Clinical evaluation of the intestinal microcirculation using sidestream dark field imaging – Recommendations of a round table meeting
Bibliographic record
Abstract
INTRODUCTION: In clinical setting, Sidestream Dark Field (SDF) imaging has provided unprecedented insights into the gut microcirculation mainly by studying the intestinal mucosa of patients with ileostomies. Visualizing microvascular structure and function of ileal mucosa at the bedside brings unique opportunity for clinical research, particularly in critically ill patients. Several papers that were focused on intestinal microcirculation, used different methods of assessment because an accepted scoring systems does not exist so far and it is no surprise that it is rather difficult to compare the results from these studies. The present paper presents recommendations concerning specific aspects of image acquisition and proposes some parameters for the description of the intestinal microcirculation in human studies, as suggested by the participants of a round table meeting. METHODS: The round table meeting participants reviewed all relevant literature, discussed various aspects of image acquisition by SDF technology in patients with ileostomy and parameters for the description of intestinal mucosa microcirculation. Selected key conditions for high quality and reproducible image recordings were identified. To evaluate quality of intestinal microcirculation, selected parameters and scoring system were suggested and described. RESULTS: For image acquisition in ileostomies, five key points were proposed: optimal timing, optimal SDF device probe positioning, optimal stabilization, optimal number and length of acquired video recordings, and optimal avoidance of pressure artefacts. With regard to image analysis, simplified set of quantitative and qualitative parameters for the description of the intestinal mucosa microcirculation for the clinical studies has been proposed: vessels per villus, microvascular flow index, proportion of perfused villi, and borders of villi. The proposed parameters can be included in a semi-quantitative scoring system; however, this scoring system needs further validation. This simplified analysis does not require sophisticated software and can be performed manually on the video screen. CONCLUSION: We propose a simple methodology for image acquisition and suggest specific microvascular parameters to analyze SDF imaging studies of the intestinal mucosa microcirculation in patients with ileostomy. Proposed scoring system needs to be validated in further clinical studies.
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 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 | 0.017 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.009 |
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".