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Treatment of intrathoracic anastomotic leak by nose fistula tube drainage after esophagectomy for cancer

2010· article· en· W1936917076 on OpenAlexaff
Zhang Hu, Rong Yin, Xinjuan Fan, Q. Zhang, Chao Feng, Fengfeng Yuan, J. Chen, Feng Jiang, N. Li, Lin Xu

Bibliographic record

VenueDiseases of the Esophagus · 2010
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineEsophagectomySurgeryLeakEsophageal cancerFistulaAnastomosisComplicationNoseMedical recordCancerInternal medicine

Abstract

fetched live from OpenAlex

Esophageal anastomotic leak remains a lethal complication after esophagectomy for cancer. The aim of the present study is to describe an effective new management, nose fistula tube drainage (NFTD), to treat postoperative intrathoracic leaks. From July 2003 to August 2009, 41 of 4132 patients (0.99%) requiring transthoracic esophagectomy for esophageal and cardiac carcinoma had developed an intrathoracic esophageal anastomotic leak in our hospital as well as another three patients with similar conditions from other hospitals, excluding three patients with gastric necrosis (two) and tracheo-esophageal fistula (one); 23 patients were treated by NFTD, and the remaining 18 patients were treated by conventional chest tube drainage (CCTD). Clinical records of these patients were reviewed and analyzed, including the healing of the leak, mortality, and morbidity. In the NFTD group, 4 patients (17.4%) died, 1 patient (4.3%) required reoperation, and 18 patients (78.3%) healed. However, in the CCTD group, 3 patients (16.7%) died, 1 patient (5.5%) required reoperation, and 14 patients (77.8%) healed. As compared with the CCTD group, patients of the NFTD group had a shorter intensive care course (11.95 vs 33.62 days, P= 0.01) and hospital stay (39.74 vs 77.54 days, P= 0.02). Although this novel NFTD management did not significantly decrease mortality when compared with CCTD, it could gain more effective drainage than CCTD and eventually shorten hospital stay.

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)0.000
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 score0.140
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.290
Teacher spread0.283 · 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

Citations26
Published2010
Admission routes1
Has abstractyes

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