Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70168, first published .
Authors’ Reply: Advancing Insights Into Postoperative Sleep Quality and Influencing Factors

Authors’ Reply: Advancing Insights Into Postoperative Sleep Quality and Influencing Factors

Authors’ Reply: Advancing Insights Into Postoperative Sleep Quality and Influencing Factors

Letter to the Editor

1Department of Critical Care Medicine, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

2Department of Infection Control, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China

3School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China

4Department of Critical Care Medicine, Peking Union Medical College Hospital, Beijing, China

5Institute of Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany

*these authors contributed equally

Corresponding Author:

Zhe Li, MD, PhD

Department of Critical Care Medicine

Renji Hospital

School of Medicine, Shanghai Jiao Tong University

No. 160, Pujian Road

Pudong New District

Shanghai, 200127

China

Phone: 86 68383162

Fax:86 68383162

Email: slamy1987@126.com



Thank you for your thoughtful feedback on our article, “Quantitative Impact of Traditional Open Surgery and Minimally Invasive Surgery on Patients’ First-Night Sleep Status in the Intensive Care Unit: Prospective Cohort Study” [1]. We appreciate your insights and would like to address the key points you raised [2].


We fully agree that baseline sleep quality is crucial. In our study design, we excluded participants with chronic sleep disorders based on preoperative medical history and medication use. The suggestion to incorporate sleep scoring tools like the Pittsburgh Sleep Quality Index is valuable, as it could help investigate the impact of surgery on sleep status in different patient populations. Inspired by your comments, continuous monitoring using wearable devices during the preoperative and intensive care unit (ICU) periods could provide valuable insights into how sleep is dynamically affected by different clinical treatment protocols.


We completely agree that pain is one of the greatest “enemies” of sleep quality. Working in a surgical ICU in a teaching hospital, we use standardized protocols along with the Richmond Agitation-Sedation Scale and Numeric Rating Scale (NRS) to manage pain and sedation. Our sedation and analgesia goals were maintained with Richmond Agitation-Sedation Scale scores of –1 to 0, aiming for an NRS below 3 [3,4]. Our unpublished data showed that both the minimally invasive surgery and traditional open surgery groups demonstrated comparable NRS scores (mean NRS: 1.86, SD 0.76, vs 1.85, SD 0.62; P=.96). This consistency allowed us to isolate the effects of surgical methods on sleep.


Rapid screening and diagnosis of sleep disorders in ICU settings remain challenging. Our study aimed to explore the use of wearable devices for patients who were awake in the ICU, helping to reduce bias introduced by sedative medications. We agree that ICU-specific environmental factors affect all electronic monitoring tools. Examining how these environmental factors impact device accuracy would be a meaningful research topic. The development of more sophisticated algorithms—whether embedded in device software or integrated with artificial intelligence–based predictive models using clinical data—represents a promising direction for the field of medical engineering integration.


Lastly, we appreciate your emphasis on the psychological factors influencing sleep, such as preoperative anxiety and depression. These factors may indirectly affect sleep quality, and the reduced trauma and faster recovery associated with minimally invasive surgery could positively influence psychological well-being. Exploring dynamic and quantitative methods to assess psychological states, alongside studying the effects of clinical treatments and mind-body interventions, presents a valuable opportunity to uncover their relationships with clinical outcomes. Combining these approaches with dynamic sleep state monitoring provides technical support to illuminate both direct and mediating relationships, paving the way for large-scale controlled trials to enhance patient care.

Thank you again for your valuable feedback. We look forward to further discussions and advancing this important field.

Acknowledgments

The study was supported by the Wu Jieping Medical Foundation (320.6750.2024-2-4) and the Shanghai Hospital Development Center Foundation (SHDC12024628).

Conflicts of Interest

None declared.

  1. Shang C, Yang Y, He C, Feng J, Li Y, Tian M, et al. Quantitative impact of traditional open surgery and minimally invasive surgery on patients' first-night sleep status in the intensive care unit: prospective cohort study. J Med Internet Res. Nov 22, 2024;26:e56777. [FREE Full text] [CrossRef] [Medline]
  2. Zhao Y, Hu X. Advancing insights into postoperative sleep quality and influencing factors. J Med Internet Res. 2025:e69193. [CrossRef]
  3. Arroyo-Novoa CM, Figueroa-Ramos MI, Puntillo KA. Occurrence and practices for pain, agitation, and delirium in intensive care unit patients. P R Health Sci J. Sep 2019;38(3):156-162. [FREE Full text] [Medline]
  4. Devlin JW, Skrobik Y, Gélinas C, Needham DM, Slooter AJC, Pandharipande PP, et al. Clinical practice guidelines for the prevention and management of pain, agitation/sedation, delirium, immobility, and sleep disruption in adult patients in the ICU. Crit Care Med. Sep 2018;46(9):e825-e873. [FREE Full text] [CrossRef] [Medline]


ICU: intensive care unit
NRS: Numeric Rating Scale


Edited by T Leung, S Gardezi; This is a non–peer-reviewed article. submitted 17.12.24; accepted 28.12.24; published 03.02.25.

Copyright

©Chen Shang, Ya Yang, Chengcheng He, Junqi Feng, Yan Li, Meimei Tian, Zhanqi Zhao, Yuan Gao, Zhe Li. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.02.2025.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.