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Record W4281391638 · doi:10.14639/0392-100x-n1837

Treatment for parotid abscess: a systematic review

2022· review· en· W4281391638 on OpenAlexaff
Alberto Maria Saibene, Fabiana Allevi, Tareck Ayad, Jérôme R. Lechien, Miguel Mayo-Yáñez, Krzysztof Piersiala, Carlos M. Chiesa‐Estomba

Bibliographic record

VenueActa Otorhinolaryngologica Italica · 2022
Typereview
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineHumanitiesGynecologyArt

Abstract

fetched live from OpenAlex

A parotid abscess is a dangerous complication of parotitis. In this study, we aimed to define current treatment concepts for parotid abscess, focusing on different management options. The authors performed a PRISMA-compliant systematic review across multiple databases including all original studies published until January 2021 focusing on treatment of parotid abscess. Studies specifying treatment modalities and treatment success rates were included based on abstract and full-text selection. The authors assessed study quality, demographics, success rates, management modalities and adverse events. Among 1,318 citations, 18 studies met our inclusion criteria. Twelve studies relied only on incision and drainage with antibiotic therapy; the remaining 6 compared different treatment modalities (incision and drainage versus exclusive medical therapy or ultrasound-guided drainage). Heterogeneity between studies precluded meta-analysis of data. The review showed that antibiotics remain the mainstay of treatment for parotid abscess. Conversely, the role of incision and drainage, and aspiration should be studied further. The higher rate of complications following incision and drainage suggests a more conservative approach is needed. Incision and drainage remain the main salvage option for conservative treatment failures.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.736
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.119
GPT teacher head0.376
Teacher spread0.257 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueActa Otorhinolaryngologica ItalicaSame topicSalivary Gland Tumors Diagnosis and TreatmentFrench-language works237,207