The trilateral link between anaesthesia, perioperative visual loss and Flammer syndrome
Bibliographic record
Abstract
BACKGROUND: A variety of factors have been linked to perioperative visual loss during or directly after nonocular and ocular surgeries. Prolonged immobilization, biochemical factors and hemodynamic instability have been discussed as factors in the pathogenesis of this devastating complication. Perioperative visual loss in four consecutive patients, all featuring Flammer syndrome, is reported herein. To our knowledge, we present the first case series, which associates perioperative visual loss with Flammer syndrome. We assume that a low perfusion pressure, disturbed autoregulation of the ocular blood flow and altered drug sensitivity in such subjects, play significant role in the pathogenesis of this dreaded complication. CASES PRESENTATION: We analysed the medical records of four consecutive patients with permanent perioperative visual loss and complemented our findings with additional history taking and clinical examinations. A variety of tests was performed, including colour Doppler ultrasonography of the retroocular vessels, static and dynamic retinal vessel analysis. The visual loss was unilateral in three patients and bilateral in one. An extensive review of published perioperative vision loss cases was conducted. All four patients were male Caucasians, and exhibited prominent signs and symptoms of Flammer syndrome. The visual loss originated from a propensity for unstable ocular blood flow, combined with hyperreactivity toward pharmacological stimuli, leading together to disturbed autoregulation of the blood supply, and subsequently - to ocular hypoxia. An identified intrinsic hypoperfusion diathesis was a crucial pathophysiologic link in all of the patients. Other, yet unknown systemic or local factors may also be involved in this process. CONCLUSIONS: A review of numerous publications of perioperative visual loss and our data, support our hypothesis for a novel pathophysiologic model and incorporate Flammer syndrome as a distinct risk factor for paradoxical visual loss, during nonocular and ocular surgeries, or invasive procedures. To prevent the complications produced by disturbed blood flow autoregulation in such patients, guidelines for screening and tailored preoperative approach are given.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".