Abstract
Background:
Hospital noise pollution represents a major environmental stressor for patients with coronary artery disease (CAD), potentially affecting cardiovascular parameters and recovery outcomes. This study aims to investigate the effect of noise exposure on heart rate variability (HRV) and stress responses in CAD patients.
Methods:
A retrospective cohort study was conducted between January 2022 and December 2023 with 200 CAD patients who underwent percutaneous coronary intervention. In accordance with a temporal sequential design, 97 patients were treated in standard wards (January–August 2022), whereas 103 patients were treated in noise-controlled wards (November 2022–December 2023) after noise reduction protocols were implemented. Noise parameters, HRV indices [standard deviation of normal-to-normal intervals (SDNN), standard deviation of the averages of normal-to-normal intervals (SDANN) and low frequency/high frequency ratio (LF/HF)], salivary cortisol level, sleep quality [Pittsburgh Sleep Quality Index (PSQI)] and clinical outcomes were measured at preoperation and on postoperative day 5.
Results:
Noise levels were significantly lower in noise-controlled wards than in standard wards during daytime and nighttime hours (P < 0.001). After 5 days of hospitalisation, patients in noise-controlled wards exhibited significantly improved HRV parameters, including higher SDNN and SDANN, lower LF/HF ratios, lower salivary cortisol levels and better PSQI scores (P < 0.05), than those in standard wards. Additionally, patients in noise-controlled wards experienced shorter hospital stays and a lower incidence of recurrent angina (P < 0.05) than those in standard wards.
Conclusions:
Noise reduction in hospital wards significantly improved HRV parameters and reduced stress markers in CAD patients. The implementation of noise control measures may represent a cost-effective strategy to improve outcomes for CAD patients during hospitalisation.
Keywords: coronary artery disease, heart rate variability, hospital environment, noise exposure, stress response
KEY MESSAGES
-
(1)
Noise control in patients with coronary artery disease (CAD) can improve heart rate variability and reduce stress markers, such as cortisol levels.
-
(2)
CAD patients in noise-controlled wards experienced significantly better sleep quality than those in standard wards.
-
(3)
The clinical outcomes of CAD patients in noise-controlled wards were significantly better than those in standard wards, including shortened hospital stays and reduced recurrent angina incidents.
INTRODUCTION
Coronary artery disease (CAD) remains a leading cause of morbidity and mortality worldwide.[1] Patients with CAD are particularly vulnerable to environmental stressors, which can precipitate physiological changes that may exacerbate their condition.[2] Amongst these environmental factors, noise pollution in healthcare settings has attracted increasing attention as a potential modifiable risk factor that can influence cardiovascular parameters and recovery outcomes.[3,4] Hospital environments are characterised by multiple noise sources, including medical equipment, staff activities, conversations and alarms. A previous study has reported that average noise levels in hospital wards range from 45 to 68 dB, with peaks frequently exceeding 85 dB.[5] These levels substantially exceed the World Health Organisation’s recommendation that average hospital noise levels should not exceed 35 dB.[6]
Heart rate variability (HRV) has emerged as an important non-invasive measure of autonomic nervous system function and a predictor of cardiovascular health outcomes.[7] Reduced HRV has been associated with increased morbidity and mortality in patients with CAD.[8] Environmental noise exposure has been shown to affect HRV parameters in healthy individuals, but comprehensive data regarding its effects in CAD patients remain limited.[9] Noise exposure can influence cardiovascular health through multiple pathways, including the dysregulation of the autonomic nervous system and activation of stress response systems. Furthermore, exposure to noise can trigger a cascade of stress responses, including the activation of the hypothalamic–pituitary–adrenal (HPA) axis and subsequent elevation of cortisol levels.[10] The chronic elevation of cortisol has been linked to adverse cardiovascular outcomes through mechanisms that include inflammation, endothelial dysfunction and metabolic dysregulation.[11] For CAD patients, these pathophysiological changes may potentially complicate recovery and influence prognosis. Despite the theoretical foundation suggesting that noise reduction may benefit CAD patients, evidence regarding the effectiveness of noise control in hospital settings for this specific patient population remains insufficient.[12] Previous studies have primarily focused on intensive care settings or evaluated subjective measures without comprehensively assessing physiological parameters.[12] Notably, limited research has specifically examined the effect of noise reduction on HRV parameters and stress biomarkers in CAD patients after percutaneous coronary intervention (PCI) in general ward settings.
Our study aims to address the above knowledge gap by investigating the associations of hospital noise exposure with HRV parameters, stress responses and clinical outcomes in CAD patients after PCI. Our work represents the first comprehensive evaluation of noise reduction effects on autonomic function and stress biomarkers in post-PCI patients in general hospital wards. Its findings may provide evidence to support the implementation of noise control measures as a standard component of care for CAD patients during hospitalisation.
MATERIALS AND METHODS
Study design and participants
We conducted this retrospective cohort study at the General Hospital of the Yangtze River Shipping (Wuhan Brain Hospital) between January 2022 and December 2023. The study protocol was approved by the Ethics Committee of the General Hospital of the Yangtze River Shipping (approval number: L20210052) and adhered to the principles of the Declaration of Helsinki.[13] Written informed consent was obtained from all participants.
A total of 236 patients were assessed for eligibility between January 2022 and December 2023. Amongst these patients, 28 were excluded because of incomplete data, and eight were excluded because of severe cardiac arrhythmias. Ultimately, 200 CAD patients were included in the analysis.
This study followed a temporal sequential design. Patients were divided into two groups based on whether noise reduction renovations were performed on their wards. The standard ward group consisted of 97 patients admitted and treated between January 2022 and August 2022. The noise-controlled ward group included 103 patients who were admitted and treated between January 2023 and August 2023, after the hospital had implemented comprehensive noise reduction protocols in cardiac wards.
Inclusion and exclusion criteria
The inclusion criteria for this study were the following: (1) age ≥18 years old; (2) confirmed diagnosis of CAD and coronary angiography showing ≥70% stenosis in at least one major coronary artery or its branches; (3) underwent PCI and hospitalised for at least 5 days; (4) normal hearing and (5) complete medical data.
Exclusion criteria included the following: (1) severe cardiac arrhythmias or implanted pacemakers that could affect HRV measurements; (2) acute myocardial infarction within 30 days prior to enrolment; (3) congestive heart failure [New York Heart Association (NYHA) classes III–IV]; (4) severe hepatic or renal dysfunction; (5) endocrine disorders affecting cortisol levels; (6) use of glucocorticoid medications within 3 months and (7) psychiatric disorders or use of psychotropic medications.
Ward management
Ward environment renovation
Our Cardiology Department is situated on a single floor in the hospital’s east wing, containing 8 patient rooms with 40 hospital beds (5 beds per room). In September 2022, a comprehensive noise reduction renovation project was implemented across the entire ward area. Prior to this renovation (January–August 2022), all rooms operated as standard wards with routine noise management. After the completion of the renovation and a period of stabilisation (September–December 2022), the entire wards were operated under noise-controlled protocols. This temporal separation between standard and noise-controlled wards ensured the proper evaluation of noise reduction. The average ward occupancy during the study period was approximately 85%.
Routine ward management
Patients in the standard ward group received routine care in standard wards. Patients were provided with routine CAD care, including medication, vital sign monitoring and cardiac rehabilitation guidance. Nursing staff conducted routine rounds every 2–4 hours. Vital sign measurements were performed every 4 hours (including during nighttime). Blood sampling and other routine diagnostic procedures were scheduled in accordance with departmental convenience. Routine cleaning procedures were conducted during regular daytime hours. Medical equipment was operated with default alarm settings, and patient monitoring systems and infusion pumps functioned at manufacturer-recommended alarm volumes. Regular television sets and intercoms were available to patients, without restrictions on volume during daytime hours. Communication systems included standard nurse call systems and overhead paging for staff communications, and routine medical team discussions were often conducted at patient bedsides or in corridors. Standard visiting hours (10:00–20:00) were implemented with no strict enforcement of visitor numbers and no specific rules regarding visitor-generated noise.
Noise-controlled ward management
Patients in the noise-controlled ward group received care in noise-controlled wards. The noise reduction protocols included the following measures:
(1) Facility modifications: All patient room doors were replaced with sound-insulated doors featuring acoustic seals around the edges. Windows were upgraded to double-glazed panels with acoustic lamination to reduce noise transmission from outside the building. Door hinges were lubricated and adjusted for silent operation, and automatic door closers were installed with delayed, gentle closing mechanisms. Flooring was upgraded to sound-absorbing materials in corridors and patient rooms to reduce footstep noise and equipment rolling sounds.
(2) Equipment adaptations: Alarm volumes on monitoring equipment were reduced. Visual alarm systems were used to complement auditory alerts and vibrating pagers for staff to reduce overhead paging. Television sets equipped with headphone jacks were implemented.
(3) Staff training: Staff underwent comprehensive education on noise reduction practices before noise-control ward management. This education included a 2-day intensive training programme for a total of 16 hours. Monthly 3-hour reinforcement sessions were held throughout the study period. Training content included noise awareness education, quiet communication techniques, gentle equipment handling and coordinated care delivery methods. Staff followed protocols that included a modified nursing workflow to consolidate patient care activities, wearing soft-soled shoes, speaking in a low and soft voice as much as possible and staggering medication rounds to avoid peak visiting hours (10:00–12:00 and 18:00–20:00). Adherence to noise reduction protocols was monitored through weekly supervisor observations and monthly noise level feedback sessions with corrective action when necessary.
(4) Temporal strategies: Designated quiet hours (22:00–06:00) were established to minimise disturbances. Clinical procedures were reduced during these hours, and cleaning schedules were modified to avoid early mornings and late evenings. Cleaning staff received specialised training on noise reduction techniques. Care activities to minimise nighttime disruptions, reduced frequency of nighttime vital sign measurements for stable patients and bundled care approaches to minimise room entries/exits were implemented.
(5) Patient-centred approaches: Earplugs and eye masks were provided to all patients. Sleep hygiene education was offered to patients and their caregivers at admission. White noise machines were available upon request. Visitor numbers during visiting hours were restricted (maximum 2 person/day). Patient-controlled lighting devices with dimming capabilities were also provided.
(6) Communication protocols: Overhead paging was eliminated except for emergencies, and text-based communication systems were used for routine staff communications. Designated areas away from patient rooms were set for staff discussions and handovers. Bedside tablets for patient–staff communication were provided instead of call bells. All patients received personalised training on device usage upon admission to ensure independent use.
Noise measurement
Noise levels were continuously monitored in both ward types by using calibrated sound level meters (Model SLM-100, AudioTech Inc., Japan). The devices were positioned at 1.2 m above the floor and at least 1 m from walls and major reflective surfaces. The number of sound level meters in each patient room was allocated in accordance with room area, with rooms smaller than 30 m2 equipped with one sound level meter positioned at the geometric centre and those larger than 30 m2 equipped with two sound level meters positioned to ensure the comprehensive coverage of the acoustic environment. Measurements were recorded at 5-minute intervals throughout the 24-hour period and averaged for each day of hospitalisation. Parameters analysed included A-weighted equivalent continuous sound level (LAeq), minimum sound level (LAmin) and maximum sound level (LAmax) during the day (06:00–22:00) and night (22:00–06:00).
Data collection
Baseline characteristics
Data on baseline characteristics were collected retrospectively from electronic medical records and patient questionnaires administered during hospitalisation. Core demographic data, including sex (male/female), age, body mass index and CAD severity, were collected. Current smoking status (nonsmoker/active smoker/cessation ≥6 months) and alcohol consumption patterns [nondrinker/moderate (<14 units/week)/heavy (≥14 units/week)] were obtained via self-reported questionnaires. Cardiac function was assessed by using NYHA classification. Comorbidity and medication regimens were extracted from electronic medical records. Pharmacotherapeutic regimens included antiplatelet agents (single, dual, or triple therapy); β-blockers and statin utilisation patterns. All parameters underwent dual-source verification by independent clinical researchers blinded to experimental endpoints.
HRV assessment
HRV data were collected prospectively during hospitalisation by using standardised protocols. HRV was assessed through 24-hour Holter monitoring (CardioTracker-3000, BioSignal Corp., Tokyo, Japan) with recordings initiated between 08:00 and 09:00. Patients were maintained on their regular medication regimen during the recording period. The Holter was applied at preoperation and on postoperative day 5. Time-domain HRV parameters were analysed. They included the following: (1) standard deviation of normal-to-normal intervals (SDNN) and (2) the standard deviation of the averages of N–N intervals in all 5-minute segments (SDANN). Frequency-domain parameters, including low-frequency (LF: 0.04–0.15 Hz) power, high-frequency (HF: 0.15–0.4 Hz) power and LF/HF ratio, which reflects sympatho-vagal balance, were also analysed.
Stress biomarkers
Salivary cortisol level was detected by Salivette devices (Sarstedt, Nümbrecht, Germany) at the following three time points: morning (08:00), afternoon (16:00) and evening (22:00) at preoperation (upon admission) and on postoperative day 5. Patients were instructed to avoid eating, drinking or brushing their teeth for at least 30 minutes before collection. Samples were centrifuged at 1000 × g for 2 minutes and stored at −20 °C until analysis. Cortisol levels were determined by using a commercial enzyme immunoassay kit (Salimetrics, LLC, State College, PA, USA).
Vital signs
Vital signs were collected prospectively during hospitalisation following standardised measurement protocols. Systolic blood pressure (SBP), diastolic blood pressure (DBP) and heart rate (HR) were measured every 4 hours in triplicate by using a calibrated automated device (OmronHEM-7320, Omron Healthcare, Kyoto, Japan). Data were taken at preoperation and on postoperative day 5.
Sleep quality assessment
Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI) at preoperation and on postoperative day 5.[14,15] It contains the following seven domains: subjective sleep quality (one item); sleep latency (time to fall asleep, two items); sleep duration (hours/night, one item); habitual sleep efficiency (ratio of time asleep to time in bed, one item); sleep disturbances (e.g., nighttime awakenings, nine items); use of sleep medications (one item) and daytime dysfunction (two items). Each domain is scored 0–3, with a global score range of 0–21 and a cut-off >7 indicating poor sleep quality (Cronbach’s α = 0.82). Certified nurses administered all evaluations in dedicated confidential environments, implementing standardised digital data collection protocols to ensure optimal accuracy.
Clinical outcomes
The clinical outcomes indicators included hospital stay; incidence of major adverse cardiac events (recurrent angina, acute myocardial infarction, malignant arrhythmias or cardiac death) during hospitalisation; requirement for rescue antianginal medications and readmission within 30 days after discharge.
Statistical analysis
Statistical analyses were performed with SPSS 26.0 (IBM Corp., Armonk, NY, USA), and tables were generated by using Microsoft Excel 2021 (Microsoft Corporation, Redmond, WA, USA). The distributional characteristics of continuous variables were verified through Shapiro–Wilk normality testing. Continuous data conforming to normal distribution were expressed as mean ± standard deviation (SD) and subjected to intergroup comparisons via independent samples t-tests, with longitudinal within-subject analyses conducted through paired t-test. Categorical variables were expressed as frequency distributions (counts and proportional percentages) and analysed by using appropriate statistical tests on the basis of the following criteria: Chi-squared test (χ2) was applied when all expected cell frequencies were ≥5 and the total sample size was ≥40. Fisher’s exact test was used when any expected cell frequency was <5, when the total sample size was <40 or when dealing with 2 × 2 contingency tables with small sample sizes to ensure accurate probability calculations. P < 0.05 (two-tailed) was considered statistically significant.
RESULTS
Baseline characteristics
The baseline demographic and clinical characteristics of the participants are presented in Table 1. No significant differences were observed between the noise-controlled and standard ward groups in terms of age, sex distribution, body mass index, smoking status, alcohol consumption or educational level. Additionally, no significant differences were observed in cardiac function classification, vessel involved, comorbidities, previous treatment history or current medications. These findings revealed that the two groups were balanced and comparable.
Table 1.
Baseline demographic and clinical characteristics of the study participants
| Characteristic | Noise-controlled ward group (n = 103) | Standard ward group (n = 97) | Statistics | P |
|---|---|---|---|---|
| Age (years) | 62.43 ± 8.71 | 63.08 ± 9.24 | t = 0.512 | 0.609 |
| Male sex, n (%) | 65 (63.10) | 66 (68.04) | χ2 = 0.538 | 0.463 |
| Body mass index (kg/m2) | 23.83 ± 2.64 | 23.12 ± 2.89 | t = 1.816 | 0.071 |
| Smoking status, n (%) | χ2 = 0.725 | 0.696 | ||
| Non-smoker | 52 (50.49) | 45 (46.39) | ||
| Cessation ≥6 months | 20 (19.42) | 19 (19.59) | ||
| Active smoker | 31 (30.09) | 33 (34.02) | ||
| Alcohol consumption, n (%) | χ2 = 0.627 | 0.731 | ||
| None | 60 (58.25) | 53 (54.64) | ||
| Moderate | 16 (15.54) | 15 (15.47) | ||
| Heavy | 27 (26.21) | 29 (29.89) | ||
| Educational level, n (%) | χ2 = 1.086 | 0.581 | ||
| Primary school or below | 30 (29.13) | 33 (34.02) | ||
| Secondary school | 49 (47.57) | 44 (45.36) | ||
| College or above | 24 (23.30) | 20 (20.62) | ||
| NYHA classification, n (%) | χ2 = 0.232 | 0.630 | ||
| Class I | 65 (63.11) | 58 (59.79) | ||
| Class II | 38 (36.89) | 39 (40.21) | ||
| Vessel involved, n (%) | χ2 = 0.543 | 0.762 | ||
| Single vessel | 38 (36.89) | 34 (35.05) | ||
| Double vessel | 42 (40.78) | 37 (38.14) | ||
| Triple vessel | 23 (22.33) | 26 (26.81) | ||
| Previous MI, n (%) | 22 (21.36) | 24 (24.74) | χ2 = 0.323 | 0.570 |
| Previous PCI, n (%) | 18 (17.48) | 19 (19.59) | χ2 = 0.153 | 0.696 |
| Previous CABG, n (%) | 8 (7.77) | 10 (10.31) | χ2 = 0.394 | 0.530 |
| Comorbidities, n (%) | ||||
| Hypertension | 58 (56.31) | 56 (57.73) | χ2 = 0.019 | 0.890 |
| Diabetes mellitus | 33 (32.04) | 35 (36.08) | χ2 = 0.364 | 0.546 |
| Dyslipidaemia | 72 (69.91) | 71 (73.19) | χ2 = 0.266 | 0.606 |
| COPD | 12 (11.65) | 14 (14.43) | χ2 = 0.342 | 0.559 |
| Antiplatelet therapy, n (%) | χ2 = 0.231 | 0.891 | ||
| Single antiplatelet | 19 (18.45) | 16 (16.49) | ||
| Dual antiplatelet | 78 (75.73) | 75 (77.32) | ||
| Triple antiplatelet | 6 (5.82) | 6 (6.19) | ||
| Current medications, n (%) | ||||
| P2Y12 inhibitors | 81 (78.64) | 78 (80.41) | χ2 = 0.096 | 0.756 |
| Statins | 98 (95.14) | 93 (95.87) | - | 0.538 |
| Beta-blockers | 82 (79.61) | 77 (79.38) | χ2 = 0.002 | 0.968 |
| ACEIs/ARBs | 73 (70.87) | 69 (71.13) | χ2 = 0.002 | 0.969 |
| CCBs | 31 (30.09) | 33 (34.02) | χ2 = 0.352 | 0.552 |
| Nitroglycerin | 57 (55.34) | 53 (54.63) | χ2 = 0.010 | 0.921 |
ACEI, angiotensin-converting enzyme inhibitor; ARB, angiotensin receptor blocker; CABG, coronary artery bypass grafting; CAD, coronary artery disease; CCB, calcium channel blocker; COPD, chronic obstructive pulmonary disease; MI: myocardial infarction; NYHA, New York Heart Association; PCI, percutaneous coronary intervention. ‘-’ Indicated using Fisher’s exact test.
Noise level assessment
During daytime (06:00–22:00) and nighttime (22:00–06:00) hours, noise-controlled wards showed significantly (all P < 0.001) lower LAeq, LAmin and LAmax levels than standard wards [Table 2]. These findings confirmed the effectiveness of the noise control management protocol in our study.
Table 2.
Comparison of noise levels between noise-controlled and standard wards
| Noise parameter | Noise-controlled wards (n = 103) | Standard wards (n = 97) | t | P |
|---|---|---|---|---|
| Daytime (06:00–22:00) | ||||
| LAeq | 44.63 ± 4.12 | 55.92 ± 4.73 | 18.03 | <0.001 |
| LAmin | 35.23 ± 3.02 | 41.07 ± 4.82 | 10.33 | <0.001 |
| LAmax | 67.28 ± 4.36 | 79.53 ± 5.28 | 17.93 | <0.001 |
| Nighttime (22:00–06:00) | ||||
| LAeq | 38.47 ± 3.19 | 43.43 ± 2.76 | 11.73 | <0.001 |
| LAmin | 34.21 ± 2.53 | 38.67 ± 2.12 | 13.47 | <0.001 |
| LAmax | 54.17 ± 3.09 | 63.34 ± 4.71 | 16.37 | <0.001 |
LAeq, A-weighted equivalent continuous sound level; LAmin, minimum sound level; LAmax, maximum sound level.
HRV and vital signs
At baseline (preoperation), no significant differences in HRV parameters or vital signs were found between the two groups. Both groups showed significant improvements in SDNN, SDANN and LF/HF ratio on postoperative day 5 (P < 0.05). The noise-controlled ward group demonstrated significantly better SDNN, SDANN and LF/HF ratio than the standard ward group on postoperative day 5 (P < 0.05).
For vital signs, on postoperative day 5, the noise-controlled ward group had significantly lower HR than the standard ward group (P < 0.05). However, SBP and DBP showed no significant differences between two groups on postoperative day 5 [Table 3].
Table 3.
Comparison of HRV and vital signs between groups
| Variables | Time | Noise-controlled ward group (n = 103) | Standard ward group (n = 97) | t | P |
|---|---|---|---|---|---|
| SDNN (ms) | Preoperation | 64.45 ± 10.34 | 65.76 ± 10.32 | 0.896 | 0.371 |
| Postoperative day 5 | 102.73 ± 18.41* | 95.32 ± 15.58* | 3.063 | 0.003 | |
| SDANN (ms) | Preoperation | 83.16 ± 10.27 | 82.42 ± 10.87 | 0.495 | 0.621 |
| Postoperative day 5 | 98.27 ± 8.52* | 95.64 ± 7.13* | 2.360 | 0.019 | |
| LF/HF ratio | Preoperation | 1.32 ± 0.25 | 1.35 ± 0.22 | 0.899 | 0.370 |
| Postoperative day 5 | 1.16 ± 0.23* | 1.24 ± 0.28* | 2.213 | 0.028 | |
| SBP (mmHg) | Preoperation | 123.42 ± 5.87 | 124.53 ± 6.74 | 1.244 | 0.215 |
| Postoperative day 5 | 125.34 ± 6.53 | 125.76 ± 6.68 | 0.445 | 0.654 | |
| DBP (mmHg) | Preoperation | 75.63 ± 6.84 | 75.15 ± 6.26 | 0.517 | 0.606 |
| Postoperative day 5 | 76.83 ± 5.52 | 75.28 ± 6.13 | 1.881 | 0.061 | |
| HR (bpm) | Preoperation | 72.38 ± 9.15 | 73.26 ± 9.42 | 0.670 | 0.506 |
| Postoperative day 5 | 68.27 ± 6.73* | 70.54 ± 7.36 | 2.278 | 0.023 |
DBP, diastolic blood pressure; HF, high frequency; HR, heart rate; LF, low frequency; SBP, systolic blood pressure; SDANN, standard deviation of the averages of NN intervals in all 5 minutes segments; SDNN, standard deviation of normal-to-normal intervals. *Indicates comparison with preoperative values, P < 0.05.
Stress markers and sleep quality
Stress markers and sleep quality parameters were comparable between groups at baseline (preoperation). By postoperative day 5, patients in noise-controlled wards demonstrated significantly lower salivary cortisol levels at all measurement time points than those in standard wards (P < 0.05). Sleep quality exhibited a similar trend, showing no difference between groups at baseline but improving in the noise-controlled ward group on postoperative day 5 relative to the standard ward group (P < 0.001). These findings suggested that a noise-controlled environment can reduce postoperative stress and improve sleep quality [Table 4].
Table 4.
Comparison of stress markers and PSQI scores between groups
| Variable | Time | Noise-controlled ward group (n = 103) | Standard ward group (n = 97) | t | P | |
|---|---|---|---|---|---|---|
| Salivary cortisol (nmol/L) | Morning (08:00) | Preoperation | 677.43 ± 42.18 | 682.67 ± 39.74 | 0.912 | 0.363 |
| Postoperative day 5 | 298.72 ± 35.63* | 362.84 ± 41.29* | 11.673 | <0.001 | ||
| Afternoon (16:00) | Preoperation | 485.38 ± 31.67 | 491.29 ± 28.94 | 1.384 | 0.168 | |
| Postoperative day 5 | 256.91 ± 28.42* | 302.18 ± 35.76* | 9.648 | <0.001 | ||
| Evening (22:00) | Preoperation | 164.73 ± 22.86 | 168.91 ± 19.42 | 1.398 | 0.164 | |
| Postoperative day 5 | 89.67 ± 15.28* | 118.53 ± 20.74* | 10.936 | <0.001 | ||
| PSQI score | Preoperation | 6.24 ± 1.43 | 6.65 ± 1.68 | 1.862 | 0.064 | |
| Postoperative day 5 | 4.32 ± 1.13* | 5.23 ± 1.42* | 5.029 | <0.001 | ||
PSQI, Pittsburgh Sleep Quality Index; * Indicates comparison with preoperative values, P < 0.05.
Clinical outcomes
Patients in the noise-controlled ward group had shorter hospital stays than those in the standard ward group (P < 0.001). The incidence of recurrent angina during hospitalisation was lower in the noise-controlled ward group (11.65% vs. 22.68%, P = 0.038) than in the standard ward group. No significant differences were observed between groups for other major adverse cardiac events, including acute myocardial infarction and malignant arrhythmias (P > 0.05). No significant difference was observed in the 30-day re-admission rate between the noise-controlled and standard ward groups (P > 0.05), as shown in Table 5.
Table 5.
Comparison of clinical outcomes between groups
| Parameter | Noise-controlled ward group (n = 103) | Standard ward group (n = 97) | Statistics | P |
|---|---|---|---|---|
| Hospital stay (days) | 7.72 ± 1.34 | 8.93 ± 1.79 | t = 5.432 | <0.001 |
| Recurrent angina, n (%) | 12 (11.65) | 22 (22.68) | χ2 = 4.307 | 0.038 |
| Acute myocardial infarction, n (%) | 1 (0.97) | 2 (2.06) | - | 0.614 |
| Malignant arrhythmias, n (%) | 2 (1.94) | 3 (3.09) | - | 0.675 |
| 30 day re-admission, n (%) | 7 (6.80) | 10 (10.31) | χ2 = 0.793 | 0.373 |
Note: − indicated using Fisher’s exact test.
DISCUSSION
Our study examined the associations between patients in noise-controlled wards and those in standard wards. It showed that compared with the latter, the former exhibited significantly better HRV parameters, lower cortisol levels, improved sleep quality and superior clinical outcomes.
The noise levels recorded in standard wards substantially exceeded World Health Organization recommendations for hospital environments and align with those in previous reports on hospital noise pollution.[5] Multiple studies have demonstrated noise as a risk factor for the occurrence and development of CAD.[16,17,18] Despite targeted interventions, noise levels in noise-controlled wards still exceed ideal standards, highlighting the challenge of achieving optimal acoustic environments in hospitals. We conducted a comprehensive multifaceted noise reduction programme combining facility modifications, equipment adaptations, staff training, temporal strategies, patient-centred approaches, communication protocols and ongoing monitoring. These approaches addressed noise sources across multiple domains simultaneously, potentially achieving synergistic effects that surpass the benefits of individual interventions.
We observed remarkable improvements in HRV parameters in patients assigned to noise-controlled wards. SDNN, recognised as a predictor of mortality and morbidity in cardiac patients, was significantly higher in the noise-controlled ward group than in the standard ward group by postoperative day 5. Similarly, in the noise-controlled ward group, SDANN values significantly improved and the LF/HF ratio was reduced, suggesting enhanced vagal tone.[19,20] Noise reduction interventions enhanced parasympathetic tone and reduced sympathetic activation. These effects may lead to progressive improvements in cardiovascular regulation, reduced arrhythmia risk and decreased myocardial oxygen demand, thus potentially contributing to improved long-term outcomes. These findings aligned with the results of previous research showing the acute effects of noise on autonomic function while also documenting sustained effects in a clinical population with existing cardiovascular disease.[21] Environmental noise exposure has been associated with complex physiological responses involving the autonomic nervous system, endocrine activity and cardiovascular regulation.[21] Acoustic stimuli are not only processed through auditory pathways but also activate non-auditory structures, particularly the amygdala and hypothalamus.[22] This autonomic dysregulation has been linked to increased cardiovascular risk through multiple pathways, including enhanced platelet aggregation, endothelial dysfunction and myocardial electrical instability.[23]
While the reduction in HR may appear modest, even small improvements in autonomic balance can be clinically meaningful in CAD patients because reduced HR and enhanced vagal tone are associated with improved cardiovascular prognosis. Despite the significant differences in HRV parameters and HR, no significant differences in SBP and DBP on postoperative day 5 were found between groups. This absence of blood pressure variation likely reflects the standardised antihypertensive medication regimens administered to post-PCI patients. The therapeutic effects of these medications may have masked any potential noise-induced changes in blood pressure. This pharmacological control represents an important confounding factor when assessing environmental noise effects on cardiovascular parameters in this clinical population.
Environmental noise exposure has been associated with stress responses and HPA axis activation, leading to the release of corticotropin-releasing hormone and vasopressin, which stimulates the pituitary to release adrenocorticotropic hormone, ultimately driving the adrenal cortex to secrete glucocorticoids like cortisol.[24,25] The results of our work showed that after 5 days of hospitalisation, cortisol levels were higher in the standard ward group than in the noise-controlled ward group. The observed disruption of normal diurnal cortisol patterns in our present study may affect CAD patients, given that flattened cortisol rhythms are linked to accelerated atherosclerosis and an increased risk of recurrent cardiac events.[26] In addition, although our work only recorded the effect of noise exposure over a short period, previous studies have reported that chronic noise exposure can lead to prolonged HPA axis activation. This situation may potentially downregulate glucocorticoid receptors on immune cells, weakening the ability of glucocorticoids to suppress inflammatory responses, a phenomenon known as cortisol resistance.[27,28]
Moreover, sleep disturbance may serve as a mediating pathway between noise exposure and cardiovascular effects. Noise can fragment sleep architecture without causing full awakening, resulting in reduced slow-wave and rapid eye movement sleep.[29] These changes in sleep microstructure have been linked to metabolic dysregulation, increased oxidative stress and enhanced inflammatory responses, which may exacerbate underlying CAD conditions.[29] The improved PSQI scores in the noise-controlled ward group likely reflect improved sleep quality that may benefit cardiovascular regulation.
The observed associations between noise exposure and clinical outcomes in our study suggest potential clinical relevance. The higher incidence of recurrent angina in the standard ward group than in the noise-controlled ward group is likely due to noise-triggered sympathetic activation, which could potentially increase myocardial oxygen demand by elevating HR and blood pressure while also reducing oxygen supply through coronary vasoconstriction.[30] This combination is particularly dangerous for CAD patients. Prolonged hospital stays in the standard ward group may be associated with noise-mediated sleep fragmentation, which could potentially impair tissue healing through disrupted growth hormone secretion and altered immune function. Additionally, noise-associated psychological stress may activate pro-inflammatory pathways, potentially delaying the resolution of coronary inflammation and contributing to the increased incidence of recurrent symptoms.[31]
The clinical implications of our findings suggest that noise reduction should be considered as an intervention for CAD patients rather than merely a comfort measure. The modifications implemented in noise-controlled wards were inexpensive yet yielded measurable physiological and clinical benefits. Given the observed reductions in hospital stay and recurrent angina rates, these modifications may offer favourable cost-effectiveness ratios. However, formal economic evaluations are needed to quantify their financial benefits relative to their implementation costs. Nighttime noise control may be achieved through operational changes even when facility modifications are not feasible. The integration of noise monitoring and feedback systems may help maintain awareness amongst staff and facilitate continuous improvement in the acoustic environment.
Several limitations of our study should be acknowledged. Its retrospective design limits causal inferences. The temporal sequential design comparing patients from different time periods may have been influenced by concurrent variables, such as changes in treatment protocols, staff experience, seasonal effects or other temporal confounders that could weaken the explanatory power of our conclusions. Our single-centre study was conducted in a specific hospital setting. This situation may limit the generalisability of our findings to other hospital environments with different architectural designs, staffing patterns or patient populations. We did not assess preadmission HRV parameters, which would have allowed for the evaluation of within-subject changes and accurate assessment of the interventions’ effects on individual patients. Additionally, the short follow-up period precluded the assessment of long-term outcomes and major adverse cardiac events, limiting our ability to determine whether the observed noise reduction effects are sustained over time. Our study did not control for several potential confounding factors, including socioeconomic status and individual noise sensitivity, which may influence patient outcomes. The implementation of noise control measures may have inadvertently introduced a Hawthorne effect, wherein staff behaviour and nursing practices differed between groups beyond the intended noise reduction.
Future research should address these limitations through randomised controlled trials and prospective multicentre studies with preadmission baselines and extended follow-up periods. Future studies should also include the comprehensive assessment of potential confounders, multiple stress biomarkers and major adverse cardiac events as primary endpoints. The investigation of dose–response relationships between noise exposure and cardiovascular parameters may help establish threshold values for clinical significance. Additionally, the identification of patient subgroups who might derive particular benefit from noise reduction could inform targeted approaches.
CONCLUSION
Our study revealed associations between reduced hospital noise levels and improved physiological parameters in CAD patients. Our findings suggest the potential relationships of noise-controlled environments with enhanced HRV, reduced stress biomarkers, improved sleep quality and favourable clinical outcomes. The implementation of noise reduction strategies appears feasible in hospital settings and may represent a consideration for optimising care environments for cardiac patients.
Availability of data and materials
The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.
Author contributions
Jinyu Wang: Led the research design and execution, managed data collection and analysis, and authored the initial draft of the manuscript.
Fang Li: Contributed to the research design, supported data analysis, and made initial revisions to the manuscript.
Yafen Zheng: Oversaw the overall research design and supervision, offered technical and theoretical expertise, and conducted the final review and approval of the manuscript.
Ethics approval and consent to participate
This study was approved by the Ethics Committee of General Hospital of the Yangtze River Shipping (Wuhan Brain Hospital), with an approval number of L20210052. All patients have provided written informed consent.
Conflicts of Interest
The authors declare no conflicts of interest.
Acknowledgment
The authors thank the patients and their families for participating in this research.
Funding Statement
None.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analysed during the current study are available from the corresponding author upon reasonable request.
