Predictors of Acute Hemodynamic Decompensation in Early Sepsis: An Observational Study
Bibliographic record
Abstract
BACKGROUND: The study of sepsis is hindered by its heterogeneous time course and evolution. A subgroup of patients with severe sepsis develops shock soon after the initiation of treatment while others present hypotensive. We sought to determine the incidence of hypotension after the initiation of treatment for sepsis, and characterize their clinical features and course. METHODS: A retrospective review of electronic medical record of all septic patients (n = 542) that met the definition of septic shock within 24 hours of admission (2011 - 2012) at an urban Veteran Affairs Hospital was performed. Subjects either had 1) initial normotension (INT) with hypotension developing within 24 hours or 2) initial hypotension (IH). Logistic regression was used to model associated factors of INT/IH. RESULTS: INT occurred in 62 patients (11%) with average initial blood pressure of 120/71 mm Hg and developed hypotension to 79/48 mm Hg. IH was identified in 52 patients (10%) with average presenting blood pressure of 81/46 mm Hg. INT showed evidence of increased sympathetic tone with significantly higher heart rate, blood pressure and temperature. INT patients were younger, more frequently on alpha-blockers, and more likely septic from pneumonia compared to IH patients. INT and IH patients had similar timing of antibiotic initiation, amount of 24-hour fluid resuscitation, vasopressor use, organ dysfunction and mortality at 28 days. Using alpha-blockers, being Caucasian, and having higher temperatures were independent predictors of INT. CONCLUSION: INT is a distinctive presentation of septic shock characterized by rapid deterioration during early treatment. By further studying this subgroup, mediators of septic shock may be identified that clarify pathophysiology and provide timely targeted treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".