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January 19, 2021
Technology to Identify Fatigue?
Our many columns listed below have highlighted the role fatigue in healthcare workers plays in medical errors and patient safety. A major problem is that we, ourselves, are not very good at recognizing when we are fatigued to a point that we are putting our patients in jeopardy. We’ve always suspected we will ultimately adopt technology as a means to identify fatigue earlier. In our July 29, 2014 Patient Safety Tip of the Week “The 12-Hour Nursing Shift: Debate Continues” we predicted that someday we will have the equivalent of the brief “sobriety” or “breathalyzer” test that can rapidly identify healthcare workers who are impaired by fatigue. We envision that at regular intervals beyond 8 hours (maybe even sooner) or during periods of prolonged concentration the healthcare worker will get buzzed on his/her smartphone and have to complete some simple test of reaction times or attention span. If the worker scores outside the established threshold the hospital will need to have resources in place to take over duties of that worker (completely or at least temporarily until fatigue is alleviated by, for example, a nap).
When driving long distances or at night, we use a cellphone app that uses the camera to focus on our face. When it detects any degree of eyelid drooping, it sounds an audible alarm to alert us. And it sounds an even louder alarm if it detects a repeat episode of eyelid drooping within a specified amount of time. But, obviously, we can’t wait for eyelid drooping to identify fatigue in healthcare workers on the job.
Fortunately, there are a variety of other ocular phenomena that can be used to detect early fatigue. In addition to eyelid drooping, alteration of saccadic eye movements, changes in the blink rate, and changes in pupillary responses may be early signs of fatigue. In our December 2, 2014 Patient Safety Tip of the Week “ANA Position Statement on Nurse Fatigue” we noted there are other technologies that might do the trick. Studies have demonstrated alteration of saccadic eye movement metrics correlate with fatigue in several settings and studies in surgical residents confirmed such a correlation (Di Stasi 2014). Such a test could probably be easily adapted to most of today’s smartphones.
Yamada and colleagues (Yamada 2018) developed a model to detect mental fatigue of younger and older adults in natural viewing situations. They collected eye-tracking data from younger and older adults as they watched video clips before and after performing cognitive tasks. Their model improved detection accuracy, achieving 91.0% accuracy, which was 13.9% higher compared with a model based on the previous studies.
Zargari Marandi et al. (Zargari Marandi 2018) similarly studied eye movements in young and older adults during a prolonged functional computer task. The task lasted 40 minutes involving 240 cycles divided into 12 segments. Each cycle consisted of a sequence involving memorization of a pattern, a washout period, and replication of the pattern using a computer mouse. The participants rated their perceived fatigue after each segment. Parameters they measured were blink duration (BD) and frequency (BF), saccade duration (SCD) and peak velocity (SPV), pupil dilation range (PDR), and fixation duration (FD), along with the task performance based on clicking speed and accuracy. They also used a subjective (self-reported) measure of fatigue. They found that BD, BF, and PDR increased whereas SPV and SCD decreased over time in the young and elderly groups. But there were some age-related differences. Longer FD, shorter SCD, and lower task performance were observed in the elderly compared with the young group.
The Yamada and Zargari Marandi studies assessed the value of oculometrics during prolonged mentally demanding computer tasks. So, how about healthcare professionals who might similarly be engaged in prolonged mentally demanding computer tasks? How about radiologists? Our April 2018 What's New in the Patient Safety World column “Radiologists Get Fatigued, Too” highlighted a study looking at the effect of overnight shifts on performance of radiologists (Hanna 2018). The researchers used a tool for measuring fatigue and advance eye tracking technology to assess the performance of radiologists (both attendings and residents). During each session, radiologists viewed 20 bone radiographs consisting of normal and abnormal findings. The Swedish Occupational Fatigue Inventory results demonstrated worsening in all five variables (lack of energy, physical exertion, physical discomfort, lack of motivation, and sleepiness) after overnight shifts. Not surprisingly, participants demonstrated worse diagnostic performance in the fatigued versus not-fatigued state. Viewing time per case was significantly prolonged when the radiologists were fatigued. Mean total fixations generated during the search increased by 60% during fatigued sessions. Mean time to first fixate on bone fractures increased by 34% during fatigued sessions. Moreover, dwell times associated with true- and false-positive decisions increased, whereas those with false negatives decreased. Effects of fatigue were more pronounced in residents. The authors concluded that further research is needed to address and reverse the impact of such fatigue-related changes. They speculate that environmental changes (eg. lighting) and activity changes (eg. periodic breaks, moving around, etc.) might help mitigate the adverse effects of fatigue on performance.
Then, in our August 25, 2020 Patient Safety Tip of the Week “The Off-Hours Effect in Radiology” we noted some other studies assessing the impact of fatigue on radiologist performance.
So, it’s no surprise that researchers have chosen radiologists as a good population in which to study the use of oculometrics for assessment of fatigue. Belgian researchers have done just that (Ward 2021). They measured saccades, blink rate, and the percentage of eyelid closure over the pupil over time. Their setup included four displays, three RGB (red, green, blue) cameras, a gaze tracker, keyboard/mouse input (no keystrokes, only number of actions per second), and acoustic information. (The Ward article has a photo of the equipment setup used by the Belgian researchers.) And the radiologists also completed a subjective assessment of fatigue every 20 minutes. Their data confirmed that self-scored fatigue labels underestimated the occurrence of fatigue. This is really a feasibility or proof-of-concept study on which to build. It demonstrates that objective measures can be easily recorded, and some day may be used to alert radiologists to the presence of fatigue that might impair their performance in imaging interpretation.
Similar technology was used in a UK study on radiologists reading digital breast tomosynthesis (DBT) cases (Ward 2020). The researchers simply modified the mammography reading station with a three-camera eye-tracking system. Measuring blinking as an indicator of fatigue, they found that after reading 20 DBT cases, individuals were beginning to show signs of visual fatigue onset. They concluded that taking a break after 20 reports might help eliminate mistakes.
The fact that the Yamada model could detect increased mental fatigue induced by the cognitive tasks with 91.0% accuracy from just 30 seconds worth of eye-tracking data suggests this could be the oculometric equivalent of the “breathalyzer” test! We could envision implementation of such systems on almost any computer terminal that might be used by physicians, nurses, pharmacists, etc. It might even be applied to any situation in which sustained concentration for long periods is required (eg. during a surgical procedure). It might provide an easy, inexpensive way to identify fatigue in healthcare workers. But the next question is whether interventions based upon such detection can actually reduce errors in patient care. It’s about time these relatively simple techniques find their niche in healthcare.
Some of our other columns on the role of fatigue in Patient Safety:
November 9, 2010 “12-Hour Nursing Shifts and Patient Safety”
April 26, 2011 “Sleeping Air Traffic Controllers: What About Healthcare?”
February 2011 “Update on 12-hour Nursing Shifts”
September 2011 “Shiftwork and Patient Safety
November 2011 “Restricted Housestaff Work Hours and Patient Handoffs”
January 2012 “Joint Commission Sentinel Event Alert: Healthcare Worker Fatigue and Patient Safety
January 3, 2012 “Unintended Consequences of Restricted Housestaff Hours”
June 2012 “June 2012 Surgeon Fatigue”
November 2012 “The Mid-Day Nap”
November 13, 2012 “The 12-Hour Nursing Shift: More Downsides”
July 29, 2014 “The 12-Hour Nursing Shift: Debate Continues”
October 2014 “Another Rap on the 12-Hour Nursing Shift”
December 2, 2014 “ANA Position Statement on Nurse Fatigue”
August 2015 “Surgical Resident Duty Reform and Postoperative Outcomes”
September 2015 “Surgery Previous Night Does Not Impact Attending Surgeon Next Day”
September 29, 2015 “More on the 12-Hour Nursing Shift”
September 6, 2016 “Napping Debate Rekindled”
April 18, 2017 “Alarm Response and Nurse Shift Duration”
July 11, 2017 “The 12-Hour Shift Takes More Hits”
February 13, 2018 “Interruptions in the ED”
April 2018 “Radiologists Get Fatigued, Too”
August 2018 “Burnout and Medical Errors”
September 4, 2018 “The 12-Hour Nursing Shift: Another Nail in the Coffin”
August 2020 “New Twist on Resident Work Hours and Patient Safety”
August 25, 2020 “The Off-Hours Effect in Radiology”
September 2020 “Daylight Savings Time Impacts Patient Safety?”
References:
Di Stasi LL, McCamy MB, Macknik, SL, et al. Saccadic Eye Movement Metrics Reflect Surgical Residents' Fatigue. Annals of Surgery 2014; 259(4): 824-829
Yamada Y, Kobayashi M. Detecting mental fatigue from eye-tracking data gathered while watching video: Evaluation in younger and older adults. Artificial Intelligence in Medicine 2018; 91: 39-48
https://www.sciencedirect.com/science/article/pii/S0933365717306140
Zargari Marandi R, Madeleine P, Omland Ø, et al. Eye movement characteristics reflected fatigue development in both young and elderly individuals. Scientific Reports 2018; 8: Article 13148
https://www.nature.com/articles/s41598-018-31577-1#citeas
Hanna TN, Zygmont ME, Peterson R, et al. The effects of fatigue from overnight shifts on radiology search patterns and diagnostic performance. J Am Coll Radiol 2018; 15(12): 1709-1716
https://www.jacr.org/article/S1546-1440(17)31661-7/fulltext
Ward P. Belgian team develops novel way to assess fatigue. AuntMinnieEurope.com 2021; January 12, 2021
https://www.auntminnieeurope.com/index.aspx?sec=sup&sub=pac&pag=dis&ItemID=619679
Ward P. What effect does fatigue have on reading breast scans? AuntMinnieEurope.com 2020; October 26, 2020
https://www.auntminnieeurope.com/index.aspx?sec=sup&sub=wom&pag=dis&ItemID=619432
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January 2021
Our August 17, 2010 Patient Safety Tip of the Week “Preoperative Consultation – Time to Change” suggested the 3 most important things to screen for during a preoperative evaluation are frailty, delirium risk, and obstructive sleep apnea. Frailty clearly has been linked to post-operative adverse events and poorer patient outcomes following surgery (see our multiple columns listed below).
We are always looking for simple tests for frailty that can be applied in brief sessions in a surgeon’s office or other preoperative assessment setting. In our May 16, 2017 Patient Safety Tip of the Week “Are Surgeons Finally Ready to Screen for Frailty?” we noted a study that looked at individual components of the Fried frailty phenotype measures (gait speed, hand-grip strength as measured by a dynamometer, and self-reported exhaustion, low physical activity, and unintended weight loss) in a primary care setting (Lee 2017). The researchers found that individual criteria all showed sensitivity and specificity of more than 80%, with the exception of weight loss. The positive predictive value of the single-item criteria in predicting the Fried frailty phenotype ranged from 12.5% to 52.5%. When gait speed and hand-grip strength were combined as a dual measure, the positive predictive value increased to 87.5%. They conclude that, while use of gait speed or grip strength alone was found to be sensitive and specific as a proxy for the Fried frailty phenotype, use of both measures together was found to be accurate, precise, specific, and more sensitive than other possible combinations and that assessing both measures is feasible within the primary care setting.
Almost all the scales we use for detecting frailty include measures of gait (such as the Timed Up-and-Go test or measures of gait speed). But what about those patients in whom it is not possible to assess gait?
Najafi and colleagues (Najafi 2020) came up with an innovative solution to screen for frailty in those patients where gait could not be assessed. Many of their patients had chronic limb-threatening ischemia (CLTI) and were often unable to perform gait-based assessments because of the presence of plantar wounds. So, they designed and assessed a device they call the Frailty Meter (“FM”). The FM consists of a wrist-worn sensor and a wirelessly connected tablet. It records the angular velocity during a 20-second repetitive elbow flexion-extension task and quantifies weakness, slowness, rigidity, and exhaustion during that exercise. It then displays a Frailty Index (“FI”). Participants were tested on their dominant arm, according to a standardized protocol.
The frailty measurement was performed within 1 week before limb revascularization in 152 patients. They then assessed the incidence of major adverse events (MAE’s) for up to 1 month after surgery. 78.2% of the patients were unable to perform the gait test, while all could perform the FM test. Overall, 34.9%, 38.1%, and 27.0% were classified as robust, pre-frail, or frail, respectively, by their FI scores.
Within 30 days after surgery, 15.7% of patients developed MAE’s, either major adverse cardiovascular events (MACE 5.2%) or major adverse limb events (MALE 10.5%). The FI was approximately 30% higher in the group that developed MAE’s than those who were MAE free.
There was a significantly lower mean FI score in the non-MAE group compared with MACE and MALE groups, but there was no significant difference of FI between MACE and MALE groups.
While this study only included patients with lower extremity vascular disease, we can see how use of the “frailty meter” could also be valuable in assessing patients whose gait cannot be assessed due to neurological or orthopedic conditions.
Some of our prior columns on preoperative assessment and frailty:
References:
Lee L, Patel T, Costa A, Bryce E, Hillier LM, Slonim K, et al. Screening for frailty in primary care. Accuracy of gait speed and hand-grip strength. Can Fam Physician 2017; 63: e51-57
https://www.cfp.ca/content/63/1/e51
Najafi B, Veranyan N, Zulbaran-Rojas A, et al. Association Between Wearable Device–Based Measures of Physical Frailty and Major Adverse Events Following Lower Extremity Revascularization. JAMA Netw Open 2020; 3(11): e2020161
https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2773096
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One of the most common risks of MRI scanning is the risk of thermal injury. Burns can result when any object containing metallic or ferromagnetic material superheats during the scan. While most burns have occurred due to things like superficial EKG electrodes or coils, the risk of thermal injury has also been attributed to some unusual items: transdermal skin patches, tattoos, tags on breast implants, ingested toy magnets, and even metallic eyelashes (see our previous columns for April 2, 2019 “Unexpected Events During MRI” and September 2019 “New MRI Hazard: Magnetic Eyelashes”).
Now the FDA has issued a warning after receiving a report of a patient suffering facial burns from a face mask during MRI (FDA 2020). That patient was wearing a face mask with metal during a 3-Tesla MRI scan of the neck. The report described the burns to the patient’s face being consistent with the shape of the face mask.
Some face masks and respirators contain metal parts or coatings. The FDA notes that metal parts, like nose pieces nose clips or wires, headband staples, nanoparticles (ultrafine particles), or antimicrobial coating that may contain metal (such as silver or copper), may become hot and burn the patient during an MRI.
The FDA acknowledges that it may be appropriate for a patient to wear a face mask during an MRI exam, especially during the COVID-19 pandemic. But it is critical to ensure the face mask contains no metal.
FDA recommends that, if the absence of metal cannot be confirmed and it is determined to be appropriate for the patient to wear a face mask, an alternative face mask where the absence of metal can be confirmed should be used. Health care providers who perform MRI exams are encouraged to provide face masks without metal to patients who will undergo an MRI.
Your pre-MRI checklist, of course, includes screening for metallic objects. Looking at the face mask could identify obvious metallic parts, like nose pieces or staples, but won’t reveal things like nanoparticles or coatings mentioned in the FDA warning. The FDA warning does not mention whether metal detection devices can detect some of those less obvious items.
So, our recommendation would be to not allow patients to wear their own face masks during MRI. Instead, each facility should provide them with a face mask known to be free of those metallic components.
That recommendation is echoed by Tobias Gilk, an MRI safety expert whom we have cited in many of our columns (Yee 2020). "The staples holding the elastic to the mask are too small to conduct heat, and since the COVID-19 pandemic, patients have been imaged in masks that have nose bridges without injury," he said. "But antimicrobial treated fabric can heat up. So, to be safe, patients should be provided with disposable surgical masks before their MRI."
And, of course, appropriate infection control procedures need to be followed when handling either the patient’s own face mask or the one provided by the facility.
Lastly, it also makes sense that your own MRI staff must wear face masks known to be free of those metallic components. That would include other hospital staff who might have to respond to an emergency in the MRI suite.
Metallic elements are showing up more and more in places we’d never think of looking for.
Some of our prior columns on patient safety issues related to MRI:
References:
FDA (US Food and Drug Administration). Wear Face Masks with No Metal During MRI Exams: FDA Safety Communication. FDA 2020; December 7, 2020
Yee KM. FDA issues face mask warning for MRI exams. AuntMinnie.com 2020; December 7, 2020
https://www.auntminnie.com/index.aspx?sec=sup&sub=mri&pag=dis&ItemID=131064
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It was January a year ago that we wrote about an FDA warning on gabapentinoids (see our January 2020 What's New in the Patient Safety World column “FDA Warning on Gabapentinoids”). In the past several years we had done a several columns on dangers of gabpentinoids, alone or in combination with opioids (see our What's New in the Patient Safety World columns for November 2017 “Bad Combination: Gabapentin and Opioids” and March 2019 “Gabapentin and Pregabalin on the Radar Screen”). So, it came as no surprise to us that the FDA has issued a warning about gabapeninoids (FDA 2019).
But most of the warnings about respiratory depression with gabapentinoids, often when used in combination with opioids, were the result of anecdotal reports and small case series. Then, in our February 25, 2020 Patient Safety Tip of the Week “More on Perioperative Gabapentinoids”, we discussed 2 studies by Duke University researchers from larger databases looking at the impact of gabapentinoids used in the perioperative period. Ohnuma et al. (Ohnuma 2019) analyzed data from a large administrative claims database, including 862,524 patients from 592 hospitals, who underwent elective primary THA or TKA between 2009 and 2014. They looked at the following drugs, alone or in combination, on the day of surgery for patients undergoing TKA or THA: acetaminophen, nonsteroidal anti-inflammatory drugs (NSAID’s), gabapentinoids (gabapentin or pregabalin), or none of the three drugs.
Compared to none of the three drugs as the reference category, exposure to gabapentinoids was associated with increased odds of naloxone use after surgery (OR 2.11), noninvasive ventilation (OR, 1.45), invasive mechanical ventilation (OR 1.25), and ICU admission (OR 1.28). A similar increase was seen in analgesic combinations including gabapentinoids. The group receiving NSAID’s plus acetaminophen showed the most protective associations with naloxone use after surgery (OR 0.59), invasive mechanical ventilation (OR, 0.72), and ICU admission (OR 0.69), and was associated with the lowest opioid consumption on the day before discharge.
The authors conclude that preoperative gabapentinoids were associated with significant increased risk of postoperative opioid-related respiratory depression. It also failed to find benefits for gabapentinoids in terms of postoperative opioid consumption and LOS. They recommended reconsideration of routine use of preoperative gabapentinoids in the adult TKA and THA population.
The researchers also looked at 108,616 patients who underwent elective colorectal surgery across the 605 hospitals, 2% of whom received gabapentinoids on the day of surgery (Yan 2019). They found that use of gabapentinoids was associated with higher odds of noninvasive ventilation (OR 1.39) and receipt of naloxone after surgery (OR 1.70). There was no difference in invasive mechanical ventilation, opioid consumption, or LOS. They cite other small studies showing increased risk of postoperative respiratory depression and naloxone use in patients receiving gabapentinoids, which may be explained by an interaction between gabapentinoids and opioids.
Now, a new study (Bykov 2020) analyzed data from the large Premier Research database to assess use of perioperative gabapentinoids in relation to the risk of opioid-related adverse events in surgical patients. The study population included adults admitted for major surgery between October 2007 and December 2017 who were treated with opioids on the day of surgery. Overall, gabapentinoids with opioids were administered to 892,484 of 5 547 667 eligible admissions (16.1%). Overall, 441 overdose events were identified, with absolute risks of 1.4 per 10,000 patients with gabapentinoid exposure and 0.7 per 10,000 patients receiving opioids only. Following propensity score trimming, the adjusted hazard ratio for an overdose in those receiving gabapentinoids and opioids compared to those receiving opioids only was 1.95. But the absolute risk was small. To put it in perspective, the number needed to treat (NNT) for an additional overdose to occur was 16,914 patients. Adjusted hazard ratios for secondary outcomes were 1.68 for respiratory complications, 1.77 for unspecified adverse effects of opioids, and 1.70 for the composite outcome of the 3 outcomes. The results were consistent across sensitivity analyses and subgroups identified by key clinical factors.
In our attempts to reduce the use of perioperative opioids, the use of multimodal analgesia has been front and center. One component of many multimodal analgesia regimens has been gabapentinoids. The Bykov study is somewhat reassuring in that the absolute risk of untoward complications is small. The overall occurrence of adverse outcomes was very low, with overdoses occurring in less than 0.1% of patients. Yet, it does confirm that concomitant use of gabapentinoids almost doubles the risk of overdose and increased the risk of respiratory complications by about 70%. That certainly calls for careful consideration of when gabapentinoids should be used perioperatively and when they might be best avoided.
Others have questioned the risks and benefits of perioperative gabapentinoids. In our February 25, 2020 Patient Safety Tip of the Week “More on Perioperative Gabapentinoids” we discussed a systematic review and meta-analysis on perioperative use of gabapentinoids (Verret 2019) that found no clinically significant analgesic effect for the perioperative use of gabapentinoids, with low level of evidence, and an increased risk of adverse events with moderate level of evidence. The authors concluded that their results do not support the use of gabapentinoids for the management postoperative acute pain in adult patients.
Unfortunately, the studies from the large databases do not tell us what other risk factors may have contributed to the adverse events related to patients receiving gabapentinoids. Taking those risk factors into account might allow better selection of patients who might benefit from gabapentinoids without the risks of respiratory depression. For example, we might avoid using gabapentinoids in patients at risk for obstructive sleep apnea (OSA).
So, again, mixed messages from the Bykov study – the absolute risk from gabapentinioids is low but they do increase the risk of adverse events in those patients receiving opioids perioperatively.
Hospitals and ambulatory surgical centers should include a look at gabapentinoids in their analysis of events following surgery. Particularly in view of the Obnuma study mentioned above (Ohnuma 2019), they should also look to see if the intended rationale for use of gabapentinoids (to reduce the need for opioids) actually achieved that goal.
Some of our prior columns on safety issues with gabapentinoids:
References:
FDA (US Food and Drug Administration). FDA warns about serious breathing problems with seizure and nerve pain medicines gabapentin (Neurontin, Gralise, Horizant) and pregabalin (Lyrica, Lyrica CR)When used with CNS depressants or in patients with lung problems12-19-2019
https://www.fda.gov/media/133681/download
OhnumaT, Raghunathan K, Ellis A, et al. Abstract S-344 Effects of Acetaminophen, NSAID’s, Gabapentinoids and Their Combinations on the Day of Surgery in Total Hip and Knee Arthroplasties. Anesthesia & Analgesia 2019; 128(5): 741
https://iars.app.box.com/v/AM19AbstractSupplement
Yan R, Ohnuma T, Krishnamoorthy V, et al. Abstract S-353 Gabapentinoids on the Day of Colorectal Surgery Are Associated with Adverse Postoperative Respiratory Outcomes. Anesthesia & Analgesia 2019; 128(5): 760
https://iars.app.box.com/v/AM19AbstractSupplement
Bykov K, Bateman BT, Franklin JM, Vine SM, Patorno E. Association of Gabapentinoids With the Risk of Opioid-Related Adverse Events in Surgical Patients in the United States. JAMA Netw Open 2020; 3(12): e2031647
Verret M, Lauzier F, Zarychanski R, et al. Perioperative Use of Gabapentinoids for the Management of Postoperative Acute Pain: A Systematic Review and Meta-analysis. 2019 annual meeting of the American Society of Anesthesiologists (ASA; abstract A2096).
http://www.asaabstracts.com/strands/asaabstracts/abstract.htm?year=2019&index=18&absnum=1927
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We’ve done several columns on the impact of surgical case duration on post-op complications and surgical outcomes (see the full list below). We’ve often cited a study (Procter 2010) that looked at a large database of general surgical procedures and demonstrated a linear relationship between duration of surgery and infectious complications. This relationship persisted even after adjustment for a variety of other risk factors for perioperative infections. The unadjusted infectious complication rate increased by 2.5% per half hour. Hospital length of stay (LOS) also increased geometrically by 6% per half hour. Logically, prolonged operative time would also be expected to increase pressure-related complications, such as decubiti and perioperative neuropathies. Longer duration also increases the likelihood of increased foot traffic into and out of the OR and the potential for distractions and interruptions, potentially contributing to errors.
A new study (Chen 2020) used data from the American College of Surgeons National Surgical Quality Improvement Program database on almost 15,000 patients who had undergone revision total knee arthroplasties (TKA’s) between 2007 and 2016. After adjustment, each additional 15 minutes of operative time increased the likelihood of wound complications (odds ratio 1.023), postoperative blood transfusion (odds ratio 1.169), and extended hospital stay (odds ratio 1.060). Of course, from such database statistics one cannot determine the reason for the prolonged surgical durations. In some cases, whatever led to complications may have also prolonged the surgery. But, undoubtedly, in many cases the complications resulted from the long surgical durations.
We recommend hospitals and any facility performing surgical procedures have a system in place to remind all the OR staff of surgical duration. After a set amount of time (based upon the average or expected duration for each type of surgery), someone such as the anesthesiologist should verbally call out the case duration so all staff are aware. Such announcement should be repeated every 10-15 minutes. That may alert staff to the need to reposition the patient, administer a second course of prophylactic antibiotics, etc.
Our prior columns focusing on surgical case duration:
References:
Procter LD, Davenport DL, Bernard AC, Zwischenberger JB. General Surgical Operative Duration Is Associated With Increased Risk-Adjusted Infectious Complication Rates and Length of Hospital Stay, Journal of the Amercican College of Surgeons 2010; 210: 60-65
https://www.journalacs.org/article/S1072-7515%2809%2901411-2/abstract
Chen AZ, Gu, A, Wei C, et al. Increase in Operative Time Is Associated With Postoperative Complications in Revision Total Knee Arthroplasty. Orthopedics 2020;
Orthopedics. 2021;44(1):xx–xx
Posted November 25, 2020
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