Evidence map›Paper›PMID 31800063›Full record

ArticlePain medicine (Malden, Mass.)2020

Geospatial Analyses of Pain Intensity and Opioid Unit Doses Prescribed on the Day of Discharge Following Orthopedic Surgery.

Patrick Tighe, François Modave, MaryBeth Horodyski, Matthew Marsik, G Lipori, Roger Fillingim, Hui Hu, Jennifer Hagen

Open access · bronzeAbstract read
In one paragraph

Article in Pain medicine (Malden, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Article
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

8 authors at 4 institutions in 1 country.

Patrick TigheDepartments of Anesthesiology.
François ModaveHealth Outcomes and Biomedical Informatics.
MaryBeth HorodyskiOrthopaedics and Rehabilitation, University of Florida College of Medicine, Gainesville, Florida.
Matthew MarsikData Science and Planning, University of Florida Health, Gainesville, Florida.
G LiporiData Science and Planning, University of Florida Health, Gainesville, Florida.
Roger FillingimPain Research & Intervention Center of Excellence, University of Florida, Gainesville, Florida.
Hui HuDepartment of Epidemiology, University of Florida College of Medicine, Gainesville, Florida, USA.
Jennifer HagenOrthopaedics and Rehabilitation, University of Florida College of Medicine, Gainesville, Florida.
Florida College · USUniversity of Florida · USUniversity of Florida Health · USHealth Outcomes Solutions (United States) · US

Funding

University of Florida Older Americans Independence Center (OAIC)P30AG028740 · NIA · UNIVERSITY OF FLORIDA · PI Peihua Qiu · 2007 to 2026
$22.8M
Finding Good TEMporal PostOperative pain Signatures (TEMPOS)R01GM114290 · NIGMS · UNIVERSITY OF FLORIDA · PI TIGHE, PATRICK J · 2015 to 2019
$2.5M
NIA NIH HHS P30 AG028740NIGMS NIH HHS R01 GM114290
6 · The paper itself

Abstract

objectiveInappropriate opioid prescribing after surgery contributes to opioid use disorder and risk of opioid overdose. In this cross-sectional analysis of orthopedic surgical patients, we examined the role of patient location on postoperative pain intensity and opioids prescribed on hospital discharge.

methodsWe used geospatial analyses to characterize spatial patterns of mean pain intensity on the day of discharge (PiDoD) and opioid units prescribed on the day of discharge (OuPoD), as well as the effect of regional social deprivation on these outcomes.

resultsAt a 500-km radius from the surgery site, the Global Moran's I for PiDoD (2.71 × 10-3, variance = 1.67 × 10-6, P = 0.012) and OuPoD (2.19 × 10-3, SD = 1.87, variance = 1.66 × 10-6, P = 0.03) suggested significant spatial autocorrelation within each outcome. Local indicators of spatial autocorrelation, including local Moran's I, Local Indicator of Spatial Autocorrelation cluster maps, and Getis-Ord Gi* statistics, further demonstrated significant, specific regions of clustering both OuPoD and PiDoD. These spatial patterns were associated with spatial regions of area deprivation.

conclusionsOur results suggest that the outcomes of pain intensity and opioid doses prescribed exhibit varying degrees of clustering of patient locations of residence, at both global and local levels. This indicates that a given patient's pain intensity on discharge is related to the pain intensity of nearby individuals. Similar interpretations exist for OuPoD, although the relative locations of hot spots of opioids dispensed in a geographic area appear to differ from those of hot spots of pain intensity on discharge.

Indexed as

Analgesics, OpioidOrthopedic ProceduresCross-Sectional StudiesHumansPatient DischargePostoperative PainPractice Patterns, Physicians'Analgesics, OpioidClusteringGeospatialOpioidOrthopedicPainSpatial AutocorrelationSurgery

Identifiers

PMID31800063
PMCPMC7530566
OpenAlexW2993789484

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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.