JMIR perioperative medicine最新文献

Background: The automated acquisition of intraoperative patient temperature data via temperature probes leads to the possibility of producing a number of artifacts related to probe positioning that may impact these probes' utility for observational research.

Objective: We sought to compare the performance of two de novo algorithms for filtering such artifacts.

Methods: In this observational retrospective study, the intraoperative temperature data of adults who received general anesthesia for noncardiac surgery were extracted from the Multicenter Perioperative Outcomes Group registry. Two algorithms were developed and then compared to the reference standard-anesthesiologists' manual artifact detection process. Algorithm 1 (a slope-based algorithm) was based on the linear curve fit of 3 adjacent temperature data points. Algorithm 2 (an interval-based algorithm) assessed for time gaps between contiguous temperature recordings. Sensitivity and specificity values for artifact detection were calculated for each algorithm, as were mean temperatures and areas under the curve for hypothermia (temperatures below 36 C) for each patient, after artifact removal via each methodology.

Results: A total of 27,683 temperature readings from 200 anesthetic records were analyzed. The overall agreement among the anesthesiologists was 92.1%. Both algorithms had high specificity but moderate sensitivity (specificity: 99.02% for algorithm 1 vs 99.54% for algorithm 2; sensitivity: 49.13% for algorithm 1 vs 37.72% for algorithm 2; F-score: 0.65 for algorithm 1 vs 0.55 for algorithm 2). The areas under the curve for time × hypothermic temperature and the mean temperatures recorded for each case after artifact removal were similar between the algorithms and the anesthesiologists.

Conclusions: The tested algorithms provide an automated way to filter intraoperative temperature artifacts that closely approximates manual sorting by anesthesiologists. Our study provides evidence demonstrating the efficacy of highly generalizable artifact reduction algorithms that can be readily used by observational studies that rely on automated intraoperative data acquisition.

Background: Long-term postoperative pain (POP) and patient responses to pain relief medications are not yet fully understood. Although recent studies have developed an index for the nociception level of patients under general anesthesia based on multiple physiological parameters, it remains unclear whether these parameters correlate with long-term POP outcomes.

Objective: This study aims to extract unbiased and interpretable descriptions of how the dynamics of physiological parameters change over time and across patients in response to surgical procedures and intraoperative medications using a multivariate-temporal analysis. We demonstrated that there is an association (correlation) between the main features of intraoperative physiological responses and long-term POP, which has a predictive value, even without claiming causality.

Methods: We proposed a complex higher-order singular value decomposition method to accurately decompose patients' physiological responses into multivariate structures evolving over time. We used intraoperative vital signs of 175 patients from a mixed surgical cohort to extract three interconnected, low-dimensional, complex-valued descriptions of patients' physiological responses: multivariate factors, reflecting subphysiological parameters; temporal factors, reflecting common intrasurgery temporal dynamics; and patients' factors, describing interpatient changes in physiological responses.

Results: Adoption of the complex higher-order singular value decomposition method allowed us to clarify the dynamic correlation structure included in the intraoperative physiological responses. Instantaneous phases of the complex-valued physiological responses of 242 patients within the subspace of principal descriptors enabled us to discriminate between mild and not-mild (moderate-severe) levels of pain at postoperative days 30 and 90. Following rotation of physiological responses before projection to align with the common multivariate-temporal dynamic, the method achieved an area under curve for postoperative day 30 and 90 outcomes of 0.81 and 0.89 for thoracic surgery, 0.87 and 0.83 for orthopedic surgery, 0.87 and 0.88 for urological surgery, 0.86 and 1 for colorectal surgery, 1 and 1 for transplant surgery, and 0.83 and 0.92 for pancreatic surgery, respectively.

Conclusions: By categorizing patients into different surgical groups, we identified significant surgery-related principal descriptors. Each of them potentially encodes different surgical stimulation. The dynamics of patients' physiological responses to these surgical events were linked to long-term POP development.

Background: Although the various advantages of clinical information systems in intensive care units (ICUs), such as intensive care information systems (ICISs), have been reported, their role in preventing medical errors remains unclear.

Objective: This study aimed to investigate the changes in the incidence and type of errors in the ICU before and after ICIS implementation in a setting where a hospital electronic medical record system is already in use.

Methods: An ICIS was introduced to the general ICU of a university hospital. After a step-by-step implementation lasting 3 months, the ICIS was used for all patients starting from April 2019. We performed a retrospective analysis of the errors in the ICU during the 6-month period before and after ICIS implementation by using data from an incident reporting system, and the number, incidence rate, type, and patient outcome level of errors were determined.

Results: From April 2018 to September 2018, 755 patients were admitted to the ICU, and 719 patients were admitted from April 2019 to September 2019. The number of errors was 153 in the 2018 study period and 71 in the 2019 study period. The error incidence rates in 2018 and 2019 were 54.1 (95% CI 45.9-63.4) and 27.3 (95% CI 21.3-34.4) events per 1000 patient-days, respectively (P<.001). During both periods, there were no significant changes in the composition of the types of errors (P=.16), and the most common type of error was medication error.

Conclusions: ICIS implementation was temporally associated with a 50% reduction in the number and incidence rate of errors in the ICU. Although the most common type of error was medication error in both study periods, ICIS implementation significantly reduced the number and incidence rate of medication errors.

Trial registration: University Hospital Medical Information Network Clinical Trials Registry UMIN000041471; https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047345.

Background: Electronic patient portal (EPP) use is associated with lower no-show rates and increased patient satisfaction. However, there are disparities in enrollment into these communication platforms.

Objective: We hypothesized that guided inpatient enrollment into an EPP would improve clinical follow-up and EPP use rates for patients who underwent orthopedic surgery compared to the usual practice of providing information in the discharge summary.

Methods: We performed a randomized controlled trial of 229 adult patients who were admitted to the hospital for an orthopedic condition that required a 3-month follow-up visit. Patients were cluster-randomized by week to either the control or intervention group. The control group received information on how to enroll into and use the EPP in their discharge paperwork, whereas the intervention group was actively enrolled and taught how to use the EPP. At 3 months postdischarge, the patients were followed to see if they attended their follow-up appointment or used the EPP.

Results: Of the 229 patients, 83% (n=190) presented for follow-up at 3 months (control: 93/116, 80.2%; intervention: 97/113, 85.8%; P=.25). The likelihood of EPP use was significantly higher in the intervention group (control: 19/116, 16.4%; intervention: 70/113, 62%; odds ratio [OR] 8.3, 95% CI 4.5-15.5; P<.001). Patients in the intervention group who used the EPP were more likely to present for postsurgical follow-up (OR 3.59, 95% CI 1.28-10.06; P=.02).

Conclusions: The inpatient enrollment of patients who underwent orthopedic surgery into an EPP increased EPP use but did not independently result in enhanced follow-up. Patients who were enrolled as inpatients and subsequently used the portal had the highest likelihood of 3-month follow-up.

Trial registration: ClinicalTrials.gov NCT03431259; https://clinicaltrials.gov/ct2/show/NCT03431259.

Background: Although the presence of medical societies on social networks (SNs) could be interesting for disseminating professional information, there is no study investigating their presence on SNs.

Objective: The aim of this viewpoint is to describe the worldwide presence and activity of national anesthesia societies on SNs.

Methods: This observational study assessed the active presence (≥1 post in the year preceding the collection date) of the World Federation of Societies of Anesthesiologists member societies on the SNs Twitter, Facebook, Instagram, and YouTube. We collected data concerning each anesthesia society on the World Federation of Societies of Anesthesiologists website.

Results: Among the 136 societies, 66 (48.5%) had an active presence on at least one SN. The most used SN was Facebook (n=60, 44.1%), followed by Twitter (n=37, 27.2%), YouTube (n=26, 19.1%), and Instagram (n=16, 11.8%). The SN with the largest number of followers was Facebook for 52 (78.8%) societies and Twitter for 12 (18.2%) societies. The number of followers was 361 (IQR 75-1806) on Twitter, 2494 (IQR 1049-5369) on Facebook, 1400 (IQR 303-3058) on Instagram, and 214 (IQR 33-955) on YouTube. There was a strong correlation between the number of posts and the number of followers on Twitter (r=0.95, 95% CI 0.91-0.97; P<.001), Instagram (r=0.83, 95% CI 0.58-0.94; P<.001), and YouTube (r=0.69, 95% CI 0.42-0.85; P<.001). According to the density of anesthetists in the country, there was no difference between societies with and without active SN accounts.

Conclusions: Less than half of national anesthesia societies have at least one active account on SNs. Twitter and Facebook are the most used SNs.

[This corrects the article DOI: 10.2196/36208.].

Background: Patient-reported outcome measures (PROMs) are commonly used to report outcomes after hip and knee arthroplasty, but response rates are rarely complete. Given that preoperative health status (as measured by PROMs) is a strong predictor of outcomes (using the same measures) and that these outcomes may influence the response rate, it is possible that postoperative response rates (the proportion of patients providing preoperative PROMs who also provide postoperative PROMs) may be influenced by preoperative health status.

Objective: This study aims to test the association between preoperative PROMs and postoperative response status following hip and knee arthroplasty.

Methods: Data from the PROMs program of the Australian national joint registry were used. The preoperative PROMs were the Oxford Hip Score or Oxford Knee Score, The EQ-5D Utility Index, and the EQ visual analog scale (VAS) for overall health. Logistic regression, adjusting for age, sex, BMI, and the American Society of Anesthesiologists (ASA) Physical Status Classification System, was used to test the association between each preoperative PROM and response status for the 6-month postsurgery survey.

Results: Data from 9499 and 16,539 patients undergoing elective total hip arthroplasty (THA) and total knee arthroplasty (TKA) for osteoarthritis, respectively, were included in the analysis. Adjusting for age, sex, BMI, and ASA, there was no significant difference in response status at the postoperative follow-up based on the preoperative Oxford Hip or Knee Scores (odds ratio [OR] 1.00, 95% CI 0.99-1.01 for both; P=.70 for THA and P=.85 for TKA). Healthier patients (based on the EQ VAS scores) preoperatively were more likely to respond postoperatively, but this difference was negligible (OR 1.00, 95% CI 1.00-1.01 for THA and TKA; P=.004 for THA and P<.001 for TKA). The preoperative EQ Utility Index was not associated with the postoperative response rate for THA (OR 1.14, 95% CI 0.96-1.36; P=.13) or TKA patients (OR 1.05, 95% CI 0.91-1.22; P=.49).

Conclusions: The likelihood of responding to a postoperative PROMs survey for patients undergoing hip or knee arthroplasty was not associated with clinically important differences in preoperative patient-reported joint pain, function, or health-related quality of life. This suggests that the assessment of postoperative outcomes in hip and knee arthroplasty is not biased by differences in preoperative health measures between responders and nonresponders.

Background: Postoperative care is influenced by various factors such as compliance, comprehension, retention of instructions, and other unaccounted elements. It is imperative that patients adhere to the instructions and prescribed regimen for smooth and placid healing. ExoDont, an Android-based mobile health app, was designed to ensure a smooth postoperative period for patients after a dental extraction. Besides providing postoperative instructions at defined intervals, the app also sends drug reminders as an added advantage over other available, conventional methods.

Objective: The aim of this study was to compare the compliance rate of individuals with respect to the prescribed regimen and postoperative instructions. Additionally, we aimed to assess any changes in the postoperative complication rate of patients assigned to 3 categories: the verbal, verbal plus written, and ExoDont app-based delivery groups.

Methods: We conducted a pilot, nonrandomized, and prospective comparative study in which patients after tooth extraction were assigned to 3 groups-verbal (Group A), verbal plus written (Group B), and ExoDont app-based delivery (Group C)-based on the eligibility criteria, and a 1-week follow-up was planned to obtain the responses regarding compliance and postoperative complications from the participants.

Results: In total, 90 patients were recruited and equally divided into 3 groups. Compliance to prescribed drug was found to be the highest in Group C, where of the 30 participants, 25 (83%) and 28 (93%) followed the entire course of antibiotics and analgesics, respectively. For postoperative instructions, higher compliance was observed in Group C in relation to compliance to diet restrictions (P=.001), not rinsing for 24 hours (P<.001), and warm saline rinses after 24 hours (P=.001). However, the difference was not significant for smoking restrictions (P=.07) and avoiding alcohol (P=.16). Moreover, the difference in postoperative complication rate was not statistically significant among the 3 groups (P=.31).

Conclusions: As evident from the results, it is anticipated that the ExoDont app will be helpful in circumventing the unaccounted possibilities of missing the prescribed dosage and postoperative instructions and ensuring the smooth recovery of patients after dental extraction. However, future studies are required to establish this app-based method of delivery of postoperative instructions as a viable option in routine clinical practice.