JMIR Perioperative Medicine

Technologies for pre- and post-operative education, preventative interventions, and clinical care for surgery and anaesthesiology patients, as well as informatics applications in anesthesia, surgery, critical care, and pain medicine

Editor-in-Chief:

John F Pearson, MD, University of Utah School of Medicine


JMIR Perioperative Medicine (JPOP, Editor-in-chief: John F. Pearson MD, University of Utah School of Medicine) is an open access journal focusing on technologies, medical devices, apps, engineering, informatics and patient education for perioperative medicine and nursing, including pre- and post-operative education, preventative interventions and clinical care for surgery and anaesthesiology patients, as well as informatics applications in anesthesia, surgery, critical care and pain medicine.

We are read by clinicians and patients alike and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).

JMIR Perioperative Medicine features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.

The journal is indexed in PubMed and PubMed Central.

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Recent Articles

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Original Papers

Hyponatremia and hypernatremia, as conventionally defined (<135 mEq/L and >145 mEq/L, respectively), are associated with increased perioperative morbidity and mortality. However, the effects of subtle deviations in serum sodium concentration within the normal range are not well-characterized.

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Postoperative Monitoring and Telemonitoring

Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established.

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Artificial Intelligence in Surgery and Perioperative Medicine

Although there is considerable interest in machine learning (ML) and artificial intelligence (AI) in critical care, the implementation of effective algorithms into practice has been limited.

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Artificial Intelligence in Surgery and Perioperative Medicine

Estimating surgical case duration accurately is an important operating room efficiency metric. Current predictive techniques in spine surgery include less sophisticated approaches such as classical multivariable statistical models. Machine learning approaches have been used to predict outcomes such as length of stay and time returning to normal work, but have not been focused on case duration.

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Postoperative Rehabilitation

Sedentary behavior (SB) is prevalent after abdominal cancer surgery, and interventions targeting perioperative SB could improve postoperative recovery and outcomes. We conducted a pilot study to evaluate the feasibility and preliminary effects of a real-time mobile intervention that detects and disrupts prolonged SB before and after cancer surgery, relative to a monitoring-only control condition.

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Postoperative Monitoring and Telemonitoring

The incidence rate of total joint replacement (TJR) continues to increase due to the aging population and the surgery that is very successful in providing pain relief to and improving function among patients with advanced knee or hip arthritis. Improving patient outcomes and patient satisfaction after TJR remain important goals. Wearable technologies provide a novel way to capture patient function and activity data and supplement clinical measures and patient-reported outcome measures in order to better understand patient outcomes after TJR.

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Original Papers

Inhaled anesthetics in the operating room are potent greenhouse gases and are a key contributor to carbon emissions from health care facilities. Real-time clinical decision support (CDS) systems lower anesthetic gas waste by prompting anesthesia professionals to reduce fresh gas flow (FGF) when a set threshold is exceeded. However, previous CDS systems have relied on proprietary or highly customized anesthesia information management systems, significantly reducing other institutions’ accessibility to the technology and thus limiting overall environmental benefit.

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Original Papers

During the quiescent periods of the COVID-19 pandemic in 2020, we implemented a weekend-scheduled pediatric surgery program to reduce COVID-19–related backlogs. Over 100 staff members from anesthesiologists to nurses, surgeons, and administrative and supporting personnel signed up to work extra weekends as part of a novel weekend elective pediatric surgery program to reduce COVID-19–related backlog: Operating Room Ramp-Up After COVID-19 Lockdown Ends-Extra Lists (ORRACLE-Xtra).

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Postoperative Monitoring and Telemonitoring

Preoperative telemonitoring of vital signs, physical activity, and well-being might be able to optimize prehabilitation of the patient’s physical and mental condition prior to surgery, support setting alarms during in-hospital monitoring, and allow personalization of the postoperative recovery process.

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Preprints Open for Peer-Review

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