Korelasi Tumor Necrosis Factor - α (TNF-α), Monocyte-to-Lymphocyte Ratio (MLR), dan Mortalitas Pasien COVID-19.

Wijaya, Sandy and dr. Agustin Iskandar, M.Kes, Sp.PK(K) and dr. Catur Suci Sutrisnani, M.Biomed, Sp.PK(K) (2023) Korelasi Tumor Necrosis Factor - α (TNF-α), Monocyte-to-Lymphocyte Ratio (MLR), dan Mortalitas Pasien COVID-19. Magister thesis, Universitas Brawijaya.

Abstract

Kasus COVID-19 yang berat dapat terjadi sebagai akibat dari sindrom badai sitokin yang melibatkan banyak sekali sitokin seperti TNF-α yang memiliki sifat pleiotropic. Pada COVID-19 juga terjadi peningkatan monocyte-to-lymphocyte ratio (MLR). Adanya peningkatan MLR diharapkan dapat menjadi salah satu sarana prediktor luaran pasien. Untuk melihat korelasi antara TNF-α, MLR, dan mortalitas kami melakukan uji regresi logistik, analisis jalur, serta analisis kesintasan. Penelitian ini menggunakan metode deskriptif dengan desain kohort retrospektif. Diagnosis COVID-19 ditegakkan dengan RT-PCR SARS-CoV2 dengan menggunakan sampel usap nasofaring atau orofaring. Pada hari pertama perawatan, sisa serum pasien COVID-19 dikumpulkan, kemudian dilakukan pemilahan berdasarkan kriteria inklusi dan ekslusi berdasarkan rekam medis. Lama rawat, tingkat keparahan, faktor komorbid dan luaran pasien dicatat. Pemeriksaan serologis TNF-α menggunakan ELISA kit (BT-Lab) dan dibaca dengan menggunakan Microplate reader Zenix-320. Data mengenai MLR pada hari pertama perawatan pasien kami dapatkan melalui analisis menggunakan alat Sysmex XN-1000. Data yang terkumpul dianalisis dengan uji normalitas distribusi, uji beda, regresi logistik, analisis jalur, analisis kurva ROC, analisis kesintasan menggunakan Kurva Kaplan Meier, dan Hazard Ratio. Penelitian ini melibatkan 74 pasien COVID-19 yang memenuhi kriteria inklusi. Dari hasil analisis perbedaan TNF-α dan MLR antara pasien survivor dan nonsurvivor COVID-19 keduanya didapatkan hubungan yang bermakna. Analisis mulitvariat regresi logistik menunjukkan kemampuan variabel TNF-α dan MLR dalam memprediksi mortalitas pasien COVID-19 sebesar 31,5% ke dalam model, dan sisanya sebesar 68,5% dipengaruhi oleh faktor lain di luar model. Dari hasil uji multivariat dengan regresi logistik diketahui pula bahwa TNF-α memiliki odd ratio yang signifikan terhadap mortalitas pasien COVID-19 (p=0,015; OR 1,013 (1,003 – 1,024)). Pada MLR juga berpengaruh signifikan terhadap mortalitas pasien COVID-19 (p=0,010; OR 6,662 (1,586 – 27,988)). Selain menggunakan regresi logistik, analisis jalur dapat digunakan untuk menggambarkan hubungan dan prediksi antara kematian (outcome) dengan TNF-α dan MLR. TNF-α dan mortalitas berhubungan signifikan (p=0.000) dengan nilai t hitung sebesar 3.670. Koefisien regresi dari TNF-α terhadap luaran adalah 0.314. Kemudian analisis jalur antara MLR dan luaran menunjukkan adanya hubungan yang signifikan (p=0,000) dengan nilai t hitung sebesar 3,936. Koefisien regresi dari MLR terhadap luaran adalah 0,263 Untuk memprediksi mortalitas, dilakukan juga analisis AUROC TNF-α dan didapatkan AUC 67,6% (95% CI 55,5% - 79,7%) dengan nilai P=0,009. Dari analisis kesintasan, kelompok penderita COVID-19 non-survivor dengan kadar TNF-α <32,4 ng/L terdapat 37,8% event yang lebih rendah daripada kelompok non-survivor dengan kadar TNF-α ≥32,4 ng/L terdapat 56,8% event. Pada kadar TNF-α <32,4 ng/L didapatkan rerata survival 24,3 hari dan median survival 28 hari, lebih panjang daripada kelompok kadar TNF-α ≥32,4 ng/L dengan rerata survival 16 hari dan median survival 11 hari. Hazard ratio (HR) kelompok TNF-α ≥32,4 ng/L

English Abstract

Severe cases of COVID-19 can occur as a result of cytokine storm syndrome involving numerous cytokines, such as TNF-α, which exhibits pleiotropic properties. COVID-19 also leads to an increase in the monocyte-to-lymphocyte ratio (MLR). The elevated MLR is expected to serve as one of the predictors of patient outcomes. To examine the correlation between TNF-α, MLR, and mortality, we conducted logistic regression analysis, path analysis, and survival analysis. This study utilized a descriptive method with a retrospective cohort design. The diagnosis of COVID-19 was confirmed using RT-PCR for SARS-CoV-2 with nasopharyngeal or oropharyngeal swab samples. On the first day of treatment, residual serum from COVID-19 patients was collected and sorted based on inclusion and exclusion criteria obtained from medical records. Length of hospital stay, severity level, comorbid factors, and patient outcomes were recorded. TNF-α serological testing was performed using an ELISA kit (BT-Lab) and read using a Zenix-320 Microplate reader. Data on MLR on the first day of patient treatment were obtained through analysis using the Sysmex XN-1000 instrument. The collected data were analyzed using tests for normal distribution, difference analysis, logistic regression, path analysis, ROC curve analysis, survival analysis using the Kaplan-Meier curve, and Hazard Ratio. This study involved 74 COVID-19 patients who met the inclusion criteria. The analysis revealed significant associations between TNF-α, MLR, and both survivor and non-survivor COVID-19 patients. Multivariate logistic regression analysis demonstrated that the variables TNF-α and MLR accounted for 31.5% of the ability to predict mortality in COVID-19 patients within the model, while the remaining 68.5% was influenced by other factors outside the model. The multivariate analysis with logistic regression also revealed that TNF-α had a significant odds ratio for COVID-19 patient mortality (p=0.015; OR 1.013 (1.003 - 1.024)). MLR also significantly affected COVID-19 patient mortality (p=0.010; OR 6.662 (1.586 - 27.988)). In addition to logistic regression, path analysis was used to describe the relationship and prediction between mortality outcome and TNF-α and MLR. TNF-α and mortality were significantly associated (p=0.000) with a t-value of 3.670. The regression coefficient of TNF-α on the outcome was 0.314. Furthermore, the path analysis between MLR and the outcome showed a significant relationship (p=0.000) with a t-value of 3.936. The regression coefficient of MLR on the outcome was 0.263. To predict mortality, an AUROC analysis was conducted for TNF-α, resulting in an AUC of 67.6% (95% CI 55.5% - 79.7%) with a p-value of 0.009. From the survival analysis, the non-survivor group of COVID-19 patients with TNF-α levels <32.4 ng/L had a lower event rate of 37.8% compared to the non-survivor group with TNF-α levels ≥32.4 ng/L, which had an event rate of 56.8%. In the <32.4 ng/L TNF-α group, the average survival was 24.3 days with a median survival of 28 days, longer than the group with TNF-α levels ≥32.4 ng/L, which had an average survival of 16 days and a median survival of 11 days.

Item Type:	Thesis (Magister)
Identification Number:	0423060013
Subjects:	600 Technology (Applied sciences) > 616 Diseases > 616.07 Pathology
Divisions:	Profesi Kedokteran > Spesialis Patologi Klinik, Fakultas Kedokteran
Depositing User:	Endang Susworini
Date Deposited:	01 Nov 2023 06:56
Last Modified:	01 Nov 2023 06:56
URI:	http://repository.ub.ac.id/id/eprint/204191

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