Anatomical complexity does not predict outcomes after COVID-19 in adults with congenital heart disease
Bibliographic record
Abstract
Few could have guessed the global devastation of COVID-19 when it was first reported more than a year ago. Community spread has been a major route of transmission as COVID-19 has a lower case fatality rate (2.3%) but much greater infectivity compared with previous outbreaks (severe acute respiratory syndrome, 2002–2003; Middle Eastern respiratory syndrome, 2012–ongoing).1 Most patients experienced mild infection (81%), while 5% developed critical illness.1 Risk factors for death that have been identified include age, disease severity and comorbidities such as cardiovascular disease, diabetes, hypertension, chronic respiratory disease and cancer.1 Patients with congenital heart disease (CHD) were perceived to be especially vulnerable to infection due to their fragile physiology, particularly those with moderate to severe complex anatomy such as repaired tetralogy of Fallot, status post atrial or arterial switch procedure or Fontan circulation.2 3 Data to quantify this risk have been limited—until now. In this issue of Heart , Schwerzmann et al 4 describe the clinical course of 105 patients with CHD with COVID-19 infection, based on either a positive biochemical test (by PCR or ELISA) or strong clinical suspicion (based on symptoms and chest CT findings). This was a collaboration between 25 centres in nine countries, as part of the European Collaboration for Prospective Outcome research in Congenital Heart Disease. It is the largest multicentre cohort study thus far and the first publication of its kind. The authors aimed to identify patient characteristics associated with ‘complicated’ infection, which they defined as either death or hospitalisation requiring non-invasive/invasive ventilation and/or inotropic support after COVID-19 infection. In total, 73/105 patients (70%) had mild disease, while 13 patients (12%) experienced a complicated infection (online supplemental table S1). At study conclusion, 91 patients (87%) had recovered; 9 cases (9%) were ongoing; and 5 patients (5%) had died. Two …
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".