Circulating Mid-regional Proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

doi:10.21203/rs.3.rs-2217760/v1

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Research Article

Circulating Mid-regional Proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

https://doi.org/10.21203/rs.3.rs-2217760/v1

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Journal Publication

published 08 May, 2023

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Background

Although there is increasing understanding of the changes in the laboratory parameters of coronavirus disease 2019 (COVID-19), the correlation between circulating Mid-regional Proadrenomedullin (MR-proADM) and clinical outcomes of patients with COVID-19 is not fully understood. In this study, we aimed to evaluate the prognostic value of MR-proADM in patients with COVID-19.

Methods

The PubMed, Embase, Web of Science, Cochrane Library, Wanfang, SinoMed and Chinese National Knowledge Infrastructure (CNKI) databases were searched from 1 January 2020 to 20 March 2022 for relevant literature. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) was used to assess quality bias, STATA was employed to pool the effect size by a random effects model, and potential publication bias and sensitivity analyses were performed.

Results

14 studies comprising 1822 patients with COVID-19 met the inclusion criteria, there were 1145 males and 677 females, and the mean age was 64.8 years. The concentration of MR- proADM was compared between the survivors and nonsurvivors in 9 studies and the difference was significant (P < 0.01), I² = 46%. The combined sensitivity was 0.88 [0.81–0.93], and the combined specificity was 0.77 [0.65–0.86]. We drew the SROC curve and calculated the AUC = 0.90 [0.87–0.93]. An increase of 1 nmol/L of MR-proADM was independently associated with a more than threefold increase in mortality (odds ratio 3.03, 95% confidence interval 2.26–4.06, I² = 0.0%, P = 0.633). The predictive value of MR-proADM for death was better than many other biomarkers.

Conclusion

MR- proADM had a very good predictive value for the poor prognosis of COVID-19 patients. Increased levels of MR-proADM were independently associated with mortality in COVID-19 patients and may allow a better risk stratification.

Mid-regional Proadrenomedullin

COVID-19

Mortality

Meta-analysis

Coronavirus disease-19 (COVID-19) is a clinical syndrome caused by the novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The COVID-19 pandemic spread rapidly with more than 535 million cases and 6.3 million deaths. COVID-19 is a global problem and an important cause of death, and accurate evaluation of the prognosis of patients is very important. Many inflammatory markers [1–5] and critical illness scores [6–10] are used to predict the prognosis and mortality of patients with COVID-19 infection.

The emergence of an increasing number of biomarkers may provide a new way to simply and quickly improve the accuracy of prognosis. Mid-regional Proadrenomedullin (MR- proADM) is a peptide produced by multiple tissues that is used to stabilize microcirculation and protect endothelial function [11–14]. Previous studies have shown that with the deterioration of microcirculation integrity and capillary leakage, the concentration of MR- proADM increases, reflecting the early development stage of organ dysfunction [14,15]. Therefore, early evaluation of microcirculation function may provide a more accurate method to evaluate disease progression and treatment effect than using traditional biomarkers or scoring systems [15].

Some studies were devoted to studying the relationship between MR- proADM and the outcome of patients with COVID-19 [16–33]. Howerver, their sample sizes are small, and the conclusions are different. Using a meta-analytic method, the aim of the present study was to provide an overview of the concentration of the MR- proADM between the survivors and nonsurvivors and to explore the predictive value of the MR- proADM for the death of the hospitalized patients with COVID-19.

This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [34]. The review protocol was registered on PROSPERO (CRD42022308638).

Search Strategy

The systematic literature search was conducted in PubMed, Embase, Web of Science, the Cochrane Library, Wanfang, SinoMed and Chinese National Knowledge Infrastructure (CNKI)for studies published from 1 January 2020 to 20 March 2022. The following search terms were used: “MR-proADM” OR “MR-pro-adrenomedullin” OR “midregional pro-adrenomedullin” OR “MR-pro-ADM” and “COVID-19” OR “SARS-CoV-2 Infection” OR “2019 Novel Coronavirus Disease” OR “2019 Novel Coronavirus Infection” OR “2019-nCoV Disease”. There was no restriction on the language of the records. See Fig. 1 for details.

Selection And Eligibility Criteria

All prospective and retrospective studies of MR-proADM and outcomes in patients with COVID-19 were included, and there were no restrictions on age, sex, setting of treatment, severity of disease, sample size, etc. Death was the primary endpoint, and studies that did not include death outcomes were excluded.

Data Extraction

Two authors independently extracted data into a standardized data collection form. Discrepancies were resolved by a third party. The following data were extracted from each study: first author, publication year, country, study period, study design, setting, population, number, age, male ratio, clinical outcomes, levels of MR-proADM, mortality rate, AUC for death, cut-off value, sensitivity and specificity. See additional files for detail.

Risk Of Bias Assessment

The quality of the included studies was assessed by two independent assessors using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) which consists of four key domains: patient selection, index test, reference standard, flow and timing (Fig. 2). Each was assessed in terms of risk of bias and the first three in terms of concerns regarding applicability. Signalling questions were included to assist in judgements about the risk of bias.

Data Synthesis And Statistical Analysis

The main analysis was to determine the predictive ability of MR-proADM on COVID-19 mortality. The mean and standard deviation (SD) of the MR-proADM values were included in the pooled analysis. A random model was used to calculate and separately pool the concentration of MR-proADM in the survivors and nonsurvivors, and the weighted mean difference (WMD) and 95% confidence interval (95% CI) of survivors and nonsurvivors were estimated. When the mean and standard deviation could not be obtained, conversion calculations were carried out according to the sample size, median and interquartile range (IQR) as suggested by Hozo et al. [35].

The heterogeneity between the different studies was presented as I² and P values for the I² statistic were derived from the chi-square distribution of Cochran’s Q test. The standard for the category of heterogeneity was defined as I² > 50%. We used STATA 16.0 to calculate the sensitivity and specificity of MR-proADM and performed the HROC analysis of MR-proADM for mortality. Public bias was examined by Egger’s test.

All statistical analyses were performed using RevMan version 5.4 (the Cochrane Collaboration) and Stata 16.0 software (StataCorp, College Station, Texas, USA). P values less than .05 were considered statistically significant.

Literature search

We found 83 relevant studies from four databases, Medline (21), Embase (37), Web of Science (18), and Wanfang (7). Endnote software was used to delete duplications, and 37 articles remained. By checking the titles and abstracts, another 20 articles were excluded. Three of the remaining 17 articles did not meet the inclusion criteria, and finally 14 articles were ultimately included. The literature search and selection process are depicted in the PRISMA flow diagram (Fig. 1).

The included studies were published between 2021 and 2022. We looked for an association between MR-proADM and the mortality of patients with COVID-19. A total of 1822 patients met the inclusion criteria, including 1145 males and 677 females, with a mean age of 64.8 years. 8 of the studies were from Italy, 3 were from Spain and others were from the Netherlands, Switzerland and United Kingdom. 3 studies were conducted in hospital settings, 3 in the intensive care unit (ICU), 3 in the emergency department, 1 in a COVID centre, 1 in an IMCU, 1 in a medium intensity-of-care COVID-19 department, 1 in an acute HNS setting and the remaining study site was not determined. 9 studies used a prospective study design, and 5 studies were retrospective studies. Of these studies, 12 were single-center studies and 2 were multicenter studies. 3 studies reported 28-day mortality, 6 reported in-hospital mortality, 4 reported 30-day mortality and 1 reported 90-day mortality. We summarized the characteristics of the included studies in Supplementary Table 1, 2, 3.

Meta-analysis Of The Effects Of Mr-proadm On Mortality

Of 14 studies, 10 studies described the specific concentration of MR-proADM in the survivors and nonsurvivors. Therefore, the concentration of MR- proADM was compared between the survivors and nonsurvivors in 10 studies and the difference was significant (P < 0.01), I² = 79%. Due to the obvious heterogeneity, we looked for the source of heterogeneity and found that after removing the first study [24], the heterogeneity of the results decreased significantly. Finally, 9 studies were included, and there was a significant difference in the concentration of MR- proADM between the survivors and the nonsurvivors (P < 0.01), I² = 46% (Fig. 3). STATA was used to calculate the combined sensitivity and specificity, the combined sensitivity was 0.88 [0.81–0.93], I² = 46.78%, and the combined specificity was 0.77 [0.65–0.86], I² = 92.82% (Fig. 4).

To evaluate the predictive ability of MR- proADM for the mortality of patients with COVID-19, we drew the SROC curve, and calculated the AUC = 0.90 [0.87–0.93] (Fig. 5).

SENS, sensitivity; SPEC, specificity; AUC, area under the curve.

Odds Ratios And Hazard Ratios

We calculated an overall prevalence of death of 19.0% (347/1822), ranging from 7.2–54.4% across all the studies. Eight studies used OR to indicate that MR- proADM was associated with mortality, and the pooled OR was 3.03 (2.26–4.06). There was no significant heterogeneity between these studies (I² = 0.0%, P = 0.633). Four studies used HR as an effect measure, and the pooled HR was 5.40 (1.82–16.06). Significant heterogeneity was observed (I² = 84.0%, P = 0.000) (Fig. 6). Both of them indicated that MR- proADM can be an independent predictor for mortality among patients with COVID-19.

Comparation With Other Biomarkers And Critical Illness Scores

Some studies compared the area under the curve (AUC) of MR-proADM with other biomarkers and critical illness scores. The predictive value of MR-proADM for death was better than the Sequential Organ Failure Assessment (SOFA) score, Acute Physiological and Chronic Health Evaluation IV (APACHEIV), Confusion blood Urea nitrogen Respiratory rate Blood pressure age 65 or older (CURB-65) score, D-dimer, cardiac troponin T (cTNT), C-reactive protein (CRP), procalcitonin (PCT), ferritin, lactate and C-terminal proendothelin-1 (CT-proET-1) [33]. Another study found that the AUC of MR-proADM was greater than those of PCT, creatinine, albumin, platelet count, interleukin-6 (IL-6) and lymphocyte count [19]. The study of Benedetti showed that its predictive power was stronger than SOFA and Simplified Acute Physiology Score II (SAPSII), but weaker than the Acute Physiology and Chronic Health Evaluation II (APACHE II) score [17]. MR-proADM was superior to CRP, PCT, neutrophils, lymphocutes [27] and many other biomarkers [18]. However, only a few studies indicated the sensitivity and specificity, and we could not calculate the combined effect of each item.

Sensitivity Analysis And Potential Publication Bias

Begg’s test was used to assess for publication bias, and the results showed no potential bias (p = 0.965) (Fig. 7). We also conducted a sensitivity analysis, and the results indicated that our study was stable (Fig. 8).

Using a meta-analytic approach, we systematically reviewed and analysed the contribution of MR-proADM to mortality in COVID-19 patients. In this study, we found that MR- proADM had a very good predictive value for the poor prognosis of COVID-19 patients. Increased levels of MR-proADM were independently associated with mortality in COVID-19 patients. These findings also confirm the feasibility of risk stratification by MR- proADM in COVID-19 patients.

COVID-19 patients have a high mortality rate. The mortality rate of in-hospital patients was 12.44% [36], that of ICU patients was 26% [37], and that of patients with acute respiratory distress syndrome (ARDS) was 50% [38]. The study population we included had different severities of illness, and the overall mortality rate was 19%. Many studies have used various biomarkers, such as CRP [39–44], PCT [39,43,45,46], IL-6 [39,43,46], WBC[40,47–49], D-dimer[42,44,46,50,51], lactate dehydrogenase (LDH) [39,42–44,46,47], N-terminal pro-B-type natriuretic peptide (NT-proBNP) [39,52,53], and Troponin T[39,54], and critical illness score, such as APACHEII [55–57], SOFA [55,56,58–60], SAPS [61–64], and CURB65 [59,61,65], to evaluate the prognosis of patients with COVID-19. The APACHE II and SOFA scoring systems require the worst values of the clinical and biological parameters to be recorded within 24 h of admission [66]. In contrast, biomarkers can be measured rapidly within hours of the admission. WBC, CRP and IL-6 are lack of specificity, and PCT is mainly used to determine if a bacterial infection is present and to guide the use of antibiotics [67].

Adrenomedullin (ADM) is a 52 amino acid peptide hormone that is associated with cardiovascular, endocrine and renal mechanisms regulating water and electrolyte balance [68]. ADM can reduce the permeability of capillaries during septic shock [11], and plays an important role in the regulation of inflammatory mediators, vascular endothelial barrier and microcirculation stability [11,69]. Because of the rapid degradation and clearance of ADM in the cycle, the measurement of ADM in the cycle becomes complex. MR-proADM has a long half-life and is relatively stable in the circulation, which can directly reflect the level of rapidly degraded active ADM peptide. It has been shown that measuring MR-proADM is more suitable for clinical practice [70].

In fact, patients with decreasing PCT concentrations but continuously high MR-proADM concentrations had a significantly increased mortality risk [71], and MR-proADM had an important function in predicting the development of organ failure over 24 h [72], suggesting that MR-proADM may have important clinical value in the early risk stratification of patients with sepsis. Recent studies have proposed that virus-induced endothelial dysfunction and damage, resulting in impaired vascular blood flow, coagulation and leakage, may partially explain the development of organ dysfunction [73,74]. The assessment of MR-proADM may provide important information to explain the pathophysiological mechanisms of vascular endothelial injury and subsequent organ dysfunction in patients with COVID-19.

Our study found that there was a significant difference in the concentration of MR- proADM between the survivors and the nonsurvivors (P < 0.01), the combined sensitivity was 0.88, and the combined specificity was 0.77. These findings are consistent with those of prior studies [71,75,76]. In a recent narrative review [77], directly testing for MR-proADM in the emergency department could contribute to improving the prognostic assessment of patients with sepsis. Spoto et al [78] conducted a retrospective analysis of MR-proADM in 571 consecutive patients with sepsis and found that MR-proADM cut-off values > 3.39 nmol/L in sepsis and > 4.33 nmol/L in septic shock were associated with a significantly higher risk of 90-day mortality. MR-proADM had the strongest association with mortality across all Sepsis-1 and Sepsis-3 subgroups and could facilitate a more accurate classification of low and high disease severity [71]. In our study, 8 studies used OR, and 4 studies used HR as an effect measure to indicate that MR- proADM can be an independent predictor for mortality among patients with COVID-19.

Our study showed that MR-proADM was superior to most biomarkers and critical illness scores in predicting the prognosis of COVID-19 patients [17–19,27,33]. However, few of them indicated the sensitivity and specificity, and we could not calculate the combined effect of each item. A recent study [79] evaluated the usefulness of MR-proADM compared to CRP, PCT, and ferritin in the prognosis of influenza A (H1N1) pneumonia, and found that the initial MR-proADM, ferritin, CRP, and PCT levels effectively determined adverse outcomes and risk of ICU admission and mortality in patients with influenza virus pneumonia. MR-proADM has the highest potency for survival prediction (AUC = 0.853, p < 0.0001). The recently published TRIAGE study [80] is a multinational, prospective, observational cohort study that included consecutive medical patients presenting with a medical urgency at three tertiary-care hospitals. A total of 7,132 patients were included in the final analysis. The study found that MR-proADM was the best biomarker, especially for mortality prediction. Another study [71] indicated that the initial use of MR-proADM within the first 24 h after sepsis diagnosis resulted in the strongest association with short-term, mid-term and long-term mortality compared to all other biomarkers or clinical scores. Other studies also yielded similar results [81,82]. Recently, a meta-analysis suggested that MR-proADM testing alone is poor at identifying invasive bacterial infections in young children [83], which may be related to the population under study, the measurement time and other factors. In addition, it may be more meaningful to determine the time trend of MR-proADM levels in septic patients with pulmonary infection [75].

There are some limitations in our study. First, selection bias and information bias are easily generated because of the observational design and different research locations. Second, there was considerable heterogeneity in some analyses, mainly due to the significant differences in the baseline patient characteristics. Third, converting the median to an average also affects our results. Due to the limited number of articles included, our analysis results may not be accurate, and more studies need to be included for verification in the future.

MR- proADM was associated with mortality in patients with COVID-19, and risk assessment using MR- proADM allows clinicians to identify patients with COVID-19 who are at higher risk of adverse clinical outcomes.

COVID-19, coronavirus disease 2019

SARS-CoV-2, Severe Acute Respiratory Syndrome Coronavirus 2

MR-proADM, Mid-regional Proadrenomedullin

PRISMA, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses

CNKI, Chinese National Knowledge Infrastructure

QUADAS-2, The Quality Assessment of Diagnostic Accuracy Studies

SD, standard deviation

WMD, weighted mean difference

CI, confidence interval

IQR, interquartile range

ICU, intensive care unit

IMCU, intermediate care unit

AUC, the area under the curve

SOFA, the Sequential Organ Failure Assessment

APACHEIV, Acute Physiological and Chronic Health Evaluation IV

CURB-65, Confusion blood Urea nitrogen Respiratory rate Blood pressure age 65 or older

cTNT, cardiac troponin T

CRP, C-reactive protein

PCT, procalcitonin

CT-proET-1, C-terminal proendothelin-1

IL-6, interleukin-6

SAPSII, Simplified Acute Physiology Score II

APACHE II, the Acute Physiology and Chronic Health Evaluation II score

ARDS, acute respiratory distress syndrome

LDH, lactate dehydrogenase

NT-proBNP, N-terminal pro-B-type natriuretic peptide

ADM, Adrenomedullin

Ethics approval and consent to participate

Not applicable.

consent for publication

Not applicable.

Availability of data and materials

The data that support the findings of this study are included in this published article and its supplementary material.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Funding

This work was not supported by any funding.

Contributions

NW and LXL performed the data analysis, and drafted the manuscript. WH and NS were responsible for literature research. JYL and ZQ conducted data acquisition and extracted all of the raw date. XXD designed the study and helped to revise manuscript. All authors read and approved the final manuscript.

Acknowledgments

The authors thank all staff of the emergency department of China rehabilitation research center, Capital Medical University.

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Circulating Mid-regional Proadrenomedullin is a predictor of mortality in patients with COVID-19: a systematic review and meta-analysis

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Meta-analysis Of The Effects Of Mr-proadm On Mortality

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