Sleep Disturbance Strongly Related to the Development of Postoperative Delirium in Proximal Femoral Fracture Patients Aged 60 or Older

The Impact of Sleep on Haematological Parameters in Firefighters

Sleep is a vital process that impacts biological functions such as cell renewal, bone regeneration, and immune system support. Disrupted sleep can interrupt erythropoiesis, leading to fewer red blood cells, reduced haemoglobin concentration, and decreased haematocrit levels, potentially contributing to haematological disorders. This is particularly concerning for shift workers for example firefighters. While previous studies have explored sleep's adverse effects on various professions, research specific to firefighters is limited. This study investigates the relationship between sleep quality and haematological parameters among firefighters in Northeast Portugal. From a sample of 201 firefighters, variations in red blood cells, haemoglobin, and haematocrit values were linked to sleep quality. The study utilised non-parametric tests (Wilcoxon-Mann-Whitney, Spearman's correlation) to explore the connection between sleep quality and haematological profile. The impact of covariates on haematological parameters was assessed using non-parametric ANCOVA (Quade's). A multiple regression analysis was employed to further understand how sleep quality and various confounding variables impact haematological levels. Findings suggest a negative link between sleep quality and haematological levels, meaning that as sleep quality deteriorates, there is a tendency for haematological levels to decrease, as indicated by Spearman's correlation (rRBC = -0.157, pRBC = 0.026; rHb = -0.158, pHb = 0.025; rHCT = -0.175, pHCT = 0.013). As observed in scientific literature, the correlation found suggests a possible inhibition of erythropoiesis, the process responsible for red blood cell production. Despite firefighters presenting a haematological profile within the reference range (RBC: 5.1 × 106/mm3 (SD ± 0.4), Hb: 15.6 g/dL (SD ± 1.3), 47% (SD ± 1.0), there is already an observable trend towards lower levels. The analysis of co-variables did not reveal a significant impact of sleep quality on haematological levels. In conclusion, this study underscores the importance of sleep quality in determining haematological parameters among firefighters. Future research should investigate the underlying mechanisms and long-term implications of poor sleep quality on firefighter health. Exploring interventions to enhance sleep quality is vital for evidence-based strategies promoting firefighter well-being.

Effect of obstructive sleep apnea on postoperative delirium: a system review and meta-analysis

PURPOSE

To investigate the impact of obstructive sleep apnea (OSA) on postoperative delirium (PD), and evaluate the effectiveness of positive airway pressure (PAP) therapy on PD among OSA patients.

METHODS

We systematically searched Embase, Cochrane Library and PubMed databases from their establishment to November 27, 2022. A random-effects approach was employed to determine aggregated results. Subgroup and sensitivity analyses were carried out to investigate heterogeneity.

RESULTS

Sixteen eligible studies were included in the analysis. Thirteen studies revealed that OSA significantly elevated the likelihood of developing PD (OR = 1.71; 95%CI = 1.17 to 2.49; p = 0.005). Subgroup analysis according to delirium assessment scales showed that OSA did not exhibit an association with the incidence of PD assessed by the Confusion Assessment Method-Intensive Care Unit (OR = 1.14; 95%CI = 0.77 to 1.67; p = 0.51) but enhanced the likelihood of developing PD evaluated with other measurement scales (OR = 2.15; 95%CI = 1.44 to 3.19; p = 0.0002). Three additional studies explored the impact of PAP treatment on PD among OSA individuals, indicating no significant reduction in PD incidence with PAP use (OR = 0.58; 95%CI = 0.13 to 2.47; p = 0.46).

CONCLUSIONS

OSA may not be a risk factor for PD in critically ill patients in the intensive care unit, but may increase the likelihood of developing PD among individuals receiving regular care in the ward postoperatively. The efficacy of PAP therapy in decreasing PD incidence among OSA patients remains debatable.

Association Between Preoperative Long-Term Poor Sleep Quality and Postoperative Delirium in Elderly Patients Undergoing Cardiac Surgery: A Multi-Center Observational Study

BACKGROUND

Delirium is a common complication in elderly patients after cardiac surgery, and sleep disorders have been suggested as a potential risk factor. However, few studies have explored the link between long-term preoperative poor sleep quality and postoperative delirium (POD) in this population. This study aimed to investigate the association between preoperative sleep quality and POD in elderly cardiac surgery patients.

METHODS

The study enrolled 194 patients aged 60 years or older who underwent cardiac surgery. The Pittsburgh Sleep Quality Index (PSQI) objectively assessed preoperative sleep quality, while the Confusion Assessment Method screened for POD. The measurable outcomes encompassed the identification of risk factors associated with POD, while the secondary outcomes focused on factors influencing levels of consciousness. The statistical analysis is logistic regression analysis.

RESULTS

Patients with POD had a higher prevalence of preoperative sleep disorders and higher PSQI scores than those without delirium (12.9 ± 5.1 vs 7.8 ± 3.4, P = .007). Logistic regression analysis demonstrated that the number of months with high PSQI scores and age were significantly associated with POD. The predictive ability of the number of months with high PSQI scores for POD was .762 (95% CI: .671-.854). Multivariate linear regression analysis revealed that preoperative sleep disorder was a significant predictor of exacerbation of POD (P < .05).

CONCLUSION

This study suggests that long-term poor preoperative sleep quality, as assessed by the PSQI, is associated with an increased risk of POD in elderly patients undergoing cardiac surgery.

Wearable Sensors in Other Medical Domains with Application Potential for Orthopedic Trauma Surgery-A Narrative Review

The use of wearable technology is steadily increasing. In orthopedic trauma surgery, where the musculoskeletal system is directly affected, focus has been directed towards assessing aspects of physical functioning, activity behavior, and mobility/disability. This includes sensors and algorithms to monitor real-world walking speed, daily step counts, ground reaction forces, or range of motion. Several specific reviews have focused on this domain. In other medical fields, wearable sensors and algorithms to monitor digital biometrics have been used with a focus on domain-specific health aspects such as heart rate, sleep, blood oxygen saturation, or fall risk. This review explores the most common clinical and research use cases of wearable sensors in other medical domains and, from it, derives suggestions for the meaningful transfer and application in an orthopedic trauma context.

The research progress of perioperative non-pharmacological interventions on postoperative cognitive dysfunction: a narrative review

Postoperative cognitive dysfunction (POCD) is a common neurological complication in elderly patients after surgery and general anesthesia. The occurrence of POCD seriously affects the postoperative recovery of patients, and leads to prolonged hospital stay, reduced quality of life, increased medical costs, and even higher mortality. There is no definite and effective drug treatment for POCD. More evidence shows that perioperative non-pharmacological intervention can improve postoperative cognitive function and reduce the incidence of POCD. Therefore, our studies summarize the current non-pharmacological interventions of POCD from the aspects of cognitive training, physical activity, transcutaneous electrical acupoint stimulation, noninvasive brain stimulation, non-pharmacological sleep improvement, music therapy, environment, and multimodal combination Interventions, to provide more data for clinical application and research.

Analysis of Changes in Sleep Quality and Patterns after Hip Fracture Using Real Evidence of Artificial Intelligence Linked (REAL) Hip Cohort Data

Background and Objectives: Hip fractures are commonly found in elderly patients, and often result in chronic pain and decreased physical function, as well as worsening of overall health. It is known that early surgical intervention during the acute phase and rehabilitation are important for improving clinical outcomes for these patients. However, the importance of management for improving the quality of life of these patients is becoming more emphasized. Studies on changes in sleep patterns after hip fractures are rare overseas. Therefore, the aim of this study is to investigate the prevalence of sleep disturbance in patients with hip fractures and to analyze the changes in sleep disturbance after surgery by comparing the preoperative and postoperative results. Materials and Methods: During the period from August 2022 to January 2023, patients who underwent surgical treatment for hip fractures and were recruited into the REAL Hip Cohort were selected as research subjects. The sleep survey was conducted using the Pittsburgh Sleep Quality Index (PSQI). The PSQI is composed of 18 questions, each divided into areas of sleep quality, sleep latency, duration, efficiency, disturbance, use of medication, and daytime dysfunction. Each area is scored 0-3 points and the total is 0-21. A score greater than five indicates sleep disorder. The PSQI was surveyed during hospitalization and three months after surgery for post-fracture sleep status. To analyze changes before and after the fracture, paired T-tests and chi-square tests were performed. Results: From August 2022 to January 2023, a total of 40 patients who were recruited into the REAL Hip Cohort responded to the PSQI survey. The average age was 77.4 years and 36 were female. Sleep quality worsened from 0.75 ± 1.0 before surgery to 1.4 ± 1.0 three months after surgery (p = 0.019), and sleep efficiency also worsened from 0.4 ± 0.6 to 1.4 ± 1.0 (p < 0.001). The PSQI increased from an average of 5.2 ± 2.8 before surgery to 8.2 ± 4.2 three months after surgery (p = 0.007), and the number of patients who could be diagnosed with sleep disorders also increased from 12 (40%) to 24 (60%) (p = 0.030). Conclusions: A decline in overall sleep status was observed in patients in a survey on sleep patterns three months after hip fracture. Additional management is needed to improve their sleep patterns.

Effect of preoperative sleep disorders on delirium in proximal femoral surgery patients aged 60 or older

OBJECTIVE

To examine the effect of preoperative sleep disorders on delirium in patients older than 60 years of age who underwent surgery for proximal femoral fracture.

METHODS

This is a prospective observational study. We prospectively selected 143 patients with proximal femoral fracture who underwent surgery between April 2021 and April 2022. The primary outcome was postoperative delirium (PD). Multiple logistic regression analyses were performed and a receiver operating characteristic (ROC) curve was generated. The preoperative sleep quality of all eligible participants was assessed through the Pittsburgh Sleep Quality Index (PSQI). The Confusion Assessment Method (CAM) was used to assess PD from the first to the seventh day postoperatively. Patients were divided into two groups according to the PD diagnosis: (1) the no PD (NPD) group and (2) the PD (PD) group.

RESULTS

Of 143 eligible patients, 43 (30.1%) were diagnosed with PD. Multiple logistic regression analysis demonstrated that postoperative ICU admissions (OR = 2.801, p = 0.049) and preoperative sleep disorders (OR = 1.477 p < 0.001) were independently associated with PD. A receiver operating characteristic (ROC) curve demonstrated that the preoperative PSQI score was predictive of PD (AUC 0.808, 95% CI 0.724 ~ 0.892, p < 0.001).

CONCLUSION

Preoperative sleeping disorders may be an independent risk factor leading to PD and an independent predictive factor for the development of delirium in proximal femoral surgery patients aged 60 or older.

Association and prediction of subjective sleep quality and postoperative delirium during major non-cardiac surgery: a prospective observational study

BACKGROUND

Postoperative delirium (POD) is an acute form of brain dysfunction that can result in serious adverse consequences. There has been a link between cognitive dysfunction and poor sleep. The present study aimed to determine the association and prediction of subjective sleep quality and postoperative delirium during major non-cardiac surgery.

METHODS

One hundred and thirty-four patients, aged 60 years or older, were scheduled for elective laparotomy or orthopaedic procedures. The Pittsburgh Sleep Quality Index (PSQI) and sleep log were used to assess perioperative subjective sleep quality in participants. Nursing Delirium Screening Checklist (NU-DESC) was used for screening, and the Confusion Assessment Method (CAM) was used to diagnose POD during the first seven days following surgery. The association between subjective sleep quality and POD was assessed using a multivariate logistic regression model. Thereafter, the prediction performance of subjective sleep quality was evaluated using a receiver operating characteristic (ROC) curve.

RESULTS

All assessments were completed on 119 patients who had an average PSQI score of 7.0 ± 2.4 before surgery. 23 patients (19.3%) suffered from POD. The multivariate logistic regression analysis showed that the occurrence of POD was closely related to age, BMI, PSQI and operation time. After adjusting for related factors, there was a statistically significant association between PSQI and POD occurrence (OR = 1.422, 95%CI 1.079-1.873, per 1-point increase in PSQI). The ROC curve analysis showed that the optimal PSQI cutoff value was 8.0 for predicting POD, and the area under the ROC (AUROC) value of PSQI was 0.741 (95%CI 0.635 to 0.817). The AUROC of the model developed by the multivariate logistic regression analysis was 0.870 (95%CI 0.797 to 0.925).

CONCLUSIONS

The study found that preoperative subjective sleep quality was strongly associated with POD during major non-cardiac surgery. Additionally, PSQI combined with age, BMI, and operation time improved POD prediction.

Factors influencing mobility among people post-surgery for hip fractures: A cross-sectional study

Background

After hip fracture surgery, patients often experience complications and a decline in mobility, leading to physical disability and increased dependency on caregivers. This may result in reduced independence, institutionalization, and higher mortality rates. However, there is limited research on mobility and its influencing factors in patients undergoing hip fracture surgery in Thailand.

Objective

This study aimed to determine the factors influencing mobility in patients with fractured hips within one year after surgery.

Methods

A cross-sectional study was conducted involving 143 randomly selected participants who had undergone hip fracture surgery between August 2022 to February 2023. Mobility and its influencing factors were measured using standardized questionnaires, including the De Morton Mobility Index, Parker Mobility Scale, Charlson Comorbidity Index, General Practitioner Assessment of Cognition, Groningen Orthopedic Social Support Scale, Fatigue Severity Scale, Pain Rating Scale, and Pittsburgh Sleep Quality Index. Descriptive statistics and multiple regression were utilized for data analysis.

Results

The mean mobility score for the patients was 48.86 out of 100 (SD = 17.89). The study found that comorbidity (β = -0.156, p = 0.009), cognitive function (β = 0.310, p <0.001), social support (β = 0.145, p = 0.010), pain (β = -0.176, p = 0.004), fatigue (β = -0.249, p <0.001), and sleep (β = -0.169, p = 0.009) collectively influenced mobility in patients after hip fracture surgery, explaining 61.8% of the variance (R2 = 0.618; F = 36.598; p <0.001).

Conclusion

The study's results provide valuable insights for nurses to target these modifiable factors to enhance patients' mobility. However, it is essential to note that patients with comorbidity and poor cognitive function may face difficulty maintaining mobility. Nurses should be attentive to these patients and provide appropriate management. Additionally, early rehabilitation should be initiated promptly to optimize outcomes.

Sleep Loss the night before surgery and incidence of postoperative delirium in adults 65-95 years of age

STUDY OBJECTIVES

To describe the association between preoperative sleep disruption and postoperative delirium.

METHODS

Prospective cohort study with six time points (3 nights pre-hospitalization and 3 nights post-surgery). The sample included 180 English-speaking patients ≥65 years old scheduled for major non-cardiac surgery and anticipated minimum hospital stay of 3 days. Six days of wrist actigraphy recorded continuous movement to estimate wake and sleep minutes during the night from 22:00 to 05:59. Postoperative delirium was measured by a structured interview using the Confusion Assessment Method. Sleep variables for patients with (n = 32) and without (n = 148) postoperative delirium were compared using multivariate logistic regression.

RESULTS

Participants had a mean age of 72 ± 5 years (range 65-95 years). The incidence of postoperative delirium during any of the three postoperative days was 17.8%. Postoperative delirium was significantly associated with surgery duration (OR = 1.49, 95% CI 1.24-1.83) and sleep loss >15% on the night before surgery (OR = 2.64, 95% CI 1.10-6.62). Preoperative symptoms of pain, anxiety and depression were unrelated to preoperative sleep loss.

CONCLUSIONS

In this study of adults ≥65 years of age, short sleep duration was more severe preoperatively in the patients who experienced postoperative delirium as evidenced by sleep loss >15% of their normal night's sleep. However, we were unable to identify potential reasons for this sleep loss. Further investigation should include additional factors that may be associated with preoperative sleep loss to inform potential intervention strategies to mitigate preoperative sleep loss and reduce risk of postoperative delirium.

The prevalence and risk factors of sleep disturbances in surgical patients: A systematic review and meta-analysis

Determining the prevalence and risk factors related to sleep disturbance in surgical patients would be beneficial for risk stratification and perioperative care planning. The objectives of this systematic review and meta-analysis are to determine the prevalence and risk factors of sleep disturbances and their associated postoperative complications in surgical patients. The inclusion criteria were: (1) patients ≥18 years old undergoing a surgical procedure, (2) in-patient population, and (3) report of sleep disturbances using a validated sleep assessment tool. The systematic search resulted in 21,951 articles. Twelve patient cohorts involving 1497 patients were included. The pooled prevalence of sleep disturbances at preoperative assessment was 60% (95% Confidence Interval (CI): 50%, 69%) and the risk factors for postoperative sleep disturbances were a high preoperative Pittsburgh sleep quality index (PSQI) score indicating preexisting disturbed sleep and anxiety. Notably, patients with postoperative delirium had a higher prevalence of pre- and postoperative sleep disturbances and high preoperative wake after sleep onset percentage (WASO%). The high prevalence of preoperative sleep disturbances in surgical patients has a negative impact on postoperative outcomes and well-being. Further work in this area is warranted.

Risk factors for postoperative delirium in geriatric patients with hip fracture: A systematic review and meta-analysis

Objectives

This systematic review and meta-analysis was conducted to identify the potential risk factors for postoperative delirium in geriatric patients with hip fracture.

Methods

PubMed, EMBASE, and Cochrane Library were searched from inception until December 31st, 2021. A combined searching strategy of subject words and free words was adopted. Studies involving risk factors for postoperative delirium in elderly patients undergoing hip fracture surgeries were reviewed. Qualities of included studies were assessed using the Newcastle–Ottawa Scale. Data were pooled and a meta-analysis was performed using Review Manager 5.3.

Results

A total of 37 studies were included. The following risk factors were significant: advanced age (per year increase) (OR: 1.05, 95% CI 1.04–1.07), age>80 years (OR: 2.26, 95% CI 1.47–3.47), male (OR: 1.53, 95% CI 1.37–1.70), preoperative cognitive impairment (OR:3.20, 95% CI 2.12–4.83), preoperative dementia (OR: 2.74, 95% CI 2.18–3.45), preoperative delirium (OR: 9.23, 95% CI 8.26–10.32), diabetes (OR: 1.18, 95% CI 1.05–1.33), preoperative functional dependence (OR: 1.31, 95% CI 1.11–1.56), ASA level (per level increase) (OR: 1.63, 95% CI 1.04–2.57), ASA level≥3(OR: 1.76, 95% CI 1.39–2.24), low albumin (OR: 3.30, 95% CI 1.44–7.55), medical comorbidities (OR: 1.15, 95% CI 1.06–1.25), Parkinson's disease (OR: 4.17, 95% CI 1.68–10.31) and surgery delay>48 h (OR: 1.90, 95% CI 1.36–2.65).

Conclusions

Clinicians should be alert to patients with those risk factors. To identify the risk factors more precisely, more research studies with larger sample size and better design should be conducted.

Perioperative neurocognitive disorders: A narrative review focusing on diagnosis, prevention, and treatment

Perioperative neurocognitive disorders (NCDs) refer to neurocognitive abnormalities detected during the perioperative periods, including preexisting cognitive impairment, preoperative delirium, delirium occurring up to 7 days after surgery, delayed neurocognitive recovery, and postoperative NCD. The Diagnostic and Statistical Manual of Mental Disorders‐5th edition (DSM‐5) is the golden standard for diagnosing perioperative NCDs. Given the impracticality of using the DSM‐5 by non‐psychiatric practitioners, many diagnostic tools have been developed and validated for different clinical scenarios. The etiology of perioperative NCDs is multifactorial and includes predisposing and precipitating factors. Identifying these risk factors is conducive to preoperative risk stratification and perioperative risk reduction. Prevention for perioperative NCDs should include avoiding possible contributors and implementing nonpharmacologic and pharmacological interventions. The former generally includes avoiding benzodiazepines, anticholinergics, prolonged liquid fasting, deep anesthesia, cerebral oxygen desaturation, and intraoperative hypothermia. Nonpharmacologic measures include preoperative cognitive prehabilitation, comprehensive geriatric assessment, implementing fast‐track surgery, combined use of regional block, and sleep promotion. Pharmacological measures including dexmedetomidine, nonsteroidal anti‐inflammatory drugs, and acetaminophen are found to have beneficial effects. Nonpharmacological treatments are the first‐line measures for established perioperative NCDs. Pharmacological treatments are still limited to severely agitated or distressed patients.

The Role of Perioperative Sleep Disturbance in Postoperative Neurocognitive Disorders

Postoperative neurocognitive disorder (PND) increases the length of hospital stay, mortality, and risk of long-term cognitive impairment. Perioperative sleep disturbance is prevalent and commonly ignored and may increase the risk of PND. However, the role of perioperative sleep disturbances in PND remains unclear. Nocturnal sleep plays an indispensable role in learning, memory, and maintenance of cerebral microenvironmental homeostasis. Hospitalized sleep disturbances also increase the incidence of postoperative delirium and cognitive dysfunction. This review summarizes the role of perioperative sleep disturbances in PND and elucidates the potential mechanisms underlying sleep-deprivation-mediated PND. Activated neuroinflammation and oxidative stress; impaired function of the blood-brain barrier and glymphatic pathway; decreased hippocampal brain-derived neurotrophic factor, adult neurogenesis, and sirtuin1 expression; and accumulated amyloid-beta proteins are associated with PND in individuals with perioperative sleep disorders. These findings suggest that the improvement of perioperative sleep might reduce the incidence of postoperative delirium and postoperative cognitive dysfunction. Future studies should further investigate the role of perioperative sleep disturbance in PND.