Evidence map›Paper›PMID 36753170›Full record

ArticleJAMA surgery2023

Implementation and Assessment of No Opioid Prescription Strategy at Discharge After Major Urologic Cancer Surgery.

Badar M Mian, Zorawar Singh, Kevin Carnes, Leanne Lorenz, Paul Feustel, Ronald P Kaufman, Svetlana Avulova, Adrien Bernstein, Theodore Cangero, Hugh A G Fisher

Open access · greenAbstract read
In one paragraph

Article in JAMA surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
5.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 20 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Badar M MianDepartment of Urology, Albany Medical Center, Albany, New York.
Zorawar SinghDepartment of Urology, Albany Medical Center, Albany, New York.
Kevin CarnesDepartment of Urology, Albany Medical Center, Albany, New York.
Leanne LorenzDepartment of Surgery, Albany Medical Center, Albany, New York.
Paul FeustelDepartment of Urology, Albany Medical Center, Albany, New York.
Ronald P KaufmanDepartment of Urology, Albany Medical Center, Albany, New York.
Svetlana AvulovaDepartment of Urology, Albany Medical Center, Albany, New York.
Adrien BernsteinDepartment of Urology, Albany Medical Center, Albany, New York.
Theodore CangeroDepartment of Information Services, Albany Medical Center, Albany, New York.
Hugh A G FisherDepartment of Urology, Albany Medical Center, Albany, New York.
Albany Medical Center Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Postoperative opioid prescriptions are associated with delayed recovery, perioperative complications, opioid use disorder, and diversion of overprescribed opioids, which places the community at risk of opioid misuse or addiction. Objective: To assess a protocol for eliminating postdischarge opioid prescriptions after major urologic cancer surgery. Design, Setting, and Participants: This cohort study of the no opioid prescriptions at discharge after surgery (NOPIOIDS) protocol was conducted between May 2017 and June 2021 at a tertiary referral center. Patients undergoing open or minimally invasive radical cystectomy, radical or partial nephrectomy, and radical prostatectomy were sorted into the control group (usual opioids), the lead-in group (reduced opioids), and the NOPIOIDS group (no opioid prescriptions). Interventions: The NOPIOIDS group received a preadmission educational handout, postdischarge instructions for using nonopioid analgesics, and no routine opioid prescriptions. The lead-in group received a postdischarge instruction sheet and reduced opioid prescriptions at prescribers' discretion. The control group received opioid prescriptions at prescribers' discretion. Main Outcomes and Measures: Primary outcome measures included rate and dose of opioid prescriptions at discharge and for 30 days postdischarge. Additional outcome measures included patient-reported pain and satisfaction level, unplanned health care utilization, and postoperative complications. Results: Of 647 opioid-naive patients (mean [SD] age, 63.6 [10.0] years; 478 [73.9%] male; 586 [90.6%] White), the rate of opioid prescriptions at discharge for the control, the lead-in, and the NOPIOIDS groups was 80.9% (157 of 194), 57.9% (55 of 95), and 2.2% (8 of 358) (Kruskal-Wallis test of medians: P < .001), and the overall median (IQR) tablets prescribed was 14 (10-20), 4 (0-5.3), and 0 (0-0) per patient in the control, lead-in, and NOPIOIDS groups, respectively (Kruskal-Wallis test of medians: P < .001). In the NOPIOIDS group, median and mean opioid dose was 0 tablets for all procedure types, with the exception of kidney procedures (mean [SD], 0.5 [1.7] tablets). Patient-reported pain surveys were received from 358 patients (72.6%) in the NOPIOIDS group, demonstrating low pain scores (mean [SD], 2.5 [0.86]) and high satisfaction scores (mean [SD], 86.6 [3.8]). There was no increase in postoperative complications in the group with no opioid prescriptions. Conclusions and Relevance: This perioperative protocol, with emphasis on nonopioid alternatives and patient instructions, may be safe and effective in nearly eliminating the need for opioid prescriptions after major abdominopelvic cancer surgery without adversely affecting pain control, complications, or recovery.

Indexed as

Opioid-Related DisordersUrologic NeoplasmsAftercareAnalgesics, OpioidCohort StudiesDrug PrescriptionsFemaleHumansMaleMiddle AgedPatient DischargePostoperative PainPractice Patterns, Physicians'Analgesics, Opioid

Identifiers

PMID36753170
PMCPMC9909575
OpenAlexW4319461323

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.