Clinical chemistry and laboratory medicine · 2021
Relationships between renal function variations and relative changes in cardiac troponin T concentrations based on quantile generalized additive models (qgam).
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Monneret Denis, Fasiolo Matteo, Bonnefont-Rousselot Dominique
Аннотация
OBJECTIVES: The relationship between high-sensitive cardiac troponin T concentration (hs-cTnT) and renal markers levels is known. However, the extent to which their variations are associated remains to be explored. Objective: model the relationship between relative changes in hs-cTnT (Δhs-cTnT) and variations in creatinine (Δcre) or estimated glomerular filtration rate (ΔeGFR), using a quantile generalized additive model (qgam).
METHODS: Concomitant plasma Δhs-cTnT and Δcre from patients aged 18-100 years, selected with a time variation (Δtime) of 3 h-7 days, were collected over a 5.8-year period. Relationships between Δhs-cTnT and covariates Δcre (A) or ΔeGFR (B), including age, Δtime, hour of blood sampling (HSB) and covariates interactions were fitted using qgam.
RESULTS: On the whole (n=106567), Δhs-cTnT was mainly associated with Δcre, in a positive and nonlinear way (-21, -6, +5, +20, +55% for -50, -20, +20, +50, +100%, respectively), but to a lesser extent with age (min -9%, max +2%), Δtime (min -4%, max +8%), and HSB (min -5%, max +7%). Δhs-cTnT was negatively associated with ΔeGFR (+46, +7, -5, -11, -20% for -50, -20, +20, +50, +100%, respectively). Classifying Δhs-cTnT as consistent or not with myocardial injury based on recommendations, an interpretation of Δhs-cTnT adjusted for model A or B led to statistically significant but small diagnostic discrepancies (<2%), as compared to an interpretation based on Δhs-cTnT only.
CONCLUSIONS: From a laboratory and statistical standpoint, considering renal function variations when interpreting relative changes in cardiac troponin T has a minor impact on the diagnosis rate of myocardial injury.
METHODS: Concomitant plasma Δhs-cTnT and Δcre from patients aged 18-100 years, selected with a time variation (Δtime) of 3 h-7 days, were collected over a 5.8-year period. Relationships between Δhs-cTnT and covariates Δcre (A) or ΔeGFR (B), including age, Δtime, hour of blood sampling (HSB) and covariates interactions were fitted using qgam.
RESULTS: On the whole (n=106567), Δhs-cTnT was mainly associated with Δcre, in a positive and nonlinear way (-21, -6, +5, +20, +55% for -50, -20, +20, +50, +100%, respectively), but to a lesser extent with age (min -9%, max +2%), Δtime (min -4%, max +8%), and HSB (min -5%, max +7%). Δhs-cTnT was negatively associated with ΔeGFR (+46, +7, -5, -11, -20% for -50, -20, +20, +50, +100%, respectively). Classifying Δhs-cTnT as consistent or not with myocardial injury based on recommendations, an interpretation of Δhs-cTnT adjusted for model A or B led to statistically significant but small diagnostic discrepancies (<2%), as compared to an interpretation based on Δhs-cTnT only.
CONCLUSIONS: From a laboratory and statistical standpoint, considering renal function variations when interpreting relative changes in cardiac troponin T has a minor impact on the diagnosis rate of myocardial injury.