Multimodal Monitoring for Hemodynamic Categorization and Management of Pediatric Septic Shock
Bibliographic record
Abstract
OBJECTIVES: To evaluate the cardiovascular aberrations using multimodal monitoring in fluid refractory pediatric septic shock and describe the clinical characteristics of septic myocardial dysfunction. DESIGN: Prospective observational study of patients with unresolved septic shock after infusion of 40 mL/kg fluid in the first hour. SETTING: Two tertiary care referral Indian PICUs. PATIENTS: Patients aged 1 month to 16 years who had fluid refractory septic shock. INTERVENTIONS: Changes in therapy were based on findings of clinical assessment, bedside echocardiography, and invasive blood pressure monitoring within 6 hours of recognition of septic shock. MEASUREMENTS AND MAIN RESULTS: Over a 4-year period, 48 patients remained in septic shock despite at least 40 mL/kg fluid infusion. On clinical examination, 21 patients had cold shock and 27 had warm shock. Forty-one patients (85.5%) had vasodilatory shock on invasive blood pressure; these included 14 patients who initially presented with cold shock. The commonest echocardiography findings were impaired left ± right ventricular function in 19 patients (39.6%) and hypovolemia in 16 patients (33%). Three patients who had normal myocardial function on day 1 developed secondary septic myocardial dysfunction on day 3. Echocardio graphy, along with invasive arterial pressure monitoring, allowed fluid, inotropy, and pressors to be titrated more precisely in 87.5% of patients. Shock resolved in 46 of 48 patients (96%) and 44 patients (91.6%) survived to discharge. CONCLUSION: Bedside echocardiography provided crucial information leading to the recognition of septic myocardial dysfunction and uncorrected hypovolemia that was not apparent on clinical assessment. With invasive blood pressure monitoring, echocardiography affords a simple noninvasive tool to determine the cause of low cardiac output and the physiological basis for adjustment of therapy in patients who remain in shock despite 40 mL/kg fluid.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".