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Record W4291732974 · doi:10.1016/j.amsu.2022.104331

The effect of COVID-19 on orthopedic elective/emergency procedures in a tertiary hospital Riyadh Saudi Arabia. A cross-sectional study

2022· article· en· W4291732974 on OpenAlexaboutno aff
Abdulellah Abunayan, Bader Aljadaan, Mohammed Almudayfir, Sayaf H. Alshareef, Abdulaziz alamer

Bibliographic record

VenueAnnals of Medicine and Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineOrthopedic surgeryCoronavirus disease 2019 (COVID-19)Tertiary careElective surgeryTraumatologyPandemicCross-sectional studyEmergency departmentEmergency medicineQuarter (Canadian coin)General surgerySurgeryInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Background: The occurrence of the COVID-19 pandemic in late December 2019 created a worldwide emergency. It affected most surgical subspecialties in many ways. Therefore, we aimed to quantitate the early effect of COVID-19 on elective and emergency orthopedic surgeries. Moreover, to identify the most affected orthopedic subspecialties during this crisis. Materials and methods: Our study was conducted in a tertiary hospital in Saudi Arabia. We included all patients who underwent orthopedic procedures from January 1, 2020 - June 30, 2020, with the same period of 2019 for comparison. Emergency procedures were considered if a patient had an acute fracture, joint dislocation, compartment syndrome, infection, and infected non-union. Results: The impact of procedure cancellation in the early COVID-19 phase was significant. Our department procedures decreased in the 2nd quarter of 2020 by 75.6% from the previous quarter of the same year and 61.1% from the 2nd quarter of 2019. No admission restrictions were made for oncology and trauma patients, though they had a reduction in their cases. The most affected subspecialties in our study were sports medicine, upper limb, arthroplasty, and pediatrics. Conclusion: During the COVID-19 crisis, elective surgeries were held in our hospital and most of Saudi Arabia. Our cohort showed a significant decrease during this period. All subspecialties were affected by elective procedure cancellation, but some were affected more because of the elective nature of their operations, such as sports and upper limb, pediatric, and arthroplasty.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.077
GPT teacher head0.432
Teacher spread0.355 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes1
Has abstractyes

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