Diagnosis of Delirium and Assessment of Sleep Quality in Patients in the Anesthesia and Intensive Care Unit

Completed

• Conditions: Delirium and Insomnia

• Registration Number: NCT06699004
• Lead Sponsor: Sakarya University

Brief Summary

This study included patients in the anesthesia and intensive care unit (ICU). Over half the patients did not experience delirium. The correct structuring of the physical conditions in the ICU and the professional approaches of the nurses contributed to this outcome. Moreover, patients with delirium had lower sleep quality and lower Glasgow Coma Scale (GCS) scores than those without delirium.

Detailed Description

Delirium is a condition involving functional losses in the brain due to both structural and vascular abnormalities caused dehydration and hypoperfusion, which prevent the transport of oxygen and glucose to neurons, thereby leading to metabolic dysfunction in the brain. Moreover, delirium, which is characterized by disorientation, inattention, and changes in thoughts and/or behaviors, is a serious and widespread neuropsychiatric condition that frequently goes unnoticed, although it is preventable and reversible following appropriate intervention. Numerous risk factors have been found to affect the development of delirium, including prolonged hospital stays, medication use, coping mechanisms during illness, personality traits, and treatment compliance. It is believed that intensive care patients face a higher risk of developing delirium. In this regard, invasive procedures, regular nursing care, environmental noise, continuous light exposure, pre-existing sleep disorders, pain, anxiety, fear, and loneliness represent physiological and psychological factors that can lead to sleep deprivation in intensive care patients. Indeed, places such as intensive care units (ICUs), where patients are exposed to constant stimuli and may experience severe pain, can trigger stress responses that lead to agitation, sleep disorders, and delirium.

Previous studies have indicated that medications used to control delirium can negatively affect sleep quality, while worsening sleep quality can exacerbate delirium. The main goal in preventing delirium is to ensure a regular sleep-wake cycle, support adequate fluid and nutrient intake, and provide both preventive and therapeutic treatments through a systematic, multidisciplinary team-based approach to reduce the frequency and duration of delirium. Artificial intelligence and machine learning approaches enable machines to simulate complex processes such as thinking and consciousness, thereby allowing computers to learn the relationships between inputs and outputs from large datasets, which helps them to make optimal decisions, analyses, and predictions. In the healthcare field, such technology is used in many areas, including the early detection and prediction of disease, disease classification, treatment, prevention of adverse outcomes, rapid analysis of clinical data, cost-saving initiatives, provision of effective and quality care, minimization of human errors, and clinical decision-making .

In the present study, the relationship between delirium and sleep quality in patients in the anesthesia and ICU was examined and a predictive analysis using a machine learning approach was performed.

The data required for this study were collected using the Patient Information Form, Nursing Delirium Screening Scale (Nu-DESC), Richards-Campbell Sleep Scale (RCSS), Richmond Agitation-Sedation Scale (RASS), and GCS. The collected data were analyzed using the SPSS statistical program (SPSS-26), and the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines were followed when reporting the results. The sample size was determined using the known population sample calculation method. Both frequency and percentage analyses were used to describe the distribution of the participants' demographic characteristics, while the mean and standard deviation were used to determine the participants' levels on the utilized scales. Cronbach's alpha reliability analysis was conducted to assess the scale reliability, and the post hoc power analysis showed that the study had medium power at a 95% confidence level with 99% significance . The skewness-kurtosis values were checked to assess the normality of the distribution. An independent samples t-test was used to assess the differences between groups. For comparisons among more than two groups, a one-way analysis of variance (ANOVA) was applied, while the prediction and receiver operating characteristic (ROC) curve analyses were conducted using R version 4.1.3.

Study Timeline

• Study Start: 2022-10-21
• Primary Completion: 2023-01-21
• Study Completion: 2023-01-21
• Status Verified: 2024-11
• Study First Submitted: 2024-11-06
• Study First Submitted QC: 2024-11-19
• Last Update Submitted: 2024-11-19
• Study First Posted: 2024-11-21
• Last Update Posted: 2024-11-21

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 107

Inclusion Criteria

• Patients aged 18 years and older, who were hospitalized in the anesthesia and reanimation intensive care unit of Sakarya Education and Research Hospital between October 2022 and January 2023

• Patients without communication problems (hearing, speech, comprehension, etc.)
• Patients who have been hospitalized in the intensive care unit for at least 24 hours
• Patients not in a coma (RASS: between -3 and +4, GCS: 10 or above)
• Patients without a diagnosed dementia
• Patients without mental status disorders or psychological illnesses
• Patients who are willing to participate in the study

Exclusion Criteria

Not provided

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Diagnosis of Delirium and Evaluation of Sleep Quality İn Patients Hospitalized İn The Anesthesia and Reanimation İntensive Care Unit	between October 2022 and January 2023	Nursing Delirium Screening Scale:The scale consists of five items. Each item is scored between 0 and 2, with a total score ranging from 0 to 10. A score of two or more indicates delirium. According to the scale results, delirium was observed in 36.4% of the patients.

Secondary Outcome Measures

Name	Time	Method
Diagnosis of Delirium and Evaluation of Sleep Quality in Patients Hospitalized in The Anesthesia and Reanimation İntensive Care Unit	between October 2022 and January 2023	Richards-Campbell Sleep Scale : Scores between 0 and 25 indicate very poor sleep, while scores between 76 and 100 indicate very good sleep. According to the scale, the average delirium score of the patients was found to be 39.30.

Trial Locations

Locations (1)

Department of Internal Medicine Nursing, Faculty of Health Sciences, Sakarya University, 54050, Serdivan / SAKARYA.; 🇹🇷 Serdivan, Sakarya, Turkey