key: cord-0743754-0y9xfmtw
authors: Gozdas, Hasan Tahsin; Kayis, Seyit Ali; Damarsoy, Tugce; Ozsari, Emine; Turkoglu, Mustafa; Yildiz, Isa; Demirhan, Abdullah
title: Multi-inflammatory Index as a Novel Mortality Predictor in Critically Ill COVID-19 Patients
date: 2022-05-11
journal: J Intensive Care Med
DOI: 10.1177/08850666221100411
sha: 00f72392cd6c829c4f7acf7686bae523fd1969fd
doc_id: 743754
cord_uid: 0y9xfmtw

AIM: Systemic inflammation has a crucial role in the pathogenesis and mortality of Coronavirus disease 2019 (COVID-19). Multi-inflammatory index (MII) is a novel index related with systemic inflammation. In this study, we investigated the relationship between MII and in-hospital mortality in COVID-19 patients admitted to the intensive care unit (ICU). METHODS: We retrospectively analyzed the medical records of COVID-19 patients followed-up in the ICU of our institution between 01.04.2020 and 01.10.2021. Patients were classified into two groups according to mortality status as survivors and non-survivors. Various inflammatory parameters of the groups were compared and their efficacy in predicting mortality was investigated. RESULTS: Out of 348 study patients, 86 cases (24.7%) were in the survived group and 262 cases (75.3%) were in the dead group. The median age of the mortal group was significantly higher than that of the survived group (65.5 vs 76, P < .001). Multiple logistic regression analysis revealed that among all the included inflammatory parameters, MII showed the best efficacy for predicting mortality (OR: 0.999; 95% CI: 0.9991-0.9998; P = .003). CONCLUSION: MII, a new combination of Neutrophil to lymphocyte ratio (NLR) and C-reactive protein (CRP), is a simple and practical biomarker that can help us in the prediction of mortality in COVID-19 patients followed-up in the ICU.

Coronavirus disease 2019 (COVID-19) which is still a global threat is a highly contagious viral disease primarly affecting the respiratory system. The causative agent is a novel coronavirus named as SARS-CoV-2. The disease has spread all over the world within a very short time period which has seriously affected health, social life, education, and economy. The most important cause of short term morbidity and mortality is viral pneumonia which can immediately progress to acute respiratory distress syndrome. 1 Neutrophils are the most important cells which firsly appear in infections. They protect against viral invasion, prevent viral replication and spreading. At the same time, neutrophils have negative effects on the host during viral infection. 2 Immune response against viral infection is mainly established by lymphocytes. In COVID-19 patients, decrease in lymphocyte count may be related to lymphocyte consumption, destruction of lymphatic tissues, and cytokine-induced T-cell apoptosis. Severe lymphopenia is a sign of worse outcome in COVID-19. 3 C-reactive protein (CRP) is one of the positive acute phase proteins. It is produced in the liver against infection and inflammation. Previous studies showed that CRP levels seriously increase in critical situations such as cancers and critical infections as well as 5 In symptomatic patients with COVID-19, SARS-CoV-2 triggers the inflammation cascade which leads to increase in the levels of inflammatory biomarkers such as CRP and ferritin, which is usually balanced by the the host's immune system whereas in some individuals SARS-CoV-2 causes excessive release of proinflammatory cytokines resulting in hyperinflammation which can not be controlled by the host's immune system. 6 Levels of the coagulation parameters such as fibrinogen and D-dimer also increase as the disease progresses while lymphocyte counts and albumin levels gradually decrease. Systemic inflammatory burden and subsequent disseminated thrombosis as a result of severe sepsis eventually cause cytokine storm which is implicated to be responsible for the clinical deterioriation of COVID-19 patients. 7, 8 Severe COVID-19 cases developing hyperinflammation and cytokine storm have greater levels of systemic inflammatory markers. Neutrophil to lymphocyte ratio (NLR), mean platelet volume to platelet ratio (MPR), mean platelet volume to lymphocyte ratio (MLR) and platelet to lymphocyte ratio (PLR) are novel systemic inflammatory markers. These hemogram based inflammatory parameters are strong predictors of mortality in critically ill patients as well as COVID-19. [9] [10] [11] [12] [13] [14] Multi-inflammatory index (MII) is a novel inflammation related index created firstly by Gardini et al. 15 It is calculated by the multiplication of NLR and CRP which were previously studied individually in COVID-19 patients. Both of them were found useful in predicting mortality. 5 COVID-19 patients admitted to intensive care unit (ICU) carry high risk for mortality, so it is important to predict mortality earlier in this critical population. MII is a combination of both NLR and CRP, 15 hence we investigated the role of MII in predicting mortality in COVID-19 patients in the ICU.

We retrospectively analyzed the data of COVID-19 patients followed-up in the adult ICU of our institution between 01.04.2020 and 01.10.2021. COVID-19 was diagnosed with positive nasopharyngeal swab PCR result. Criteria for ICU admission were sepsis, septic shock, respiratory failure (requiring mechanical ventilation), acute respiratory distress syndrome, or multiple organ failure. Some patients were excluded from the study due to pregnancy, cirrhosis, nephrotic syndrome, hematological disease, terminal malignancy and absent laboratory results.

Venous blood samples were collected from all patients at the entry to ICU. Complete blood count parameters were measured in the tubes containing ethylenediamine tetraacetic acid (EDTA) as an anticoagulant by Sysmex XN-1000 hematology analyzer. Biochemical tests other than ferritin and troponin were measured in the tubes containing clot activator by Abbott Architect c8000 analyzer after centrifugation. Ferritin and troponin were tested in the tubes containing clot activator by Abbott Architect i2000SR analyzer after centrifugation. Coagulation parameters were tested in the tubes containing sodium citrate as an anticoagulant by Sysmex CS-2500 system.

Different treatment protocols were administered during the course of the pandemic. From the beginning until the end of the study, hydroxychlorine, hydroxychlorine plus favipiravir, favipiravir, and favipiravir plus high dose corticosteroids were used against COVID-19, respectively.

The patients were divided into two groups according to mortality status as survivors and non-survivors. Demographic and clinical data, routine laboratory results and various inflammatory parameters of the groups were compared.

The formulas of the inflammatory parameters are as follows:

Neutrophil to lymphocyte ratio (NLR) = Neutrophil count/lymphocyte count Platelet to lymphocyte ratio (PLR) = Platelet count/lymphocyte count

Mean platelet volume to platelet ratio (MPR) = Mean platelet volume/platelet count Mean platelet volume to lymphocyte ratio (MLR) = Mean platelet volume/lymphocyte count

Urea to albumin ratio (UAR) = Urea/albumin Lactate dehydrogenase-to albumin ratio (LAR) = Lactate dehydrogenase/albumin C-reactive protein to albumin ratio (CAR) = CRP/albumin D-dimer to albumin ratio (DAR) = D-dimer/albumin Procalcitonin to albumin ratio (PAR) = Procalcitonin/ albumin Fibrinogen to albumin ratio (FAR) = Fibrinogen/albumin

Multi-inflammatory index (MII) = NLR × CRP 15 Prognostic nutritional index (PNI) = 10 × serum albumin (g/ dL) + 0.005 × lymphocyte count (/mm 3 ) 16 Systemic inflammatory index (SII) = neutrophil count × PLR 17 Platelet mass index (PMI) = MPV × platelet count The local ethics committee of Bolu Abant Izzet Baysal University Medical Faculty approved the study (Decision number: 2021/259). 

Although 380 patients were admitted to our ICU during the study period, 32 patients were discarded from the study according to exclusion criteria. Hence, 348 patients were enrolled in this study. Of these patients, 205 were male (59%) and 143 were female (41%). The median age of the patients was 74 (65-83). There were 86 cases (24.7%) in the survived group Abbreviations: WBC, white blood cell; RDW, red cell distribution width; MPV, mean platelet volume; PDW, platelet distribution width; LDH, lactate dehydrogenase; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate; INR, international normalized ratio; ALT, alanine aminotransferase; AST, aspartate aminotransferase; UAR, urea to albumin ratio; LAR, Lactate dehydrogenase to albumin ratio; DAR, D-dimer to albumin ratio; FAR, fibrinogen to albumin ratio; CAR, C-reactive protein to albumin ratio; PAR, procalcitonin to albumin ratio; PNI, prognostic nutritional index; SII, systemic inflammatory index; MII, Multi-inflammatory index; PMI, Platelet mass index; NLR, neutrophil to lymphocyte ratio; PLR, platelet to lymphocyte ratio; MPR, mean platelet volume to platelet ratio; MLR, mean platelet volume to lymphocyte ratio. and 262 cases (75.3%) in the dead group. The median age of the mortal group was significantly higher than that of the survived group (65.5 vs 76, P < .001). There was not a statistically significant difference between the groups with respect to gender (P = .769). Diabetes mellitus (DM), hypertension (HT), chronic obstructive pulmonary disease (COPD), chronic renal failure (CRF) and malignancy were found to be more frequent in the dead group, however the differences were not statistically significant (P = .080, P = .0236, P = .083, P = .072, P = .092, respectively). On the other hand, cardiovascular disease (CVD) was more frequent in the dead group and the difference was statistically significant (P = .019). Demographic data were presented in Table 1 .

When hemogram based inflammatory parameters were evaluated it was seen that NLR, MPR and MLR were significatly higher in the mortal group compared with the survived group. All of the albumin based inflammatory parameters (UAR, LAR, CAR, DAR, FAR and PAR) were significantly higher in the mortal group compared with the survived group. When prognostic inflammatory indexes were examined, it was seen that PNI, PMI and and MII were significantly higher in the mortal group compared with the survived group. Laboratory data of the study groups were summarized in Table 2 .

Multiple logistic regression analysis revealed that age (OR: 1.072; 95% CI: 1.0414-1.1097; P < .001), NLR (OR: 1.077; 95% CI: 1.0166-1.1506; P = .018), and MII (OR: 0.999; 95% CI: 0.9991-0.9998; P = .003) were independent predictors of mortality. Among all inflammatory parameters, MII showed the best performance in predicting mortality (Table 3 ).

First time with this study, we found MII as an independent predictor of mortality in ICU COVID-19 cases. In addition to this new finding, we also found in our study that advanced age and increased NLR level were the other independent mortality predictors as in agreement with the previous literature. 5 As the neutrophil count usually increases and lymphocyte count decreases in COVID-19, elevated NLR predicts disease severity and mortality. 5 Apart from NLR, many other inflammatory parameters showing systemic inflammation were found to be useful in predicting mortality in COVID-19 patients. [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] [29] The common mechanism of the effect of these parameters to the disease mortality is that systemic inflammation has a crucial role in the pathogenesis and mortality of COVID-19. 6, 8 Hemogram based inflammatory parameters were previously investigated in COVID-19 patients. For example, in a previous study elevated NLR and MPR were found to be associated with mortality. 19 Consistenly, our study supported that these hemogram based parameters were significantly higher in mortal cases compared with survived ones.

Albumin based inflammatory parameters (UAR, LAR, CAR, DAR, FAR and PAR) were also studied in critical illnesses as well as COVID-19 and they were all found to be useful in the prediction of prognosis. [20] [21] [22] [23] [24] [25] [26] Consistent with these studies, we also found that albumin based inflammatory parameters were significantly higher in mortal cases compared with survived ones.

CRP is a positive acute phase protein which was also associtated with the prognosis in COVID-19. Elevated CRP levels were related with poor prognosis and mortality. 5 Our study also showed that CRP levels were significantly increased in mortal COVID-19 cases compared with survived ones.

Various prognostic indexes such as SII, PNI and PMI give an idea about the prognosis of critical diseases as well as COVID-19. [27] [28] [29] In our study, PNI and PMI were found to be useful in the discrimination of mortal COVID-19 cases from survived ones.

MII is a novel prognostic index that was firstly created by Gardini et al. 15 They found it useful in determining the prognosis in colorectal cancer patients. A recent study suggested that this new index plays an important role in distinguishing massive and non-massive pulmonary embolism. 30 In our study, we searched the relationship between MII and ICU mortality in COVID-19 patients and we found that MII was higher in the mortal group which can serve as an independent predictor of in-hospital mortality.

Our study has some limitations. First, this is a retrospective study with single center data and relatively small number of patients. Second, there was some missing data for a few patients, Third, all patients did not receive the same treatment, different treatment strategies were administered because of changing treatment protocols during the pandemic. Lastly, serial measurement of laboratory parameters were not evaluated. However, to the best of our knowledge, our study is the first to demonstrate the relationship between MII and mortality status in critically ill COVID-19 patients.

In conclusion, MII is a simple and practical biomarker that can help us in the early determination of poor prognosis in COVID-19. It is easily obtained from NLR and CRP. Furthermore, it was found superior to NLR or CRP alone in the discrimination of mortal COVID-19 cases. We believe that physicians should be more careful in the management of COVID-19 cases with rising MII levels. More comprehesive and large scale studies are required to validate our results.

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Not applicable, because this article does not contain any studies with human or animal subjects.

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Hasan Tahsin Gozdas https://orcid.org/0000-0003-3857-685X Emine Ozsari https://orcid.org/0000-0001-5842-7849

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