Off-Label Drug Use in the Pediatric Cardiac Intensive Care Unit
Bibliographic record
Abstract
Off-label drug use in pediatrics has challenged the U.S. Food and Drug Administration (FDA). Historically, pharmaceutical companies have been willing to fund pediatric safety and efficacy trials but only for medications with a large market (vaccines and antibiotics). In the field of pediatric cardiac intensive care, the small number of patients and the widely varying physiologies challenge prospective clinical drug trials. There is a limited, if any, return on investment for the pharmaceutical company. However, in the past decade, there has been an increase in pediatric safety and efficacy trials as a result of the 1997 FDA Modernization Act (FDAMA) that was extended in 2002 under the Best Pharmaceutical for Children Act. The FDAMA allows companies performing an FDA-approved pediatric drug trial to extend their patent for an additional six months. Unfortunately, even well-run exclusivity clinical trials under the FDAMA do not necessarily result in a FDA-approved pediatric drug label. An example is milrinone, that has been shown to decrease low cardiac output syndrome in young infants following biventricular repair but remains off-label. Of perhaps greater challenge are drugs that are available in generic form (dopamine for example), where the incentives of the FDAMA do not apply. Maltz and associates, in a study published in this issue of World Journal for Pediatric and Congenital Heart Surgery, investigated off-label drug use in a pediatric cardiac intensive care unit (PCICU). They found that 36% of the prescribed drugs were off-label, with 94% of the patients receiving at least one off-label drug and 46% of the patients receiving greater than three off-label drugs. This is an important educational point, as most practitioners are likely unaware of which pharmaceutical agents are FDA approved for pediatrics. Not surprising, patients at higher risk were shown to receive more medications and more off-label medications. Other publications have described the off-label drug use in pediatric anesthesia and intensive care and in hospitalized children with congenital and acquired heart disease. Offlabel drug use is not confined to the pediatric critical care population but has also been described in adult critical care units. The report by Maltz and associates offers a description of the frequency of off-label drug use in one PCICU. It is important to discount any conclusion that off-label drug use was a causative factor for increased length of stay. Increased length of stay has been shown to be a surrogate for complexity of disease and intensity of care. In the study by Maltz and associates, there are far too many risk variables that were not included in the analysis. In addition, the number of patients enrolled in their study was small. It is primarily an observational study. The descriptive analysis does not control for severity of illness and complexity of disease. One should not conclude that the off-label drug use was unsafe or contributed to harm. The field of pediatric cardiac critical care has evolved since its infancy three decades ago. Due in part to advancements in pharmaceutical options, survival following neonatal heart surgery has improved, hospital length of stay has become shorter, and our ability to recover a patient from a significant event has improved. Many drugs used in pediatric cardiac critical care are brought into our environment through the expertise of other specialties (pediatric critical care, neonatology, adult critical care, anesthesiology), with modifications in their dosage and indications over time. A current example is the rapidly increasing use of dexmedetomidine, despite limited trials evaluating dose ranging or efficacy, complications, or potential drug interactions. Thus, safety and efficacy for many drugs used in pediatric cardiac critical care are a result of years of experience rather than clinical trials. The use of off-label medications is to benefit the individual patient, and the FDA is very clear that practitioners are able to use their professional judgment to determine these uses. Offlabel drug use is therefore common in both pediatric and adult critical care settings. Does this mean patients are at risk? There is no plausible data to support such a contention. Obviously, we all want to prescribe drugs that have been adequately tested so that we understand their safety and efficacy. We also want protection from litigation if there is an adverse event perceived to be related to off-label use of a medication. How do we get this data? Clinical trials are the gold standard for changes in
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".