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Original Article
ARTICLE IN PRESS
doi:
10.25259/JHASNU_43_2025

Comparison of Postoperative Pain and Sleep Quality Based on Timing of Surgery: An Observational Study

Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences (NGSMIPS), Nitte (Deemed to be University), Mangaluru, Karnataka, India
Department of Anaesthesiology, KS Hegde Medical Academy (KSHEMA), Nitte (Deemed to be University), Mangaluru, Karnataka, India.

* Corresponding author: Dr. Uday Venkat Mateti, Department of Pharmacy Practice, NGSM Institute of Pharmaceutical Sciences (NGSMIPS), Nitte (Deemed to be University), Mangaluru 575018, Karnataka, India. udayvenkatmateti@gmail.com

Licence
This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-Share Alike 4.0 License, which allows others to remix, transform, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.

How to cite this article: Babu A, Ananthesh L, Kappilumakil-Joseph LT, Thalangara-Ibrahim AN, Shetty SR, Mateti UV. Comparison of Postoperative Pain and Sleep Quality Based on Timing of Surgery: An Observational Study. J Health Allied Sci NU. doi: 10.25259/JHASNU_43_2025

Abstract

Objectives

Patients who undergo surgery are more likely to have changes in their sleep patterns and quality. Hence, the study was aimed at comparing the postoperative pain and sleep quality based on the surgeries performed at different times (morning vs. afternoon) of the day.

Material and Methods

An observational study was carried out among 50 surgical participants for a duration of six months. The data collection form was designed according to study needs, and the insomnia severity index (ISI) and visual analogue scores (VAS) were used to evaluate the sleep quality and pain scores at three time points. An Independent t test was carried out to determine the impact of the timing of surgery on sleep quality, and statistical analysis was carried out using SPSS 29.0.

Results

The participants had a mean age of 49.30 ± 17.02 years. Out of the 50 participants, 34 (68%) underwent surgery in the morning, while 16 (32%) had surgery in the afternoon. Overall, 88% of patients experienced postoperative sleep disturbances. The morning group had a mean postoperative sleep quality score of 8.01 ± 4.29, whereas the afternoon group scored 9.56 ± 5.98 (p <0.001). The morning and afternoon groups had mean postoperative visual analog scale (VAS) scores of 5.50 ± 1.5 and 6.38 ± 2.24, respectively (p = 0.109). Additionally, there was a positive correlation between postoperative sleep quality and pain control (r = 0.347, p = 0.014).

Conclusion

The patients undergoing surgeries in the afternoon had a statistically significant impact on their sleep quality compared to the morning group. However, the timing of surgery did not have any significant impact on postoperative pain.

Keywords

Insomnia severity index
Pain
Sleep quality
Timing of surgery
Visual analogue scale

INTRODUCTION

The circadian rhythm, intricately linked to the human sleep-wake cycle, is a biological mechanism developed by the body to adapt to its surroundings.[1] A circadian rhythmicity must be expressed regularly for the body to sustain homeostasis.[2] A naturally occurring resting state called sleep is marked by a reduced metabolism, a partial or complete loss of awareness, a reduction in or absence of voluntary muscular contraction, and an energy-preserving state.[3] Sleep quality disturbance is usually influenced by various endogenous factors (such as delirium, depression, and anxiety) and exogenous factors (such as ambient noise in the surroundings and frequent staff interventions).[4] In addition, post-surgically, patients are more likely to experience changes in their sleep patterns, sleep quality, and development of postoperative sleep disturbances (POSD). POSD is marked by an increase in the frequency of sleep awakenings, a decrease in rapid eye movement sleep, and a decrease in total sleep duration.[1] It exacerbates postoperative pain and fatigue, increases the risk of postoperative delirium, and causes cardiovascular adverse events.[5] Similarly, anaesthesia is another crucial aspect that can alter the quality of sleep, regardless of whether the anaesthesia is general or spinal.[6] Anaesthetics can disrupt circadian rhythms via activation of N-methyl-D-aspartate (NMDA) and gamma-aminobutyric acid (GABA) receptors in the suprachiasmatic nucleus neurons, which influences clock gene expression and internal clock entrainment.[7] Anaesthesia and surgery are also believed to impact the postoperative melatonin level, causing impairment of the sleep-wake cycle.[8] In addition to postoperative sleep quality, pain management is also a crucial factor for surgical patients. Ineffective pain management could lead to certain physiological and pathological issues that ultimately hinder the recovery of the patients.[9] Pain perception exacerbates poor sleep quality, creating a vicious circle in which pain impacts sleep quality and poor sleep quality amplifies perception of pain.[2]

Apart from the surgery and anaesthesia, the timing of the procedure is also thought to affect patients’ sleep quality and recovery.[8] However, the influence of the timing of surgery on postoperative pain and sleep quality remains uncertain. Therefore, to better understand POSD, this study set out to investigate how surgical timing influences postoperative pain and sleep quality.

MATERIAL AND METHODS

Study objective

The primary objective of this study was to compare the postoperative pain and sleep quality based on the timing of surgery (Morning vs Afternoon). The secondary objective was to compare the sleep quality and pain at three different time points (preoperatively, postoperative day (POD) 1, and POD 2).

Study design

An observational study was carried out after the approval of the Institutional Ethics Committee (Ref No: NGSMIPS/IEC/0038/2023), for a duration of 6 months in a tertiary care teaching hospital. The study was explained to the participants by the investigators using the participant information sheet, and all participants provided a signed informed consent prior to participation in the study.

Sample size

According to Nowakowski et al.,[10] the pretest and post-test mean of sleep quality were 5 and 6, respectively, and the standard deviation was 1.8 and 2.8, respectively. At 5% level of significance, 85% power of the test, and 0.43 effect size, the required sample size for the study was 50 participants.

Study participants

Participants who were scheduled to undergo lower limb surgery, patients belonging to the American Society of Anaesthesiologists Physical Status (ASA PS I or II), and patients with a body mass index of 18.5-29.9 kg/m2 were included in the study. However, patients who undergo emergency surgeries of the lower limb, have a history of exposure to anaesthesia within the past 30 days, patients with sleep disorders, pain syndrome, and psychosis were excluded from the study.

Data collection tool

A data collection form was designed to collect the disease- and surgery-related characteristics of the study participants. In addition, sleep quality and pain were evaluated using the Insomnia Severity Index (ISI) and a visual analogue pain (VAP) scale, respectively.

Insomnia Severity Index

The ISI is a questionnaire comprising seven items that assesses insomnia’s characteristics, severity, and impacts. It covers aspects like difficulty falling asleep, staying asleep, and early morning awakening, as well as overall dissatisfaction with sleep, interference with daily functioning, awareness of sleep problems, and distress caused by sleep difficulties. Each item is rated on a 5-point Likert scale, resulting in a total score ranging from 0-28. Scores are categorized as follows: 0-7 (no insomnia), 8-14 (sub-threshold insomnia), 15-21 (moderate insomnia), and 22-28 (severe insomnia).[11] Additionally, individuals scoring between 8-28 were identified as experiencing POSD.

Visual analogue pain scale

Pain ratings were measured at three time points utilizing a 10 cm VAS and two verbal descriptions for each severe symptom. Participants rated their pain subjectively, ranging from “no pain at all” (score of 0) to “the worst imaginable pain” (score of 10).[2]

Data collection

The subjects were screened for eligibility by the investigators. Participants meeting the study requirements were evaluated the day prior to surgery for preoperative sleep quality and pain. In addition, disease, surgery, and anaesthesia-related characteristics were also gathered. Similarly, on POD 1 and POD 2, sleep quality and pain were rerecorded. In addition, the sleep quality of the participants, who were induced within 8.00 am - 12.00 pm (Morning group) and 2.00 pm - 6.00 pm (Afternoon group), was compared for any significant difference in sleep quality.[12] Preoperatively, data were gathered to establish baseline information. Later, postoperative data were compared to the baseline information to determine how the sleep quality and pain were affected.

Statistical analysis

The data were summarised using descriptive statistics such as frequency (percentages), Mean (SD), or Median (Q1, Q3). Repeated measures ANOVA was employed to compare ISI scores and VAS at three different time points. An independent samples t-test was conducted to assess the impact of surgery timing on sleep quality. The normality of the data was assessed using the Kolmogorov-Smirnov test. Subsequently, either Karl Pearson’s or Spearman’s rank correlation was performed to examine the relationship between postoperative sleep quality and other clinical parameters. Data analysis was conducted using SPSS 29.0, and p <0.05 was considered statistically significant.

RESULTS

Among 50 participants involved in the study, 34 (68%) underwent surgeries in the morning and 16 (32%) in the afternoon. The participants’ mean age was 49.30 ± 17.02 years, with a distribution of 26% aged 20-40 years, 38% aged 41-60 years, and 36% aged 61-80 years. The average Body Mass Index (BMI) was 23.3 ± 2.76, with the majority (74%) falling within the normal BMI range and 26% classified as overweight. Sex distribution revealed that the majority (70%) of participants were males. In terms of hospitalization, the majority (86%) of patients had a stay of 0-20 days, with 8% staying 21-40 days and 6% requiring 41-60 days, with a median length of stay of 10 days (7, 15). Antibiotic prophylaxis was predominantly administered using cefuroxime (82%), with other antibiotics such as ceftriaxone sulbactam (6%), meropenem (4%), cefoperazone sulbactam (2%), ciprofloxacin (2%), clindamycin (2%), and piperacillin tazobactam (2%) also utilized to varying degrees. Anaesthesia methods varied significantly, with spinal anaesthesia (94%) being the primary choice, particularly in morning surgeries (68%). Comparative analysis between morning and afternoon surgeries highlighted distinct clinical differences. Among the morning surgery group, all the surgeries were performed with spinal anaesthesia, and the afternoon surgeries were performed with spinal anaesthesia among 13 (81.2%). The average estimated blood loss among the morning surgery group was 95.29 ± 44.99 mL, and afternoon surgeries were 92.5 ± 37.85 mL. The average length of the surgery among morning surgeries was 2 ± 1.06 h, and afternoon surgeries were 4.6 ± 1.79 h. The details have been summarized in Table 1.

Table 1: General characteristics of participants
Parameters Total (n = 50) (%) Morning (n = 34) (%) Afternoon (n = 16) (%)
Age in years [Mean ± SD] 49.30 ± 17.024 49.29 ± 18.97 49.31 ± 12.45
20-40 13 (26) 10 (29.4) 3 (18.7)
41-60 19 (38) 11 (32.3) 8 (50)
61-80 18 (36) 13 (38.3) 5 (31.3)
BMI in Kg/m2 [Mean ± SD] 23.85 ± 2.76 23.77 ± 3.03 24.04 ± 2.16
18.5-24.9 37 (74) 25 (73.5) 12 (75)
25.0-29.9 13 (26) 9 (35.3) 4 (25)
Sex
Male 35 (70) 22 (64.7) 13 (81.2)
Female 15 (30) 12 (35.3) 3 (18.8)
Length of hospital stay in days [Median (Q1, Q3)] 10 (7, 15) 9.5 (6.25, 15) 10 (8, 11)
0-20 43 (86) 29 (85.2) 14 (87.5)
21-40 4 (8) 2 (5.8) 2 (12.5)
41-60 3 (6) 3 (9) 0 (0)
Prophylaxis antibiotic
Cefoperazone sulbactam 1 (2) 1 (2.9) 0 (0)
Ceftriaxone sulbactam 3 (6) 2 (5.8) 1 (6.2)
Cefuroxime 41 (82) 26 (76.8) 15 (93.8)
Ciprofloxacin 1 (2) 1 (2.9) 0 (0)
Clindamycin 1 (2) 1 (2.9) 0 (0)
Meropenem 2 (4) 2 (5.8) 0 (0)
Piperacillin tazobactam 1 (2) 1 (2.9) 0 (0)
Type of anaesthesia
General anaesthesia 2 (4) 0 (0) 2 (12.5)
Spinal anaesthesia 47 (94) 34 (100) 13 (81.2)
Spinal + Epidural + General anaesthesia 1 (2) 0 (0) 1 (6.3)
Duration of surgery in hours (Mean ± SD) 2.83 ± 1.15 2.00 ± 1.06 4.60 ± 1.79
Estimated blood loss in mL (Mean ± SD) 94.40 ± 42.47 95.29 ± 44.99 92.50 ± 37.85
NPO time in hours (Mean ± SD) 6.15 ± 1.35 6.21 ± 1.26 6.00 ± 1.55

SD: Standard deviation, NPO: Nothing by mouth, BMI: Body mass index.

Overall, the POSD was observed in 29 (58%) of the study participants. The incidence of POSD among the morning group was 16 (44.44%), and in the afternoon group it was 10 (62.5%).

Sleep quality and pain levels were assessed at preoperative, POD 1, and POD 2, using the ISI and VAS, respectively. The mean ISI score increased from 8.34 pre-operatively to 9.82 on POD 1, indicating worsened sleep quality immediately after surgery, followed by an improvement to 5.58 by POD 2. Similarly, VAS pain scores decreased progressively from 7.18 pre-operatively to 3.58 by POD 2, reflecting a decline in perceived pain levels post-surgery. The details are summarized in Table 2.

Table 2: Representation of insomnia severity index and visual analogue pain responses
Parameters

Preoperative

(Mean ± SD)

Postoperative day 1

(Mean ± SD)

Postoperative day 2

(Mean ± SD)

Sleep quality
Difficulty falling asleep 2.08 ± 0.85 2.36 ± 0.87 1.32 ± 0.74
Difficulty staying asleep 1.76 ± 0.93 1.88 ± 0.84 1.22 ± 0.81
Problems waking up too early in the morning 1.42 ± 0.9 1.69 ± 0.9 1 ± 0.78
How satisfied/dissatisfied are you with your current sleep pattern? 1.34 ± 0.84 1.60 ± 0.88 0.88 ± 0.77
How noticeable to others do you think your sleep problem is in terms of impairing the quality of your life? 0.62 ± 0.66 0.74 ± 0.82 0.54 ± 0.61
How worried/distressed are you about your current sleep problem? 0.24 ± 0.43 0.46 ± 0.61 0.14 ± 0.35
To what extent do you consider your sleep problem to interfere with your daily functioning (e.g., daytime fatigue, mood, ability to function at work/daily chores, concentration, memory, etc.) currently 0.76 ± 0.79 1.16 ± 0.81 0.5 ± 0.67
Total 8.34 ± 4.55 9.82 ± 4.84 5.58 ± 3.86
Pain scores
Visual analogue pain score 7.18 ± 1.78 5.78 ± 1.79 3.58 ± 1.69

SD: Standard deviation.

The test of within subjects were carried out to determine the mean difference across three different time points (i.e., Preoperative, POD 1, and POD 2). Since the data violated the assumption of sphericity, the greenhouse gases was considered in the test. It revealed that the sleep quality was statistically significantly different [F = 90.438, effect size = 0.649, p <0.05]. Similarly, the pain scores also varied statistically significantly differently [F = 156.814, effect size = 0.762, p <0.001]. The details are summarized in Table 3.

Table 3: Mean difference of sleep quality and pain at different points in time
Parameters Mean ± SD Greenhouse Geisser
Type III sum of squares df Mean square F value Partial eta squared p value
Sleep quality
Preoperative sleep quality 8.34 ± 4.55 463.093 1.370 337.93 90.438 0.649 <0.001
Postoperative sleep quality on day 1 9.82 ± 4.84
postoperative sleep quality on day 2 5.58 ± 3.86
Pain scores
Preoperative pain scores 7.18 ± 1.78 333.213 1.776 187.57 156.81 0.762 <0.001
Postoperative pain scores on day 1 5.78 ± 1.79
Postoperative pain scores on day 2 3.58 ± 1.69

p <0.05 is statistically significant. SD: Standard deviation, df: Degree of freedom.

Table 4 summarizes the mean values of sleep quality and pain based on the timing of surgery at three different time points. The mean preoperative sleep quality in the morning surgery group (7.56 ± 4.07) and in the afternoon surgery group (7.88 ± 5.60) did not differ significantly (p = 0.126). During POD 1, the morning surgery (8.01 ± 4.29) group had a mean score slightly lower compared to the afternoon group (9.56 ± 5.98), and it was statistically significant (p = 0.043). However, on POD 2, the afternoon group (5.85 ± 3.38) had a slightly higher mean compared to the morning group (5.00 ± 4.78). Similarly, on POD 1, the afternoon group (6.38 ± 2.24) had higher pain scores compared to the morning group (5.50 ± 1.5), it was not statistically significant (p = 0.109).

Table 4: Comparison of sleep quality and pain scores based on timing of surgery
Parameters Timing of surgery (Mean ± SD)
p value
Morning Afternoon
Sleep quality
Pre-operative 7.56 ± 4.07 7.88 ± 5.60 0.126
POD 1 8.01 ± 4.29 9.56 ± 5.98 0.043*
POD 2 5.00 ± 4.78 5.85 ± 3.38 0.092
Visual analogue pain scores
Pre-operative 7.15 ± 1.28 7.25 ± 2.59 0.851
POD 1 5.50 ± 1.5 6.38 ± 2.24 0109
POD 2 3.32 ± 1.49 4.06 ± 2.01 0.152
: Statistically significant, SD: Standard deviation, POD: Post-operative day.

Further, insights into the relationships between various parameters and postoperative sleep quality were determined through the correlation coefficients and corresponding p values. The parameters like preoperative sleep quality [r = 0.830, p <0.001], preoperative pain scores [r = 0.473, p <0.001], and postoperative pain scores [r = 0.347, p = 0.014] were positively correlated and found to be statistically significant. However, age [r = 0.0.31, p = 0.830], BMI [r = -0.073, p = 0.616] and LOHS [r = 0.023, p = 0.874] was not significantly correlated. The details have been summarized in Table 5.

Table 5: Correlation of different parameters with postoperative sleep quality score
Parameters Postoperative sleep quality score
Correlation coefficient p value
Agea 0.031 0.830
Body mass indexa -0.073 0.616
Length of hospital staya 0.023 0.874
Preoperative sleep quality scoreb 0.830 <0.001*
Preoperative pain scorea 0.473 <0.001*
Postoperative pain scorea 0.347 0.014*
: Statistically significant, a: Spearman correlation, b: Pearson correlation.

DISCUSSION

Healthy individuals require adequate sleep to preserve their physical and mental health. However, the incidence of POSD following major surgeries is quite high. Postoperative sleep problems may have a substantial impact on patients’ neurocognitive function and perhaps worsen the outcomes of patients. Anaesthesia, along with the prevalent use of opioids during general anaesthesia, is considered a contributing factor to POSD. Also, the surgery timing is known to alter the postoperative sleep quality.[8] Thus, we investigated how patients undergoing lower limb surgery would perform in terms of postoperative sleep quality based on whether the surgeries were performed in the morning or the afternoon. According to our research, patients who had surgery in the morning had much higher quality postoperative sleep than patients who had procedures in the afternoon. A previously published study by Hou et al. studied the effect of morning and afternoon surgeries on sleep quality. It revealed that afternoon surgeries had a more serious effect on sleep function.[12] In contrast, a study by Yang et al. observed a better short-term sleep quality in the afternoon group compared to those in the morning. However, the disparity was justified by the short-term variation in melatonin levels following surgery.[8] A randomized controlled trial by Song et al. where surgeries performed in the afternoon had a higher degree of postoperative sleep disorders compared to surgeries in the night.[13] In addition, different from our study, their study assessed the postoperative sleep quality among the morning (8.00-12.00) and night group (18.00-22.00). Our study also found that the mean preoperative ISI score was 8.34 ± 4.55. It was contradicting to the results by Yang et al., where the mean ISI score was 11.5 ± 5.6.[14] The postoperative mean ISI score was 9.82 ± 4.84, which contradicted with the study by Wang et al., where the mean ISI score was 15.6 (range 2-25).[15]

POSD, a common postoperative brain dysfunction, was identified in 58% of our study participants, mirroring findings from Seid and Fenta, who reported poor sleep quality in 64.9% of their participants.[4] A study conducted in China and Malaysia had also observed a poor sleep quality among 65.4% and 67.3% of participants, respectively.[16,17] Notably, the afternoon surgery group showed a greater prevalence of POSD compared to the morning group (62.5% vs. 44.4%), aligning with the results of Hou et al., who similarly observed a higher occurrence of POSD in the afternoon group (70% vs. 37.9%), suggesting that afternoon surgeries may not promote early postoperative sleep recovery as effectively as morning surgeries.[12] In addition, opioids have also been shown to affect the sleep quality of patients.[18] Hence, the afternoon group were having higher impact on sleep quality. The postoperative pain scores were 5.78 ± 1.79, which gradually reduced to 3.58 ± 1.69 on POD 2. A similar pattern was observed in a study conducted among patients undergoing total joint arthroplasty by Luo et al., where the score was 4.99 ± 1.73 and reduced to 3.93 ± 1.54 on POD 3.[19] However, the timing of surgery did not have any significant impact on the postoperative pain scores.

The correlation analysis revealed that the postoperative sleep quality scores increase as age increases, but this was not statistically significant. It was in contradiction to the study results of Chung et al., where higher age was statistically associated with lower sleep efficiency after surgery.[20] In addition, LOHS increased the postoperative sleep quality scores, indicating a decreased postoperative sleep quality. It was correlating with the meta-analysis by Butris et al., where the poor postoperative sleep quality has increased length of stay.[21] A study by Yu et al. discovered that individuals with preoperative sleep problems had an affected sleep awakening in the postoperative period, which was similar to our study results, where the preoperative sleep quality scores were positively correlated with postoperative sleep scores.[22] More importantly, postoperative pain and circadian rhythm interact in a bidirectional manner. Poor surgical pain management can lead to postoperative disturbances in sleep. Similarly, our study found a positive correlation between postoperative pain and sleep quality scores. It indicated a link to poor sleep quality, heightened pressure pain sensitivity, and reduced intrinsic pain inhibition capacity. However, Cronin et al. study found the presence of sleep disturbances despite having well-controlled pain.[23]

However, the study results should be seen with certain limitations. The study did a comparison of sleep quality among morning and afternoon groups and did not take into consideration the other groups, like the night surgery group. In addition, the study did not use polysomnography, a gold standard for evaluating sleep function. The study’s results may not be generalizable as it was single centred study. The data on the sleep quality was assessed for short term after the surgery. As a result, the effect of having surgery at different times on long-term sleep quality has to be researched further. In addition to the surgery, certain factors like noise and light might have a negative effect on the postoperative sleep quality in the study, which were not assessed.

CONCLUSION

In conclusion, patients undergoing surgeries in the afternoon had a significantly higher impact on the postoperative sleep quality compared to the morning group. The timing of surgery did not have a significant impact on postoperative pain. However, the poor postoperative pain management was associated with poor postoperative sleep quality. Therefore, among high-risk individuals who are prone to developing POSD, consideration should be given to the timing of the surgery.

Acknowledgement

We would like to thank the Nitte Gulabi Shetty Memorial Institute of Pharmaceutical Sciences, Nitte (Deemed to be University), and Justice KS Hegde Charitable Hospital, Mangaluru, India, for providing the research facilities.

Ethical approval

The study approved by the Institutional Ethics Committee at Nitte Gulabi Shetty Memorial Institute of Pharmaceutical sciences, number NGSMIPS/IEC/0038/2023, dated 15th November 2023.

Declaration of patient consent

The authors certify that they have obtained all appropriate patient consent forms. In the form, the patients have given their consent for their clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

Use of artificial intelligence (AI)-assisted technology for manuscript preparation

The authors confirm that there was no use of artificial intelligence (AI)-assisted technology for assisting in the writing or editing of the manuscript, and no images were manipulated using AI.

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