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Record W1979180101 · doi:10.1097/prs.0b013e3181a3f29f

Blindness, a Rare Complication of Liposuction: Report of a Case of Unilateral Blindness; Notes on the Effect of Compassionate Care

2009· article· en· W1979180101 on OpenAlexaboutno aff
Iraj Zandi

Bibliographic record

VenuePlastic & Reconstructive Surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicBody Contouring and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCentral retinal arteryLiposuctionSurgeryRetinal Artery OcclusionCentral retinal artery occlusionOphthalmic arteryOphthalmologyRadiologyVisual acuityRetinal

Abstract

fetched live from OpenAlex

Care more particularly for the individual patient than for the special features of the disease. —William Osler (Canadian physician, 1849–1919) Sir: Approximately 2 years ago, at my accredited surgery facility, a 58-year-old woman underwent abdominoplasty and liposuction of the waistline and hips under general anesthesia in the supine position. During the 3-hour operation, 3400 ml of tumescent solution was injected, a total of 1700 ml of fat was suctioned, and 900 g of dermofat from the abdominal wall was removed. During the operation, vital signs remained within normal limits. In the recovery room, the patient complained of blurred vision that was dismissed by the recovery room nurse as the effect of general anesthesia and the use of eye lubricant during surgery. On the fifth day postoperatively, I received a call from the emergency room of the local hospital by an ophthalmologist who had seen the patient for blindness of the left eye caused by central retinal artery occlusion. Doppler study of the carotid artery, brain magnetic resonance imaging, and magnetic resonance angiography were all within normal limits, with minimal plaque in the carotid artery. No patent foramen ovale was found. All consultants agreed that the most probable cause of central retinal artery occlusion was an embolus from carotid artery plaque, even though it was minimal. There have been two other reported cases of blindness (one unilateral and one bilateral) following liposuction.1,2 In both cases, blindness was attributable to anterior ischemic optic neuropathy after liposuction. As to the possible early detection of blindness as a result of surgery, I would like to suggest that recovery room nursing staff must take complaints of visual changes earnestly and perform a basic visual acuity and confrontational visual field testing. Even though by the time diagnosis is made, the 90-minute “golden period” may have expired, recovery of vision 24 hours after the injury has been reported. The second and probably more important subjectin the article is the effect of a compassionate surgeon on the patient's well-being and physician's liability. In my case, I believe there are several reasons why no malpractice claims were made. Most important was that the patient sensed my genuine concern. Immediately upon her diagnosis of blindness, she was admitted to the hospital for a complete medical workup. I accepted all of her expenses not covered by the insurance carrier. I made all of the arrangements to have her seen by the best authorities in the field. It is true that performing these actions might have backfired and given the impression that I performed them out of guilt. However, recognizing when and how to perform these “hand holdings” is by itself an art that is so critical in patient care. DISCLOSURE The author has no financial interest to disclose in relation to the content of this article. Iraj Zandi, M.D. 2557 Mowry Avenue, Suite 20 Fremont, Calif. 94538 [email protected]

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.002
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 head0.021
GPT teacher head0.269
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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
Published2009
Admission routes1
Has abstractyes

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