Validating the Stopping Opioids after Surgery (SOS) score for sustained postoperative prescription opioid use in spine surgical patients

Opioid-Free Analgesia is Safe and Effective in Anterior Cervical Spine Surgery: A Randomized Controlled Trial

STUDY DESIGN

Randomized controlled trial (RCT).

OBJECTIVE

Compare the efficacy of a multimodal, opioid-free (OF) pain management pathway with a traditional opioid-containing (OC) pathway in patients undergoing anterior cervical procedures.

SUMMARY OF BACKGROUND DATA

Previous studies have compared opioid-based pain regimens to opioid-sparing regimens following cervical spine surgery, but have been limited by high rates of crossover, retrospective designs, reliance on indwelling pain catheters, opioid utilization for early postoperative analgesia, and/or a lack of patient-reported outcome measures.

METHODS

This is a RCT in which patients were allocated to either an OF or OC perioperative pain management protocol. Eligible study participants included adult (age up to 18 y) patients who underwent primary, 1-level or 2-level anterior cervical surgery [anterior cervical discectomy and fusion (ACDF), anterior cervical disc arthroplasty (ACDA), or hybrid (ACDF and ACDA at different levels)] for degenerative pathology. The primary outcome variable was subjective pain level at 24 hours postoperative. The final study cohort consisted of 50 patients (22 OF, 28 OC).

RESULTS

Patients in the OF group reported lower median postoperative pain levels at 6 hours (4 for OF vs. 7 for OC; P =0.041) and 24 hours (3 for OF vs. 5 for OC; P =0.032). At 2-week and 6-week follow-up, pain levels were similar between groups. Patients in the OF group reported greater comfort at 12 hours (9 for OF vs. 5 for OC; P =0.003) and 24 hours (9 for OF vs. 5 for OC; P =0.011) postoperatively. Notably, there were no significant differences in patients' reported pain satisfaction, overall surgical satisfaction, or overall sense of physical and mental well-being. In addition, there were no significant differences in falls, delirium, or constipation postoperatively.

CONCLUSIONS

A multimodal OF pain management pathway following anterior cervical surgery for degenerative disease results in statistically noninferior pain control and equivalent patient-reported outcome measures compared with a traditional OC pathway.

Does the Stopping Opioids After Surgery Score Perform Well Among Racial and Socioeconomic Subgroups?

BACKGROUND

The Stopping Opioids After Surgery (SOS) score is a validated tool that was developed to determine the risk of sustained opioid use after surgical interventions, including orthopaedic procedures. Despite prior investigations validating the SOS score in diverse contexts, its performance across racial, ethnic, and socioeconomic subgroups has not been assessed.

QUESTIONS/PURPOSES

In a large, urban, academic health network, did the performance of the SOS score differ depending on (1) race and ethnicity or (2) socioeconomic status?

METHODS

This retrospective investigation was conducted using data from an internal, longitudinally maintained registry of a large, urban, academic health system in the Northeastern United States. Between January 1, 2018, and March 31, 2022, we treated 26,732 adult patients via rotator cuff repair, lumbar discectomy, lumbar fusion, TKA, THA, ankle or distal radius open reduction and internal fixation, or ACL reconstruction. We excluded 1% of patients (274 of 26,732) because of missing length of stay information, 0.06% (15) for missing discharge information, 1% (310) for missing medication information related to loss to follow-up, and 0.07% (19) who died during their hospital stay. Based on these inclusion and exclusion criteria, 26,114 adult patients were left for analysis. The median age in our cohort was 63 years (IQR 52 to 71), and most patients were women (52% [13,462 of 26,114]). Most patients self-reported their race and ethnicity as non-Hispanic White (78% [20,408 of 26,114]), but the cohort also included non-Hispanic Black (4% [939]), non-Hispanic Asian (2% [638]), and Hispanic (1% [365]) patients. Five percent (1295) of patients were of low socioeconomic status, defined by prior SOS score investigations as patients with Medicaid insurance. Components of the SOS score and the observed frequency of sustained postoperative opioid prescriptions were abstracted. The performance of the SOS score was compared across racial, ethnic, and socioeconomic subgroups using the c-statistic, which measures the capacity of the model to differentiate between patients with and without sustained opioid use. This measure should be interpreted on a scale between 0 and 1, where 0 represents a model that perfectly predicts the wrong classification, 0.5 represents performance no better than chance, and 1.0 represents perfect discrimination. Scores less than 0.7 are generally considered poor. The baseline performance of the SOS score in past investigations has ranged from 0.76 to 0.80.

RESULTS

The c-statistic for non-Hispanic White patients was 0.79 (95% CI 0.78 to 0.81), which fell within the range of past investigations. The SOS score performed worse for Hispanic patients (c-statistic 0.66 [95% CI 0.52 to 0.79]; p < 0.001), where it tended to overestimate patients' risks of sustained opioid use. The SOS score for non-Hispanic Asian patients did not perform worse than in the White patient population (c-statistic 0.79 [95% CI 0.67 to 0.90]; p = 0.65). Similarly, the degree of overlapping CIs suggests that the SOS score did not perform worse in the non-Hispanic Black population (c-statistic 0.75 [95% CI 0.69 to 0.81]; p = 0.003). There was no difference in score performance among socioeconomic groups (c-statistic 0.79 [95% CI 0.74 to 0.83] for socioeconomically disadvantaged patients; 0.78 [95% CI 0.77 to 0.80] for patients who were not socioeconomically disadvantaged; p = 0.92).

CONCLUSION

The SOS score performed adequately for non-Hispanic White patients but performed worse for Hispanic patients, where the 95% CI nearly included an area under the curve value of 0.5, suggesting that the tool is no better than chance at predicting sustained opioid use for Hispanic patients. In the Hispanic population, it commonly overestimated the risk of opioid dependence. Its performance did not differ among patients of different sociodemographic backgrounds. Future studies might seek to contextualize why the SOS score overestimates expected opioid prescriptions for Hispanic patients and how the utility performs among more specific Hispanic subgroups.

CLINICAL RELEVANCE

The SOS score is a valuable tool in ongoing efforts to combat the opioid epidemic; however, disparities exist in terms of its clinical applicability. Based on this analysis, the SOS score should not be used for Hispanic patients. Additionally, we provide a framework for how other predictive models should be tested in various lesser-represented populations before implementation.

Validation of the Stopping Opioids After Surgery (SOS) Score for the Sustained Use of Prescription Opioids Following Orthopaedic Surgery

BACKGROUND

The Stopping Opioids after Surgery (SOS) score was developed to identify patients at risk for sustained opioid use following surgery. The SOS score has not been specifically validated for patients in a general orthopaedic context. Our primary objective was to validate the SOS score within this context.

METHODS

In this retrospective cohort study, we considered a broad array of representative orthopaedic procedures performed between January 1, 2018, and March 31, 2022. These procedures included rotator cuff repair, lumbar discectomy, lumbar fusion, total knee and total hip arthroplasty, open reduction and internal fixation (ORIF) of ankle fracture, ORIF of distal radial fracture, and anterior cruciate ligament reconstruction. The performance of the SOS score was evaluated by calculating the c-statistic, receiver operating characteristic curve, and the observed rates of sustained prescription opioid use (defined as uninterrupted prescriptions of opioids for ≥90 days) following surgery. For our sensitivity analysis, we compared these metrics among various time epochs related to the COVID-19 pandemic.

RESULTS

A total of 26,114 patients were included, of whom 51.6% were female and 78.1% were White. The median age was 63 years. The observed prevalence of sustained opioid use was 1.3% (95% confidence interval [CI], 1.2% to 1.5%) in the low-risk group (SOS score of <30), 7.4% (95% CI, 6.9% to 8.0%) in the medium-risk group (SOS score of 30 to 60), and 20.8% (95% CI, 17.7% to 24.2%) in the high-risk group (SOS score of >60). The performance of the SOS score in the overall group was strong, with a c-statistic of 0.82. The performance of the SOS score showed no evidence of worsening over time. The c-statistic was 0.79 before the COVID-19 pandemic and ranged from 0.77 to 0.80 throughout the waves of the pandemic.

CONCLUSIONS

We validated the use of the SOS score for sustained prescription opioid use following a diverse array of orthopaedic procedures across subspecialties. This tool is easy to implement for the purpose of prospectively identifying patients in musculoskeletal service lines who are at higher risk for sustained opioid use, thereby enabling the future implementation of upstream interventions and modifications to avert opioid abuse and to combat the opioid epidemic.

LEVEL OF EVIDENCE

Diagnostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Development of a machine learning algorithm to identify surgical candidates for hip and knee arthroplasty without in-person evaluation

INTRODUCTION

Arthroplasty care delivery is facing a growing supply-demand mismatch. To meet future demand for joint arthroplasty, systems will need to identify potential surgical candidates prior to evaluation by orthopaedic surgeons.

MATERIALS AND METHODS

Retrospective review was conducted at two academic medical centers and three community hospitals from March 1 to July 31, 2020 to identify new patient telemedicine encounters (without prior in-person evaluation) for consideration of hip or knee arthroplasty. The primary outcome was surgical indication for joint replacement. Five machine learning algorithms were developed to predict likelihood of surgical indication and assessed by discrimination, calibration, overall performance, and decision curve analysis.

RESULTS

Overall, 158 patients underwent new patient telemedicine evaluation for consideration of THA, TKA, or UKA and 65.2% (n = 103) were indicated for operative intervention prior to in-person evaluation. The median age was 65 (interquartile range 59-70) and 60.8% were women. Variables found to be associated with operative intervention were radiographic degree of arthritis, prior trial of intra-articular injection, trial of physical therapy, opioid use, and tobacco use. In the independent testing set (n = 46) not used for algorithm development, the stochastic gradient boosting algorithm achieved the best performance with AUC 0.83, calibration intercept 0.13, calibration slope 1.03, Brier score 0.15 relative to a null model Brier score of 0.23, and higher net benefit than the default alternatives on decision curve analysis.

CONCLUSION

We developed a machine learning algorithm to identify potential surgical candidates for joint arthroplasty in the setting of osteoarthritis without an in-person evaluation or physical examination. If externally validated, this algorithm could be deployed by various stakeholders, including patients, providers, and health systems, to direct appropriate next steps in patients with osteoarthritis and improve efficiency in identifying surgical candidates.

LEVEL OF EVIDENCE

III.

Perioperative Factors Associated With Chronic Opioid Use After Spine Surgery

STUDY DESIGN

Retrospective case control.

OBJECTIVES

The purpose of the current study is to determine risk factors associated with chronic opioid use after spine surgery.

METHODS

In our single institution retrospective study, 1,299 patients undergoing elective spine surgery at a tertiary academic medical center between January 2010 and August 2017 were enrolled into a prospectively collected registry. Patients were dichotomized based on renewal of, or active opioid prescription at 3-mo and 12-mo postoperatively. The primary outcome measures were risk factors for opioid renewal 3-months and 12-months postoperatively. These primarily included demographic characteristics, operative variables, and in-hospital opioid consumption via morphine milligram equivalence (MME). At the 3-month and 12-month periods, we analyzed the aforementioned covariates with multivariate followed by bivariate regression analyses.

RESULTS

Multivariate and bivariate analyses revealed that script renewal at 3 months was associated with black race (P = 0.001), preoperative narcotic (P < 0.001) or anxiety/depression medication use (P = 0.002), and intraoperative long lumbar (P < 0.001) or thoracic spine surgery (P < 0.001). Lower patient income was also a risk factor for script renewal (P = 0.01). Script renewal at 12 months was associated with younger age (P = 0.006), preoperative narcotics use (P = 0.001), and ≥4 levels of lumbar fusion (P < 0.001). Renewals at 3-mo and 12-mo had no association with MME given during the hospital stay or with the usage of PCA (P > 0.05).

CONCLUSION

The current study describes multiple patient-level factors associated with chronic opioid use. Notably, no metric of perioperative opioid utilization was directly associated with chronic opioid use after multivariate analysis.

Utilizing previous patient opioid experiences for pain plan implementation: Role of opioid use categorization on inpatient and outpatient opioid use, length of stay, pain scores, and clinic resource utilization following elective spine surgery

Background

A Pain Plan was formulated for all patients undergoing elective spine surgery at our institution. It was based on prior opioid experiences and developed collaboratively between the patient and the surgeon at a preoperative clinic visit. Category 1 patients had no previous opioid experience, Category 2 patients had remote previous opioid experience with acceptable pain control and no side effects, Category 3 patients had remote previous opioid experience with unacceptable pain control and/or side effects, and Category 4 patients had opioid use leading up to surgery.

Methods

This is a retrospective cohort study comparing adult patients within four different pain plan categories over one year (n = 313) to determine if categorization is predictive. Demographic data collected included age, gender, ASA class, BMI, smoking status, insurance status, substance abuse, and comorbid psychiatric diagnoses. Demographic factors between categories were compared and controlled for as covariates within analyses. Outcomes measures comprised self-reported pain scores and functional measurements, including inpatient opioid use, outpatient opioid prescription quantities, and postoperative healthcare utilization.

Results

Inpatient and outpatient opioid use were statistically significant amongst the categories, with prescription quantities greatest in Category 4, followed by Categories 2, 3, and 1, respectively. There was no difference in LOS or complexity of communication encounters amongst any of the groups. Patient-reported pain scores showed statistically significant differences and followed the same trend as opioid quantities, 4, 2, 3, and 1. The number of communication encounters was significant exclusively for Category 3 vs. 4.

Conclusions

The use of categorization in Pain Plan formation has been a helpful tool for postoperative pain management at our institution. Categorization is predictive of pain scores and opioid use after surgery, allowing the surgical team to tailor their care and counseling towards individual patients. In addition, the plan's collaborative nature enables patients to be involved in their pain management decisions while also setting limits and expectations.

A machine learning algorithm for predicting prolonged postoperative opioid prescription after lumbar disc herniation surgery. An external validation study using 1,316 patients from a Taiwanese cohort

BACKGROUND CONTEXT

Preoperative prediction of prolonged postoperative opioid prescription helps identify patients for increased surveillance after surgery. The SORG machine learning model has been developed and successfully tested using 5,413 patients from the United States (US) to predict the risk of prolonged opioid prescription after surgery for lumbar disc herniation. However, external validation is an often-overlooked element in the process of incorporating prediction models in current clinical practice. This cannot be stressed enough in prediction models where medicolegal and cultural differences may play a major role.

PURPOSE

The authors aimed to investigate the generalizability of the US citizens prediction model SORG to a Taiwanese patient cohort.

STUDY DESIGN

Retrospective study at a large academic medical center in Taiwan.

PATIENT SAMPLE

Of 1,316 patients who were 20 years or older undergoing initial operative management for lumbar disc herniation between 2010 and 2018.

OUTCOME MEASURES

The primary outcome of interest was prolonged opioid prescription defined as continuing opioid prescription to at least 90 to 180 days after the first surgery for lumbar disc herniation at our institution.

METHODS

Baseline characteristics were compared between the external validation cohort and the original developmental cohorts. Discrimination (area under the receiver operating characteristic curve and the area under the precision-recall curve), calibration, overall performance (Brier score), and decision curve analysis were used to assess the performance of the SORG ML algorithm in the validation cohort. This study had no funding source or conflict of interests.

RESULTS

Overall, 1,316 patients were identified with sustained postoperative opioid prescription in 41 (3.1%) patients. The validation cohort differed from the development cohort on several variables including 93% of Taiwanese patients receiving NSAIDS preoperatively compared with 22% of US citizens patients, while 30% of Taiwanese patients received opioids versus 25% in the US. Despite these differences, the SORG prediction model retained good discrimination (area under the receiver operating characteristic curve of 0.76 and the area under the precision-recall curve of 0.33) and good overall performance (Brier score of 0.028 compared with null model Brier score of 0.030) while somewhat overestimating the chance of prolonged opioid use (calibration slope of 1.07 and calibration intercept of -0.87). Decision-curve analysis showed the SORG model was suitable for clinical use.

CONCLUSIONS

Despite differences at baseline and a very strict opioid policy, the SORG algorithm for prolonged opioid use after surgery for lumbar disc herniation has good discriminative abilities and good overall performance in a Han Chinese patient group in Taiwan. This freely available digital application can be used to identify high-risk patients and tailor prevention policies for these patients that may mitigate the long-term adverse consequence of opioid dependence: https://sorg-apps.shinyapps.io/lumbardiscopioid/.

Predicting persistent opioid use after surgery using electronic health record and patient-reported data

BACKGROUND

More than 100 million surgeries take place annually in the United States, and more than 90% of surgical patients receive an opioid prescription. A sizable minority of these patients will go on to use opioids long-term, contributing to the national opioid epidemic.

METHODS

The objective of this study was to develop and validate a model to predict persistent opioid use after surgery. Participants included surgical patients (≥18 years old) enrolled in a cohort study at an academic medical center between 2015 and 2018. Persistent opioid use was defined as filling opioid prescriptions in postdischarge days 4 to 90 and 91 to 180. Predictors included electronic health record data, state prescription drug monitoring data, and patient-reported measures. Three models were developed: a full, a restricted, and a minimal model using a derivation and validation cohort.

RESULTS

Of 24,040 patients, 4,879 (20%) experienced persistent opioid use. In the validation cohort, the full, restricted, and minimal model had C-statistics of 0.87 (95% CI 0.86-0.88), 0.86 (0.85-0.88), and 0.85 (0.84-0.87), respectively. All models performed better among patients with preoperative opioid use compared to opioid-naive patients (P < .001). The models slightly overpredicted risk in the validation cohort. The net benefit of using the restricted model to refer patients for preoperative counseling was 0.072 to 0.092, which is superior to evaluating no patients (net benefit of 0) or all patients (net benefit of -0.22 to -0.63).

CONCLUSION

This study developed and validated a prediction model for persistent opioid use using accessible data resources. The models achieved strong performance, outperforming prior published models.

Peri-Operative Pain and Opioid Use in Opioid-Naïve Patients Following Inpatient Head and Neck Surgery

Pain management is an important consideration for Head and Neck Cancer (HNC) patients as they are at an increased risk of developing chronic opioid use, which can negatively impact both quality of life and survival outcomes. This retrospective cohort study aimed to evaluate pain, opioid use and opioid prescriptions following HNC surgery. Participants included patients undergoing resection of a head and neck tumor from 2019-2020 at a single academic center with a length of admission (LOA) of at least 24 h. Exclusion criteria were a history of chronic pain, substance-use disorder, inability to tolerate multimodal analgesia or a significant post-operative complication. Subjects were compared by primary surgical site: Neck (neck dissection, thyroidectomy or parotidectomy), Mucosal (resection of tumor of upper aerodigestive tract, excluding oropharynx), Oropharyngeal (OP) and Free flap (FF). Average daily pain and total daily opioid consumption (as morphine milligram equivalents, MME) and quantity of opioids prescribed at discharge were compared. A total of 216 patients met criteria. Pain severity and daily opioid consumption were comparable across groups on post-operative day 1, but both metrics were significantly greater in the OP group on the day prior to discharge (DpDC) (5.6 (1.9-8.6), p < 0.05; 49 ± 44 MME/day, p < 0.01). The quantity of opioids prescribed at discharge was associated with opioid consumption on the DpDC only in the Mucosal and FF groups, which had longer LOA (6-7 days) than the Neck and OP groups (1 day, p < 0.001). Overall, 65% of patients required at least one dose of an opioid on the DpDC, yet 76% of patients received a prescription for an opioid medication at discharge. A longer LOA (aOR = 0.82, 95% CI: 0.63-0.98) and higher Charlson Comorbidity Index (aOR = 0.08, 95% CI: 0.01-0.48) were negatively associated with receiving an opioid prescription at the time of discharge despite no opioid use on the DpDC, respectively. HNC patients, particularly those with shorter LOA, may be prescribed opioids in excess of their post-operative needs, highlighting the need the for improved pain management algorithms in this patient population. Future work aims to use prospective surveys to better define post-operative and outpatient pain and opioid requirements following HNC surgery.

The opioid epidemic from the acute care hospital front line

Prescription opioid use has risen steeply for over two decades, driven primarily by advocacy for better management of chronic non-cancer pain, but also by poor opioid stewardship in the management of acute pain. Inappropriate prescribing, among other things, contributed to the opioid 'epidemic' and striking increases in patient harm. It has also seen a greater proportion of opioid-tolerant patients presenting to acute care hospitals. Effective and safe management of acute pain in opioid-tolerant patients can be challenging, with higher risks of opioid-induced ventilatory impairment and persistent post-discharge opioid use compared with opioid-naive patients. There are also increased risks of some less well known adverse postoperative outcomes including infection, earlier revision rates after major joint arthroplasty and spinal fusion, longer hospital stays, higher re-admission rates and increased healthcare costs. Increasingly, opioid-free/opioid-sparing techniques have been advocated as ways to reduce patient harm. However, good evidence for these remains lacking and opioids will continue to play an important role in the management of acute pain in many patients.Better opioid stewardship with consideration of preoperative opioid weaning in some patients, assessment of patient function rather than relying on pain scores alone to assess adequacy of analgesia, prescription of immediate release opioids only and evidence-based use of analgesic adjuvants are important. Post-discharge opioid prescribing should be contingent on an assessment of patient risk, with short-term only use of opioids. In partnership with pharmacists, nursing staff, other medical specialists, general practitioners and patients, anaesthetists remain ideally positioned to be involved in opioid stewardship in the acute care setting.

Clinical Practice Guideline: Opioid Prescribing for Analgesia After Common Otolaryngology Operations

OBJECTIVE

Opioid use disorder (OUD), which includes the morbidity of dependence and mortality of overdose, has reached epidemic proportions in the United States. Overprescription of opioids can lead to chronic use and misuse, and unused narcotics after surgery can lead to their diversion. Research supports that most patients do not take all the prescribed opioids after surgery and that surgeons are the second largest prescribers of opioids in the United States. The introduction of opioids in those with OUD often begins with prescription opioids. Reducing the number of extra opioids available after surgery through smaller prescriptions, safe storage, and disposal should reduce the risk of opioid use disorder in otolaryngology patients and their families.

PURPOSE

The purpose of this specialty-specific guideline is to identify quality improvement opportunities in postoperative pain management of common otolaryngologic surgical procedures. These opportunities are communicated through clear actionable statements with explanation of the support in the literature, evaluation of the quality of the evidence, and recommendations on implementation. Employing these action statements should reduce the variation in care across the specialty and improve postoperative pain control while reducing risk of OUD. The target patients for the guideline are any patients treated for anticipated or reported pain within the first 30 days after undergoing common otolaryngologic procedures. The target audience of the guideline is otolaryngologists who perform surgery and clinicians who manage pain after surgical procedures. Outcomes to be considered include whether the patient has stopped using opioids, has disposed of unused opioids, and was satisfied with the pain management plan.The guideline addresses assessment of the patient for OUD risk factors, counseling on pain expectations, and identifying factors that can affect pain duration and/or severity. It also discusses the use of multimodal analgesia as first-line treatment and the responsible use of opioids. Last, safe disposal of unused opioids is discussed.This guideline is intended to focus on evidence-based quality improvement opportunities judged most important by the guideline development group. It is not a comprehensive guide on pain management in otolaryngologic procedures. The statements in this guideline are not intended to limit or restrict care provided by clinicians based on their experiences and assessments of individual patients.

ACTION STATEMENTS

The guideline development group made strong recommendations for the following key action statements: (3A) prior to surgery, clinicians should identify risk factors for opioid use disorder when analgesia using opioids is anticipated; (6) clinicians should advocate for nonopioid medications as first-line management of pain after otolaryngologic surgery; (9) clinicians should recommend that patients (or their caregivers) store prescribed opioids securely and dispose of unused opioids through take-back programs or another accepted method.The guideline development group made recommendations for the following key action statements: (1) prior to surgery, clinicians should advise patients and others involved in the postoperative care about the expected duration and severity of pain; (2) prior to surgery, clinicians should gather information specific to the patient that modifies severity and/or duration of pain; (3B) in patients at risk for OUD, clinicians should evaluate the need to modify the analgesia plan; (4) clinicians should promote shared decision making by informing patients of the benefits and risks of postoperative pain treatments that include nonopioid analgesics, opioid analgesics, and nonpharmacologic interventions; (5) clinicians should develop a multimodal treatment plan for managing postoperative pain; (7) when treating postoperative pain with opioids, clinicians should limit therapy to the lowest effective dose and the shortest duration; (8A) clinicians should instruct patients and caregivers how to communicate if pain is not controlled or if medication side effects occur; (8B) clinicians should educate patients to stop opioids when pain is controlled with nonopioids and stop all analgesics when pain has resolved; (10) clinicians should inquire, within 30 days of surgery, whether the patient has stopped using opioids, has disposed of unused opioids, and was satisfied with the pain management plan.

Perioperative Pain Management in Ambulatory and Inpatient Shoulder Surgery

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Acetaminophen is an effective addition to a multimodal pain regimen; however, evidence to support intravenous versus oral administration requires further evaluation.

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While nonsteroidal anti-inflammatory drugs are a valuable addition to a multimodal pain strategy, concerns regarding their effect on healing after certain procedures (i.e., rotator cuff repair) in select patients may preclude their use.

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The use of perioperative gabapentinoids have varied results for pain control, and additional research is warranted to support their use after certain shoulder procedures.

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Opioid-prescribing should be limited and reserved for severe postoperative pain. When prescribed, opioids should be taken at the lowest possible dose and for the shortest period.

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Centrally acting analgesics such as tramadol have been shown to be as effective as opioids and have a lower risk of complications.

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Nerve blocks are an excellent addition to multimodal pain management strategies. Longer-lasting formulations of perioperative single-shot injections and indwelling catheters may reduce rebound pain.

An international multidisciplinary consensus statement on the prevention of opioid-related harm in adult surgical patients

This international multidisciplinary consensus statement was developed to provide balanced guidance on the safe peri-operative use of opioids in adults. An international panel of healthcare professionals evaluated the literature relating to postoperative opioid-related harm, including persistent postoperative opioid use; opioid-induced ventilatory impairment; non-medical opioid use; opioid diversion and dependence; and driving under the influence of prescription opioids. Recommended strategies to reduce harm include pre-operative assessment of the risk of persistent postoperative opioid use; use of an assessment of patient function rather than unidimensional pain scores alone to guide adequacy of analgesia; avoidance of long-acting (modified-release and transdermal patches) opioid formulations and combination analgesics; limiting the number of tablets prescribed at discharge; providing deprescribing advice; avoidance of automatic prescription refills; safe disposal of unused medicines; reducing the risk of opioid diversion; and better education of healthcare professionals, patients and carers. This consensus statement provides a framework for better prescribing practices that could help reduce the risk of postoperative opioid-related harm in adults.

Comparison of the Stopping Opioids after Surgery (SOS) score to preoperative morphine milligram equivalents (MME) for prediction of opioid prescribing after lumbar spine surgery

BACKGROUND CONTEXT

Reliable estimation of the likelihood for prolonged postoperative opioid use may aid targeted interventions for high-risk patients. Previous studies have recommended differing methodologies for prediction of sustained postoperative opioid use.

PURPOSE

To compare the performance of the Stopping Opioids after Surgery (SOS) score and preoperative morphine milligram equivalents (MME) for postoperative opioid prescription exposure in a contemporary cohort of lumbar surgery patients.

PATIENT SAMPLE

Adult patients undergoing posterior decompression with or without fusion for degenerative lumbar conditions between January 31, 2016 and May 31, 2019.

STUDY DESIGN/SETTING

Retrospective review at two academic medical centers and three community hospitals.

OUTCOME MEASURES

The primary outcome was sustained postoperative prescription opioid exposure at 3 months and 6 months. Reoperations and readmissions were considered secondarily.

METHODS

The Stopping Opioids after Surgery score and MME were assigned to patients based on data from their preoperative surgical evaluation. Performance for both measures was assessed for all outcomes by discrimination, including c-statistic and receiver-operating curve analysis. Calibration of the low, medium and high-risk strata with the observed rates of postoperative adverse events were examined.

RESULTS

Overall, 4,165 patients were included in this study. Preoperative prevalence of prescription opioid use was 31%. Rates of postoperative opioid prescriptions at 3 months and 6 months, were 3.3% (n=136) and 1.5% (n=61). The c-statistics of preoperative oral MME and SOS score for 3-month sustained opioid prescriptions were 0.64 and 0.78, respectively. The c-statistics of preoperative oral MME and SOS score for 6-month sustained opioid prescriptions were 0.64 and 0.82, respectively. C-statistics of preoperative oral MME and SOS score were much lower for reoperation and readmission, although SOS score outperformed MME for both outcomes.

CONCLUSIONS

The SOS score clinically outperformed oral MME as a predictive measure for outcomes following lumbar spine surgery. The SOS score may be valuable for identifying individuals at high-risk for sustained prescription opioid use and associated adverse events following spine surgery.

Chronic Opioid Therapy: A Scoping Literature Review on Evolving Clinical and Scientific Definitions

The management of chronic noncancer pain (CNCP) with chronic opioid therapy (COT) is controversial. There is a lack of consensus on how COT is defined resulting in unclear clinical guidance. This scoping review identifies and evaluates evolving COT definitions throughout the published clinical and scientific literature. Databases searched included PubMed, Embase, and Web of Science. A total of 227 studies were identified from 8,866 studies published between January 2000 and July 2019. COT definitions were classified by pain population of application and specific dosage/duration definition parameters, with results reported according to PRISMA-ScR. Approximately half of studies defined COT as "days' supply duration >90 days" and 9.3% defined as ">120 days' supply," with other days' supply cut-off points (>30, >60, or >70) each appearing in <5% of total studies. COT was defined by number of prescriptions in 63 studies, with 16.3% and 11.0% using number of initiations or refills, respectively. Few studies explicitly distinguished acute treatment and COT. Episode duration/dosage criteria was used in 90 studies, with 7.5% by Morphine Milligram Equivalents + days' supply and 32.2% by other "episode" combination definitions. COT definitions were applied in musculoskeletal CNCP (60.8%) most often, and typically in adults aged 18 to 64 (69.6%). The usage of ">90 days' supply" COT definitions increased from 3.2 publications/year before 2016 to 20.7 publications/year after 2016. An increasing proportion of studies define COT as ">90 days' supply." The most recent literature trends toward shorter duration criteria, suggesting that contemporary COT definitions are increasingly conservative. PERSPECTIVE: This study summarized the most common, current definition criteria for chronic opioid therapy (COT) and recommends adoption of consistent definition criteria to be utilized in practice and research. The most recent literature trends toward shorter duration criteria overall, suggesting that COT definition criteria are increasingly stringent.

Duration and Dosage of Opioids After Spine Surgery: Implications on Outcomes at 1 Year

STUDY DESIGN

Longitudinal Cohort Study OBJECTIVE.: The aim of this study was to determine whether duration of postoperative opioids is associated with long-term outcomes, and if initial postoperative opioid dosage is associated with opioid cessation after spine surgery.

SUMMARY OF BACKGROUND DATA

Preoperative opioid use is associated with poor outcomes, but little evidence exists regarding the implications of opioid dosage and duration after spine surgery.

METHODS

Data from our state's prescription drug database was linked to our prospective clinical spine registry to analyze opioid dispensing and outcomes in elective surgical spine patients between 2010 and 2017. Patients were stratified based on preoperative chronic opioid use and multivariable regression was used to assess associations between duration of postoperative opioids and outcomes at one year, including satisfaction, chronic opioid use, and meaningful improvements in pain, disability, and quality of life. In a secondary aim, a Cox proportional hazards model was used to determine whether initial postoperative opioid dosage was associated with time to opioid cessation.

RESULTS

Of 2172 patients included, 35% had preoperative chronic opioid use. In patients without preoperative chronic opioid use, a postoperative opioid duration of 31 to 60 days was associated with chronic opioid use at 1 year (adjusted odds ratio [aOR]: 4.1 [1.7-9.8]) and no meaningful improvement in extremity pain (aOR: 1.8 [1.3-2.6]) or axial pain (aOR: 1.6 [1.1-2.2]); cessation between 61 and 90 days was associated with no meaningful improvement in disability (aOR: 2 [1.3-3]) and dissatisfaction (aOR:1.8 [1-3.1]). In patients with preoperative chronic opioid use, postoperative opioids for ≥90 days was associated with dissatisfaction. Cox regression analyses showed lower initial postoperative opioid dosages were associated with faster opioid cessation in both groups.

CONCLUSION

Our results suggest that a shorter duration of postoperative opioids may result in improved 1-year patient-reported outcomes, and that lower postoperative opioid dosages may lead to faster opioid cessation.

LEVEL OF EVIDENCE

2.

Long-Term Opioid Prescriptions After Spine Surgery: A Meta-Analysis of Prevalence and Risk Factors

BACKGROUND

Opioids are frequently prescribed for back pain, but the prevalence of and risk factors for long-term opioid use after spine surgery were not clearly reported. We conducted a systematic review and meta-analysis to summarize the evidence for long-term opioid use (>90 days) among adults who underwent spine surgery.

METHODS

PubMed, EMBASE, and Cochrane indexing databases were searched until November 9, 2018 for studies reporting the prevalence of and risk factors for long-term opioid use after spine surgery. Separate meta-analyses were conducted for commercial claims databases or registries (claims/registries) and nonclaims observational studies using the random-effects model to estimate the pooled odds ratio (OR). Prevalence meta-analysis was performed in a clinically homogeneous subset of these patients who underwent lumbar spine surgery.

RESULTS

Eight claims and 5 nonclaims were meta-analyzed to avoid double-counting participants. The meta-analysis showed that preoperative opioid users (OR, 5.59; 95% confidence interval [CI], 3.37-9.27 vs. OR 4.21; 95% CI, 2.72-6.51) and participants with preexisting depression and/or anxiety (OR, 1.86, 95% CI, 1.43-2.42 and OR, 1.20; 95% CI, 0.83-1.74, respectively) had a statistically significantly higher odds of long-term postoperative opioids, compared with their peers. Males showed lower odds of long-term postoperative opioid use in the claims group (OR, 0.85; 95% CI, 0.79-0.92), but not in the nonclaims group (OR, 0.99; 95% CI, 0.71-1.39). The pooled prevalence of post-lumbar spine surgery long-term opioid use was 63% (95% CI, 50%-74%) in claims and 47% (95% CI, 38%-56%) in nonclaims.

CONCLUSIONS

Patients undergoing spine surgery represent a high-risk surgical population requiring special attention and targeted interventions, with the strongest evidence for those treated with opioids before surgery and those with psychiatric comorbidities.

Predicting prolonged opioid prescriptions in opioid-naïve lumbar spine surgery patients

IMPORTANCE

Preoperative determination of the potential for postoperative opioid dependence in previously naïve patients undergoing elective spine surgery may facilitate targeted interventions.

OBJECTIVE

The purpose of this study was to develop supervised machine learning algorithms for preoperative prediction of prolonged opioid prescription use in opioid-naïve patients following lumbar spine surgery.

DESIGN

Retrospective review of clinical registry data. Variables considered for prediction included demographics, insurance status, preoperative medications, surgical factors, laboratory values, comorbidities, and neighborhood characteristics. Five supervised machine learning algorithms were developed and assessed by discrimination, calibration, Brier score, and decision curve analysis.

SETTING

One healthcare entity (two academic medical centers, three community hospitals), 2000 to 2018.

PARTICIPANTS

Opioid-naïve patients undergoing decompression and/or fusion for lumbar disk herniation, stenosis, and spondylolisthesis.

MAIN OUTCOME

Sustained prescription opioid use exceeding 90 days after surgery.

RESULTS

Overall, of 8,435 patients included, 359 (4.3%) were found to have prolonged postoperative opioid prescriptions. The elastic-net penalized logistic regression achieved the best performance in the independent testing set not used for algorithm development with c-statistic=0.70, calibration intercept=0.06, calibration slope=1.02, and Brier score=0.039. The five most important factors for prolonged opioid prescriptions were use of instrumented spinal fusion, preoperative benzodiazepine use, preoperative antidepressant use, preoperative gabapentin use, and uninsured status. Individual patient-level explanations were provided for the algorithm predictions and the algorithms were incorporated into an open access digital application available here: https://sorg-apps.shinyapps.io/lumbaropioidnaive/.

CONCLUSION AND RELEVANCE

The clinician decision aid developed in this study may be helpful to preoperatively risk-stratify opioid-naïve patients undergoing lumbar spine surgery. The tool demonstrates moderate discriminative capacity for identifying those at greatest risk of prolonged prescription opioid use. External validation is required to further support the potential utility of this tool in practice.