Back

A population model of age and gender specific cardiac troponin levels

Corlan, A. D.

2024-12-21 cardiovascular medicine
10.1101/2024.12.20.24319414 medRxiv
Show abstract

The range of the high-sensitivity cardiac troponin (HSCTN) values in the gen-eral population increases progressively with age, being several times higher in older patients, beyond 70 years old, than in younger ones, below 40. More accurate normal limits for HSCTN, taking into account age and gender, are needed for the differential diagnosis and evaluation of the prognostic signif-icance of increases that do not reach the vendor-supplied upper reference limits (URL). We performed an analysis of the high sensitivity cardiac troponin (HSCTN) of 21743 individuals, representative for the general US population, that were studied in the NHANES survey performed by the Center for Disease Control of the USA. The vendor supplied URL values are typically several times higher than the actual upper limit in subjects under 40 and correspond to the URL at ages between 51 and 84 for specific vendors and genders. For each HSCTN test variant, we considered each one year age group between 1 and 85 and either gender. The distribution of the logarithmed HSCTN for a given test variant and gender, in each subsample i, is relatively close to Gaussian (N ({micro}i, {sigma}i)). Two quadratic models, for the 1-15 and the 16-85 age ranges, were found to fit well with the {micro}i, while the{sigma} i follow a linear model. These theoretical distributions can be used used to estimate any quantiles of the HSCTN distribution as functions of age and gender, including the upper reference limit (URL) for the HSCTN I and T in the general population. Consequently, it is possible to construct a calculated HSCTN indicator that represents the estimated age and gender specific centile in which a measurement with a specific test kit falls, or the percentual distance above the 99th centile. This indicator would be independent of age, gender and kit-vendor, and thus more accurate and easier to employ in clinical practice.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

1
PLOS ONE
5266 papers in training set
Top 16%
12.1%
2
Frontiers in Cardiovascular Medicine
53 papers in training set
Top 0.3%
8.0%
3
Scientific Reports
3612 papers in training set
Top 7%
8.0%
4
Biomedicines
67 papers in training set
Top 0.1%
6.4%
5
MethodsX
16 papers in training set
Top 0.1%
4.9%
6
Computer Methods and Programs in Biomedicine
28 papers in training set
Top 0.1%
4.4%
7
Journal of Clinical Medicine
97 papers in training set
Top 0.8%
4.1%
8
Diagnostics
50 papers in training set
Top 0.5%
3.3%
50% of probability mass above
9
Biology Methods and Protocols
61 papers in training set
Top 0.5%
2.4%
10
American Journal of Physiology-Heart and Circulatory Physiology
36 papers in training set
Top 0.5%
2.2%
11
European Heart Journal - Digital Health
18 papers in training set
Top 0.5%
2.2%
12
Journal of the American Heart Association
140 papers in training set
Top 3%
1.9%
13
Computers in Biology and Medicine
128 papers in training set
Top 2%
1.9%
14
Frontiers in Physiology
106 papers in training set
Top 1%
1.5%
15
BMC Cardiovascular Disorders
18 papers in training set
Top 0.7%
1.4%
16
BioData Mining
22 papers in training set
Top 0.4%
1.4%
17
Cureus
68 papers in training set
Top 3%
1.1%
18
Heliyon
152 papers in training set
Top 5%
1.1%
19
Biomedical Signal Processing and Control
22 papers in training set
Top 0.5%
1.1%
20
Annals of Biomedical Engineering
37 papers in training set
Top 0.8%
1.1%
21
PLOS Neglected Tropical Diseases
466 papers in training set
Top 5%
1.1%
22
Sensors
43 papers in training set
Top 1%
1.1%
23
IEEE Access
35 papers in training set
Top 1%
1.1%
24
JMIRx Med
32 papers in training set
Top 2%
1.0%
25
Open Heart
21 papers in training set
Top 1.0%
1.0%
26
The American Journal of Cardiology
17 papers in training set
Top 1%
0.9%
27
npj Systems Biology and Applications
125 papers in training set
Top 2%
0.9%
28
BMJ Open
601 papers in training set
Top 12%
0.9%
29
PLOS Computational Biology
1863 papers in training set
Top 20%
0.9%
30
NAR Genomics and Bioinformatics
242 papers in training set
Top 5%
0.6%