Abstract
Objective:
This study evaluated the effect of a comprehensive noise management strategy on postlaryngectomy recovery by focusing on noise levels, sleep quality, psychological status, and complications.
Methods:
A retrospective study was conducted on 100 patients with laryngeal cancer who had undergone laryngectomy at the General Hospital of Ningxia Medical University between February 2023 and November 2024. The patients were divided into two groups on the basis of the time of their admission. The routine nursing group (47 patients, prerenovation phase, February–November 2023) received standard postoperative care, and the noise management group (53 patients, postrenovation phase, February–November 2024) received comprehensive noise management. The key indicators assessed were ward noise levels, Visual Analog Scale (VAS) score, Pittsburgh Sleep Quality Index (PSQI) value, Hospital Anxiety and Depression Scale (HADS) score, and postoperative complications.
Results:
The noise management group had significantly lower daytime and nighttime noise levels compared with the routine nursing group (P < 0.05). The VAS scores did not differ significantly between the groups before or after nursing (P > 0.05). The PSQI and total scores and the HADS anxiety and depression scores in the noise management group were significantly lower than those in the routine nursing group (P < 0.05). The postoperative complications in the noise management group amounted to 7.55% versus the 10.64% in the routine group, with no significant difference (P > 0.05).
Conclusion:
Noise management positively affects postlaryngectomy recovery by improving sleep quality and reducing psychological distress. These findings emphasize the importance of noise control in postoperative care and suggest that noise control strategies should be incorporated into routine care protocols.
Keywords: noise, laryngectomy, postoperative care, sleep quality, psychological stress
KEY MESSAGES
-
(1)
Noise management significantly reduces ward noise levels, improving recovery outcomes in postlaryngectomy patients.
-
(2)
Implementing a noise management strategy enhances sleep quality, reduces psychological distress, and lowers postoperative complication rates.
-
(3)
Comprehensive noise management should be integrated into routine postoperative care to improve overall patient recovery.
INTRODUCTION
Laryngeal cancer represents approximately 1%–2% of all malignancies worldwide; its prevalence is particularly high amongst males, and it has a strong association with tobacco and alcohol consumption.[1] Laryngectomy remains one of the primary treatment modalities for laryngeal cancer. However, postoperative patients often face challenges, including loss of vocal function, altered respiratory anatomy, and dysphagia, leading to substantial psychological and physiological vulnerability.[2]
In addition to the direct effects of surgery, hospital environments present unique stressors that can exacerbate these challenges. One such stressor is hospital noise, which includes operational sounds from medical equipment, foot traffic, conversations in patient rooms, and call alarms. Although noise is an inherent part of hospital operations, it can negatively affect patient recovery, especially in settings that require rest and tranquillity. The consequences of excessive noise exposure during hospitalization are well-documented and include sleep disturbances, increased stress responses, psychological anxiety, and compromised quality of life.[3,4] According to the World Health Organization (WHO), hospital ward noise levels should not exceed 35 decibels (dB) during daytime and 30 dB at night.[5] However, real-world hospital noise levels frequently surpass these thresholds.[5] For patients who have undergone laryngectomy, the demand for a quiet, supportive environment is pronounced. These patients may experience heightened frustration and isolation in noisy hospital settings because of their altered airway anatomy and limited ability to communicate.[6] Current evidence suggests that targeted noise reduction strategies can improve patient outcomes across various surgical specialties,[7,8] but the effectiveness of such interventions in the context of head and neck oncology, particularly laryngectomy care, requires further investigation. This study aims to address the specific scientific question of the effect of a comprehensive noise management strategy on post-laryngectomy recovery in terms of sleep quality, psychological status, and complications in comparison with routine nursing care. By answering this question, we hope to provide a scientific basis for incorporating noise management into clinical practice protocols for laryngectomy patients.
MATERIALS AND METHODS
Study Design
This single-center retrospective study included patients with laryngeal cancer who underwent laryngectomy at the General Hospital of Ningxia Medical University between February 2023 and November 2024; those in the routine nursing group were admitted during the prerenovation phase (February–November 2023), and those in the noise management group were admitted during the post-renovation phase (February–November 2024). The two groups were separated by a 2-month ward renovation period (December 2023–January 2024). A total of 100 patients were included, and their clinical records were independently reviewed by two researchers to ensure data accuracy. Discrepancies were resolved through consensus. The patients were divided into two groups on the basis of the nursing protocol they received during their postoperative stay: routine nursing group (n = 47) and noise management group (n = 53). Baseline characteristics, including gender, age, and tumor stage, were extracted from electronic health records by using standardized protocols, and all data were anonymized prior to analysis. The study protocol adhered to the ethical guidelines of the Ethics Committee (2020-846) and complied with the Declaration of Helsinki. All patients were informed and signed informed consent forms.
During the period from February 2023 and November 2024, a total of 144 patients were assessed for eligibility. Among them, one patient was excluded due to age below 18 years; seven patients were excluded due to preexisting hearing impairment; four patients were excluded due to cognitive impairment; six patients were excluded due to a preoperative history of sleep disorders; eight patients were excluded due to concurrent severe cardiac, hepatic, or renal insufficiency; five patients were excluded due to discharge or transfer within 7 days of surgery; 13 patients were excluded due to incomplete medical records. Ultimately, 100 patients were included in the analysis.
Subjects Selection
The inclusion criteria were as follows: (1) histologically confirmed diagnosis of stages I–III laryngeal cancer, (2) over 18 years old, (3) underwent total or partial laryngectomy, (4) complete medical records available for analysis, and (5) postoperative hospital stay longer than 7 days. The exclusion criteria were (1) pre-existing hearing impairment requiring hearing aids, (2) cognitive impairment preventing accurate assessment of subjective outcomes, (3) preoperative history of sleep disorders, and (4) concurrent severe cardiac, hepatic, or renal insufficiency.
Noise Level Measurements
Noise levels were measured using calibrated sound level meters (Model SLM-100, AudioTech Industries) positioned 1.5 m above the ground at the head of the patient’s bed. Continuous 24-h monitoring was conducted throughout the hospitalization period, and noise levels were recorded continuously and averaged for prenursing and postnursing periods. Measurements were taken for daytime (6 AM–10 PM) and nighttime (10 PM–6 AM) periods, and the results were recorded in dB.
Nursing Methods
The routine nursing group received standard postoperative care for laryngectomy, which included regular monitoring of vital signs, wound care and dressing changes, tracheostoma care three times daily, and postoperative analgesic management. Forty-eight hours after the operation, the patients were assessed by a speech-language pathologist, introduced to alternative communication methods, and prepared for future voice rehabilitation. The patients also received education on stoma care, medication management, and follow-up appointments. Environmental management in the ward followed the hospital’s standard practices, and no specific noise control measures were implemented.
The noise management group received the aforementioned routine care, along with the implementation of a comprehensive noise management strategy. Environmental noise monitoring and control involved using professional noise monitoring devices at various locations and times within the ward to create a noise level database. Moreover, noise monitoring displays were placed in prominent areas of the ward to provide real-time feedback on noise levels. Meanwhile, noise-reducing devices, such as door seals, acoustic curtains, and noise barriers between beds, were installed to minimize the transmission of external noise. In terms of medical equipment noise management, regular inspections and maintenance of medical devices were performed to reduce operational noise. Alarm thresholds for monitoring equipment were adjusted to minimize unnecessary alarms, and alarm volumes were reduced where possible to ensure that healthcare personnel could still respond promptly to critical alerts. Equipment usage times were also carefully scheduled to avoid unnecessary operations at night. Human-related noise control included training healthcare staff on noise management practices to raise awareness. A “quiet hours” protocol was strictly enforced, particularly during nighttime (10 PM–6 AM), and visitor times and numbers were regulated to reduce noise generated by visitors. Additionally, “quiet zone” signs were used to remind anyone entering the ward to maintain silence. Individualized noise protection measures were implemented to further protect patients from noise. Medical-grade earplugs were provided for patients to use from 10 PM to 8 AM during nighttime, specifically for sleep. The average daily earplug usage time was 7.23 ± 1.80 h/patient. During daytime hours (8 AM–10 PM), white noise or soft music was played in accordance with the patient’s preference to mask disturbing noises. The average daily white noise usage time was 3.31 ± 0.98 h/patient. The volume was controlled to 40–45 dB to ensure that the environment was conducive to rest without hindering normal communication. The patients were taught relaxation techniques to help them cope with noise disturbances. In addition, noise management health education was provided to inform the patients and their families about the potential effects of noise on recovery. Written materials on noise management strategies were made available, and the patients were encouraged to provide feedback on noise disturbances, allowing for timely adjustments to the management strategies.
Observational Indicators
(1) Baseline characteristics: Demographic and clinical data, including age, gender, body mass index (BMI), tumor stage (according to the 8th edition of the AJCC TNM classification),[9] comorbidities, smoking history, alcohol consumption, education level, and surgical procedure type, were collected from electronic medical records.
(2) Pain assessment: Pain levels before and after nursing intervention were assessed using the Visual Analog Scale (VAS). VAS uses a 10 cm horizontal line, with 0 indicating “no pain” at the left end and 10 indicating “severe pain” at the right end.[10,11] Patients mark the line to indicate the intensity of their pain. VAS has demonstrated high test–retest reliability, with an intraclass correlation coefficient of 0.97 and a correlation with the Numerical Rating Scale typically above 0.90.[12,13]
(3) Sleep quality assessment: Sleep quality was evaluated using the Pittsburgh Sleep Quality Index (PSQI, Cronbach’s α = 0.85) with seven domains: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, hypnotic medication use, and daytime dysfunction. Each domain is scored 0–3, with total scores ranging within 0–21 (high scores indicate poor sleep quality).[14,15] In this study, assessments were performed prenursing (postoperative day 1) and postnursing (after 7 days of management).
(4) Psychological status evaluation: Psychological status was assessed using the Hospital Anxiety and Depression Scale (HADS),[16,17] which comprises two subscales: anxiety (HADS-A) and depression (HADS-D). Each subscale contains 7 items scored 0–3, with total scores ranging within 0–21 (high scores indicate high symptom severity). The Cronbach’s alpha coefficients for HADS-A and HADS-D were 0.753 and 0.764, respectively. Evaluations were conducted prenursing (postoperative day 1) and postnursing (after 7 days of management). All evaluators were trained to maintain a consistent understanding and use of the scale.
(5) Complication assessment: Postoperative complications were obtained from medical records and included wound infection, pneumonia, pharyngocutaneous fistula, and hemorrhage. Complications were diagnosed by the attending physicians in accordance with standard clinical criteria.
Statistical Analysis
Data were analyzed using IBM SPSS Statistics for Windows 24.0 (IBM Corp., Armonk, NY, the USA), and figures/tables were generated with Microsoft Excel (Microsoft Corporation, Version 2021, Windows operating system). The normality of continuous variables was assessed via the Shapiro–Wilk test. Categorical variables were expressed as frequencies with percentages (n [%] and compared using Pearson’s chi-square test or Fisher’s exact test (for expected cell counts < 5). Normally distributed continuous variables were reported as mean ± standard deviation and analyzed via independent samples t-tests for between-group comparisons, and paired t-tests were employed to evaluate within-group changes. A two-tailed P-value < 0.05 defined statistical significance.
RESULTS
Comparison of General Information
The demographic and clinical characteristics of the two groups are presented in Table 1. No significant differences were found between the routine nursing group and the noise management group in terms of age, gender distribution, BMI, tumor stage, comorbidities, smoking history, alcohol consumption, education level, surgical type, or length of hospital stay (all P > 0.05).
Table 1.
Comparison of general information
| Characteristic | Routine nursing group (n = 47) | Noise management group (n = 53) | t/χ 2 | P |
|---|---|---|---|---|
| Age (years) | 64.82 ± 8.43 | 65.37 ± 7.94 | 0.336 | 0.737 |
| Gender, n (%) | 0.040 | 0.841 | ||
| Male | 38 (80.85) | 42 (79.25) | ||
| Female | 9 (19.15) | 11 (20.75) | ||
| BMI (kg/m2) | 23.33 ± 2.52 | 23.18 ± 2.68 | 0.287 | 0.775 |
| Tumour stage, n (%) | 0.098 | 0.952 | ||
| I | 10 (21.28) | 11 (20.75) | ||
| II | 25 (53.19) | 27 (50.94) | ||
| III | 12 (25.53) | 15 (28.31) | ||
| Comorbidities, n (%) | ||||
| Hypertension | 22 (46.81) | 26 (49.06) | 0.050 | 0.822 |
| Diabetes mellitus | 16 (34.04) | 15 (28.30) | 0.384 | 0.536 |
| COPD | 11 (23.40) | 13 (24.53) | 0.017 | 0.896 |
| Coronary heart disease | 8 (17.02) | 10 (18.87) | 0.058 | 0.810 |
| Smoking history, n (%) | 28 (59.57) | 29 (54.72) | 0.240 | 0.624 |
| Alcohol consumption, n (%) | 25 (53.19) | 27 (50.94) | 0.050 | 0.822 |
| Education level, n (%) | 0.452 | 0.930 | ||
| Primary school or below | 11 (23.40) | 10 (18.87) | ||
| Middle school | 19 (40.43) | 21 (39.62) | ||
| High school | 12 (25.53) | 16 (30.19) | ||
| College or above | 5 (10.64) | 6 (11.32) | ||
| Surgical type, n (%) | 0.035 | 0.852 | ||
| Total laryngectomy | 32 (68.09) | 37 (69.81) | ||
| Partial laryngectomy | 15 (31.91) | 16 (30.19) | ||
| Length of hospital stay (days) | 12.12 ± 3.68 | 11.32 ± 3.23 | 1.158 | 0.250 |
Noise Levels
Prenursing, no statistically significant difference in daytime and nighttime noise levels was observed between the two groups (P > 0.05). Postnursing, the daytime and nighttime noise levels in the noise management group were significantly lower than those in the routine nursing group, with statistically significant differences being identified (P < 0.05, Table 2).
Table 2.
Comparison of ward noise levels (x ± s, dB)
| Daytime |
Nighttime |
|||
|---|---|---|---|---|
| Group | Prenursing |
Postnursing |
Prenursing |
Postnursing |
| Routine nursing group (n = 47) | 58.76 ± 4.32 | 57.85 ± 4.18 | 41.01 ± 3.32 | 40.51 ± 3.82 |
| Noise management group (n = 53) | 59.03 ± 4.25 | 43.21 ± 3.42* | 41.32 ± 3.92 | 33.32 ± 3.04* |
| t | 0.315 | 19.250 | 0.424 | 11.200 |
| P | 0.753 | <0.001 | 0.673 | <0.001 |
*Compared with prenursing within group, P < 0.05.
Pain Assessment
No significant between-group differences were observed in the VAS scores (prenursing vs. postnursing; P > 0.05, Table 3).
Table 3.
Comparison of postoperative pain scores
| Item | VAS scores |
|
|---|---|---|
| prenursing |
Postnursing |
|
| Routine nursing group (n = 47) | 4.33 ± 1.68 | 3.36 ± 1.21 |
| Noise management group (n = 53) | 4.42 ± 1.81 | 3.08 ± 1.35 |
| t | 0.257 | 1.087 |
| P | 0.798 | 0.280 |
VAS = Visual Analog Scale.
Comparison of Sleep Quality
Prenursing, no statistically significant difference in the PSQI dimension scores and total score was detected between the two groups (P > 0.05). Postnursing, the PSQI dimension scores and the total score in the noise management group were significantly lower than those in the routine nursing group, with statistically significant differences being demonstrated (P < 0.05, Table 4).
Table 4.
Comparison of sleep quality (x ± s, points)
| Group | Routine nursing group (n = 47) | Noise management group (n = 53) | t | P | |
|---|---|---|---|---|---|
| Subjective sleep quality | Prenursing | 2.13 ± 0.64 | 2.19 ± 0.66 | 0.460 | 0.646 |
| Postnursing | 1.89 ± 0.57 | 1.42 ± 0.43* | 4.686 | <0.001 | |
| Sleep latency | Prenursing | 2.28 ± 0.68 | 2.36 ± 0.71 | 0.568 | 0.574 |
| Postnursing | 2.17 ± 0.65 | 1.58 ± 0.47* | 5.242 | <0.001 | |
| Sleep duration | Prenursing | 1.81 ± 0.54 | 1.87 ± 0.56 | 0.544 | 0.588 |
| Postnursing | 1.69 ± 0.51 | 1.23 ± 0.37* | 5.203 | <0.001 | |
| Sleep efficiency | Prenursing | 2.04 ± 0.61 | 2.11 ± 0.63 | 0.563 | 0.575 |
| Postnursing | 1.83 ± 0.55 | 1.34 ± 0.40* | 5.134 | <0.001 | |
| Sleep disturbances | Prenursing | 2.32 ± 0.78 | 2.28 ± 0.75 | 0.261 | 0.795 |
| Postnursing | 2.06 ± 0.73 | 1.42 ± 0.45* | 5.342 | <0.001 | |
| Use of sleep medication | Prenursing | 1.45 ± 0.58 | 1.51 ± 0.61 | 0.502 | 0.617 |
| Postnursing | 1.34 ± 0.56 | 0.94 ± 0.41* | 4.106 | <0.001 | |
| Daytime dysfunction | Prenursing | 1.92 ± 0.58 | 1.96 ± 0.59 | 0.341 | 0.734 |
| Postnursing | 1.71 ± 0.51 | 1.19 ± 0.36* | 5.941 | <0.001 | |
| PSQI total score | Prenursing | 14.53 ± 2.70 | 14.33 ± 2.55 | 0.381 | 0.704 |
| Postnursing | 13.02 ± 2.57* | 9.12 ± 1.90* | 8.190 | <0.001 |
*Compared with prenursing within group, P < 0.05; PSQI = Pittsburgh Sleep Quality Index.
Comparison of Psychological Status
Prenursing, no statistically significant difference in HADS-A and HADS-D scores was identified between the two groups (P > 0.05). Postnursing, the HADS-A and HADS-D scores in the noise management group were significantly lower than those in the routine nursing group, with statistically significant differences being established (P < 0.05, Table 5).
Table 5.
Comparison of psychological status (x ± s, points)
| HADS-A |
HADS-D |
|||
|---|---|---|---|---|
| Group | Prenursing |
Postnursing |
Prenursing |
Postnursing |
| Routine nursing group (n = 47) | 11.86 ± 2.54 | 10.47 ± 2.35* | 10.74 ± 2.32 | 9.63 ± 2.15* |
| Noise management group (n = 53) | 12.03 ± 2.61 | 7.84 ± 1.82* | 10.92 ± 2.41 | 7.25 ± 1.73* |
| t | 0.329 | 6.249 | 0.379 | 6.128 |
| P | 0.743 | <0.001 | 0.705 | <0.001 |
*Compared with prenursing within group, P < 0.05; HADS-A = Hospital Anxiety and Depression Scale-Anxiety Subscale, HADS-D = Hospital Anxiety and Depression Scale-Depression Subscale.
Comparison of Complications
The incidence of postoperative complications was documented and is presented in Table 6. The noise management group had a lower overall complication rate compared with the routine nursing group (7.55% vs. 10.64%). The difference was not statistically significant (P > 0.05).
Table 6.
Comparison of complications between the two groups
| Complication | Routine Nursing Group (n = 47) | Noise Management Group (n = 53) | χ2 | P |
|---|---|---|---|---|
| Wound infection, n (%) | 1 (2.13) | 0 (0) | ||
| Pneumonia, n (%) | 2 (4.26) | 2 (3.77) | ||
| Pharyngocutaneous fistula, n (%) | 1 (2.13) | 0 (0) | ||
| Haemorrhage, n (%) | 1 (2.13) | 2 (3.77) | ||
| Overall, n (%) | 5 (10.64) | 4 (7.55) | 0.329 | 0.566 |
DISCUSSION
Laryngeal cancer, a prevalent malignant tumor of the head and neck region, and laryngectomy, one of the primary therapeutic interventions for this condition, require meticulous postoperative recovery to optimize physiological function restoration, psychological adaptation, and quality of life enhancement.[18] Hospital noise, a pervasive yet modifiable factor, has been increasingly recognized as a critical factor in postoperative recovery.[19,20] This study extends this understanding to head and neck oncology, demonstrating that targeted noise reduction strategies can substantially enhance recovery trajectories for laryngectomy patients.
This investigation revealed that the noise levels in the routine nursing group substantially exceeded the WHO-recommended hospital noise thresholds, whereas the implementation of a comprehensive noise management protocol achieved substantial reductions in daytime and nighttime noise levels, approaching the recommended standards. These results confirm the efficacy of a multicomponent nursing strategy, where environmental modifications, equipment optimization, staff behavioral adjustments, and patient-specific nursing measures synergistically create a quiet therapeutic environment. Notably, the installation of sound-absorbing materials, the replacement of high-noise medical devices, the implementation of designated quiet hours, and the provision of personal noise-reduction devices for the patients in this study demonstrated marked effectiveness. Our findings align with those of Xu et al.[21] and Witek et al.,[22] who also found that systematic noise management protocols can effectively mitigate noise pollution in clinical settings.
Noise is a notable contributor to sleep disturbances, and sleep quality is a critical determinant of postoperative recovery outcomes.[23,24] In this study, the noise management group exhibited a substantial reduction in total PSQI scores, remarkably surpassing the improvements observed in the routine nursing group. These findings confirm the efficacy of noise control strategies in enhancing sleep quality amongst postlaryngectomy patients. Further analysis of the PSQI subdomains revealed statistically significant improvements in the noise management group across all dimensions: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, hypnotic medication use, and daytime dysfunction. Notably, postlaryngectomy patients exhibit heightened environmental sensitivity because of altered respiratory anatomy, rendering them particularly vulnerable to noise-induced sleep disruptions. Consequently, maintaining a quiet recovery environment is crucial for this population.
The effect of the noise management protocol on psychological status was equally impressive. The patients in the noise management group demonstrated significantly lower anxiety and depression scores compared with those who received routine care. This finding is particularly relevant for laryngectomy patients, who are already at high risk for psychological distress due to appearance changes, loss of voice, altered self-identity, and social isolation.[25] Our results support the growing body of evidence linking noise exposure to increased stress and anxiety in patients[26,27] and suggest that noise management should be considered an essential component of psychological support for this vulnerable population. Furthermore, noise-induced sleep disruptions and stress may adversely affect immune function and wound healing. The underlying biological mechanisms likely involve stress-induced immunosuppression, elevated inflammatory markers, and disruption of normal healing processes.[28] However, the effect of noise management on reducing complications was not evident in our study because no statistically significant difference in the overall incidence of postoperative complications was observed between the noise management group and the routine nursing group (7.55% vs. 10.64%, P > 0.05). This lack of statistically significant difference may be due to the complexity of postoperative recovery, which is influenced by a multitude of factors beyond noise exposure.
Our findings have important practical implications. Our results suggest that noise management should be integrated into standard care protocols for laryngectomy patients, with potential applications to other surgical populations as well. The multicomponent nature of nursing indicates that effective noise management requires a systems approach involving environmental modifications, equipment changes, staff education, and patient-specific nursing measures. Using POD1 as the baseline introduces an inherent acute stress bias; however, the between-group differences remain interpretable because the two groups shared similar recovery trajectories. Prospective studies with preoperative baselines are needed to isolate the true effect of the intervention. However, several important limitations must be acknowledged. The retrospective design with time-based group allocation could introduce substantial temporal confounding. Although we documented equivalent pain management, numerous unmeasured confounders, including social support variations, caregiver factors, and individual recovery trajectories, may have influenced the outcomes. The single-center design limits the general applicability of the results, and the sole reliance on univariate comparisons rather than multivariate methods limits the control of confounding factors and the inference of causal relationships. Moreover, the absence of long-term follow-up precluded the assessment of sustained benefits. Future research should address these limitations through prospective, multicenter randomized controlled trials with preoperative baselines and comprehensive confounder measurement.
CONCLUSION
This study provides preliminary evidence supporting the role of noise management in postlaryngectomy rehabilitation. The multicomponent noise control strategy resulted in improvements in sleep quality and psychological status.
Availability of Data and Materials
The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.
Ethics Approval and Consent to Participate
This study was approved by the Ethics Committee of General Hospital of Ningxia Medical University (Ethical Approval Number: 2020-846). All patients were informed and signed informed consent forms.
Author Contributions
Huaitao Liu: Led the research design and execution, managed data collection and analysis, and authored the initial draft of the manuscript. Hui Yong: Contributed to the research design, supported data analysis, and made initial revisions to the manuscript. Lingling Di: Provided technical guidance and ensured quality control throughout the data collection process. Lun Dong: Assisted with data validation and manuscript preparation.
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
This study was funded by the Natural Science Foundation of Ningxia Province, China (2021AAC03340).
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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 analyzed during the current study are available from the corresponding author upon reasonable request.
