key: cord-0759532-3m8htj0u authors: Papadopoulos, V. P.; Avramidou, P.; Bakola, S.-A.; Zikoudi, D.-G.; Touzlatzi, N.; Koutroulos, M.-V.; Filippou, D. K. title: Mortality of Diabetes-related Acute Metabolic Emergencies in COVID-19 patients: a systematic review and meta-analysis date: 2021-01-15 journal: nan DOI: 10.1101/2021.01.12.21249697 sha: fc0905e63d16934b4e7d904f90eb5f184e870306 doc_id: 759532 cord_uid: 3m8htj0u Purpose: Little is known on the mortality rate in COVID-19 related acute metabolic emergencies, namely diabetic ketoacidosis (DKA), hyperglycaemic hyperosmolar state (HHS), combined DKA/HHS, and euglycaemic diabetic ketoacidosis (EDKA). Methods: A systematic literature review was conducted using EMBASE, PubMed/Medline, and Google Scholar from January 1, 2020 to January 9, 2021 to identify all case report series, cross-sectional studies, and meta-analyses of case reports describing mortality rate in DKA, HHS, and EDKA, in COVID-19 patients. The Joanna Briggs Institute critical appraisal checklist for case reports was used for quality assessment. Results: From 313 identified publications, 4 fulfilled the inclusion criteria and analyzed qualitatively and quantitatively. A systematic review and meta-analysis with subgroup analyses examined mortality rate in a total of 152 COVID-19 patients who had developed DKA, HHS, combined DKA/HHS, or EDKA. Combined mortality rate and confidence intervals (CI) were estimated using random effects model. The study was registered to PROSPERO database (ID: 230737). Results: Combined mortality rate was found to be 27.1% [95% CI: 11.2-46.9%]. Heterogeneity was considerable (I2=83%; 95% CI: 56-93%), corrected to 67% according to Von Hippel adjustment for small meta-analyses. Funnel plot presented no apparent asymmetry; Eggers and Beggs test yielded in P=0.44 and P=0.50, respectively. Sensitivity analysis failed to explain heterogeneity. Conclusion: COVID-19 related acute metabolic emergencies (DKA, HHS, and EDKA) are characterized by considerable mortality; thus, clinicians should be aware of timely detection and immediate treatment commencing. Diabetes mellitus (DM) has been recognized as a major risk factor for unfavorable outcomes in patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1] . The underlying pathophysiology of COVID-19 and DM intertwining has not been totally explained; however, diabetes patients have an increased risk of infection and acute respiratory distress syndrome compared with the general population [2] COVID-19 is associated with hyperglycaemic emergencies as diabetic ketoacidosis (DKA), hyperglycaemic hyperosmolar State (HHS), euglycaemic diabetic ketoacidosis (EDKA), and combined DKA/HHS [8] [9] . The over-activity of immune system might further explain COVID-19-related severe and resistant to conventional therapy DKA episodes [10] . High mortality in COVID-19 and diabetic ketoacidosis has been reported in a single letter [11] . In contrast, two small case series exhibited significantly lower mortality rates that range from 7.7% [8] to 12.9% [12] . Additionally, a few dozen of case reports concerning acute emergencies related to glucose metabolism in COVID-19 patients have been reported, all reviewed in a very recent meta-analysis [13] . The present study aimed to provide further evidence regarding the mortality rate in COVID-19-related acute metabolic emergencies (DKA, HHS, combined DKA/HHS, and EDKA) by identifying all relevant studies and summarize their results. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint three couples were blinded to each other's decisions. D.F. closely observed the process and was responsible for any discordance. The Joanna Briggs Institute (JBI) critical appraisal checklist for case reports, which includes 8 questions addressing the internal validity and risk of bias of case reports designs, particularly confounding and information bias, in addition to the importance of clear reporting, was used for quality assessment of case series [16] [17]. All studies that failed to fulfill requirements of first six questions were considered as of "suboptimal quality"; controversially, an "optimal quality" remark was given. Moreover, the JBI critical appraisal list for case control studies, which includes 12 questions addressing the internal validity and risk of bias of case control studies, was used for quality assessment of case series [16] [17]. All studies that were characterized as of "fair" or "poor" quality were considered as of "suboptimal quality"; controversially, an "optimal quality" remark was given. Furthermore, quality of evidence was approached using GRADE (Grading of Recommendations, Assessment, Development and Evaluations), transparent framework for developing and presenting summaries of evidence [18] [19] [20] . GRADE level of evidence was rated down for risk of bias, imprecision, inconsistency, indirectness, and publication bias, whereas was rated up for large magnitude of effect. The process was carried out by six reviewers (V.P., M.-V.K., N.T., S.-A.B., P.A., D.-G.-Z.) who performed quality assessment as three independent couples of investigators; the process performed manually and the three couples were blinded to each other's decisions. In case of disagreement within a couple, D.F, who closely observed the process, was responsible to dissolve any discordance. Data synthesis was performed using MedCalc® Statistical Software version 19.6 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org; 2020). As effect estimates, mortality rates were extracted from each study and combined together using the random effects, generic inverse variance method of DerSimonian and Laird, which assigned the weight of each study in the pooled analysis inversely to its variance [21] . Randomeffects model allows generalizing common effect size beyond the (narrowly defined) population included in the analysis [22] . However, as I 2 has a substantial bias when the number of studies is small (positive when the true fraction of heterogeneity is small and negative when the true fraction of heterogeneity is large), the point estimate I 2 should be interpreted cautiously when a meta-analysis has few studies; in fact, in small metaanalyses, confidence intervals should supplement or replace the biased point estimate I 2 [23] . Analysis of publication bias (small size effect) was performed by funnel plot visualization for asymmetry and use of Egger's and Begg's tests. Heterogeneity was based on Q test and I 2 ; Q test P value <0.10 and/or I 2 >50% was indicative of significant heterogeneity and was further analyzed. Analysis of heterogeneity was performed through sensitivity analysis focusing on types of studies, types of acute metabolic emergencies, quality assessment, and GRADE level of evidence to seek whether qualitative or quantitative interaction exists. Univariate comparisons were performed with the use of Pearson's Chi-square test for discrete variables. All is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. All characteristics regarding title of the study, name of the first author, country where the study was conducted, type of diabetes-related acute metabolic emergency, total number of survivors, total number of non-survivors, and mortality rate were analytically presented in Table 1 . Quality remarks are provided in Table 1 ; all details concerning quality assessment items as well as GRADE level of evidence are depicted analytically in Table 2 and Table 3 , respectively. Combined mortality rate was found to be 27.1% [95% CI: 11.2-46.9%] ( Figure 2 ). Heterogeneity was considerable (I 2 =83%; 95% CI: 56-93%), corrected to 67% according to Von Hippel adjustment for small metaanalyses; this value was based on an approximation for I 2 =80% yielding a real value 64%, and consequently, an bias leading to 16% overestimation (Supplementary Figure 1 ). No significant publication bias (small size effect) was detected as funnel plot presented no apparent asymmetry. Moreover, both Egger's and Begg's tests yielded an insignificant result (P=0.44 and P=0.50, respectively). Sensitivity analysis was carried out according to: i) study type (meta-analyses included vs excluded), ii) emergency type (DKA patients included vs excluded, EDKA patients included vs excluded, HHS patients included vs excluded, DKA/HHS patients included vs excluded), iii) quality assessment (studies of "suboptimal" quality included vs excluded), iv) GRADE level of evidence (studies of "very low" level of evidence excluded vs included); furthermore, sensitivity analysis was performed at single study level. There was no difference as deduced by the inspection of the relevant confidence intervals and thus, sensitivity analysis failed to explain the observed heterogeneity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint Our findings are in keeping with a recent meta-analysis of 41 case reports carried out by our team, which yielded a mortality rate of 32.4% among 68 patients with known outcome [13] . We are totally aware that including a self-report in a meta-analysis can import a severe bias. However, there are at least four reasons which alleviate this danger: first, the meta-analysis of Papadopoulos et al. exhibits the least deviation from the vertical line of the funnel plot, representing the mean; second, sensitivity analysis did not reveal any profound difference regarding combined mortality rate and I 2 ; third, it is of "optimal" quality and has a GRADE "low" level of evidence, namely the best that a study of such a kind can achieve at first; fourth, it is the most Alkundi et al. report the very intriguing -if not controversial -finding that COVID-19 patients presented with DKA, when compared with COVID-19 patients who had not developed DKA, were more likely to survive (P=0.046). Their analysis was carried out with the use of Kaplan-Meier survival curves. However, the authors did not adjust their finding for potent confounders, using Cox-regression, most probably due to the small number of sample size. As a matter of fact, their result needs at least to be considered cautiously and has to be further evaluated in larger studies [12] . The major limitation of the present study might be dual: first, the combination of data from different kind of studies, namely two case report series, one case-control study, and one meta-analysis of 41 case reports; second, the very small number of studies included. However, as the topic is totally novel, any study that respects adherence to protocol followed, investigates causes of heterogeneity, and assesses the impact of risk of bias on the evidence synthesis might be valuable [24] . A serious query could focus on the decision to proceed to the meta-analysis despite the considerable amount of heterogeneity. However, several reasons might support our approach: 1) there was little evidence of publication bias (as funnel plot did not decline from asymmetry), there was no evidence of small size studies effect (as Egger's and Begg's tests were not statistically significant), 3) there was no considerable qualitative interaction. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint Q2: Was the patient's history clearly described and presented as a timeline? Q3: Was the current clinical condition of the patient on presentation clearly described? Q4: Were diagnostic tests or assessment methods and the results clearly described? Q5: Was the intervention(s) or treatment procedure(s) clearly described? Q6: Was the post-intervention clinical condition clearly described? Q7: Were adverse events (harms) or unanticipated events identified and described? Q8: Does the case report provide takeaway lessons? . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. ; https://doi.org/10.1101/2021.01.12.21249697 doi: medRxiv preprint is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint The copyright holder for this this version posted January 15, 2021. corrects 80% to ~64% in case that the number of included studies is n = 4; consequently, I 2 =83 is estimated to be corrected to ~67%. . 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