Serum calcium as a biomarker of clinical severity and prognosis in patients with coronavirus disease 2019

Sun, Jianfang; Zhang, Wenhao; Zou, Lei; Liu, Ying; Li, Jingjing; Kan, Xiao-Hua; Lian, Dai; Shi, Qiankun; Yuan, Shuo; Yu, Wenkui; Xu, Hongpeng; Gu, Wei; Qi, Jianwei

doi:10.18632/aging.103526

Cited by 148 publications

(190 citation statements)

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“…Although many studies [24][25][26] have described a positive relationship between procalcitonin levels and mortality and morbidity in COVID-19 patients, few have commented on the importance of calcium as a prognostic value, as we have found in our study. Calcium was negatively correlated with all 3 measured clinical outcomes, which is consistent with other studies linking hypocalcemia with increased morbidity and mortality in COVID-19 patients [27][28][29] . Theoretically, hypocalcemia could be a result of increased procalcitonin, since procalcitonin is the precursor of calcitonin whose function is to reduce serum calcium.…”

Section: Discussionsupporting

confidence: 90%

Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications

Wang

Liu

Chen

et al. 2020

Preprint

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ObjectiveRetrospective study of COVID-19 positive patients treated at NYU Langone Health (NYULH) to identify clinical markers predictive of disease severity to assist in clinical decision triage and provide additional biological insights into disease progression.Materials and MethodsClinical activity of 3740 de-identified patients at NYULH between January and August 2020. Models were trained on clinical data during different parts of their hospital stay to predict three clinical outcomes: deceased, ventilated, or admitted to ICU.ResultsXGBoost model trained on clinical data from the final 24 hours excelled at predicting mortality (AUC=0.92, specificity=86% and sensitivity=85%). Respiration rate was the most important feature, followed by SpO2 and age 75+. Performance of this model to predict the deceased outcome extended 5 days prior with AUC=0.81, specificity=70%, sensitivity=75%. When only using clinical data from the first 24 hours, AUCs of 0.79, 0.80, and 0.77 were obtained for deceased, ventilated, or ICU admitted, respectively. Although respiration rate and SpO2 levels offered the highest feature importance, other canonical markers including diabetic history, age and temperature offered minimal gain. When lab values were incorporated, prediction of mortality benefited the most from blood urea nitrogen (BUN) and lactate dehydrogenase (LDH). Features predictive of morbidity included LDH, calcium, glucose, and C-reactive protein (CRP).ConclusionTogether this work summarizes efforts to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.BACKGROUND AND SIGNIFICANCEThe first cluster of SARS-CoV-2 was reported in Wuhan, Hubei Province on December 31, 2019. Inciting symptoms remarkably similar to pneumonia, the disease quickly traveled around the world, earning its pandemic status by the World Health Organization on March 11, 2020. Although the first wave has since passed for hardest-hit regions such as New York City (NYC) and most of Asia, a resurgence of cases has already been reported in Europe and record new cases tallied in the Midwest and rural United States (US). As of November 12th, the US alone logged its highest tally to date with a 317% growth over the preceding 30 days1. The coronavirus disease (COVID-19) is far from seeing the end of its days and there remains a compelling need to prioritize care and resources for patients at elevated risk of morbidity and mortality.Previous work building machine learning models used patient data from Tongji Hospital2,3 (Wuhan, China), Zhongnan Hospital4 (Wuhan China), Mount Sinai Hospital5 (NYC, US), and NYU Family Health Center6 (NYC, US). Surprisingly, clinical features selected varied widely across studies. For example, while McRae et al.’s 2-tiered model6 trained on 701 NYC patients to predict mortality was based on actual age, C-reactive protein (CRP), procalcitonin, and D-dimer, Yan et al.’s model2 trained on 485 patients from Wuhan selected lactate dehydrogenase (LDH), lymphocyte count, and CRP as the most predictive for mortality. Variations in selected features differed greatly even when trained to predict similar outcomes on data from patients of the same city. Yao et al.’s model3 was trained on 137 patients from Wuhan and relied on 28 biomarkers in their final model to predict morbidity. Given the differences among prior models, some of which were driven by domain-specific knowledge, we decided to systematically examine the importance of a wide range of features across different endpoint outcomes and at different hospitalization time points.This study analyzes retrospective PCR-confirmed COVID-19 inpatient data collected at NYU Langone Hospital spanning 1/1/2020 to 8/7/2020 to predict three sets of clinical outcomes: alive vs deceased, ventilated vs not ventilated, or ICU admitted vs not ICU admitted. The clinical information of 3740 patient encounters included demographic data (age, sex, insurance, past diagnosis of diabetes, presence of cardiovascular comorbidities), vital signs (SpO2, pulse, respiration rate, temperature, blood pressure), and the 50 most frequently ordered lab tests in our dataset. Models were developed using two methods: logistic regression with feature selection using Least Absolute Shrinkage and Selection Operator7 (LASSO) and gradient tree boosting with XGBoost8. An explainable algorithm, such as logistic regression, provides easy to interpret insights into the features of importance. Conversely, the larger model capacity of XGBoost better handles data complexities to explore the extent that predictive performance can be optimized. Together, these methods ensure a holistic survey that explores the clinical underpinnings of disease etiology and the prospects of building models that are sufficiently competent to be effective decision support tools.

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Section: Discussionsupporting

confidence: 90%

Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications

Wang

Liu

Chen

et al. 2020

Preprint

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“…After further exclusion for non-Covid related, not relevant and only protocols, 59 publications were reviewed ( Supplementary Table S1). Twenty five (8 observational, 4 ecological, 1 interventional non-RCT, 4 Systematic review/meta-analysis/review and 8 editorial) new studies specifically explored the role of vitamin D deficiency in the progression of ARDS in COVID-19 infection (Arnold, 2020;Aygun, 2020;Brenner et al, 2020;Chakhtoura et al, 2020;D'Avolio et al, 2020;Ebadi and Montano-Loza, 2020;Faul et al, 2020;Haj Bloukh et al, 2020;Hastie et al, 2020;Ilie et al, 2020;Laird et al, 2020;Martineau and Forouhi, 2020;Meltzer et al, 2020;Ohaegbulam et al, 2020;Panagiotou et al, 2020;Quesada-Gomez et al, 2020; Raisi-Estabragh et al, 2020; Silberstein, 2020; Singh et al, 2020;Slominski et al, 2020;Sun et al, 2020;Townsend et al, 2020;Tramontana et al, 2020;Whittemore, 2020) (Tables 2, 3). Figure 2 presents a PRISMA diagram of the review search B.…”

Section: Resultsmentioning

confidence: 99%

Association Between Vitamin D and Novel SARS-CoV-2 Respiratory Dysfunction – A Scoping Review of Current Evidence and Its Implication for COVID-19 Pandemic

et al. 2020

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ObjectivesTo assess the association between vitamin D deficiency and increased morbidity/mortality with COVID-19 respiratory dysfunction.DesignScoping review.Data SourcesOvid MEDLINE (1946 to 24 of April 2020) and PubMed (2020 to 17 of September 2020).Eligibility Criteria for Selecting StudiesA search using the search terms: [(cholecalciferol or ergocalciferol or vitamin D2 or vitamin D3 or vitamin D or 25OHD) and (SARS-CoV-2 or coronavirus or COVID or betacoronavirus or MERS-CoV or SARS-CoV or respiratory infection or acute respiratory distress syndrome or ARDS)]m.p. was conducted on the 24/04/2020 (Search A) and 17/09/2020 (Search B).Results91 studies were identified as being concerned with Acute Respiratory Infection (ARI)/Acute Respiratory Distress Syndrome (ARDS) and vitamin D, and 25 publications specifically explored the role of vitamin D deficiency in the development and progression of SARS-CoV-2/COVID-19 related ARDS. Search “A” identified three main themes of indirect evidence supporting such an association. Consistent epidemiological evidence exists linking low vitamin D levels to increased risk and severity of respiratory tract infections. We also report on plausible biological processes supporting such an association; and present weaker evidence supporting the benefit of vitamin D supplementation in reducing the risk and severity of ARIs. Uncertainty remains about what constitutes an appropriate dosing regimen in relation to reducing risk/severity of ARI/ARDS. More recent evidence (Search B) provided new insights into some direct links between vitamin D and COVID-19; with a number of cohort and ecological studies supporting an association with PCR-positivity for SARS-CoV-2 and vitamin D deficiency. The exact efficacy of the vitamin D supplementation for prevention of, or as an adjunct treatment for COVID-19 remains to be determined; but a number of randomized control trials (RCTs) currently underway are actively investigating these potential benefits.ConclusionOur rapid review of literature supports the need for observational studies with COVID-19 infected populations to measure and assess vitamin D levels in relation to risk/severity and outcomes; alongside RCTs designed to evaluate the efficacy of supplementation both in preventive and therapeutic contexts. The overlap in the vitamin D associated biological pathways with the dysregulation reported to drive COVID-19 outcomes warrants further investigation.

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“…However, the role of vitamin D in SARS-CoV-2 infection is not well understood. Some recent investigations have highlighted the beneficial role of vitamin D against SARS-CoV-2 infection and related clinical severity [6] , [7] , [8] , [9] , [10] , [11] , [12] , [13] , by modulating the immune system [14] . In addition, a recent study in UK population reported the worst morbidity outcome in older patients with vitamin D deficiency [13] .…”

Section: Introductionmentioning

confidence: 99%

Lower levels of vitamin D are associated with SARS-CoV-2 infection and mortality in the Indian population: An observational study

Padhi¹,

Suvankar²,

Panda³

et al. 2020

International Immunopharmacology

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Serum calcium as a biomarker of clinical severity and prognosis in patients with coronavirus disease 2019

Cited by 148 publications

References 16 publications

Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications

Predictive modeling of morbidity and mortality in COVID-19 hospitalized patients and its clinical implications

Association Between Vitamin D and Novel SARS-CoV-2 Respiratory Dysfunction – A Scoping Review of Current Evidence and Its Implication for COVID-19 Pandemic

Lower levels of vitamin D are associated with SARS-CoV-2 infection and mortality in the Indian population: An observational study

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