Bibliographic record
Abstract
I read with interest the article entitled: “Cardiac Troponin I in Calves with Congenital Heart Disease” (Suzuki, et al., JVIM, 2012 DOI: 10.1111/j.1939-1676.2012.00953.x).1 This study deals with an understudied area of internal medicine: cardiology in food animals. Adding evidence-based studies is of great importance but can be challenging especially for unfrequent diseases. The authors concluded that the blood levels of cardiac troponin I (cTnI) can be of interest in for diagnosing congenital heart disease (CHD) in calves. They also state that “using a cutoff value of ≥ 0.035 ng/mL, cTnI in plasma may distinguish calves with and without significant CHD with reasonnable sensitivity and specificity.” Designing of diagnostic accuracy studies is challenging not only in veterinary medicine but also in human medicine.2 The case selection of control group to assess the specificity of the cTnI levels needs to be discussed since it may certainly overestimate test accuracy. Using healthy control subjects in case-control studies commonly led to overestimation of diagnostic accuracy compared with cohort study.3 As discussed by the authors, the clinical diagnosis of CHD in calves is challenging without echocardiography since the clinical signs especially cardiac murmur can be found in calves without CHD (anemia, excitement or fever) as well as various signs of respiratory distress. It has been shown that cTnI can be increased in cattle due to various thoracic diseases4, 5 or endotoxemia.6 Such animals may represent a better group to establish the specificity of the diagnostic accuracy of cTnI in calves with heart murmur and CHD to calves with heart murmur due to various cardiorespiratory condition or endotoxemia/sepsis. Another concern that has not been addressed in that study is that the test accuracy has been determined in only 12 cases with various CHD and 19 healthy control animals. With this small sample although the receiver operating characteristic lead to interesting Se/Sp of this test in their sample of calves, the authors did not mention that before doing any inference of their best Se/Sp value of cTnI, they need to calculate the 95% confidence interval (CI) for their values. Such a small sample of animals would lead to a wider imprecision of their Se/Sp estimate to extrapolate to the general population that needs to be known by any clinician attempting to include cTnI determination in their diagnostic workup for suspected calves with CHD. Morerover, determining a threshold (here 0.035 ng/mL) although interesting, needs to be discussed in regard with the method of determination of cTnI. Previous studies in dogs7 have shown that normal ranges should be established for every technique/analyzer used for establishing cTnI levels since difference in the antibodies used in the assays could lead to differences in results obtained with different analyzers. Moving from this point, it is difficult to extrapolate the proposed threshold without comparisons of other point of care cTnI analyzers that could be used in the farm with portative analyzers that may be used for cTnI determination. Finally, despite having a threshold for diagnosing CHD in calves could be interesting, from a practical perspective, it would have been interesting to know if the cTnI values were quite different depending on the exact nature of CHD. The impact of the heart defect on cardiomyocytes oxygen delivery may (or may not) be different in a case of early VSD without any cardiac chamber modification whereas hypoxemia due to intracardiac shunt may lead to increased cTnI due to myocardial hypoxia in cyanotic heart disease (Tetralogy of Fallot or double outlet right ventricle which represent 6 of 12 cases investigated in the present study1). This study raises interesting points concerning potential interest of cTnI in the diagnosis of CHD in calves. However, the authors did not convince me that it could replace transthoracic echocardiography which is more specific in living animals and more sensitive (for experienced user) especially for commonly encountered CHD such as VSD. Having higher number of CHD calves and calves with various conditions that could clinically mimick CHD would be of great interest to investigate more accurately Se/Sp of this cardiac biomarker. Using the proposed threshold to diagnose CHD in calves without other confirmatory test would certainly lead to overdiagnosing CHD in calves with simple infectious respiratory conditions or endotoxemic condition.
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 | 0.002 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.018 | 0.018 |
| Insufficient payload (model declined to judge) | 0.041 | 0.024 |
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".