Midodrine therapy for vasopressor dependent shock in the intensive care unit: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Intensive care unit (ICU) lengths of stay are modified by ongoing need for haemodynamic support in critically ill patients. This is most commonly provided by intravenous vasopressor therapy. Midodrine has been used as an oral agent for haemodynamic support in patients with orthostatic hypotension or cirrhosis. However, its efficacy in treating shock in the ICU, particularly for patients weaning from intravenous vasopressors, remains uncertain. The objective of this systematic review is to determine the efficacy of midodrine in vasopressor dependent shock. METHODS AND ANALYSIS: We will search Ovid MEDLINE, Ovid Embase, CINAHL and Cochrane Library for observational trials and randomised controlled trials evaluating midodrine in critically ill patients from inception to 21 April 2022. We will also review unpublished data and relevant conference abstracts. Outcomes will include ICU length of stay, duration of intravenous vasopressor support, ICU mortality, hospital mortality, hospital length of stay and rates of ICU readmission. Data will be analysed in aggregate, where appropriate. We will evaluate risk of bias using the modified Cochrane tool and certainty of evidence using Grading of Recommendations, Assessment, Development and Evaluations methodology. We will perform trial sequential analysis for the outcome of ICU length of stay. ETHICS AND DISSEMINATION: Ethics approval is not required as primary data will not be collected. Findings of this review will be disseminated through peer-related publication and will inform future clinical trials. PROSPERO REGISTRATION NUMBER: CRD42021260375.
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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 | 0.048 | 0.075 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.024 | 0.030 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.042 | 0.004 |
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".