In December 2019, Coronavirus disease-2019 (COVID-19) emerged in Wuhan, China, causing novel coronavirus pneumonia.(1) This severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic has been the most destructive of the modern era.

SARS-CoV-2 belongs to the coronaviridae family and is an enveloped, positive single-stranded RNA virus.(2) It shares 80% sequence identity with SARS-CoV and 20% with MERS-CoV, making it highly pathogenic.(3,4) As of September 24, 2022, WHO reported 611,421,786 cases and 6,512,438 deaths worldwide.(5) In India, 4,45,65,526 cases and 5,28,510 deaths were reported by September 25, 2022.(6)

COVID-19 symptoms range from mild fever, cough, myalgia, and fatigue to severe dyspnoea, central cyanosis, and multiple organ failure, increasing mortality risk.(7,8) Co-morbidities like hypertension, diabetes, cardiovascular, and respiratory diseases worsen the prognosis.(9)

WHO has identified 8 variants of interest, with potential for further mutation, highlighting the need for early, reliable, and affordable biomarkers.(10) The triglyceride to High Density Lipoprotein-cholesterol (Tg/HDLc) ratio has been linked to reduced insulin sensitivity(11) and cardiovascular events, serving as a better cardiovascular risk marker than HDLc or LDLc alone.(12)

This study aims to assess the clinical and biochemical markers predicting COVID-19 severity using the TG/HDLc ratio, addressing a gap in rural Indian settings regarding its association with COVID-19 prognosis.

Type of study- An institutional hospital based, cross-sectional retrospective study was carried out in a rural tertiary medical college and hospital.

Study period- The study was conducted from 27th July 2022 to 27th September 2022 after the approval of the institutional ethics committee.

Inclusion and exclusion criteria- Patients whose mortality and sufficient test records were available during the study period were included in the study. Patients whose sufficient records were not available at the time of the study were excluded.

Sample size and data extraction- The records of 270 COVID-19 positive patients (tested through RT-PCR) who were admitted to our hospital setting between April 2021 and June 2021 (3 months) were extracted from the hospital records. Also, records of 152 patients who died due to COVID-19 during the same period were extracted. The details of the patients were recorded in Microsoft Excel and the results of the biochemical tests and immunologic tests (D-dimer, CRP, serum ferritin, LDH, triglycerides, total cholesterol, LDLc, HDLc, and IL-6) performed in those patients were entered in the excel sheet.

All the information extracted from hospital records was kept highly confidential and was used only for the study purpose. The records of the aforementioned patients were analyzed and the triglyceride to HDL cholesterol ratio was calculated in the admitted COVID-19 patients (survivors and non-survivors) and its relation to mortality in all those patients was assessed.

The data entered in an excel sheet was presented in tables and graphs and analysis was done using open epi info, Chi-square test was used to see the association between socio-clinical profile and COVID-19 prognosis; and Mann Whitney U test was used to compare the means of biochemical markers and prognosis as the data was found to be not normally distributed (skewed), also Logistic Regression test was used to determine the predictors of mortality and the significance level was set at p<0.05.

TABLE NO.1: SOCIO-DEMOGRAPHIC PROFILE OF COVID-19 PATIENTS

According to table no.1, the majority of COVID -19 patients belonged to the age group 61 -80 years i.e. 172 patients (40.8%). Among the 422 patients, 260 (61.6%) were males and 162 (38.4%) were females

TABLE NO.2: CLINICAL PROFILE OF COVID-19 PATIENTS

Other*-facial puffiness, loose motion, vomiting, chest pain, pain in abdomen, swelling in eye, convulsion, slurred speech.

The most common complaint with which the patients presented was breathlessness i.e in 109 (25.9%) patients and as inferred from table no.2 and figure no.1, 328 (77.7%) patients had no comorbidity, and among those with co morbidity, hypertension was the most common (58 patients). Most of the patients i.e 205 (48.6%) had spO2 <90% on admission which also reflects on the findings that 305 (72.3%) required O2 support. Among the 422 patients, only 12 (12.8%) were vaccinated and most of them i.e 354 (83.9%) were admitted for less than 15 days as is evident from table 2 and figure no.2. The table no.2 also states that maximum COVID-19 patients were discharged i.e 270 (64%). As per the findings from fig no.3, respiratory illness was the most common complication developed in the admitted patients.

FIGURE NO.1: CO-MORBIDITIES PRESENT IN COVID-19 CASES AND DEATHS

*Respiratory illness includes- Asthama, T.B, COPD

 *The numbers in the figure indicate the no. of patients with the co-morbidity.

FIGURE NO.2: DURATION OF HOSPITAL STAY

FIGURE NO.3: COMPLICATIONS DEVELOPED

        #- Multiple responses, N¹422

        *Other- Shock, Diabetic ketoacidosis, hemiparesis

TABLE NO.3: ASSOCIATION OF CLINICAL PROFILE OF COVID-19 PATIENTS WITH MORTALITY

According to this table, majority of the patients who had participated in study had no co morbidities and the results were also statistically significant. The table also shows that majority of them had spo2 <90% on admission and the same group also had maximum number of deaths and the results were statistically significant. Among the 422 patients, majority of the deaths were from the group that had not taken vaccination and the results were found to be statistically significant.                              

TABLE NO.7: LABORATORY PROFILE OF COVID-19 PATIENTS

The data was found to be not normally distributed (skewed), therefore to compare the means in continuous data of two groups Mann-Whitney U test has been used.

The table no.7 reflects on the findings that the mean triglyceride levels in the dead (238.22) were higher than those who had survived (196.46). Similar results were also found in the mean triglyceride/HDLc ratio (277.68 in dead and 174.28 in discharged), mean IL-6 levels (264.80 in dead and 181.50 in discharged), mean D-dimer values (310.36 in dead and 155.84 in discharged) and mean serum ferritin levels (242.73 in dead and 193.92 in discharged). The results were found to be statistically significant, as the p value was 0.00 in all the above mentioned parameters. The table also states that the mean HDLc values in the discharged (230.24) were significantly higher (p = 0.00) than in the dead (178.21).   

TABLE NO.8: BINARY LOGISTIC REGRESSION TABLE

To determine the predictors of mortality, binary logistic regression test had been used. From table no.8, it has been found that the Tg/HDLc ratio (p=0.00), the D-dimer (p=0.00) and the IL-6 (p=0.00) values are statistically significant.

The present study was conducted to understand the clinical profile of COVID-19 patients and the various biochemical markers that can aid in accurate and early diagnosis. It also emphasizes the need to incorporate the TG/HDLc ratio into routine examinations to predict mortality and the course of COVID-19. In terms of clinical profile, the presence of comorbidities, SpO2 on admission, and vaccination status were found to be statistically significant parameters (p=0.00, p=0.00, p=0.043, respectively). A higher number of patients without comorbidities (77.7%) compared to those with comorbidities (22.3%) was observed, with more discharges in the non-comorbidity group (69.2%). Additionally, patients with SpO2 >90% on admission (51.4%) outnumbered those with SpO2 <90% (48.6%), with the latter group experiencing a higher mortality rate (27.01%). Unvaccinated patients (97.15%) showed significantly higher mortality (151 deaths) compared to the vaccinated group (2.60%), which recorded only one death. Similar findings were reported in a study by Mahendra et al. (2021), where a higher number of patients had comorbidities (61.25%) with increased deaths (66.5%), and the results were statistically significant (p=0.0001) (13). Chauhan et al. (2021) also reported a higher proportion of non-survivors (95.8%) with SpO2 <90% on admission compared to survivors (11.9%) (14).

Regarding the laboratory profile, the mean HDLc levels were significantly higher in discharged patients (230.24) compared to deceased patients (178.21) (p=0.00). Conversely, the mean triglyceride levels (238.42), TG/HDLc ratio (277.68), IL-6 levels (264.80), D-dimer values (310.36), and serum ferritin levels (242.73) were elevated in deceased patients compared to discharged patients, whose respective means were 196.46, 174.24, 181.50, 155.84, and 193.92 (p=0.00 for all). A study by Alcantara-Alonso et al. (2021) reported similar results, with hospitalized patients having lower mean HDLc levels (25.6) than outpatients (40.5) (p=0.009). Their study also showed higher mean TG/HDLc ratios (6.4), D-dimer values (882), and serum ferritin levels (658) in hospitalized patients compared to outpatients, whose respective means were 3.3, 99, and 361, all statistically significant (p=0.005, p=0.001, p=0.002) (15). Similarly, Zhang et al. (2020) observed that the mean HDLc levels were higher in survivors (0.9) than non-survivors (0.7) (p=0.002). They also reported elevated mean triglyceride levels (1.6), TG/HDLc ratios (2.3), IL-6 levels (80), and serum ferritin levels (1362) in non-survivors compared to survivors, who had respective means of 1.3, 1.5, 19, and 683, with statistically significant results (p=0.038, p=0.001, p=0.000, p=0.000) (16).

This study was an attempt to bring into focus the potentiality of the TG/HDLc ratio as a biomarker in predicting COVID-19 outcome, and also to understand the clinical and laboratory profile of COVID-19 patients in rural India. Although not statistically significant, it was observed that the majority of the affected population, as well as the non-survivors belonged to the 61-80 years age group with males being more severely affected than females. Breathlessness was the most common presenting symptom (in 206 COVID-19 cases and 111 COVID-19 deaths), followed by fever (in 164 cases and 89 deaths) in the admitted patients. A large proportion of the admitted patients had no co-morbidities (77.7%). Hypertension as the most common co-morbidity among the affected; followed by Diabetes Mellitus. The majority of the admitted patients had severe disease (spO2<90%). Maximum non-survivors had spO2 less than 90% and survivors had spO2>93% on admission. Vaccines have been highly effective in preventing mortality as 91.7% of the vaccinated patients survived.

The majority of the admitted patients required additional O2 supply. 1-15 days was the most common duration for which the patients were admitted to the hospital. 46.92% of the admitted patients developed complications. The most common complication was respiratory failure, followed by mucormycosis.

Statistically significant association was found between mortality and high triglyceride (TG) levels, TG/HDLc ratio, interleukin-6 (IL-6), D-dimer, and serum ferritin levels. High density lipoprotein cholesterol (HDLc) was found to be statistically lower in the dead. Although high Low density lipoprotein cholesterol (LDLc), Total cholesterol (TC), Very low density cholesterol (VLDLc), Lactate dehydrogenase (LDH), and C-reactive protein (CRP) values were found in the deceased, the results were not statistically significant.

FURTHER SCOPE- This research does not take into consideration the lipid profile of the patients before COVID-19 infection; therefore the decrease in the levels of various biochemical markers before and after infection was not known. As the present study was a cross-sectional study, therefore there was no follow-up of the discharged patients. Also as the number of patients with completed records were limited, patients with incomplete records had to be excluded therefore limiting the sample size.

AKNOWLEDGEMENTS

We thank ICMR-STS for the grant they provided for the study.

1. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet Lond Engl. 2020 Feb 15;395(10223):507–13.
2. Coronaviridae Study Group of the International Committee on Taxonomy of Viruses. The species Severe acute respiratory syndrome-related coronavirus: classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol. 2020 Apr;5(4):536–44.
3. Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020 Mar;579(7798):270–3.
4. Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet Lond Engl. 2020 Feb 22;395(10224):565–74.
5. Coronavirus disease (COVID-19) – World Health Organization [Internet]. [cited 2022 Sep 5]. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019
6. #IndiaFightsCorona COVID-19 [Internet]. MyGov.in. 2020 [cited 2022 Sep 26]. Available from: https://www.mygov.in/covid-19/
7. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet Lond Engl. 2020 Feb 15;395(10223):497–506.
8. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis. 2020 Apr;34:101623.
9. Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020 Aug 1;81(2):e16–25.
10. Aleem A, Akbar Samad AB, Slenker AK. Emerging Variants of SARS-CoV-2 And Novel Therapeutics Against Coronavirus (COVID-19). In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 [cited 2022 Feb 2]. Available from: http://www.ncbi.nlm.nih.gov/books/NBK570580/
11. Bg BD, I ZG, R GD, E TR, G RV, R PF, et al. Triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) index as a reference criterion of risk for metabolic syndrome (MetS) and low insulin sensitivity in apparently healthy subjects. Gac Med Mex [Internet]. 2017 Apr [cited 2022 Feb 4];153(2). Available from: https://pubmed.ncbi.nlm.nih.gov/28474700/
12. Sh Y, Y D, Xl L, Y Z, S L, Rx X, et al. Triglyceride to High-Density Lipoprotein Cholesterol Ratio and Cardiovascular Events in Diabetics With Coronary Artery Disease. Am J Med Sci [Internet]. 2017 Aug [cited 2022 Feb 4];354(2). Available from: https://pubmed.ncbi.nlm.nih.gov/28864368/
13. Mahendra M, Nuchin A, Kumar R, Shreedhar S, Mahesh PA. Predictors of mortality in patients with severe COVID-19 pneumonia — a retrospective study. Adv Respir Med. 2021;89(2):135–44.
14. Chauhan NK, Shadrach BJ, Garg MK, Bhatia P, Bhardwaj P, Gupta MK, et al. Predictors of Clinical Outcomes in Adult COVID-19 Patients Admitted to a Tertiary Care Hospital in India: an analytical cross-sectional study. Acta Bio Medica Atenei Parm. 2021;92(3):e2021024.
15. Alcántara-Alonso E, Molinar-Ramos F, González-López JA, Alcántara-Alonso V, Muñoz-Pérez MA, Lozano-Nuevo JJ, et al. High triglyceride to HDL-cholesterol ratio as a biochemical marker of severe outcomes in COVID-19 patients. Clin Nutr ESPEN. 2021 Aug;44:437–44.
16. Zhang B, Dong C, Li S, Song X, Wei W, Liu L. Triglyceride to High-Density Lipoprotein Cholesterol Ratio is an Important Determinant of Cardiovascular Risk and Poor Prognosis in Coronavirus Disease-19: A Retrospective Case Series Study. Diabetes Metab Syndr Obes Targets Ther. 2020;13:3925–36.
17. Hernández-Alcaraz C, Aguilar-Salinas CA, Mendoza-Herrera K, Pedroza-Tobías A, Villalpando S, Shamah-Levy T, et al. Dyslipidemia prevalence, awareness, treatment and control in Mexico: results of the Ensanut 2012. Salud Publica Mex. 2020 Apr;62(2):137–46.
18. da Luz PL, Favarato D, Junior JRFN, Lemos P, Chagas ACP. High Ratio of Triglycerides to HDL-Cholesterol Predicts Extensive Coronary Disease. Clin Sao Paulo Braz. 2008 Aug;63(4):427–32.
19. Comel AC, Mosaner W, Bragantini D, Lanzafame M. Rapid radiological improvement of COVID-19 pneumonia after treatment with tocilizumab. Infection. 2021 Feb 1;49(1):195–6.
20. Said EA, Al-Reesi I, Al-Shizawi N, Jaju S, Al-Balushi MS, Koh CY, et al. Defining IL-6 levels in healthy individuals: A meta-analysis. J Med Virol. 2021 Jun;93(6):3915–24.