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Record W2983369390 · doi:10.22605/rrh5348

Klippel–Trénaunay syndrome: a case report of a rare vascular disorder identified in a rural Canadian hospital

2019· article· en· W2983369390 on OpenAlexaboutno aff
Kaan Yilmaz, Lauren Smithson

Bibliographic record

VenueRural and Remote Health · 2019
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsnot available
Fundersnot available
KeywordsKlippel-Trenaunay syndromeMedicineFamily medicinePediatricsSurgerySoft tissue

Abstract

fetched live from OpenAlex

CONTEXT: Klippel-Trénaunay syndrome (KTS) is a very rare congenital vascular anomaly. It is characterized by the presence of capillary malformation, venous malformation as well as limb overgrowth, generally affecting one extremity. Although clinical characteristics of KTS are well known, the epidemiology and pathophysiology still remain to be defined. Awareness of these disorders is important for rural physicians for managing potential complications. ISSUE: A 60-year-old male presented with symptomatic varicosities and chronic venous insufficiency of the left leg. The patient had a history of several episodes of ulceration and thrombophlebitis on the left side. Physical examination revealed extensive varicosities and a large port-wine stain on the lateral side of the left leg, despite a previous ligation of the saphenofemoral junction. The left leg was circumferentially larger than the right leg. Additional investigations were conducted to rule out arterial disorders and confirm the venous nature of the abnormalities. The patient was clinically diagnosed with KTS and his varicosities were treated surgically using phlebectomy with stab avulsion technique. LESSONS LEARNED: KTS is a distinct entity that belongs to the vascular malformations group. In a rural practice, identification and accurate diagnosis are challenging, as these patients often require a multidisciplinary approach and do not present until later in the course of the condition. An understanding of the correct nomenclature and associated complications is imperative for proper assessment and management in rural and remote settings.

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 score0.373
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.005
GPT teacher head0.244
Teacher spread0.239 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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