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      The association of hypertension with the severity and mortality of COVID-19 patients: evidence based on adjusted effect estimates

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          Abstract

          To the Editor, Previous studies have shown that common comorbidities were significantly associated with the increased risk of adverse outcomes in patients with coronavirus disease 2019 (COVID-19) 1 . As we know, hypertension was the most common comorbidities among COVID-19 patients 2 . Recently, a paper in the Journal of Infection by Zheng et al 3 has reported that the proportion of hypertension was significantly higher in critical/mortal patients compared to the non-critical patients (hypertension: odds ratio (OR) = 2.72, 95%: confidence interval (CI) 1.60-4.64, P = 0.0002). However, the findings were based on unadjusted effect estimates. It was worth mentioning that the data based on unadjusted effect estimates indicated hypertension was an important risk factor for the adverse outcomes of COVID-19 patients, but the pooled effects based on adjusted effect estimates were significantly reduced or even disappeared in several studies4, 5, 6, 7, 8. For instance, in the study of Wang et al., univariate analysis showed that hypertension was a risk factor for death in patients with COVID-19 (OR = 5.000, 95% CI: 1.748-14.301), while multivariate analysis showed that hypertension was not significantly associated with the risk of mortality (OR= 1.099, 95% CI: 0.264-4.580) 7 . Similarly, univariate analysis in Cummings et al. indicated that hypertension was significantly associated with patient death (hazard ratio (HR) = 2.24, 95% CI: 1.40-3.59), but this association disappeared in the multivariate analysis (HR = 1.58, 95% CI: 0.89-2.81) 5 . The same findings were also observed in Wang et al.’s study 8 . This meant that the association of hypertension with the adverse outcomes of COVID-19 patients might be affected by various factors such as age, gender and other comorbidities. Therefore, it is urgently required to clarify the association between hypertension and the adverse outcomes of COVID-19 patients by a systematically quantitative meta-analysis on the basis of the published studies reporting the adjusted effect estimates. Therefore, we systematically searched the electronic databases, including Web of Science, Chinese National Knowledge Infrastructure (CNKI) and PubMed to identify all observational studies published between Jan 1, 2020 and June 15, 2020 that compared outcomes in hospitalized COVID-19 patients with and without hypertension. These search engines used the following two sets of keywords to capture available literature: "Coronavirus 2019, 2019-nCoV, SARS-CoV-2, COVID-19" and "Hypertension”. Only articles that reported adjusted effect estimates of hypertension and adverse outcomes (severity including severe and critical, and mortality) in patients with COVID-19 were qualified. All calculations were implemented with Stata 11. 2 software. The pooled OR and pooled HR with their corresponding 95% CI were used to evaluate the risk of adverse outcomes in patients with COVID-19 and hypertension. The degree of heterogeneity between studies was tested using I2 statistics. The I2 values were 25%, 50%, and 75%, indicating low, medium, and high heterogeneity, respectively 9 . If there was no evidence of between-studies heterogeneity (I2 ≤ 50%), a fixed-effects model was used to calculate the combined effects. Otherwise, a random-effects model was selected 10 . The sensitivity analysis was used to evaluate the robustness of the results. Both Begg's test and Egger's test were used to evaluate publication bias. Overall, 521 documents were initially identified according to our search criteria, and the final analysis included 19 studies of 15,302 patients4, 5, 6, 7, 8 , 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24. As shown in Table 1 , the median age of COVID-19 patients ranged from 43.9 to 71 years, of which 38.2% had hypertension. The sample size ranged from 63 to 2,877. Seventeen studies were retrospective and two prospective. Table 1 : Characteristics of the included studies. Table 1 Author Location Case Age (years) Male (%) Study design HTN Adjusted effect estimate(95%CI) Confounders Chen C [12] China 150 59(16) 84(56) R 49(32.6) OR 2.586(0.609-10.980) Age, gender, NT-proBNP, cTnI, hs-CRP, creatinine, CHD Wang D [7] China 107 51(31-65) 57(53.3) R 26(24.3) OR 1.099(0.264-4.580) Age, gender, CVD, creatinine concentration Sun H [21] China 244 NR 137(54.5) R 138(56.6) OR 0.82(0.24-2.75) Age, gender, vital signs, previous respiratory diseases, laboratory values Shi S [20] China 671 63(50-72) 322(48) R 199(29.7) HR 1.07(0.46-2.53) Age, gender, diabetes, CHD, chronic renal disease, chronic heart failure, atrial fibrillation, CVD, COPD, procalcitonin, CRP Yan X [23] China 1004 NR 493(49.1) R 235(23.4) OR 2.606(0.988-6.870) NLR, hs-CRP, NT-proBNP, BUN, respiratory failure, digestive system disease, CVD Wang G [8] China 209 NR 105(50.2) R 27(12.9) OR 0.357(0.078-1.639) Age, gender, creatine kinase, lymphocyte, AST, CRP Cummings MJ [5] American 257 62(51-72) 171(67) P 162(63) HR 1.58(0.89-2.81) Age, gender, symptom duration before hospital presentation, chronic cardiac disease, COPD or interstitial lung disease, diabetes, interleukin-6, D-dimer Phipps MM [6] American 2273 65(52-76) 1297(57) R 1375(60) OR 1.15(0.85-1.56) age, peak ALT, BMI >35, diabetes, intubation, renal replacement therapy Galloway JB [14] UK 1157 71(57-82) 666(57.6) R 611(52.9) HR 1.53(1.24-1.90) Age, gender Huang S [16] China 310 62(40-70) 174(56.1) R 113(36.5) OR 1.562(0.929-2.625) Age, gender Escalera-Antezana JP [13] Bolivia 107 43.9(17.6) 55(51.4) R 10(9.35) OR 3.284(1.276-6.291) Age Gao C [15] China 2877 NR 1479(51.1) R 850(29.5) HR 2.06(1.10-3.83) Age, gender, medical history of diabetes, insulin-treated diabetes, myocardial infarction, underwent PCI/CABG, renal failure, stroke, heart failure, COPD Zhao M [24] China 1000 61(46-70) 466(46.6) R 282(28.2) HR 1.974(1.297-3.003) Age Sabri A [19] Iran 63 54.1(15.5) NR R 15(23.8) OR 1.42(1.13-1.71) History of heart disease, pericardial effusion, blood oxygen saturation Lim JH [18] Korea 160 NR 86(53.8) R 77(48.1) HR 1.34(0.71-2.52) Acute kidney injury network, age, gender, diabetes Chen F [4] China 660 55(34-68) 295(44.7) R 230(34.8) OR 0.920(0.420-2.016) Age, cerebral infarction, SOFA, CRP, LDH Targher G [22] China 310 47 149(48.1) R NR OR 2.68(1.20-5.98) Age, gender Lala A [17] American 2736 66.40(15.8) 1630(59.6) R 1065(38.9) OR 0.99(0.79-1.23) Age, gender, troponin strata, race, ethnicity, coronary artery disease, diabetes, heart failure, atrial fibrillation, chronic kidney disease Cen Y [11] China 1007 61 (49-68) 493(49.0) P 270(26.8) HR 1.442(1.109-1.876) Age, gender, smoking, diabetes, chronic obstructive lung disease, coronary artery disease, duration of anti-viral therapy All values are n (%), mean (SD) or median (IQR); NR, not reported; HTN, hypertension; P, prospective; R, retrospective; HR, hazard ratio; OR, odds ratio; NT-proBNP, amino-terminal pro-brain natriuretic peptide; cTnI, cardiac troponin I; hs-CRP, high-sensitivity C-reactive protein; CHD, Coronary heart disease; CVD, cardiovascular or cerebrovascular disease; COPD, chronic obstructive pulmonary disease; CRP, C-reactive protein; NLR, neutrophil-to-lymphocyte ratio; BUN, blood urea nitrogen; ALT, alanine aminotransferase; AST, aspartate aminotransferase; BMI, body mass index; SOFA, Sequential Organ Failure Assessment; PCI/CABG, percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG); LDH, lactate dehydrogenase. Totally, our meta-analysis showed that hypertension was significantly associated with the increased risk of adverse outcomes in COVID-19 patients on the basis of 19 studies with 15,302 cases (OR= 1.44, 95% CI [1.24-1.66]; I2 = 41.4%, random-effects model) (Fig. 1 A). Of the 19 studies, 12 reported adjusted OR and 7 reported adjusted HR. Therefore, we conducted a subgroup analysis based on the adjusted OR and adjusted HR. We also found a significant correlation between hypertension and adverse outcomes on the basis of both 12 OR-adjusted studies with 8,173 cases (OR= 1.37, 95% CI [1.08-1.72]; I2 = 51.9%) and 7 HR-adjusted studies with 7,129 cases (HR= 1.55, 95% CI [1.35-1.78]; I2 = 0.0%) (Fig. 1A). As shown by the sensitivity analysis, none of the studies had a significant impact on the overall results, which proves the robustness of our results (Fig. 1B). No publication bias was detected in Begg's test (P=0.889) or Egger's test (P=0.432). Fig. 1 The pooled effects and their 95% confidence interval (CI) of the relationship between hypertension and adverse outcomes in patients with COVID-19 (A). Sensitivity analysis of the relationship between hypertension and adverse outcomes in patients with COVID-19 (B). Fig 1 Previous studies have suggested that hypertension was a risk factor for adverse outcomes of COVID-19 patients, but the studies did not consider the effects of confounding factors on the findings 2 , 25, 26, 27, 28. Presently, our results showed that hypertension was significantly associated with the increased risk of adverse outcomes in COVID- 19 patients on the basis of the adjusted effect estimates, which suggests that hypertension is an independent risk factor for predicting the severity and mortality of COVID-19 patients. Thus COVID-19 patients with hypertension deserve more clinical attention. It should be acknowledged that some limitations existed in our study. Firstly, the judgment criteria of adverse results in the included studies were not uniform. Secondly, all the included studies reported the adjusted effect estimates, but the confounding factors adjusted in each study were not entirely consistent. Thirdly, the stage of hypertension and whether it is controlled or poorly controlled are also unknown. The included studies did not adequately report data on chronic hypertension medications and therefore these could not be analyzed. In summary, our meta-analysis demonstrated for the first time that hypertension was an independent risk factor for predicting the adverse outcomes of patients with COVID-19. Further well-designed studies with larger sample sizes are required to verify the findings of our present study. Declaration of Competing Interest All authors report that they have no potential conflicts of interest.

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          Most cited references26

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          Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

          In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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            Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis

            Highlights • COVID -19 cases are now confirmed in multiple countries. • Assessed the prevalence of comorbidities in infected patients. • Comorbidities are risk factors for severe compared with non-severe patients. • Help the health sector guide vulnerable populations and assess the risk of deterioration.
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              Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study

              Summary Background Over 40 000 patients with COVID-19 have been hospitalised in New York City (NY, USA) as of April 28, 2020. Data on the epidemiology, clinical course, and outcomes of critically ill patients with COVID-19 in this setting are needed. Methods This prospective observational cohort study took place at two NewYork-Presbyterian hospitals affiliated with Columbia University Irving Medical Center in northern Manhattan. We prospectively identified adult patients (aged ≥18 years) admitted to both hospitals from March 2 to April 1, 2020, who were diagnosed with laboratory-confirmed COVID-19 and were critically ill with acute hypoxaemic respiratory failure, and collected clinical, biomarker, and treatment data. The primary outcome was the rate of in-hospital death. Secondary outcomes included frequency and duration of invasive mechanical ventilation, frequency of vasopressor use and renal replacement therapy, and time to in-hospital clinical deterioration following admission. The relation between clinical risk factors, biomarkers, and in-hospital mortality was modelled using Cox proportional hazards regression. Follow-up time was right-censored on April 28, 2020 so that each patient had at least 28 days of observation. Findings Between March 2 and April 1, 2020, 1150 adults were admitted to both hospitals with laboratory-confirmed COVID-19, of which 257 (22%) were critically ill. The median age of patients was 62 years (IQR 51–72), 171 (67%) were men. 212 (82%) patients had at least one chronic illness, the most common of which were hypertension (162 [63%]) and diabetes (92 [36%]). 119 (46%) patients had obesity. As of April 28, 2020, 101 (39%) patients had died and 94 (37%) remained hospitalised. 203 (79%) patients received invasive mechanical ventilation for a median of 18 days (IQR 9–28), 170 (66%) of 257 patients received vasopressors and 79 (31%) received renal replacement therapy. The median time to in-hospital deterioration was 3 days (IQR 1–6). In the multivariable Cox model, older age (adjusted hazard ratio [aHR] 1·31 [1·09–1·57] per 10-year increase), chronic cardiac disease (aHR 1·76 [1·08–2·86]), chronic pulmonary disease (aHR 2·94 [1·48–5·84]), higher concentrations of interleukin-6 (aHR 1·11 [95%CI 1·02–1·20] per decile increase), and higher concentrations of D-dimer (aHR 1·10 [1·01–1·19] per decile increase) were independently associated with in-hospital mortality. Interpretation Critical illness among patients hospitalised with COVID-19 in New York City is common and associated with a high frequency of invasive mechanical ventilation, extrapulmonary organ dysfunction, and substantial in-hospital mortality. Funding National Institute of Allergy and Infectious Diseases and the National Center for Advancing Translational Sciences, National Institutes of Health, and the Columbia University Irving Institute for Clinical and Translational Research.
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                Author and article information

                Contributors
                Journal
                J Infect
                J. Infect
                The Journal of Infection
                The British Infection Association. Published by Elsevier Ltd.
                0163-4453
                1532-2742
                25 June 2020
                25 June 2020
                Affiliations
                [a ]Department of Epidemiology, School of Public Health, Zhengzhou University, Zhengzhou, 450001, China
                [b ]Department of Toxicology, Henan Center for Disease Control and Prevention, Zhengzhou, 450016, China
                Author notes
                [* ]Corresponding author: Haiyan Yang, Department of Epidemiology, School of Public Health, Zhengzhou University, No. 100 of Science Avenue, Zhengzhou 450001, China; Phone: 86-371-67781248; Fax: 86-371-67781248 yhy@ 123456zzu.edu.cn
                [** ]Yadong Wang, Department of Toxicology, Henan Center for Disease Control and Prevention, No. 105 of South Nongye Road, Zhengzhou 450016, China. wangyd76@ 123456163.com
                Article
                S0163-4453(20)30441-2
                10.1016/j.jinf.2020.06.060
                7315979
                32593655
                24e6e479-bf38-46b7-946e-cbe26b2712c2
                © 2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 23 June 2020
                Categories
                Article

                Infectious disease & Microbiology
                covid-19,hypertension,severity,mortality
                Infectious disease & Microbiology
                covid-19, hypertension, severity, mortality

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