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Impact of an Outpatient Appendectomy Protocol on Clinical Outcomes and Cost: A Case-Control Study

2010· article· en· W2121528167 on OpenAlexaff
Luc Dubois, Kelly Vogt, Ward Davies, Christopher M. Schlachta

Bibliographic record

VenueJournal of the American College of Surgeons · 2010
Typearticle
Languageen
FieldMedicine
TopicAppendicitis Diagnosis and Management
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineEmergency departmentAppendicitisComplicationComorbiditySurgeryAcute appendicitisEmergency medicineProtocol (science)General surgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although elective outpatient surgery is commonplace, surgeons remain hesitant to discharge patients the same day after emergent surgery. We created a formal protocol to select patients for early discharge after laparoscopic appendectomy for acute appendicitis, and we assessed its safety and potential cost savings. STUDY DESIGN: We matched patients who were discharged early from the recovery room with similar patients from a control group on the basis of age ± 3 years, presence or absence of a comorbidity, laparoscopic procedure, and nonperforated appendicitis; we compared them to assess the impact of early discharge on morbidity, return visits to the emergency room, and total cost incurred by our institution. RESULTS: During the first year of our protocol, 72 of 161 (45%) patients who presented with acute appendicitis and underwent appendectomy were discharged early, with a median post-operative length of stay of 4.7 hours. When compared with matched controls, patients discharged early had similar complication rates (4.3% early group vs 7.1%, p = 0.72) and number of postoperative visits to the emergency room (11.4% vs 11.4%, p = 0.8), but had a reduced median length of stay (4.7 vs 16.2 hours, p < 0.001) and an average reduction in cost of $323.46 per patient. CONCLUSIONS: Adoption of a protocol to select patients for early discharge after laparoscopic appendectomy resulted in a 45% reduction in the need for in-hospital beds, with no negative impact on return visits to the emergency room or number of complications. This translates to an approximate savings of $323 per patient when compared with standard care.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.398
Teacher spread0.366 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations72
Published2010
Admission routes1
Has abstractyes

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