Developing and Implementing a Patient-Centered Opioid Prescribing Algorithm among Gynecological Oncology Patients

Abstract

Background:

The opioid epidemic is a public health crisis. However, opioid prescription recommendations have not been established in gynecological oncology, and guidelines that incorporate patient-reported pain are lacking.

Objectives:

The article aims to evaluate prescribing patterns, utilization, and patient-reported pain control in gynecological oncology patients at a large tertiary academic center.

Methods:

This was a two-phase, prospective cohort study. For Phase 1, patients undergoing hysterectomy through the gynecological oncology division at the University of New Mexico were enrolled. Postoperative opioid use was collected and standardized to oral morphine milligram equivalents (MMEs). The factors associated with outpatient opioid use were used to develop an opioid prescription algorithm. In Phase 2, we evaluated the implementation of the prescription algorithm. For both phases, patients completed a demographic survey, satisfaction survey, and validated pain questionnaires.

Results:

In Phase 1, the amount of opioids used was significantly lower than the amount of opioids prescribed. Factors that correlated with postoperative opioid use included surgical procedures and last 24-hour inpatient MME use. A standardized opioid prescription algorithm was developed by incorporating these factors. In Phase 2, the opioid prescribing algorithm there was no significant difference in pain scores between the two phases.

Conclusions:

Opioids were substantially overprescribed in gynecological oncology patients undergoing hysterectomy. Our study found that the surgical route and last 24-hour MME inpatient usage were reliable predictors of outpatient opioid use. We developed and implemented a standardized opioid prescription algorithm that was validated by comparing the pain control measures in the two phases.

Introduction

The opioid epidemic in the United States is a prominent health crisis that continues to worsen. In 2020, the U.S. Department of Health estimated that more than 91,000 individuals died of an overdose-related death. In addition, the age-adjusted overdose death rate increased by about 31% from 2019 to 2020.^1,2 Many patients’ first exposure to opioid medications is for postoperative pain, indicating that surgeons play a vital role in the opioid crisis. For many surgical specialties, there is both a wide variation in prescribing practices and overprescribing of opioid medications.^3,4 In an evaluation of common general surgery procedures, there was a large range in the opioid prescriptions for the same procedure and many studies revealed overprescribing tendencies.^5,6

Opioid use and misuse are significant public health concerns in women.⁷ The Centers for Disease Control and Prevention (CDC) estimates that 18 women die every day of an opioid overdose in the United States alone, and gynecological oncologists have a unique challenge in caring for these women, including balancing not only postoperative pain control but also cancer-related pain and palliative care indications.⁸ Studies have shown that gynecological oncologists commonly overprescribe opioids.⁹ Multiple studies have implemented more restrictive opioid prescription protocols after gynecological surgery, traditionally stratifying prescriptions by type of surgery.^10,11 However, there is still little knowledge of the patient-specific characteristics that determine postoperative opioid use and how patients’ perception of their pain is associated with opioid use. Furthermore, many of these studies have been completed with a majority of white patients, and the external validity of these algorithms in other practice settings remains unclear.

Optimization of opioid prescription practices is particularly pertinent to women in New Mexico (NM). NM is one of the most ethnically diverse areas in the United States, with a large proportion of Hispanic and Native American populations. NM is a very rural state, with 32 of the 33 counties qualifying as medically underserved.¹² In addition, NM has an overdose death rate that is 41% higher than the national average.^8,9 The unique qualities of the state contribute to distinct challenges in access and safe opioid prescribing.

The ongoing opioid crisis and its impact on gynecological oncology patients, especially in more vulnerable patient populations, highlight the need for further study of safe and effective prescribing patterns.¹³ In addition, patient-reported outcomes are becoming increasingly important in providing patient-centered care. We developed our study with the overall objective of gaining a better understanding of the current prescription, utilization patterns, and patient-reported pain control for gynecological oncology surgery patients in a pragmatic clinical setting within a large tertiary academic center in NM. Specifically, the study was divided into two phases as follows: (1) the development of an opioid-prescribing algorithm and (2) the implementation of the algorithm.

Materials and Methods

We performed a two-phase prospective cohort study of patients who underwent hysterectomy at the University of New Mexico (UNM) through the Gynecological Oncology Division. This study was approved by the Institutional Review Board of the University of New Mexico. The inclusion criteria for this study were patients undergoing a hysterectomy procedure with the UNM gynecological oncology service, female sex, at least 18 years of age, English and/or Spanish speaking, and opioid-naïve status (defined as having no history of opioid use within 30 days of their scheduled procedure). Patients with a history of opioid use were excluded from this study, defined as a history of opioid use disorder or recent opioid use in the last 30 days noted during standardized screening of the electronic medical record and confirmed during enrollment with research staff.

Phase 1: Development phase

The goals of Phase 1 were to quantify the amount of opioids prescribed and used and to identify factors that were predictive of postoperative opioid usage. These data indicate the need for the development of a standardized opioid prescription algorithm. For this first phase, based on a review of surgical case numbers through the gynecological oncology division, a preliminary power analysis estimated that by recruiting at least 50 patients and assuming that half of them require fewer opioids than prescribed, the true proportion of patients requiring fewer opioids than prescribed would be within 36–64% with 95% confidence interval. The patients were enrolled between January 2021 and July 2021. Providers approached eligible patients regarding their interest in the study before their surgical date. If interested, research staff described the study overview and details to the patients including the purpose of evaluating pain control after surgery. They were also given medication diaries with detailed instructions on how to complete them. Due to significant safety concerns during the COVID-19 pandemic, patients were electronically sent virtual consent for participation. Subsequently, the patients underwent planned operative procedures and hospital admission. They were discharged with postoperative pain prescriptions dictated by their provider and instructed on how to complete their 2- and 6-week medication diaries to document usage of pain medications, including opioids, Tylenol, ibuprofen, and gabapentin.

The Patient-Reported Outcomes Measurement Information System (PROMIS) is a collection of validated instruments that assess physical, social, and mental well-being in patients.^12,14 The collection of PROMIS pain-specific questionnaires describes how pain affects the patient’s daily life and activities, and has been utilized in the postoperative setting. The PROMIS Physical Function SF and Pain Interference Questionnaires are two validated questionnaires measuring patient-reported physical activity and pain in the preceding 7 days. At the 1–2-week postoperative visit, patients completed a demographic survey, a patient satisfaction survey, and two PROMIS questionnaires. In addition, the research coordinator reviewed the patients’ medication diaries and documented their pain medication use. At the 4–6-week postoperative visit, the patients again completed the PROMIS questionnaires and reviewed their medication diaries for pain medication usage. Participants received compensation at both their 2- and 6-week postoperative visits for their participation in the study.

The electronic medical records of each patient were reviewed to obtain information regarding their surgery and postoperative stay, including patient demographics, comorbidities, surgical approach, surgical procedure, operative time, estimated blood loss, intraoperative and postoperative complications, length of hospital stay, use of epidural/transversus abdominis plane (TAP) block, and type and stage of cancer diagnosis. Inpatient opioid use was collected and standardized by conversion to oral morphine milligram equivalents (MMEs). The number and type of opioids prescribed at discharge were collected, along with the rate of naloxone prescription.

Descriptive statistics and medians with interquartile ranges (IQR) were used to quantify opioid prescription and utilization patterns in MME. Wilcoxon rank-sum tests were used to compare opioid requirements by surgical route. Nonparametric statistical methods (either Spearman correlations or Wilcoxon rank-sum tests for continuous or categorical variables, respectively) were used to identify factors associated with outpatient opioid use. Finally, using these significant factors as well as the 95th percentile of outpatient opioid use, an algorithm for future opioid prescription was created. The 95th percentile was utilized to maintain low-level PROMIS pain scores while still reducing opioid prescriptions overall.

Phase 2: Implementation phase

The goal of Phase 2 was to assess the feasibility of implementing the opioid prescription algorithm and compare the PROMIS pain scores between the two phases. Given that the primary outcome of the second phase was the feasibility of implementation, a power calculation was not performed for Phase 2 and the study intended to enroll 40 patients. The patients were enrolled between February 2022 and August 2022. The enrollment and consent process were similar with additional information including that the second cohort’s purpose was to evaluate a new process of prescribing postoperative pain medications and that their opioid prescription would be determined by a new algorithm.

At the time of hospital discharge after the planned operative procedure, patients were administered an opioid prescription based on a standardized opioid prescription algorithm as well as additional informational handouts about opioid use. At the patient’s 1–2-week postoperative visit, the patients completed a demographic survey, a patient satisfaction survey, and the two PROMIS questionnaires, similar to Phase 1. Participants received a $10 merchandise card at their 2-week postoperative visit. The electronic medical records were reviewed for the same variables collected in Phase 1. Additional information, including adherence to the standardized opioid prescription algorithm, additional opioid prescriptions sent, and the percentage of same-day discharges, was obtained.

Similar descriptive statistics were obtained as in Phase 1. To assess the feasibility of the algorithm implementation, Wilcoxon rank-sum tests were used to compare PROMIS T-scores between the two study cohorts. All statistical analyses were performed using SAS 9.4 (Cary, NC).

Results

Phase 1: Development phase

From January 2021 to July 2021, 65 women were recruited in Phase 1, with 60 completing the follow-up data collection (Supplementary Fig. S1). Patient demographic and clinical characteristics in both phases are described in Table 1. The average age of the enrolled patients was 56 years and the average body mass index (BMI) was 33. 78% of the patients identified as white, 19% were identified as American Indian/Alaska Native (AI/AN), and 3.8% were identified as other. There were also a wide variety of health insurance types. In addition, approximately 50% of the patients had previous abdominal surgery. In addition, the surgical approach for cases was relatively even, with 51% of patients undergoing an open procedure and 48% undergoing an Minimally Invasive Surgery (MIS) procedure. All patients in this cohort were admitted for at least one night in the hospital, with an average hospital stay of 2.4 days.

Table 1.

Demographic and Clinic Characteristics of Participants in Each Study Cohort

	Phase 1, n = 60 ^a	Phase 2, n = 40 ^a	p value^b
Demographic characteristics
Age	56 (46, 62)	60 (48, 64)	0.2
Ethnicity			0.14
American Indian or Alaska Native	10 (19%)	10 (26%)
Asian or Pacific Islander	1 (1.9%)	1 (2.6%)
Black or African American	1 (1.9%)	—
Other	0 (0%)	3 (7.7%)
White	42 (78%)	25 (64%)
BMI	33 (26, 39)	33 (29, 37)	>0.9
Marital status			0.087
Partnered	5 (8.5%)	3 (7.5%)
Divorced	4 (6.8%)	3 (7.5%)
Married	22 (37%)	24 (60%)
Single	22 (37%)	10 (25%)
Widowed	6 (10%)	—
Health Insurance			0.3
BCBS	9 (15%)	5 (12%)
HIS	9 (15%)	7 (18%)
Medicaid	14 (23%)	8 (20%)
Medicare	8 (13%)	7 (18%)
Other	10 (17%)	10 (25%)
Self-pay	10 (17%)	3 (7.5%)
Tobacco use			0.2
No	40 (67%)	31 (78%)
Yes	20 (33%)	9 (22%)
Clinic characteristics
ECOG score			0.4
0	50 (85%)	37 (92.5%)
1	9 (15%)	3 (7.5%)
Prior Abdominal Surgery			0.2
Laparoscopic abdominal surgery	15 (25%)	5 (12.5%)
None	28 (47%)	18 (45%)
Open abdominal surgery	17 (28%)	17 (42.5%)
Surgical approach			0.057
Laparoscopic	2 (3.3%)	2 (5%)
Open	29 (48%)	10 (25%)
Robotic assisted	29 (48%)	28 (70%)
Anesthesia			0.4
GET	37 (62%)	20 (50%)
GET + ESP	7 (12%)	4 (10%)
GET + TAP	16 (27%)	16 (40%)
Estimated Blood Loss, mL	150 (100, 300)	50 (50, 112)	0.004
Hospital Stay in Days	2 (1, 3)	1 (0, 2)	<0.001
Started on gabapentin while inpatient?			0.001
No	42 (71%)	38 (97%)
Yes	17 (29%)	1 (2.6%)
Cancer			0.2
No	30 (50%)	14 (37%)
Yes	30 (50%)	24 (63%)

n (%); Median (IQR).

Pearson’s Chi-squared test; Wilcoxon rank sum test.

BCBS, Blue Cross Blue Shield; ECOG, Eastern Cooperative Oncology Group Performance Status; GET, General Endotracheal; TAP, Transabdominal plane; ESP, Erector Spinae Plane.

The number of outpatient opioids prescribed and used was lower in the MIS group than in the open surgery group (p = 0.011 and p = 0.045, respectively). In the MIS group, the median (interquartile range) prescribed opioids was 38 MME (IQR 21, 75 MME), equivalent to five pills of 5 mg oxycodone. The median usage was 4 MME (IQR 0, 22), equivalent to one pill of 5 mg oxycodone. For the open group, 96 MME were prescribed (IQR 38, 150), equivalent to 20 pills, while 31 MME were used (IQR 0, 82), equivalent to five pills. A comparison of the prescribed and used MMEs is shown in Figure 1. Notably, 24 patients (42%) did not use opioids as outpatients.

FIG. 1.

Phase 1 MME prescribed vs used by the surgical route. MME, morphine milligram equivalent.

In the univariate analysis, factors that correlated with postoperative opioid use included surgical approach, the amount of opioids taken during the last 24 hours as inpatients, tobacco use, and patient’s BMI. For the multivariate analysis, after adjusting for confounders, higher inpatient MME use was associated with a higher outpatient requirement, which was statistically significant. Univariate and multivariate analyses are presented in Table 2.

Table 2.

Patient and Clinic Factors Correlated with Outpatient Opioid Use from Phase 1

Variables	Univariate analysis			Multivariable analysis
Variables	β	95% CI	p value	β	95% CI	p value
Age	−0.047	−0.096, 0.002	0.059	−0.031	−0.071, 0.009	0.14
BMI	−0.072	−0.135, −0.009	0.026	−0.052	−0.112, 0.007	0.091
Surgical approach			0.076
Minimally invasive	Ref	Ref		Ref	Ref
Open	1.197	−0.124, 2.518		0.179	−1.259, 1.617	0.8
Last 24-hour MME used during hospital stay	0.082	0.050, 0.113	<0.001	0.067	0.038, 0.095	<0.001
Hospital stay in days	0.258	0.025, 0.490	0.03	0.196	−0.011, 0.404	0.069
Smoke cigarette			0.077
No	Ref	Ref
Yes	2.883	−0.314, 6.080
Prior abdominal surgery			>0.9
Laparoscopic abdominal surgery	Ref	Ref
None	0.174	−1.073, 1.421
Open abdominal surgery	−0.077	−1.484, 1.331
Estimated blood loss	0.000	−0.002, 0.003	0.7
Blood transfusion required			0.4
No	Ref	Ref
Yes	1.442	−1.652, 4.536
Uterine Weight > 250 g			0.5
No	Ref	Ref
Yes	0.41	−0.885, 1.705
Diagnosed with cancer			>0.9
No	Ref	Ref
Yes	0.068	−1.030, 1.166

CI, confidence interval; Ref, reference category.

For Phase 1, the PROMIS interference pain ratings revealed that 73% of the patients had mild to within normal limits in their pain rating at 2 weeks, which increased to 91% at 6 weeks (Supplementary Figs. S3 and Figs. S4). In the patient satisfaction surveys, 81% of patients felt prepared for surgery and 85% of patients reported that a healthcare professional talked to them about pain control. 82% of patients rated their overall satisfaction with the preoperative process as 9/10 or greater.

Finally, incorporating the surgical approach, 24-hour inpatient MME usage, and 95 percentile of outpatient MME usage, a standardized opioid prescribing algorithm was developed, as shown in Figure 2.

FIG. 2.

Opioid prescribing algorithm in gynecological oncology for patients undergoing hysterectomy. MME, morphine milligram equivalent.

Phase 2: Implementation phase

From February 2022 to August 2022, 40 patients were enrolled in Phase 2, with 34 patients completing the study (Supplementary Fig. S2). Compared with Phase 1, there were no statistically significant differences between the demographics of the two cohorts. Clinically, there was a significant difference in the estimated blood loss and the number of hospital stays between the two groups. Phase 2 had a larger variation in the surgical route with 25% open and 75% MIS, although this was not statistically significant (p = 0.057).

For Phase 2, the inpatient MME requirement was slightly higher for both MIS and open procedures. Of note, of the patients undergoing MIS (n = 30), 53% had same-day discharges (n = 16), while no patients underwent same-day discharge in Phase 1. Opioid use in both study cohorts is shown in Table 3.

Table 3.

Patterns of Opioid Prescription and Use by Surgical Route in Each Study Cohort

	Phase 1			Phase 2
	Surgical route			Surgical route
	Minimally invasive, n = 31 ^a	Open, n = 29 ^a	p value^b	Minimally invasive, n = 30 ^a	Open, n = 10 ^a	p value^b
Inpatient MME usage	17 (7, 26)	57 (30, 76)	<0.001	22 (15, 41)	92 (62, 201)	0.005
Last 24 hours MME	7.5 (6, 16)	8 (0, 22.5)	0.6	15 (11, 15)	8 (8, 15)	0.15
MME prescribed for outpatient use^c	38 (21, 75)	112 (38, 150)	0.004
Outpatient MME usage^c	4 (0, 22)	31 (0, 82)	0.025

n (%); Median (IQR).

Wilcoxon rank sum test.

One of the goals in Phase 1 was to quantify patterns of outpatient opioid prescription and use and therefore these statistics were captured only in Phase 1.

MME, morphine milligram equivalent.

In Phase 2, 93% of the patients received the correct prescription based on the algorithm. Five patients (13%) received an additional opioid prescription during the postoperative period; however, three of these five patients were noted to have a postoperative complication that facilitated the additional prescription. Of the patients, 64.6% had mild to within normal limits pain ratings at 2 weeks (Supplementary Fig. S5). Most notably, there was no significant difference in PROMIS T-scores between the two study cohorts at two weeks (median [IQR]: 57 [53,62]) (Table 4).

Table 4.

PROMIS Pain Rating by Study Cohort

	Cohort 1, n = 59 ^a	Cohort 2, n = 34 ^a	p value^b
T Score	57 (53, 62)	57 (54, 63)	>0.9
Rating			0.2
Within normal limit	23 (39%)	11 (32%)
Mild	12 (20%)	11 (32%)
Moderate	19 (32%)	12 (35%)
Severe	5 (8.5%)	0 (0%)

n (%); Median (IQR).

Pearson’s Chi-squared test; Wilcoxon rank sum test.

PROMIS, Patient-Reported Outcomes Measurement Information System.

Discussion

In this two-phase prospective study, opioids were overprescribed by 52% of gynecological oncology patients undergoing hysterectomy in Phase 1, and 42% of patients did not use any opioids in the postoperative period. These findings highlight that overprescription is an ongoing problem in gynecological oncology. Our findings further support the need for better tools to individualize opioid prescriptions to balance pain control and safety. This study also suggested that opioid use by patients was sufficient for adequate pain control. There was a statistically significant difference in opioid usage for open versus minimally invasive procedures and the multivariate regression revealed that in addition to the surgical route, the last 24 hours MME usage inpatient was associated with outpatient MME usage, facilitating the development of a standardized opioid prescribing protocol. Finally, this study revealed that implementation of the opioid algorithm in phase 2 was feasible at our large academic center and maintained the same acceptable pain rating for patients at their 2-week visit.

Experts in gynecological oncology have expressed a need for more restrictive and standardized opioid prescribing guidelines, and other academic institutions have similarly studied and implemented opioid algorithms. For example, the University of Alabama Birmingham implemented a restrictive opioid prescribing algorithm for gynecological oncology patients undergoing surgery with similar opioid prescriptions and found that approximately 75% of patients were very satisfied with the process.¹⁵ A similar study was performed at the Roswell Park Comprehensive Cancer Center, where an ultra-restrictive opioid prescription protocol was implemented, which also found a significant reduction in opioid prescription without adversely affecting patient pain scores.¹⁶ Other studies of opioid algorithms have further documented the feasibility of reducing opioid prescriptions, and while they have contributed to the feasibility of reducing opioid prescriptions, little is known about implementing these algorithms in more diverse populations.^10,11 Our study is consistent with these previously reported findings but also includes the first opioid prescription algorithm developed from a prospective cohort of actual patient opioid usage. In addition, our study is the first to include a validated pain scoring system and PROMIS surveys to document acceptable pain control with a more restrictive opioid prescription protocol. Finally, our study includes a pragmatic, real-world population with a higher representation of both native and Hispanic/Latinx-identified patients. This study contributes to the generalizability of the use of restrictive opioid prescription practices across different practice settings, which has not been previously studied.

This study affirms that opioids are being overprescribed after hysterectomy, and both the surgical route and inpatient opioid use can be used to implement more restrictive, patient-specific prescribing guidelines. Second, this study demonstrates that this standardized, more restrictive opioid algorithm is easily implemented and effective in decreasing opioid use and maintaining acceptable patient pain scores in a pragmatic clinical setting. While this algorithm was developed in a gynecological oncology patient population, there may be applications for other obstetrics and gynecology surgical procedures; hysterectomies for both benign and oncologic indications are very common procedures, and opioid prescribing techniques are applicable to the benign gynecology population as well.

This study provides a validated way to incorporate patient-centered pain control, which has been emphasized by the CDC as a vital component in combatting the rising opioid epidemic.¹⁷ CDC’s Clinical Practice Guidelines for Prescribing Opioids for Pain also emphasizes providing culturally appropriate care and understanding patients’ different perceptions of pain. Research on effective patient-centered preoperative counseling and a better understanding of pain expectations is also needed to further optimize pain control while minimizing opioid use.

Our study has several strengths. First, it included a two-phase prospective design, which allowed the development and implementation of the algorithm. There was a high retention of patients throughout the postoperative period in both phases. This study also enrolled a heterogeneous population, with 19% and 23% of patients identified as American Indian/Native, and 45% and 32% of patients identified as Hispanic, in Phases I and II, respectively. With enrollment at a large academic tertiary referral center, both the setting and the patient population allow these findings to be generalizable to other hospitals and practices that may serve a similar gynecological oncology patient population that is not always well studied in the literature.

The limitations of our study include the small sample size, with 60 patients completing the final analysis for Phase 1 and 34 patients completing the study for Phase 2. The rate of refusal was different among these two cohorts (27% for Phase 2 vs. 20% for Phase 1), which could have been related to the implementation of the opioid algorithm. However, the demographic and clinical characteristics of the two cohorts were still very similar, with no significant differences except for estimated blood loss, number of days in the hospital, and the addition of gabapentin while inpatient same-day discharges of patients after surgery only occurred in Phase 2 after this practice was implemented in our institution. The practice patterns changed during the course of the study, with an increased number of same-day discharges during the implementation phase, which could have affected the number of days in the hospital. In addition, this could have impacted our ability to accurately assign the correct prescribing amount for this new type of patient experience. However, the same-day discharge patients reported similar overall pain control metrics. With the similar demographic and clinical characteristics of the two cohorts, the second cohort appears well-represented in the patient population of interest, which supports the feasibility of this study.

At our hospital, many aspects of Enhanced recovery after surgery (ERAS) are routinely performed, including multimodal pain control and encouraging early ambulation and feeding. However, there is currently no formalized ERAS protocol that can influence patient opioid utilization.¹⁸ Finally, this study excluded patients with a history of chronic opioid use or a documented opioid use disorder, limiting the applicability of these findings in these patient situations.

Conclusion

In summary, the opioid epidemic is a national concern and a women’s health priority and is particularly relevant for the gynecological oncology community. Providers can have an impact by critically evaluating prescription patterns. Gynecological oncologists are responsible for focusing efforts on improving prescribing practices. Decreasing opioid prescription patterns while maintaining adequate pain control for gynecological oncology patients can help prevent significant morbidity and mortality from opioid misuse.

Footnotes

Acknowledgments

We thank the clinicians, nurses, and students who helped facilitate this study. We also thank the University of New Mexico Comprehensive Cancer Center and the Department of Obstetrics and Gynecology.

Authors’ Contributions

A.C.: Conceptualization, Methodology, Investigation, Visualization, Writing—Original Draft Preparation. L.M.: Investigation, Writing—Original Draft Preparation. J.G.: Investigation, Project Administration. D.K.: Formal Analysis, Data Curation. T.R.: Conceptualization, Methodology, Writing—Review & Editing, Supervision, Funding Acquisition.

Author Disclosure Statement

The authors report no conflict of interest.

Funding Information

This study was funded by the University of New Mexico OBGYN Grant in honor of Henrietta Lacks.

Supplementary Material

Supplementary Figure S1

Supplementary Figure S2

Supplementary Figure S3

Supplementary Figure S4

Supplementary Figure S5

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Supplementary Material

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