Clinical and hemodynamic factors in predicting response to fluid challenge during right heart catheterization
Bibliographic record
Abstract
Fluid challenge during right heart catheterization has been used for unmasking pulmonary hypertension (PH) related to left-sided heart disease. We evaluated the clinical and hemodynamic factors affecting the response to fluid challenge and investigated the role of fluid challenge in the classification and management of PH patients. We reviewed the charts of 67 patients who underwent fluid challenge with a baseline pulmonary arterial wedge pressure (PAWP) of ≤ 18 mmHg. A positive fluid challenge (PFC) was defined as an increase in PAWP to > 18 mmHg after 500 mL saline infusion. Clinical characteristics and echocardiographic and hemodynamic parameters were compared between PFC and negative fluid challenge (NFC). PFC was associated with female sex, increased BMI, and hypertension. A greater rise in PAWP was observed in PFC (6.8 ± 2.3 vs. 3.8 ± 2.7 mmHg, P = 0.001). A larger increase in PAWP correlated with a lower transpulmonary gradient (r = -0.42, P < 0.001), diastolic pulmonary gradient (r = -0.42, P < 0.001), and pulmonary vascular resistance (r = -0.38, P < 0.001). We found 100% of the patients with PFC were classified as WHO group 2 PH compared to 49% of the NFC patients ( P < 0.001). Fewer patients with PFC were started on advanced PH therapies and more were discharged from PH clinic. A PFC and the magnitude of PAWP increase after saline loading are associated with parameters related to left heart disease. In our population, fluid challenge appeared to influence the classification of PH and whether patients are started on therapy or discharged from clinic.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".