Abstract
Study Objectives:
We aimed to study the association between sleep quality, total sleep duration, and wound healing among adult patients who had good sleep quality at the time of admission to the hospital who underwent laparotomy for various reasons.
Methods:
In this observational study, consecutive adult patients undergoing emergency laparotomy were followed up until the eighth postoperative day. The primary outcome (wound healing) was assessed using the Southampton Wound Grading System. Sleep quality (assessed by the single-item sleep quality scale) was the primary predictor. Pain was assessed using a visual analog pain scale. We studied the effect of postoperative sleep quality on wound healing on postoperative day 8. Secondary analyses assessed the effect of total sleep time, severity of pain, and markers of systemic inflammation on wound healing.
Results:
In this study 110 participants were included. The average age of participants was 41.7 ± 16.2 years. On postoperative day 8, 34.5% rated their sleep quality as “poor to fair” and the rest as “good.” Postoperative poor sleep quality was associated with impaired wound healing, starting from the third postoperative day (P < .001 for each subsequent day). Multiple logistic regression was overall significant (χ2 = 118.40; degrees of freedom = 9; P < .001), classified 92.7% cases correctly, and explained 88% variance to the outcome. This model showed that shorter total sleep time (P = .009), higher total leukocyte count (P = .005), presence of comorbidities (P = .01), and poor sleep quality during the postoperative week (odds ratio = 78.14; P = .005) increased the odds for impaired healing of wounds.
Conclusions:
Poor sleep quality during the healing phase is associated with wound complications, a surrogate marker of impaired wound healing.
Citation:
Das A, Gupta R, Huda F, Kumar N, Krishnan V, Basu S. Effect of sleep quality on wound healing among patients undergoing emergency laparotomy: an observational study. J Clin Sleep Med. 2025;21(3):503–512.
Keywords: sleep quality, wound healing, postoperative, total sleep time
BRIEF SUMMARY
Current Knowledge/Study Rationale: Data from animal studies have shown that sleep disturbance impairs wound healing. However, it is not known whether sleep quality influences wound healing in human participants.
Study Impact: In this study of 110 participants who underwent emergency laparotomy and had low risk for obstructive sleep apnea, poor sleep quality during the postoperative period was associated with poor wound healing (odds ratio = 78.14; P = .005).
INTRODUCTION
Sleep is important for immune function and both processes have a bidirectional relationship.1 The effect of sleep on immune function has been investigated through the manipulation of sleep (acute total sleep deprivation or partial sleep deprivation), using different methods (stimulated or unstimulated), and by following different markers of immunity (eg, total leukocyte count, measurement of cytokines, activity and proliferation of immune cells, and circulating levels of antibodies). However, most studies have reported conflicting results.1 However, the available data suggest that sleep disruption may increase levels of proinflammatory cytokines and dampen the function of natural killer cells.1 Such conditions are likely to increase predisposition to infection.
Wound healing depends on several factors, including age, obesity status, smoking, alcohol consumption, nutrition, medication, oxygenation, diabetes, pressure or friction on the wound, radiation, chemotherapy, infection, and stress.2–4 Disturbed sleep is a stressful condition that negatively affects certain aspects of the immune system. Hence, it is possible that disturbed sleep can also impair wound healing.
Assessing the effect of sleep quality on wound healing is important, because available data show that sleep worsens after hospital admission.5 During hospitalization, worsening of sleep occurs across different domains: total sleep time decreases, sleep fragmentation increases, and a delayed sleep–wake phase appears.5 These changes result in an altered immunological response, activation of the autonomic system, increase in oxidative stress, mood instability, and cognitive impairment.5 These conditions also result in emotional stress, which contributes to impaired wound healing.6
Furthermore, sleep quality is also affected by pain and the perception of pain, indicating that sleep quality and pain have a bidirectional relationship.7,8 Pain commonly occurs during the postoperative period. Thus, the effect of pain should be controlled during the outcome assessment of any research related to surgical patients in which sleep is a predictor variable. This could not be controlled in the available studies because the perception of pain is subjective.
Despite extensive search, only 5 studies (including animal and human observational studies) that have assessed the effect of sleep deprivation, sleep duration, or sleep quality on wound healing were found.9–13 Two animal studies did not identify any effects of sleep deprivation on wound healing.9,11 However, in 1 of these studies, sleep deprivation was induced 7 days after skin lesion production, and in another study selective rapid eye movement (REM) sleep deprivation was induced either before or after punch biopsy of the skin.9,11 In another study, Chen et al10 found that near-total sleep deprivation for 3 days in rats, after the induction of oral ulcers, impaired healing during the sleep deprivation period. However, the difference between the sleep-deprived and non-sleep-deprived groups decreased during recovery sleep. In this study, impaired wound healing was associated with an increase in proinflammatory cytokines—tissue necrosis factor α, interleukin1β, interleukin 6, interleukin 8, and monocyte chemoattractant protein-1. These became comparable to those in non-sleep-deprived rats after the recovery sleep.10 However, the sleep-deprived rats in this study had significantly lower food intake and lost more body weight than the non-deprived and control animals, suggesting an additional role for nutrition in retarded healing.10 In the fourth study, McLain et al13 showed that sleep fragmentation impaired wound healing in obese diabetic mice but not in wild-type mice, even though they had body weight comparable to that of the nonfragmented group throughout the study. An online survey among students showed that participants who self-reported slow wound healing with or without wound infection reported poor sleep quality, insomnia, and poorer perceived immune function.14 On the other hand, a systematic review of 11 studies that assessed wound healing in patients with obstructive sleep apnea (OSA) reported that patients with OSA had greater chances of wound dehiscence; however, results regarding “time to heal” were contradictory.15
Considering the importance of this issue and the absence of studies on human participants, this cross-sectional study aimed to investigate the association between sleep quality, total sleep duration, and wound healing in adult patients undergoing emergency laparotomy for various reasons. The primary outcome of the study was the association between sleep quality (as measured on day 8 after surgery) and wound status (measured using the Southampton score on the same day). As a secondary outcome, the effects of various measures such as age, sex, body mass index, daily pain score, and inflammation biomarkers (ie, C-reactive protein and leukocyte count) were compared between individuals with good and poor sleep quality. We hypothesized that patients with poor sleep quality during the postoperative period would experience impaired surgical wound healing.
METHODS
This observational study was conducted in the in-patient department of general surgery between July 2021 and December 2022, after obtaining approval from the Institutional Ethics Committee. The sample size was calculated considering that 12.4% of the participants would develop surgical-site infection.16 The calculated sample size was 166 (precision: δ = 0.05 [5%]; Type I error: α = 0.05 [5%], beta = 20%, power: 80%); however, due to recurrent waves of the coronavirus disease 2019, only 110 participants were included.
Consecutive adult patients undergoing emergency laparotomy were informed of the rationale of the study and were requested to participate. Written informed consent was obtained from all the participants. However, patients who had been diagnosed with OSA in the past, those who were using a positive airway pressure device, those with cognitive deficits (eg, dementia or delirium), those who were not able to communicate for any reason (eg, intellectual disability or aphasia), and those who were using addictive substances in dependence patterns according to standard diagnostic criteria were excluded from the study.17
Preoperatively, each participant’s demographic data (age, sex, and address) were recorded. The history of presenting symptoms was explored, followed by physical and laboratory examinations to make the diagnosis. Medical histories were gathered to identify comorbidities. All participants were screened for OSA using the Berlin Questionnaire.18 Laparotomy was then performed under general anaesthesia. Postoperatively, the participants were followed up until day 8. In the event of death in the hospital or where postoperative ventilatory support was required, the recruited participants were excluded from the analysis. All participants received an injection or the tablet form of diclofenac sodium (75 mg in each dose) for pain relief, as and when required, but never more than 3 times a day.
Berlin Questionnaire
The Berlin Questionnaire18 is a screening tool for OSA. It classifies patients into 2 groups: low and high risk for OSA. It has good internal consistency (Cronbach’s alpha 0.86–0.92). It has also shown acceptable psychometric properties for a respiratory disturbance index > 5, with a sensitivity of 0.86, specificity of 0.77, positive predictive value of 0.89, and a positive likelihood ratio of 3.79.18 Because this is a patient-reported questionnaire, the version that was translated into the local language was used.19 The translated version had a sensitivity of 89% and a specificity of 58% for the diagnosis of OSA. The positive predictive value of the translated version was 0.87, and the negative predictive value was 0.63.19 Screening was performed preoperatively.
Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST)20
All participants were screened for use of addictive substances preoperatively. This screening questionnaire was used to determine the lifetime consumption of addictive substances. Further questions gathered information about the use of addictive substances during the past 3 months, including frequency, urge, problems associated with substance use, concern raised by family members or friends regarding substance use, and failure to cut down. The test–retest reliability coefficients (kappa) ranged from 0.58–0.90.20
Laboratory investigations
C-reactive protein-high sensitivity (CRP-h), total leukocyte count, and serum albumin levels were measured preoperatively and on days 1, 3, 5, and 7 postoperatively.
Acute Physiology and Chronic Health Evaluation II score21
This uses 12 physiological measures to provide a composite score that indicates the general severity of disease. These include mean arterial blood pressure, heart rate, temperature, respiratory rate, oxygenation, arterial pH, electrolytes (serum sodium, potassium, and bicarbonate), hematocrit, total leukocyte count, serum creatinine, Glasgow Coma Scale score, age, and previous health status.21 It was recorded every day until the eighth postoperative day.
Single-item sleep quality scale22
This scale contains a single item that assesses self-reported sleep quality on a 5-point Likert scale: terrible, poor, fair, good, and excellent. It also considers 5 aspects of sleep: (1) ease of falling asleep, (2) total sleep time, (3) awakenings during the night (excluding those intended for going to the washroom), (4) waking up earlier than the desired wake time, and (5) feeling refreshed after sleep in the morning. Respondents were asked to mark 1 choice on a 5-point Likert scale. This scale measures sleep quality over the previous 7 days. It has been validated against the Pittsburgh Sleep Quality Index (week 8 Goodman–Kruskal correlation −0.92) and morning questionnaire-insomnia (week 1 Pearson correlation −0.76) in patients with insomnia and depression.22 Sleep quality was assessed preoperatively and on postoperative day 8.
Southampton wound grading system
This system classifies wounds into 5 major categories: normal healing, erythema with other signs of inflammation, clear or hemoserous discharge, pus, and deep or severe wound infections (with or without tissue breakdown or hematoma requiring aspiration). The wound was graded daily postoperatively until day 8 on this scale. For the analysis, the data were dichotomized. Categories of normal healing and erythema with other signs of inflammation were considered as the absence of wound complications/good healing, whereas the remaining 3 categories were considered signs of wound complications/impaired healing.
Visual analog pain scale23
The visual analog pain scale is a 100-mm horizontal line having “no pain” at one end and “worst pain imaginable” at the other end. Participants were asked to mark the intensity of their pain on this scale twice daily, in the morning and evening. This was found to correlate well with the dose of patient-controlled analgesia.23
Statistical analysis
Statistical analyses were performed using the Statistical Package for Social Sciences v 29.0 (IBM Corp., Armonk, New York). Descriptive statistics were calculated. The chi-square test was used to test the association between categorical variables. The results were adjusted using the Bonferroni correction for multiple tests for variables with a 2 × 2 cell distribution. Mann–Whitney U test was used to compare nonnormally distributed continuous variables between the 2 groups. For normally distributed variables, an independent sample t test was used. Repeated-measures analysis of variance was used to assess changes in longitudinally collected continuous variables. The interaction between time and sleep quality was calculated as the main effect and a Bonferroni adjustment was made for the confidence interval.
Only 2 participants reported sleep quality as “poor” during the postoperative week, and hence this category was combined with “fair sleep quality” during the same period. Similarly, to assess the effect of other medical comorbidities, the participants were categorized into 2 groups: with and without comorbidities. This was done because only one fifth of the participants reported other medical comorbidities and the frequency of individual disorders was low.
Initially, binary logistic regression was conducted to assess the relationship between sleep quality and wound status on the eighth postoperative day. The test was repeated after adjusting for age, body mass index, and sex. Finally, a multivariate logistic regression analysis was conducted to determine the predictors of wound outcomes on day 8. Factors found to be associated with complicated wounds in the univariate analysis were included in this model. For this model, the average values of continuous variables during the postoperative period were considered. For example, total sleep time, morning and evening pain scores, total leukocyte count, serum CRP-h, and serum albumin.
RESULTS
A total of 110 participants were included in the study. Males accounted for 73.6% and the average age of participants was 41.7 ± 16.2 years (range 18–82 years). The average body mass index of participants was 20.4 ± 2.28 kg/m2 (range 14.9–31.5).
Nine participants were excluded because they used addictive substances (6 alcohol and 3 tobacco), 3 experienced delirium at the time of admission, and 2 were diagnosed with OSA using a continuous positive airway pressure device. Therefore, 14 participants were excluded from the study.
Nearly three quarters of the participants presented with the following conditions at admission: intestinal obstruction (27.3%), prepyloric perforation (23.6%), and ileal perforation (27.3%). Other participants sought help for other reasons, including perforation of other parts of the gastrointestinal tract (8.18%), perforation peritonitis (3.6%), large bowel obstruction (2.7%), mesenteric ischemia (1.8%), intestinal stricture (1.8%), strangulated hernia (0.9%), ruptured liver abscess (0.9%), chronic pancreatitis (0.9%), and biliary peritonitis (0.9%). Nearly one fifth (18.5%) of the patients had other medical comorbidities. Their diagnoses included pulmonary tuberculosis (3.6%), abdominal tuberculosis (1.9%), Crohn’s disease (1.9%), diabetes mellitus (1.9%), systemic hypertension (0.9%), hepatitis C infection (0.9%), chronic obstructive pulmonary disease (0.9%), asthma (0.9%), coronary artery disease (0.9%), renal stone (0.9%) and, finally, carcinoma of the rectum (0.9%), oropharynx (0.9%), and urinary bladder (0.9%). The use of addictive substances was reported by 55.5% of the participants. Among these, 30% reported alcohol use disorders, 50% reported smoking, and a minority (2.7%) used chewable tobacco. Preoperatively, 79.1% reported excellent sleep quality, and the rest reported good sleep quality. On postoperative day 8, 34.5% rated their sleep quality as poor to fair, and the rest rated it as good. Among all the participants, only 3.6% were categorized as having a high risk for OSA.
Factors affecting postoperative sleep quality
Table 1 depicts a comparison of the study variables between participants with good and poor sleep quality during the postoperative period. Interestingly, poor-to-fair sleep quality during the postoperative period was associated with higher CRP-h levels, a marker of inflammation. There was no association between other medical comorbidities and postoperative sleep quality (31.8% of patients without any comorbidity had poor sleep quality and 45.5% had other medical comorbidities; χ2 = 1.44; degrees of freedom [df] = 1; P = .22). Postoperative poor sleep quality was also associated with wound complications starting on the third postoperative day (Figure 1). Sleep quality was also dependent on total sleep time (Figure 2); however, total sleep time was poorly correlated with pain scores (morning and evening), total leukocyte count, serum albumin, and CRP-h (Figure 3).
Table 1.
Comparison of continuous variables based on sleep quality during the postoperative period.
| No. | Variable | Postoperative Sleep Quality | P | |
|---|---|---|---|---|
| Poor–Fair (n = 38) | Good (n = 72) | |||
| 1. | Age (years) | 44.47 ± 17.99 | 40.22 ± 15.01 | .28 |
| 2. | BMI (kg/m2) | 20.54 ± 2.66 | 20.32 ± 2.05 | .88 |
| 3. | Evening pain score |
|
||
| Preoperative | 8.71 ± 1.06 | 8.56 ± 1.27 | ||
| POD1 | 3.63 ± 1.10 | 2.92 ± 0.85 | ||
| POD2 | 3.23 ± 1.30 | 2.20 ± 0.88 | ||
| POD3 | 2.97 ± 1.19 | 1.54 ± 0.90 | ||
| POD4 | 2.36 ± 1.39 | 0.95 ± 0.95 | ||
| POD5 | 1.78 ± 1.11 | 0.68 ± 0.83 | ||
| POD6 | 1.28 ± 0.92 | 0.38 ± 0.54 | ||
| POD7 | 0.76 ± 0.94 | 0.16 ± 0.41 | ||
| POD8 | 0.39 ± 0.75 | 0.09 ± 0.34 | ||
| 4. | APACHE-II score |
|
||
| Preoperative | 11.68 ± 3.35 | 10.29 ± 3.01 | ||
| POD1 | 8.81 ± 1.70 | 7.41 ± 1.78 | ||
| POD2 | 7.63 ± 1.65 | 6.34 ± 1.67 | ||
| POD3 | 6.81 ± 1.48 | 5.66 ± 1.69 | ||
| POD4 | 5.65 ± 1.68 | 4.95 ± 1.61 | ||
| POD5 | 4.76 ± 1.28 | 4.26 ± 1.42 | ||
| POD6 | 4.13 ± 1.27 | 3.68 ± 1.07 | ||
| POD7 | 3.63 ± 1.14 | 3.20 ± 0.55 | ||
| POD8 | 3.23 ± 0.88 | 3.00 ± 0.16 | ||
| 5. | Total leukocyte counts (×103/mm3) |
|
||
| Preoperative | 10.52 ± 6.37 | 13.12 ± 6.12 | ||
| POD1 | 12.80 ± 7.02 | 10.86 ± 6.48 | ||
| POD3 | 11.55 ± 5.47 | 11.24 ± 6.13 | ||
| POD5 | 11.57 ± 4.63 | 10.58 ± 5.03 | ||
| POD7 | 10.65 ± 3.97 | 10.58 ± 5.37 | ||
| 6. | Serum CRP-h |
|
||
| Preoperative | 180.97 ± 26.74 | 169.65 ± 41.26 | ||
| POD1 | 157.36 ± 28.52 | 145.10 ± 42.16 | ||
| POD3 | 117.09 ± 33.93 | 94.47 ± 38.74 | ||
| POD5 | 72.50 ± 38.02 | 53.16 ± 28.58 | ||
| POD7 | 32.17 ± 27.32 | 8.81 ± 1.70 | ||
| 7. | Serum albumin |
|
||
| Preoperative | 2.88 ± 1.66 | 2.83 ± 0.68 | ||
| POD1 | 2.32 ± 0.54 | 2.54 ± 0.60 | ||
| POD3 | 2.30 ± 0.50 | 2.67 ± 0.49 | ||
| POD5 | 2.50 ± 0.51 | 2.92 ± 0.50 | ||
| POD7 | 2.69 ± 0.53 | 3.12 ± 0.49 | ||
APACHE II = Acute Physiology and Chronic Health Evaluation II, BMI = body mass index, CRP-h = C-reactive protein high sensitivity, POD = postoperative day.
Figure 1. Proportion of wound complications between groups having poor-to-fair and good sleep quality during the postoperative period.
Figure 2. Comparison of total sleep time based on postoperative sleep quality.
Figure 3. Scatterplot depicting the correlation between various continuous variables.
CRP-h = C-reactive protein high sensitivity, TLC = total leukocyte count.
Factors affecting wound complications/impaired healing on day 8
Wound status on the postoperative day was not affected by sex (P = .30), age (P = .26), body mass index (P = .23), use of addictive substances (P = .35), or risk of OSA (P = .19). However, chances of wound complications were greater in those with poor sleep quality (92.1% with poor sleep quality vs 18.1% with good sleep quality; χ2 = 55.45; df = 1; P < .001), other medical comorbidities (68.2% in participants with comorbidities compared with 37.5% without comorbidities; χ2 = 6.73; df = 1; P = .009), higher Acute Physiology and Chronic Health Evaluation II score during the postoperative period (9.98 + 2.26 in uncomplicated vs 11.87 + 3.05 in complicated wound; t = −3.26; df = 99.81; P < .001), lesser average total sleep time during the postoperative period (7.89 + 0.56 in uncomplicated vs 7.11 + 0.46 hours in complicated wound; t = 7.90; df = 107.49; P < .001), greater average pain scores during the morning (2.08 + 0.47 in uncomplicated vs 2.82 + 0.64 in complicated wound; t = −6.63; df = 82.73; P < .001) and at night (1.90 + 0.52 in uncomplicated vs 2.66 + 0.76 in complicated wound; t = −5.87; df = 79.09; P < .001), greater mean total leukocyte count (Mann–Whitney U = 866.5; P < .001), higher mean CRP-h (Mann–Whitney U = 1,058.50; P = .01), and lesser serum albumin (2.80 + 0.49 in uncomplicated vs 2.61 + 0.57 in complicated wound; t = 1.85; df = 92.92; P = .03).
Association between sleep quality and wound healing
Table 2 shows the binary logistic regression analysis of the effect of postoperative sleep quality on wound status on postoperative day 8 in the unadjusted model and the model adjusted for age, sex, and body mass index. Table 3 depicts the results after including all the factors significantly associated with wound healing. This model was significant overall (χ2 = 118.40; df = 9; P < .001), correctly classified 92.7% of the cases, and explained 88% of the variance in the outcome (Negelkerke R2 = 0.88). It suggested that impaired wound healing on postoperative day 8 was associated with shorter total sleep time, greater total leukocyte count, presence of comorbidities, and poor sleep quality during the postoperative week.
Table 2.
Relationship between wound complication* on postoperative day 8 and self-reported sleep quality during postoperative period.
| No. | Factor | B | Standard Error | P | Odds Ratio | 95% CI | Correction Classification (%) | Negelkerke R2 | |
|---|---|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||||
| 1. | Unadjusted model | ||||||||
| Poor–fair sleep quality | 3.96 | 0.67 | <.001 | 52.94 | 14.09 | 198.84 | 85.5 | 0.57 | |
| 2. | Adjusted for age, sex and BMI | ||||||||
| Poor–fair sleep quality | 4.00 | 0.69 | <.001 | 54.93 | 14.18 | 212.75 | 85.5 | 0.57 | |
| Age | −0.008 | 0.01 | .65 | 0.99 | 0.95 | 1.02 | |||
| Male sex | 0.11 | 0.64 | .86 | 1.11 | 0.31 | 3.93 | |||
| BMI | 0.07 | 0.13 | .58 | 1.07 | 0.82 | 1.40 | |||
Dichotomized at Southampton scale grade 3. BMI = body mass index, CI = confidence interval.
Table 3.
Multivariate analysis of factors associated with wound complication* at postoperative day 8.
| No. | Factor | B | Standard Error | P | Odds Ratio | 95% CI for Odds Ratio | |
|---|---|---|---|---|---|---|---|
| Lower | Upper | ||||||
| 1. | Poor–fair sleep quality during postoperative period | 4.35 | 1.56 | .005 | 78.14 | 3.65 | 1,670.62 |
| 2. | Presence of other comorbidities | 4.58 | 1.82 | .01 | 98.43 | 2.74 | 3,526.83 |
| 3. | Average APACHE II score | 0.29 | 0.18 | .11 | 1.34 | 0.93 | 1.94 |
| 4. | Average total sleep time (hours/day) | −5.68 | 2.17 | .009 | 0.003 | 0.00 | 0.24 |
| 5. | Average pain score (morning) | 2.58 | 3.15 | .41 | 13.20 | 0.02 | 6,374.61 |
| 6. | Average pain score (evening) | 0.62 | 2.93 | .83 | 1.85 | 0.006 | 579.31 |
| 7. | Mean total leukocyte count (×103/mm3) | 0.57 | 0.20 | .005 | 1.78 | 1.19 | 2.66 |
| 8. | Serum albumin (average) (g %) | 2.58 | 1.42 | .06 | 13.23 | 0.81 | 214.30 |
| 9. | Serum CRP-h (mg %) | 0.03 | 0.02 | .20 | 1.03 | 0.98 | 1.09 |
Dichotomized at Southampton scale grade 3. APACHE II = Acute Physiology and Chronic Health Evaluation II, CI = confidence interval, CRP-h = C-reactive protein high sensitivity.
DISCUSSION
This study showed that poor sleep quality, medical comorbidities, lower total sleep time, and higher total leukocyte count during the postoperative period were associated with a higher chance of wound complications, after controlling for other confounders. To our knowledge, this is the first study to assess the association between sleep quality and wound healing by primary intention.
As previously mentioned, 3 animal studies have assessed the effect of sleep on wound healing.10,11,13 However, there are certain differences between these studies and the present study. First, animal models focused on healing by secondary intention, whereas the present study deals with healing by primary intention. Second, the animal studies assessed healing by measuring the ulcer area, whereas the present study focuses on wound complications as a surrogate marker for wound healing. Third, the animal studies were of an experimental design and used sleep deprivation protocols, whereas the present study is observational and focuses on observed sleep quality and sleep duration. Finally, sleep deprivation (total or partial) and sleep fragmentation were used as surrogate markers of poor sleep quality in animal studies because direct measurement of sleep quality is not possible in animals.
Animal studies have shown that a reduced total sleep time negatively affects wound healing. In 1 study, the sleep deprivation protocol was initiated after ulcer formation, which resulted in partial sleep deprivation (complete deprivation of REM sleep along with 31% loss of non-REM sleep for 3 days), akin to reduced total sleep time.10 Sleep-deprived rats had larger ulcer areas and a slower “rate of healing” compared with non-sleep-deprived rats. When the rats were allowed to resume sleep, healing improved in sleep-deprived rats, although the ulcer area remained larger in sleep-deprived rats than in normal-sleeping rats. This may have resulted from an initial difference in the ulcerated area caused by sleep deprivation.10 In contrast, sleep deprivation (> 80% deprivation of REM sleep along with > 35% loss of non-REM sleep for 3 days) initiated 7 days following ulcer creation did not show any difference.9 Although the models are different, the findings of animal studies and the present study show that a reduction in total sleep time, an aspect of poor sleep quality, impairs wound healing (Figure 2).22
Interestingly, the timing of sleep deprivation relative to the phase of wound healing is also important. Sleep deprivation occurring only during the inflammatory and proliferative phases of wound repair was found to alter healing, and no effect was observed when the sleep deprivation protocol was initiated 7 days after wound formation.9 In the present study, total sleep was less in the “poor sleep group” throughout the postoperative period, starting from the first postoperative day (Figure 2).
In addition, the sleep stage (REM or non-REM) also plays an important role in wound healing. The effect appears to be related to deprivation of non-REM sleep. This is because selective REM sleep deprivation after wound production did not affect the “time to complete healing of wound” or the “rate of healing.”11 This effect could be related to the secretion of growth hormone, which promotes healing and is secreted during the deep sleep phase of non-REM sleep.24 Poor sleep quality is associated with a reduced proportion of deep sleep as well as sleep fragmentation, which impairs continuity of sleep.25,26 Sleep stages were not directly assessed in the present study. However, it may be deduced that participants reporting poor sleep quality experienced a loss of deep sleep. Another contributor to sleep quality, the number of arousals, was taken into consideration when assessing sleep quality by participants. Participants with poor sleep quality likely experienced them as well.22 Sleep fragmentation is also associated with poor wound healing in obese mice.13
To ensure a causal relationship between sleep quality and wound healing, pieces of evidence obtained from opposite directions must be assessed. A recent meta-analysis reported that nonpharmacological interventions to improve sleep among surgical patients improved several outcomes, but not wound healing.27 Similarly, another meta-analysis reported that patients with burn injuries have poor sleep quality, and the effect of interventions to improve sleep on the outcome remains a research agenda.28
Comorbidities play a significant role in influencing wound healing. In this study, the participants had different comorbidities ranging from systemic infections to carcinoma. Although comorbidities did not affect sleep quality, they were associated with poor wound healing in the univariate and multivariate analyses. The comorbidities reported by the participants in this study could have induced chronic systemic inflammation.29,30 Furthermore, poor sleep quality and short sleep durations also contribute to systemic inflammation.31 Systemic inflammation alters the activity of leukocytes and macrophages, delays wound healing, and further worsens sleep quality.32–34 Finally, systemic inflammation is associated with leukocytosis.35 The findings of this study support the same (Table 3). However, owing to the cross-sectional analysis, it is difficult to discern which came first: inflammation, poor sleep quality, or poor wound healing. A look at the longitudinal data (Figure 2 and Figure 3) suggests that although sleep quality and total sleep time varied from that of the first postoperative day, differences in wound complications appeared on postoperative day 3. This may suggest that poor sleep quality led to systemic inflammation (refer to the difference in the values of CRP-h in Table 1) and impaired wound healing.
The proposed model is based on the findings of previous studies. Chen et al10 reported that sleep deprivation increased the levels of proinflammatory cytokines (tissue necrosis factor α, interleukin 1β, interleukin 6, and interleukin 8) and biomarkers of oxidative stress in wounds (malonaldehyde and superoxide dismutase), along with an increase in serum serotonin levels. The authors proposed that this resulted in wound progression and induced hyperalgesia.10 Similarly, McLain et al13 reported that sleep fragmentation was associated with an increased expression of messenger ribonucleic acid within the wound. Although inflammation is important for wound healing, persistent inflammation impairs healing by blocking the proliferative phase.10,13 This could explain why pain perception and inflammation markers were higher among patients reporting poor sleep quality in the present study (Table 1).
It must be kept in mind that pain and sleep have a bidirectional relationship, in which pain interferes with sleep and disturbed sleep escalates pain perception.8 Pain relief measures have been reported to improve wound healing36 whereas pain has been reported to impair healing.37 Similarly, addressing sleep disturbances has been found to improve the perceptions and biomarkers associated with chronic pain.7 Preclinical studies have shown that maintenance of the sleep cycle is important for various phases of wound healing.38 Thus, improvements in pain and sleep are likely to enhance wound healing. Although high pain scores were associated with impaired healing in the present study, the effects were not significant in the multivariate analysis (Table 3). Thus, the effects of pain appear to be mediated by sleep quality. However, few studies have assessed the differential effects of pain and sleep quality on wound healing, and this issue needs to be addressed in future studies, preferably in randomized trials.
However, the present study is not without limitations. First, the proportion of patients with poor sleep quality was relatively small. Second, the variation in the ages of the participants was large, which may have influenced healing and sleep quality.4 Third, polysomnography was not conducted to rule out other sleep disorders such as OSA, which can potentially impair abdominal wound healing.15 Polysomnography could also have helped in assessing microarousal, the proportion of deep sleep, and the calculation of sleep efficiency, which affect the perception of sleep quality. Finally, inflammatory marker levels were not assessed either in the wound or serum. It could have helped to better understand the process of how wound healing was affected. A point to note here is that one should be aware of reversed causality, because diminished sleep could be caused by factors associated with more wound complications, such as psychological distress arising out of a hospital stay and surgical and medical interventions, and the effect of antibiotics and pharmaceutical agents on sleep. Importantly, because the participants were aware of the study objectives, it is possible that those with poor wound healing reported poor sleep quality. This can be overcome by using polysomnography in future studies.
To conclude, this is the first human study analyzing the association between sleep quality and surgical wound healing. Poor sleep quality during the postoperative wound-healing phase is associated with wound complications and may be considered a surrogate marker of impaired healing.
DISCLOSURE STATEMENT
All authors have seen and approved this manuscript. The authors report no conflicts of interest.
ACKNOWLEDGMENTS
The authors thank Dr. Netzer and Dr. Snyder, who allowed them to use Berlin Questionnaire and the single-item sleep quality scale, respectively, in this study.
ABBREVIATIONS
- CRP-h
c-reactive protein high sensitivity
- df
degrees of freedom
- OSA
obstructive sleep apnea
- REM
rapid eye movement
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