The impact of PICCO monitoring on traumatic shock: a systematic review and meta-analysis
Bibliographic record
Abstract
Purpose: This study aims to provide a systematic review and meta-analysis of Pulse Indicator Continuous Cardiac Output (PICCO) compared with conventional central venous pressure (CVP) monitoring in the treatment of traumatic shock. Methods: A systematic literature retrieval was conducted in databases including PubMed, Web of Science, Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI) from database inception to October 22, 2024. Keywords such as "PICCO," "traumatic shock," and "hemorrhagic shock" were used. Retrieved studies were screened according to pre-determined inclusion and exclusion criteria. The methodological quality and risk of bias were assessed using the Newcastle-Ottawa Scale (NOS) for cohort studies and the Cochrane "risk of bias" tool for randomized controlled trials (RCTs). Outcomes, including mortality, duration of mechanical ventilation, and length of ICU stay, were extracted and meta-analyzed. Results: A total of 15 studies comprising 1,188 patients were included, with 597 monitored by PICCO and 591 by routine CVP. The risk of bias was assessed as low for all studies. PICCO-monitored patients showed a significantly shorter duration of mechanical ventilation compared to the control group [SMD in random effects model: -1.66; 95% CI: (-2.38, -0.94)]. However, no significant differences were found in mortality or length of ICU stay. Conclusion: PICCO monitoring can improve the prognosis of traumatic shock patients by shortening the duration of mechanical ventilation, but it does not significantly affect mortality or length of ICU stay. Given the limitations of the included studies, further exploration is warranted to verify these conclusions.
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 | 0.042 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.040 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".