{'fraction_non_alphanumeric': 0.02763819095477387, 'fraction_numerical': 0.0020100502512562816, 'mean_word_length': 5.681208053691275, 'pattern_counts': {'":': 0, '<': 2, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Novel White Blood Cell Subtypes and Ratios in Patients With Essential Hypertension

To the Editor: We would like to thank Kundi for the reply to our article “The Role of Plasma Triglyceride/High-Density Lipoprotein Cholesterol Ratio to Predict New Cardiovascular Events in Essential Hypertensive Patients.” Increased levels of systemic inflammatory markers are associated with cardiovascular outcomes. As known, neutrophil to lymphocyte ratio (NLR) has been shown to be a useful biomarker to predict cardiovascular outcomes. Recently, several white blood cell (WBC) subtypes and ratios were researched in patients with cardiovascular diseases such as the platelet to lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR), and monocyte to high-density lipoprotein cholesterol ratio (MHR). These ratios may help predict outcomes in patients with coronary artery disease. Novel biomarkers could potentially help decision-making regarding treatment. However, our findings did not show relevance with WBC subtypes and ratios. In addition, there are several studies that have researched the association between NLR, PLR, and MHR and cardiovascular outcomes in patients with hypertension. Therefore, we did not feel it was necessary to research these novel biomarkers in patients with essential hypertension. The patients with secondary hypertension, chronic liver disease, obvious active illness (eg, malignancy or acute infection) at baseline, history of cerebrovascular events, coronary heart disease, significant cardiac arrhythmias, obstructive sleep apnea, or familial hyperlipidemias were excluded from the study. We added the variables with P values <.05 in baseline characteristics of patients to the univariate regression model. Subsequently, the variables for which the unadjusted P value was <.10 in univariate analysis were identified as potential risk markers and included in the multivariable Cox regression model. Therefore, we think that this regression model is appropriate.