When Numbers Mislead: Reassessing Statistical Foundations in PCA-Based Prognostication of Fontan Outcomes

Zhihao Lei

Cardiovasc. Sci. ›› 2026, Vol. 3 ›› Issue (1) : 10015

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Cardiovasc. Sci. ›› 2026, Vol. 3 ›› Issue (1) :10015 DOI: 10.70322/cvs.2025.10015
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When Numbers Mislead: Reassessing Statistical Foundations in PCA-Based Prognostication of Fontan Outcomes
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Zhihao Lei. When Numbers Mislead: Reassessing Statistical Foundations in PCA-Based Prognostication of Fontan Outcomes. Cardiovasc. Sci., 2026, 3(1): 10015 DOI:10.70322/cvs.2025.10015

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The author declares no conflicts of interest.

References

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Ferrari MR, Schäfer M, Di Maria MV, Hunter KS. Application of principal component analysis to heterogeneous Fontan registry data identifies independent contributing factors to decline. Cardiovasc Sci. 2025, 2, 10005. doi:10.70322/cvs.2025.10005.

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Jolliffe IT.Principal Component Analysis, 2nd ed.; Springer: New York, NY, USA, 2002.

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Ferreira-González I, Permanyer-Miralda G, Domingo-Salvany A, Busse JW, Heels-Ansdell D, Montori VM, et al. Problems with use of composite end points in cardiovascular trials: Systematic review of randomised controlled trials. BMJ 2007, 334, 786. doi:10.1136/bmj.39136.682083.AE.

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Jakobsen JC, Gluud C, Wetterslev J, Winkel P. When and how should multiple imputation be used for handling missing data in randomised clinical trials—A practical guide with flowcharts. BMC Med. Res. Methodol. 2017, 17, 162. doi:10.1186/s12874-017-0442-1.

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Iyengar AJ, Winlaw DS, Galati JC, Celermajer DS, Wheaton GR, Gentles TL, et al. Trends in Fontan surgery and risk factors for early adverse outcomes after Fontan surgery: The Australia and New Zealand Fontan Registry experience. J. Thorac. Cardiovasc. Surg. 2014, 148, 566-575. doi:10.1016/j.jtcvs.2013.09.074.

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DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 1988, 44, 837-845. doi:10.2307/2531595.

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