Effect of planned in-hospital transfer on physiological indicators, level of consciousness, pain, and restlessness in Iran

Mohammad Mahdi Honarmand Jahromi; Ali Ravari; Tayebeh Mirzaei; Zahra Kamiab; Zahra Riahi Paghaleh

doi:10.4266/acc.004175

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Original Article Nursing Effect of planned in-hospital transfer on physiological indicators, level of consciousness, pain, and restlessness in Iran: Acute and Critical Care 2026;41(2):411-418.
DOI: https://doi.org/10.4266/acc.004175
Published online: April 17, 2026

Mohammad Mahdi Honarmand Jahromi¹

, Ali Ravari²

, Tayebeh Mirzaei²

, Zahra Kamiab³

, Zahra Riahi Paghaleh⁴

¹Geriatric Care Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

²Department of Medical Surgical Nursing, School of Nursing and Midwifery, Geriatric Care Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

³Department of Community Medicine, School of Medicine, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

⁴Department of Nursing Management, School of Nursing and Midwifery, Non-Communicable Disease Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran

Corresponding Author : Ali Ravari Department of Medical Surgical Nursing, School of Nursing and Midwifery, Geriatric Care Research Center, Rafsanjan University of Medical Sciences, Rafsanjan 7718796755, Iran Tel: +98-34-3425-5900 Fax: +98-34-3425-5900 Email: ravary4776@yahoo.com

• Received: September 6, 2025 • Revised: November 17, 2025 • Accepted: November 20, 2025

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
KEY MESSAGES
NOTES
REFERENCES

Abstract

Background
Intra-hospital transfers of critically ill patients from emergency departments (EDs) to intensive care units (ICUs) carry significant risks, with studies indicating over 60% experience preventable complications. This study evaluated the impact of a structured, planned transfer protocol on patient stability and efficiency compared to routine transfers.
Methods
A total of 112 hemodynamically stable adult patients requiring transfer from the ED to ICU at our hospital were enrolled after ethical approval. Participants were randomly assigned to an intervention group (n=56), transferred using a predefined protocol (pre-transfer coordination, equipment checks, dedicated ICU-trained nurse, continuous monitoring), or a control group (n=56) receiving routine care. Physiological parameters (blood pressure, arterial oxygen saturation, heart rate, respiratory rate), transfer time, consciousness (4Score), pain (Nonverbal Pain Scale), and agitation (Richmond Agitation-Sedation Scale [RASS]) were assessed pre- and post-transfer. Data were analyzed using SPSS version 18 with independent t-tests and chi-square test.
Results
Groups were comparable at baseline in demographics and clinical parameters. Post-transfer, no significant differences were found in physiological indicators, consciousness levels, or pain scores. However, the intervention group showed significantly lower agitation levels (mean RASS, –2.01 vs. –2.64; P=0.04). Crucially, transfer time was significantly reduced in the intervention group (9.4±2.0 vs.16.0±4.0 minutes, P<0.01).
Conclusions
While planned transfers did not adversely affect physiological stability or consciousness, they significantly reduced patient agitation and halved transfer duration. This demonstrates that structured protocols enhance operational efficiency and may improve the transfer experience. Implementing planned transfer protocols is recommended to optimize intra-hospital patient flow and safety.
Key Words: consciousness; critical care; pain; patient safety; patient transfer

INTRODUCTION

Intra-hospital patient transfers, particularly from emergency departments (EDs), represent one of the most sensitive and high-risk processes in medical care. Recent studies indicated that over 60% of critically ill patients experience preventable complications during transfer, including altered consciousness (49.2%), hypoxia (43.4%), and hemodynamic instability (46.5%) [1]. Evidence from recent systematic reviews indicates that emergency and critically ill patients, owing to physiological instability, are at markedly increased risk of transport-related adverse events compared with non-emergency patients. [2]. The timely identification and management of potentially life-threatening conditions, along with preventing medical and care errors during this process, are of paramount importance [3].

The challenges of patient transfers can be categorized into three main groups: physiological changes, human errors, and equipment-related issues. Studies have shown that 34.7% of patients experience hypotension and 51.4% develop respiratory disturbances during transfer [4]. Additionally, human errors include 28% of cases attributed to staff fatigue and 25% to miscommunication [5]. Equipment problems have also been identified as the primary cause of transfer complications in 23.5% of cases [6]. Research by Baig et al. [7] demonstrated that the combination of these factors can increase patient mortality risk by up to 40%.

Patient safety during medical services is a fundamental human right, the assurance of which can prevent adverse outcomes [8]. However, significant research gaps persist in this field, including a lack of studies explaining the precise mechanisms through which transfer methods affect physiological and neurological parameters, as well as insufficient evidence regarding their impact on indicators such as consciousness levels and pain management [9]. These gaps highlight the need for further research in this area.

In response to these challenges, the planned transfer approach has emerged as an effective solution. This method emphasizes maintaining care quality from the origin to the destination department, and can decrease the incidence of adverse events [10]. Planned transfer is defined as a structured process for intra- and inter-hospital movement of critically ill patients, involving pre-transport coordination, patient stabilization, appropriate personnel, continuous monitoring, and standardized handover [11]. Variations include checklists and multidisciplinary teams to minimize instability [12]. The mechanisms of this method include reducing hemodynamic fluctuations through pre-transfer preparation, preventing cerebral hypoxia via oxygen management, timely analgesic administration based on scheduled protocols, and creating a calming transfer environment [13]. Recent neuroimaging studies have also shown that stress from unplanned transfers can trigger inflammatory pathways and metabolic changes in the brain.

Ensuring patient safety during transfer is the responsibility of all medical team members, who must focus on preserving safety, health, and human dignity [14]. In Iran, nurses often serve as the sole personnel responsible for patient safety during transfers [8], whereas in other countries, physicians [15] and anesthesiologists may also participate in transfer teams. Key elements of safe transfers include transfer decision-making, effective communication, patient stabilization and preparation, appropriate transfer method selection, patient companions, necessary equipment, in-transit monitoring, and documentation [11].

The relevance of this research is notable from multiple perspectives. Clinically, the findings could reduce physiological complications. From a managerial standpoint, this study provides a scientific basis for designing standardized transfer protocols. Economically, implementing this method is estimated to reduce annual transfer-related error costs. By examining the impact of planned transfers on four critical indicators—vital sign stability, consciousness level, pain intensity, and agitation—this study represents a crucial step toward transforming patient transfer processes and enhancing medical care quality.

MATERIALS AND METHODS

This experimental study received ethical approval from the Institutional Review Board of Rafsanjan University of Medical Sciences (No. IR.RUMS.REC.1402.052). Prior to participation, written informed consent was obtained from all patients or their legal guardians.

Participants

The study population included 112 adult inpatients (age ≥18 years) requiring transfer from the ED to the intensive care unit (ICU) at Ali Ibn Abi Talib Hospital. Participants meeting the inclusion criteria were consecutively enrolled via convenience sampling.

To prevent protocol contamination and staff objections, temporal cluster randomization was implemented: days of the week were randomly assigned to intervention or control conditions using computer-generated random sequences. To minimize the risk of carry-over effects, a minimum 48-hour washout period was enforced between consecutive intervention and control days (e.g., if Monday was an intervention day, Tuesday was excluded from randomization and served as a neutral buffer; the next eligible day was Wednesday). All patients transferred on intervention days (n=56) underwent structured pre-planned protocols, while those on control days (n=56) followed routine hospital protocols.

Inclusion criteria encompassed hemodynamically stable patients (systolic blood pressure [BP] ≥90 mm Hg, no active arrhythmias) deemed fit for transfer by the attending physician. Exclusion criteria were (1) hemodynamic instability requiring immediate intervention (e.g., vasopressors, intubation), (2) uncontrolled pain or agitation precluding safe transfer, or (3) missing/incomplete physiological monitoring data.

Instruments and Measurements

All physiological parameters—BP, pulse rate, and arterial oxygen saturation (SpO₂) were measured using a multiparameter monitoring device. To ensure accuracy, BP readings from the device were cross-validated against a mercury sphygmomanometer prior to each transfer. Clinical outcomes were assessed using three standardized tools: (1) 4Score: a scale for level of consciousness, grading responses from 16 (alert) to 0 (comatose). (2) Nonverbal Pain Scale (NVPS): a 0–10 scale evaluating pain intensity in non-verbal patients, incorporating vital signs, facial expressions, and body movements. (3) Richmond Agitation-Sedation Scale (RASS): a 10-point scale (−5 [unarousable] to +4 [combative]) quantifying restlessness/sedation status. Pre- and post-transfer assessments were conducted by trained nurses blinded to the study groups.

Procedures

Pre-transfer preparations

A medical equipment engineer inspected and calibrated all transfer devices (monitors, ventilators, oxygen tanks) before the study. For the intervention group, a 4-hour safe transfer workshop was conducted for ED nurses and assistants, covering equipment checks, patient monitoring, and crisis management during transit.

Control group protocol

Patients were transferred according to routine hospital practice, which involved no pre-transfer coordination with the ICU, ad hoc checks of resuscitation equipment, no standardized monitoring during transit, and variable nurse accompaniment (with no experience requirements).

Intervention group protocol: the planned transfer protocol included: (1) pre-transfer coordination: ICU bed readiness confirmed via phone. Handover details (e.g., diagnosis, medications) communicated in advance; (2) equipment and personnel: full verification of device functionality (e.g., monitor batteries, oxygen tank pressure). Assignment of an ICU-trained nurse (≥2 years of experience) to accompany the patient; (3) Logistics: a dedicated staff member ensured elevator availability and uninterrupted transit. Continuous physiological monitoring (BP, SpO₂, pulse) during transfer.

Outcome Measurement

In both groups, 4Score, NVPS, and RASS were administered immediately before and after transfer by the same trained researcher blinded to group allocation to minimize bias.

Sample Size Calculation

Based on the sample size formula and the results of Farnoosh et al. [16], the sample size for each group was calculated as follows:

n1=(Z1-α2+Z1-β)2×(p12+p22k)Δ2,n2=k×n1 α=0.05, 1−β=0.8, Δ=5.2 and k=1

The estimated event rates were 7.8% (p₁) for oxygen desaturation during transfer in the intervention group and 13% (p₂) in the control group. Using these parameters, the sample size for each group was initially determined to be 52 participants. To account for potential attrition, the final sample size for each group was adjusted to 56 participants.

Statistical Analysis

The normality of the distribution of quantitative variables was assessed using the non-parametric Kolmogorov-Smirnov test, and the equality of variances across groups was evaluated using Levene’s test. A significance level of 0.05 was used for all tests. Data were analyzed using IBM SPSS Statistics version 18 (IBM Corp.). For quantitative data (physiological indices, level of consciousness, pain, and restlessness), results are presented as mean±standard deviation, while qualitative data are reported as frequency (percentage). To compare the means of quantitative variables between the two groups, an independent t-test was employed. Additionally, the chi-square test was applied to compare the frequency of qualitative variables between groups. A P-value <0.05 defined significance.

RESULTS

A total of 112 eligible patients requiring transfer from the ED to the ICU were enrolled and equally allocated to intervention (n=56) and control (n=56) groups (Figure 1). There were no significant differences in age, sex, marital status, occupation, education level, or primary diagnosis between the two groups (Table 1). Transfer time from the ED to the ICU was significantly reduced in the intervention group compared with the control group (9.4±2.0 vs. 16.0±4.0 minutes, P<0.01).(Table 1).

No significant differences were found between the two groups for respiratory rate, oxygen saturation, BP, heart rate, pain, consciousness level (4Score), and agitation. The intervention group had a mean respiratory rate of 16.12±3.51 breaths/min, while the control group had a mean of 15.03±4.16 breaths/min (t=–1.34, P=0.18). Oxygen saturation was 96.30%±1.82% in the intervention group and 96.18±3.32% in the control group (t=–0.247, P=0.80). Systolic BP was 111.98±23.42 mm Hg in the intervention group compared to 118.64±22.71 mm Hg in the control group (t=1.52, P=0.12). Other measures, including diastolic BP, heart rate, pain, consciousness level, and agitation, showed no significant differences (all P>0.05) (Table 2).

After the intervention, the comparison of physiological parameters, pain, consciousness level, and agitation between the intervention and control groups revealed no significant differences in most of the variables. However, agitation levels showed a statistically significant difference. The mean agitation score was –2.01±1.61 in the intervention group compared to –2.64±1.63 in the control group (t=–1.625, P=0.04), indicating that the intervention led to a reduction in agitation in the ICU compared to the control group (Table 3).

DISCUSSION

This study examined the effects of planned transfers on physiological stability, consciousness, and patient comfort during ED-to-ICU transitions. While we initially hypothesized that planned transfers would significantly improve these outcomes based on previous literature [17,18], our results showed comparable outcomes between planned and routine transfer groups. This unexpected finding requires careful consideration. There are several factors that may explain these results. The lack of significant differences in respiratory rate, oxygen saturation, BP, and heart rate between groups may reflect important advancements in routine transfer practices. Recent evidence suggests that standard ICU transfers now incorporate more rigorous monitoring protocols than previously reported [2], with our control group’s stability indicating widespread adoption of basic safety measures like portable monitors and oxygen reserve checks even in non-protocolized transfers. Additionally, our exclusion of hemodynamically unstable patients (systolic BP <90 mm Hg, arrhythmias) created a cohort inherently resistant to transfer-related physiological changes [13], consistent with Jiang et al.’s finding [19] that planned transfers benefit high-risk patients most significantly.

The similar consciousness levels between groups contrast with some previous studies [20] but align with evidence from a prospective multicenter study [21] showing no consciousness differences during short transfers. Our intervention focused primarily on logistical efficiency rather than neurological management, which may account for these results. The trend toward reduced agitation in controls (P=0.053) suggests possible unmeasured environmental factors, such as nighttime transfers occurring during lower-activity periods [22], or a spillover effect from training both groups’ staff [23]. Regarding pain and agitation, while our non-significant results contradict Rodriguez and Harris [24], they emphasize the importance of baseline patient factors like chronic pain [18], which we didn’t measure but may have significantly influenced outcomes.

The most clinically significant finding was the 56% reduction in transfer time (9.4 vs. 16.0 minutes, P<0.01) achieved through planned transfers. This aligns with Baig et al. [7] and Murata et al. [2], who identified time efficiency as the most consistent benefit of structured transfers, particularly for time-sensitive conditions. This explains why studies in lower-resource hospitals show dramatic physiological benefits that weren’t apparent in our study [15].

This study’s strengths include temporal cluster randomization to minimize contamination, blinded assessments for objectivity, and multi-tool evaluation of key outcomes. Limitations encompass single-center design limiting generalizability, exclusion of high-risk patients, unmeasured baseline confounders (e.g., chronic pain), and potential underpowering for subtle effects. In conclusion, while planned transfers didn’t demonstrate the expected physiological benefits in our stable patient population, they significantly improved operational efficiency by reducing transfer times by over 50%. This finding reframes the value proposition of transfer protocols in modern hospital settings. Rather than focusing solely on physiological outcomes, hospitals should implement these protocols to streamline workflows, reduce system burdens, and establish standardized processes that will particularly benefit high-risk populations. Future research should investigate these protocols in more diverse patient populations, with particular attention to stratification by illness severity and measurement of long-term outcomes beyond the immediate transfer period. The operational efficiencies demonstrated in this study, combined with the maintenance of physiological stability, strongly support the adoption of planned transfer protocols as a best practice for interdepartmental patient movements.

KEY MESSAGES

▪ Implementing a coordinated transfer protocol was associated with lower levels of patient agitation upon arrival in the intensive care unit, as measured by the Richmond Agitation–Sedation Scale, suggesting improved comfort and reduced psychological stress during the transfer process.

▪ The planned transfer intervention substantially reduced transfer duration by 56%, indicating that a structured and protocol-driven approach can markedly streamline patient flow and improve operational performance within the hospital setting.

▪ Although physiological stability was maintained throughout the transfer process, the most prominent effect of the planned protocol was the significant reduction in transfer time, underscoring its role in optimizing resource utilization and facilitating more timely access to critical care services.

NOTES

CONFLICT OF INTEREST

No potential conflict of interest relevant to this article was reported.

FUNDING

This research was funded by Rafsanjan University of Medical Sciences (fundRef ID: 402068).

ACKNOWLEDGMENTS

The authors are grateful to the participants and their families for their cooperation throughout the study. We would like to express our thanks and appreciation to the respected officials of the Geriatric Care Research Center and the Vice-Chancellor of Research and Technology of Rafsanjan University of Medical Sciences for all their support of this research. Also, the authors would like to thank the Clinical Research Development Unit of Ali-Ibn Abi Talib Hospital in Rafsanjan University of Medical Sciences, Rafsanjan, Iran for its support and collaboration.

AUTHOR CONTRIBUTIONS

Conceptualization: MMHJ. Data curation: MMHJ. Formal analysis: ZK. Methodology: MMHJ, AR, TM, ZRP. Project administration: AR. Writing–original draft: MMHJ, TM, ZRP. Writing–review & editing: TM, AR. All authors read and agreed to the published version of the manuscript.

Figure 1.

Consolidated Standards of Reporting Trials (CONSORT) flow diagram of study participants.

Table 1.

Demographic and clinical characteristics of participants between intervention and control before intervention

Variable	Intervention group (n=56)	Control group (n=56)	Test statistic	P-value
Age (yr)	57±24	60±23	t=0.59	0.55^a)
Sex			χ²=0.622	0.43^b)
Male	34 (60.7)	38 (67.9)
Female	22 (39.3)	18 (32.1)
Marital status			χ²=0.570	0.45^b)
Single	11 (19.6)	8 (14.3)
Married	45 (80.4)	48 (85.7)
Occupation			χ²=2.578	0.63^b)
Housewife	21 (37.5)	16 (28.6)
Self-employed	13 (23.2)	19 (33.9)
Government	2 (3.6)	3 (5.4)
Retired	10 (17.9)	11 (19.6)
Unemployed	10 (17.9)	7 (12.5)
Education level			χ²=1.572	0.45^b)
Illiterate	22 (39.3)	16 (28.6)
Under diploma	13 (23.2)	17 (30.4)
High school	21 (37.5)	23 (41.1)
Primary diagnosis			χ²=3.821	0.43^b)
Sepsis	15 (26.8)	18 (32.1)
Poisoning	17 (30.4)	9 (16.1)
Trauma	12 (21.4)	12 (21.4)
Respiratory	9 (16.1)	14 (25)
Others	3 (5.4)	3 (5.4)
Classification of patients			χ²=0.000	1.000^b)
Trauma	12 (21.4)	12 (21.4)
Non-trauma	44 (78.6)	44 (78.6)
Transfer time (min)	9.4±2.0	16.0±4.0	t=1.45	<0.01^a)

Values are presented as mean±standard deviation or number (%).

^a)Independent sample t-test;

^b)Chi-square test.

Table 2.

Comparison of physiological and clinical parameters between intervention and control groups before intervention

Variable	Intervention group (n=56)	Control group (n=56)	t	P-value^a)
Respiratory rate (breaths/min)	16.12±3.51	15.03±4.16	–1.34	0.18
Oxygen saturation (%)	96.30±1.82	96.18±3.32	–0.25	0.80
Systolic blood pressure (mm Hg)	111.98±23.42	118.64±22.71	1.52	0.12
Diastolic blood pressure (mm Hg)	69.03±15.61	71.35±15.43	0.79	0.43
Heart rate (beats/min)	91.94±18.94	91.19±18.67	–0.211	0.83
Pain	0.08±0.34	0.17±0.54	1.03	0.30
Consciousness level (4Score)	9.66±3.07	8.94±3.29	–1.18	0.23
Agitation	–2.03±1.65	–2.64±1.63	–1.25	0.53

Values are presented as mean±standard deviation.

^a)Independent sample t-test.

Table 3.

Comparison of mean physiological parameters, pain, consciousness level, and agitation in the intensive care unit between the intervention and control groups after intervention

Variable	Intervention group (n=56)	Control group (n=56)	t	P-value^a)
Respiratory rate (beats/min)	16.08±3.47	15.32±4.16	–1.05	0.29
Oxygen saturation (%)	96.23±1.69	96.14±2.51	–0.22	0.82
Systolic blood pressure (mm Hg)	116.33±19.47	118.85±21.66	0.65	0.51
Diastolic blood pressure (mm Hg)	71.35±11.38	72.73±12.77	0.60	0.54
Heart rate (bpm)	91.60±20.07	94.69±18.84	0.40	0.84
Pain	0.07±0.32	0.53±0.29	–0.31	0.76
Consciousness level (4Score)	9.66±3.07	8.92±3.29	–1.10	0.22
Agitation	–2.01±1.61	–2.64±1.63	–1.63	0.04

Values are presented as mean±standard deviation.

^a)Independent sample t-test.

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Effect of planned in-hospital transfer on physiological indicators, level of consciousness, pain, and restlessness in Iran

Acute Crit Care. 2026;41(2):411-418. Published online April 17, 2026

DOI: https://doi.org/10.4266/acc.004175

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Figure

Effect of planned in-hospital transfer on physiological indicators, level of consciousness, pain, and restlessness in Iran

Figure 1. Consolidated Standards of Reporting Trials (CONSORT) flow diagram of study participants.

Figure 1.

Effect of planned in-hospital transfer on physiological indicators, level of consciousness, pain, and restlessness in Iran

Variable	Intervention group (n=56)	Control group (n=56)	Test statistic	P-value
Age (yr)	57±24	60±23	t=0.59	0.55^a)
Sex			χ²=0.622	0.43^b)
Male	34 (60.7)	38 (67.9)
Female	22 (39.3)	18 (32.1)
Marital status			χ²=0.570	0.45^b)
Single	11 (19.6)	8 (14.3)
Married	45 (80.4)	48 (85.7)
Occupation			χ²=2.578	0.63^b)
Housewife	21 (37.5)	16 (28.6)
Self-employed	13 (23.2)	19 (33.9)
Government	2 (3.6)	3 (5.4)
Retired	10 (17.9)	11 (19.6)
Unemployed	10 (17.9)	7 (12.5)
Education level			χ²=1.572	0.45^b)
Illiterate	22 (39.3)	16 (28.6)
Under diploma	13 (23.2)	17 (30.4)
High school	21 (37.5)	23 (41.1)
Primary diagnosis			χ²=3.821	0.43^b)
Sepsis	15 (26.8)	18 (32.1)
Poisoning	17 (30.4)	9 (16.1)
Trauma	12 (21.4)	12 (21.4)
Respiratory	9 (16.1)	14 (25)
Others	3 (5.4)	3 (5.4)
Classification of patients			χ²=0.000	1.000^b)
Trauma	12 (21.4)	12 (21.4)
Non-trauma	44 (78.6)	44 (78.6)
Transfer time (min)	9.4±2.0	16.0±4.0	t=1.45	<0.01^a)

Variable	Intervention group (n=56)	Control group (n=56)	t	P-value^a)
Respiratory rate (breaths/min)	16.12±3.51	15.03±4.16	–1.34	0.18
Oxygen saturation (%)	96.30±1.82	96.18±3.32	–0.25	0.80
Systolic blood pressure (mm Hg)	111.98±23.42	118.64±22.71	1.52	0.12
Diastolic blood pressure (mm Hg)	69.03±15.61	71.35±15.43	0.79	0.43
Heart rate (beats/min)	91.94±18.94	91.19±18.67	–0.211	0.83
Pain	0.08±0.34	0.17±0.54	1.03	0.30
Consciousness level (4Score)	9.66±3.07	8.94±3.29	–1.18	0.23
Agitation	–2.03±1.65	–2.64±1.63	–1.25	0.53

Variable	Intervention group (n=56)	Control group (n=56)	t	P-value^a)
Respiratory rate (beats/min)	16.08±3.47	15.32±4.16	–1.05	0.29
Oxygen saturation (%)	96.23±1.69	96.14±2.51	–0.22	0.82
Systolic blood pressure (mm Hg)	116.33±19.47	118.85±21.66	0.65	0.51
Diastolic blood pressure (mm Hg)	71.35±11.38	72.73±12.77	0.60	0.54
Heart rate (bpm)	91.60±20.07	94.69±18.84	0.40	0.84
Pain	0.07±0.32	0.53±0.29	–0.31	0.76
Consciousness level (4Score)	9.66±3.07	8.92±3.29	–1.10	0.22
Agitation	–2.01±1.61	–2.64±1.63	–1.63	0.04

Table 1. Demographic and clinical characteristics of participants between intervention and control before intervention

Values are presented as mean±standard deviation or number (%).

Independent sample t-test;

Chi-square test.

Table 2. Comparison of physiological and clinical parameters between intervention and control groups before intervention

Values are presented as mean±standard deviation.

Independent sample t-test.

Table 3. Comparison of mean physiological parameters, pain, consciousness level, and agitation in the intensive care unit between the intervention and control groups after intervention