given that individuals with ASD are susceptible to PTSD, it is critical to follow up hospitalized patients with ischemic stroke for screening for PTSD and referral to appropriate psychological services. Maladaptive cognitive emotion regulation can increase the impact of uncertainty on the traumatic experience of stroke patients. Therefore, health care institutions should increase their efforts to provide psychosocial support services to hospitalized patients and make continuous efforts to screen for symptoms of trauma and psychological distress in hospitalized stroke patients.

Acute stress disorder in patients with accidental traumatic fractures: What can we do

AIM

To evaluate the potential influencing factors of acute stress disorder (ASD) in patients with accidental traumatic fractures to provide evidence for clinical nursing care.

DESIGN

A retrospective study.

METHODS

Patients with traumatic fractures treated in our hospital from 1 January 2020 to 30 November 2021 were included. The characteristics of ASD and no ASD patients were assessed.

RESULTS

A total of 468 patients with traumatic fractures were included, the incidence of ASD was 28.20%. Logistic regression analysis showed that age ≤50 years (OR2.918, 95% CI1.994 ~ 3.421), female (OR2.074, 95% CI1.489 ~ 3.375), AIS-ISS at admission ≥20 (OR3.981, 95% CI2.188 ~ 5.091), VAS at admission≥7 (OR2.804, 95% CI2.027 ~ 3.467), introverted personality (OR1.722, 95%CI1.314 ~ 2.432) and CD-RISC at admission≤60 (OR3.026, 95% CI2.338 ~ 4.769) were the risk factors of ASD in patients with traumatic fractures (all p < .05).

CONCLUSIONS

The development of ASD in patients with traumatic fractures is affected by multiple factors. Medical workers should take early and timely management and nursing measures for related risk factors to reduce the occurrence of ASD.

Prevalence of depression and anxiety and associated factors among geriatric orthopedic trauma inpatients: A cross-sectional study

BACKGROUND

Common mental disorders such as anxiety and depression in geriatric orthopedic trauma patients have received little attention in research.

AIM

To investigate the prevalence of emotional disorders among geriatric orthopedic trauma patients and identify demographic, social and clinical risk factors.

METHODS

This cross-sectional study was performed in geriatric patients (aged ≥ 60 years, both sexes) with orthopedic trauma admitted to a level I trauma center between May 2015 and December 2017. Demographic, social, and clinical characteristics were described. Huaxi Emotional-Distress Index (HEI) was used to evaluate the severity of anxiety and depression status. Differences in continuous variables were tested using the t-test, and differences in categorical variables were assessed using the Pearson χ² test. Binary logistic regression analyses were used to identify the factors associated with a HEI score > 8.

RESULTS

Among the 966 patients, 487 were male and 479 were female, with a mean age of 70.2 ± 7.1 years. The age ranged from 60 to 90 years. Seventy-five patients had an HEI score > 8, accounting for about 7.8% of all patients. A higher Injury Severity Score (4.17 ± 3.10 vs 7.96 ± 6.68, P < 0.001), higher Visual Analog Score (5.05 ± 1.09 vs 6.89 ±1.23, P < 0.001), number of chronic diseases (P < 0.001), injury type (P = 0.038), and education level (P = 0.001) were significantly associated with HEI score > 8. On logistic regression, a higher education level was a protective factor for emotional disorders (P = 0.047), whereas Injury Severity Score (P = 0.024), Visual Analog Score (P < 0.001), two or more chronic diseases (P < 0.001) were the related independent risk factors.

CONCLUSION

Emotional disorders are common in geriatric patients with orthopedic trauma. Clinicians should remain vigilant of emotional disorders in geriatric patients and screen for anxiety and depression in higher risk groups.