key: cord-0782148-m1y1cpgm authors: Dong, Yonghai; Li, Zhongjian; Ding, Sheng; Liu, Shulong; Tang, Zhiyuan; Jia, Lina; Liu, Jiahong; Liu, Yun title: HIV infection and risk of COVID-19 mortality: A meta-analysis date: 2021-07-02 journal: Medicine (Baltimore) DOI: 10.1097/md.0000000000026573 sha: 18071fbacdf0377b4204a2fbdcb0ea4c0c261d1a doc_id: 782148 cord_uid: m1y1cpgm BACKGROUND: This meta-analysis aimed to estimate the association of human immunodeficiency virus (HIV) infection and risk of coronavirus disease 2019 (COVID-19) mortality. METHODS: We systematically retrieved articles published on HIV infection and risk of COVID-19 mortality through PubMed, EMBase, China National Knowledge Infrastructure, WanFang, and Chongqing VIP databases using a predefined search strategy from December 1, 2019 to January 31, 2021. Newcastle–Ottawa Scale (NOS) was used to assess the quality of the included studies. Cochran Q test and I(2) statistics were quantified to measure heterogeneity. Odds ratio (OR) and 95% confidence intervals (CI) were computed and displayed in the form of forest plots. Subgroup analysis was performed to explore the source of heterogeneity. Funnel plot, Begg test, and Egger test were used to assess potential publication bias. Stata software version 11.0 was used to analyze all the statistical data. RESULTS: We included 10 studies with 18,122,370 COVID-19 patients, of whom 41,113 were with HIV infection and 18,081,257 were without HIV infection. The pooled overall results suggested that people living with HIV infection had a higher risk of mortality from COVID-19 than those without HIV infection (OR = 1.252, 95% CI 1.027–1.524). Subgroup analysis showed that people living with HIV infection had a higher risk of COVID-19 mortality than those without HIV infection in the United States (OR = 1.520, 95% CI 1.252–1.845) and in South Africa (OR = 1.122, 95% CI 1.032–1.220); however, no significant association was found in the United Kingdom (OR = 0.878, 95% CI 0.657–1.174). CONCLUSION: Patients with HIV infection should be the emphasis population to prevent the risk of mortality during the clinical treatment of COVID-19 patients. As of January 31, 2021, 103 million people from 223 countries had been confirmed to be infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since its emergence in late 2019, and this virus had caused more than 2.4 million people death. [1] The global pandemic of coronavirus disease 2019 (COVID- 19) is having a dramatic impact on social, economic, and population health all over the world. [2] [3] [4] [5] It is not clear when the outbreak will stop. A large number of studies have shown that comorbidities, [6] [7] [8] [9] [10] [11] [12] such as hypertension, diabetes, cardiovascular disease, hepatic, pulmonary disease, etc can increase the risk of COVID-19 mortality. Could COVID-19 patients also have an increased risk of death after suffering from human immunodeficiency virus (HIV) co-infection? So far, some studies [13] [14] [15] [16] have reported the relationship between HIV co-infection and COVID-19, but the results are inconsistent. Now, there were 2 meta-analyses [17, 18] that showed no association between HIV co-infection and the risk of COVID-19 mortality. However, there have been many new studies in this field to reveal the relationship between them since the 2 meta-analyses were performed, and the pooled results of these studies need to be further updated. In addition, some studies included in these 2 meta-analysis studies were with small sample sizes. Studies with a small sample size were more likely to produce negative results due to their insufficient efficacy. Also, the 2 meta-analyses point out that further researches with a larger sample size are needed. Recently, a large-scale population-based study [19] with over 17 million individuals was performed in England to investigate the association of HIV co-infection and the risk of COVID-19 mortality, and found that people living with HIV had a higher risk of COVID-19 mortality than those without HIV after adjusting for age and sex (HR = 2.90, 95% CI 1.96-4.30). If we combined the COVID-19 epidemic information around the world, would this relationship hold up as well as the England study? Are there differences among different countries? So far there is no clear answer. In view of this, our study intends to adopt the meta-analysis method by selecting literature studies with a relatively large sample size to explore whether HIV co-infection increases the risk of death due to COVID-19. This present study was being reported according to the guidance of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement. All the studies revealing the relation-ship between HIV co-infection and the risk of COVID-19 mortality were included. In this study, we searched PubMed (December 1, 2019 to January 31, 2021), EMBase (December 1, 2019 to January 31, 2021), China National Knowledge Infrastructure (December 1, 2019 to January 31, 2021), WanFang Data (December 1, 2019 to January 31, 2021), and Chongqing VIP (December 1, 2019 to January 31, 2021) using a predefined search strategy (Fig. 1) . The keywords included the following items: ("COVID-19" OR "2019-nCoV" OR "severe acute respiratory syndrome coronavirus 2" OR "SARS-CoV-2") AND ("HIV" OR "human immunodeficiency virus infection" OR "AIDS" OR "acquired immune deficiency syndrome"). Two reviewers independently screened the titles and abstracts of the studies. No limitations were applied to language and study design. Additionally, reference lists in this present review were screened to identify the additional relevant studies. All the included studies should be selected if they met the following criteria: (1) the participants (population) were positive/ confirmed cases of COVID-19; (2) the participants were divided (3) outcomes of mortality due to COVID-19 were provided; (4) the sample size for each of the 2 groups should not be less than 100; and (5) the study design was a randomized control trial, cohort study, and case-control study. Those articles, such as review articles, case reports, commentaries, and letters, were excluded. If 2 or more articles were published based on the same population, the study with larger samples was included. The information of the articles included the first author, publication year, age, country, study design, the number of participants with HIV who died and did not die, or the effect size (the OR or relative risk (RR)), etc, were independently extracted by the same researchers. According to the Newcastle-Ottawa Scale, [20] 2 reviewers independently evaluated the quality of the included articles. The evaluation criteria mainly included 3 aspects, such as the selection, comparability, and outcomes, and the total score of the Newcastle-Ottawa Scale checklist ranged from 0 to 9. In this review, studies with scores ≥7 were considered good quality, 4to 6 scores were considered moderate quality, and 3 scores were considered low quality. There was no need for ethical approval for this review because all the data were extracted from previously published articles. In this study, OR along with the 95% CI was set as the outcome for each study. Cochran Q test and I 2 statistics were quantified to measure heterogeneity. When I 2 < 50% was observed, low heterogeneity among studies was considered, and DerSimonian and Laird random-effect method was used to pool the effect size. Otherwise, the fixed-effects methods were used. Potential ascertainment bias was assessed with the funnel plots. While the Begg and Egger tests were considered an objected measure of publication bias statistically. Subgroup analysis and sensitivity analysis were conducted to investigate the source of heterogeneity. A P value .05 was considered to be statistically significant. All statistical analyses were analyzed using the Stata software version 11.0 (Stata Corporation, College Station, TX, USA). A total of 632 records were obtained through electronic searches. After screening through strict literature retrieval procedures, a total of 10 literature were finally included in this review (see Fig. 1 Table 1 Characteristics of articles included in this meta-analysis. and Table 1 ). The 10 studies [19, [21] [22] [23] [24] [25] [26] [27] [28] [29] [21, [24] [25] [26] 28, 29] were carried out in United States, 2 studies [19, 23] were in United Kingdom, and 2 studies [22, 27] were in South Africa. Eight studies [19, 21, 22, [25] [26] [27] [28] [29] were designed as a retrospective cohort study and 2 studies [23, 24] were designed as a prospective cohort study. All the included studies were written in English. Detailed data source information for each study was listed in Table 1 . For the countries variables, subgroup analysis was performed in this meta-analysis (Fig. 3) . In the United States, people living with HIV infection had a higher risk of COVID-19 mortality than those without HIV infection (OR = 1.520, 95% CI 1.252-1.845). In South Africa, people living with HIV infection also had a higher risk of COVID-19 mortality than those without HIV infection (OR = 1.122, 95% CI 1.032-1.220). However, there was no significant association between HIV infection and the mortality risk of COVID-19 in the United Kingdom (OR = 0.878, 95% CI 0.657-1.174). Subjectively, the funnel plot analysis showed symmetry among the included studies (Fig. 4) . Statistically, the Begg test and Egger test revealed that there was no publication bias for the publications (Z = 1.07, P = .283; t = 0.37, P = .718). This is the first meta-analysis to analyze the association between HIV infection and risk of COVID-19 mortality which includes a larger sample size in each selected study. The key findings of our present study suggested that people living with HIV infection had a higher risk of death from COVID-19 than those without HIV infection (OR = 1.252, 95% CI 1.027-1.524). The larger the sample size, the smaller the error range will be and the more reflective of the overall characteristics. Therefore, the inclusion of research literature in this study ensured that the sample size of the HIV-positive population should be relatively large, that is, the sample size should be more than 100 subjects so that the calculated results are more representative and can better reflect the overall characteristics. Ssentongo et al [17] searched 3 articles published from December 1, 2019 to July 9, 2020, and performed a meta-analysis resulting that HIV/AIDS comorbidity was not significantly associated with a greater risk of COVID-19 mortality (RR = 0.88, 95% CI 0.34-2.31). But 1 study had a very small sample size in the included studies, while the other 2 studies had more than 100 times that size. Therefore, there was a huge difference in the sample size and the effectiveness of the research results. Sarkar et al [18] screened electronic databases up to September 3, 2020, and pooled the results of 7 articles that reported the association of HIV and risk of COVID-19 mortality, and they reported that no significant relationship was resulted (RR = 0.99, 95% CI 0.82-1. 19 ). The weakness of this metaanalysis is the same as that of the previous study, 4 of the 7 included studies had very small sample sizes for the HIV-positive group. However, we found that the CI for the pooled effect in this study had been narrowing as the number of the included studies increased. Our current review abandoned the shortcomings of the previous meta-analysis and only selected studies with a large sample size, which made the research results more reliable. In addition, we also analyzed HIV infection to the risk of COVID-19 mortality in different countries. Based on the data with 0.74 million individuals from 6 surveys, people living with HIV infection had a higher risk of COVID-19 mortality than those without HIV infection in the United States (OR = 1.520, 95% CI 1.252-1.845). A similar risk was also achieved in South Africa from 2 studies, our subgroup analysis found that people living with HIV infection also had a higher risk of COVID-19 mortality than those without HIV infection (OR = 1.122, 95% CI 1.032-1.220). However, no significant association between HIV infection and the mortality risk of COVID-19 was found in the United Kingdom (OR = 0.878, 95% CI 0.657-1.174). The reason for this difference might be related to SARS-CoV-2 virus mutations in different countries. [30] [31] [32] In addition, the affordability of health services in different countries could also affect it. [33] [34] [35] This present meta-analysis had several limitations. Firstly, of the literature that met the inclusion criteria, only 3 countries were covered. At present, the epidemic of COVID-19 is sweeping almost all countries in the world, but the vast majority of countries have not reported the research results in this field. Therefore, the association of HIV infection and the mortality risk of COVID-19 will need to be updated in the future through the synthesis of more homogeneous studies. Secondly, the mortality of COVID-19 was also linked to the severity of the COVID-19. Despite the immunocompromised status, HIV patients are more likely to suffer from SARS-CoV-2 infection than ordinary beings. [36] [37] [38] Laracy et al [39] carried out a retrospective cohort study of COVID-19 and found people with HIV were more likely to be admitted from the emergency department than patients without HIV (91% vs 71%; P = .001). However, among hospitalized patients, patients living with HIV did not differ from HIV-uninfected controls by the rate of mechanical ventilation or death/discharge to hospice. Patel et al [40] systematically compiled 63 reports of HIV-1 and SARS-CoV-2 coinfection, and found the presence of comorbidities was associated with a poorer prognosis in HIV/SARS-CoV-2 patients, despite cART and viral suppression. Some studies [41] [42] [43] [44] also reported that HIV co-infection could influence the severity of patients with COVID-19. However, it was not possible to analyze the effect of HIV infection on the severity of COVID-19 patients, as there were no available data in our current studies. Thirdly, how frequently people living with HIV mount the intense cytokine response leading to severe COVID-19 was unknown. Finally, some factors, such as age and sex, could influence the accuracy of the results if they were not adjusted. For example, Bhaskaran et al [19] revealed that people living with HIV had a higher risk of COVID-19 mortality than those without HIV after adjusting for age and sex, but this relationship was not significant if the result was not adjusted. Given that we could only get the crude raw data for most studies, our conclusion needed to be treated with caution. To sum up, during the clinical treatment of COVID-19 patients, those people with HIV co-infection should be regarded as the key crowd to prevent the risk of mortality. However, the association of HIV co-infection and the mortality risk of COVID-19 still need to be updated in the future. World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard Analysis of COVID-19 burden, epidemiology and mitigation strategies in Muslim majority countries Funnel plot of the included studies in this meta-analysis Sex differences in the association between stress, loneliness, and COVID-19 burden among people with HIV in the United States Estimating the unknown: greater racial and ethnic disparities in COVID-19 burden after accounting for missing race and ethnicity data The COVID-19 burden for health care professionals: results of a global survey Clinical features and outcomes of hospitalized COVID-19 patients in a low burden region Arterial oxygen saturation and other clinical predictors of survival in patients with covid-19: a review of cases in a tertiary care hospital in Nigeria Descriptive epidemiology of SARS-CoV-2 infection in Karnataka state, South India: transmission dynamics of symptomatic vs. asymptomatic infections Cohort profile: SARS-CoV-2/ COVID-19 hospitalised patients in Switzerland Predictors of morbidity and mortality in COVID-19 Clinical outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19) in Boston Causes of death and comorbidities in hospitalized patients with COVID-19 Indirect HIV morbidity and mortality due to COVID-19 Incidence and outcomes of COVID-19 in kidney and liver transplant recipients with HIV: report from the national HOPE in action consortium Clinical outcomes of patients with COVID-19 and HIV coinfection COVID-19 death in people with HIV: interpret cautiously Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: a systematic review and meta-analysis Impact of COVID-19 in patients with concurrent co-infections: a systematic review and meta-analyses HIV infection and COVID-19 death: a population-based cohort analysis of UK primary care data and linked national death registrations within the Open-SAFELY platform Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses COVID-19 infection among people with HIV in New York City: a population-level analysis of linked surveillance data Risk factors for COVID-19 death in a population cohort study from the Western Cape Province Outcomes of coronavirus disease 2019 (COVID-19) related hospitalization among people with human immunodeficiency virus (HIV) in the ISARIC World Health Organization (WHO) clinical characterization protocol (UK): a prospective observational study Descriptive analysis of patients living with HIV affected by COVID-19 Characteristics and outcomes of COVID-19 in patients with HIV: a multicentre research network study Comorbidities associated with mortality in 31,461 adults with COVID-19 in the United States: a federated electronic medical record analysis COVID-19 in-hospital mortality in South Africa: the intersection of communicable and non-communicable chronic diseases in a high HIV prevalence setting Prognosis of coronavirus disease 2019 (COVID-19) in patients with HIV infection in New York City Elevated COVID-19 outcomes among persons living with diagnosed HIV infection in New York State: results from a population-level match of HIV, COVID-19, and hospitalization databases The 501.V2 and B 1. 1. 7 variants of coronavirus disease 2019 (COVID-19): a new time-bomb in the making? Emergence of SARS-CoV-2 B.1.1.7 Lineage -United States Temporal dominance of B.1.1. 7 over B. 1. 354 SARS-CoV-2 variant: a hypothesis based on areas of variant co-circulation Impact of COVID-19 on health services utilization in Province-2 of Nepal: a qualitative study among community members and stakeholders A review of prospective pathways and impacts of COVID-19 on the accessibility, safety, quality, and affordability of essential medicines and vaccines for universal health coverage in Africa Racial disparities in medication use: imperatives for managed care pharmacy COVID-19 in HIV: a review of published case reports New HIV diagnoses in patients with COVID-19: two case reports and a brief literature review An HIV-infected patient with coronavirus disease 2019 has a favourable prognosis: a case report HIV-1 infection does not change disease course or inflammatory pattern of SARS-CoV-2-infected patients presenting at a large urban medical center Human immunodeficiency virus and severe acute respiratory syndrome coronavirus 2 coinfection: a systematic review of the literature and challenges COVID-19 in people living with HIV: a multicenter case-series study Incidence and severity of COVID-19 in HIV-positive persons receiving antiretroviral therapy: a cohort study Immune deficiency is a risk factor for severe COVID-19 in people living with HIV The characteristics of HIVpositive patients with mild/asymptomatic and moderate/severe course of COVID-19 disease-a report from Central and Eastern Europe Medicine (2021) 100:26 www.md-journal Editor: Vipul Kumar Singh. This research was funded by Science and Technology Planning Project of Health Commission of Jiangxi Province, China (Nos: 202130994 and 20162001).The authors have no conflicts of interest to disclose.All data generated or analyzed during this study are included in this published article [and its supplementary information files]. We acknowledge all those who help us during the various stages of this study.