Evidence map›Paper›PMID 41216290›Full record

ArticleOTA international : the open access journal of orthopaedic trauma2025

Can weather patterns predict orthopaedic trauma volume: a retrospective review at a level 1 trauma center in the Northeast.

Christina M Melian, Deepika R Kothakapa, Alvarho J Guzman, Ernesto M Acosta, Patrick J Huang, Paul P Hospodar

Abstract read
In one paragraph

Article in OTA international : the open access journal of orthopaedic trauma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Christina M MelianDepartment of Orthopaedic Surgery, Albany Medical Center, Albany, NY.ORCID https://orcid.org/0000-0003-4440-2346
Deepika R KothakapaAlbany Medical College, Albany, NY.
Alvarho J GuzmanAlbany Medical College, Albany, NY.
Ernesto M AcostaDepartment of Orthopaedic Surgery, Albany Medical Center, Albany, NY.
Patrick J HuangDepartment of Orthopaedic Surgery, Albany Medical Center, Albany, NY.
Paul P HospodarDepartment of Orthopaedic Surgery, Albany Medical Center, Albany, NY.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To analyze the effect of weather on orthopaedic trauma volume to allocate hospital resources more judiciously. Design: Retrospective review. Setting: Albany Medical Center, a level 1 trauma center in the Northeast. Patients/Participants: All orthopaedic trauma consults placed from July 1, 2022 to June 31, 2023, excluding spine consults. Main Outcome Measures: Patient demographics, total number of consults, total number of orthopaedic injuries, type of consult (inpatient vs. outpatient), type of injury, mechanism of injury, nonorthopaedic injuries, and weather conditions (temperature, wind, rainfall, and snowfall). Results: A total of 4,097 patients (4,664 injuries) were seen during this 1-year period. Of these patients, 74% were treated inpatient, 44% required operative intervention, and 17% sustained a nonorthopaedic injury. Consult volume was significantly higher during the weekends of summer months (May‒August), positively correlating with higher temperatures ( Conclusions: Orthopaedic consult volume positively correlates with summer months, warmer temperature, and lack of precipitation. Snow and wind conditions do not affect orthopaedic consult volume. The findings of this study support the need for increased staffing and resources during these expected times of heightened trauma volume. Level of Evidence: 3.

Indexed as

orthopaedic traumaweather

Identifiers

PMID41216290
PMCPMC12591706

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Registered trials

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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.