Clinical Predictors of COVID-19 Severity and Mortality: A Perspective

The COVID-19 pandemic has caused huge socio-economic losses and continues to threat humans worldwide. With more than 4.5 million deaths and more than 221 million confirmed COVID-19 cases, the impact on physical, mental, social and economic resources is immeasurable. During any novel disease outbreak, one of the primary requirements for effective mitigation is the knowledge of clinical manifestations of the disease. However, in absence of any unique identifying characteristics, diagnosis/prognosis becomes difficult. It intensifies misperception and leads to delay in containment of disease spread. Numerous clinical research studies, systematic reviews and meta-analyses have generated considerable data on the same. However, identification of some of the distinct clinical signs and symptoms, disease progression biomarkers and the risk factors leading to adverse COVID-19 outcomes warrant in-depth understanding. In view of this, we assessed 20 systematic reviews and meta-analyses with an intent to understand some of the potential independent predictors/biomarkers/risk factors of COVID-19 severity and mortality.


INTRODUCTION
Coronaviruses belong to Coronaviridae family of viruses. The degree of disease caused by coronaviruses can vary from mild like common cold to severe like severe acute respiratory syndrome (SARS) and the middle east respiratory syndrome (MERS). These viruses have been successful in crossing inter-species barriers. SARS-coronavirus jumped from civet cats to humans while MERS-coronavirus got transmitted to humans from camels (Woo et al., 2012). The recent emergence of the novel SARS Coronavirus 2 (SARS-CoV-2) is another incidence of zoonotic transmission of coronaviruses. As per the genomic sequence analysis, the source of novel SARS-CoV-2 is speculated to be a previously identified bat coronavirus strain RaTG13 (96.2-97.41% identity match) (Shi, 2021;Malaiyan et al., 2021) or pangolin-CoV (91.02-92.22% genomic identity match) (Zhang T. et al., 2020;Malaiyan et al., 2021). However, the origin of the SARS-CoV-2 is still unclear due to the lack of definitive evidence. Further investigations are being undertaken in this regard (WHO News release, 2021).
Since the first case reported late in 2019, SARS-CoV-2 has taken more than 4.5 million human lives (as of September 08, 2021) and continues to spread worldwide with more than 221 million confirmed cases (WHO, 2021). The case fatality rate of the disease caused by the SARS-CoV-2 (3.26-4.16% in Latin America; 5.8% in the United States) (Undurraga et al., 2021;Loomba et al., 2021) is way less as compared to the previous coronavirus outbreaks (Zhu et al., 2020). Nevertheless, the fatality caused by Coronavirus Disease 2019  has surpassed that of the SARS and MERS combined (Song et al., 2019). The COVID-19 pandemic has also resulted in huge economic losses (speculated to be trillions of dollars) around the world (Emem, 2020).
COVID-19 initially emerged as novel pneumonia of unknown etiology with majorly non-specific symptoms and quite quickly engulfed the entire globe. During the initial months of the pandemic, lack of specific diagnostic modalities, the variable intensity of the disease surveillance, changing case definitions, asymptomatic period of infection and overwhelmed health care facilities largely contributed to the rapid spread of the virus, resulting in the global outbreak. Also, the novel COVID-19 in a way bridged the gap between the developing and developed world, bringing all on the same footing. With more than 85 million confirmed cases, the Americas are the worst affected, followed by Europe (> 66 million), South-East Asia (> 41 million), the East Mediterranean region (> 15 million), Western Pacific (> 7 million) and Africa (> 5 million) (WHO, 2021). A major breakthrough in the current pandemic period witnessed rapid development and administration of different vaccines against COVID-19. However, despite the massive vaccine roll-out programs, the emergence of virus variants sustains the challenge of controlling the pandemic and continues to spread in its wild-type and mutant forms across the globe.
Since the onset of the disease, several groups have published various systematic reviews and meta-analyses that aim to shed light on the disease prognosis. However, the evidence was limited and the data were mostly heterogenous. Further, due to everchanging viral dynamics, multiple new symptoms have been witnessed. With the generation of more data, it is expected that the analysis will continue with a focus on identifying unique clinical manifestations, laboratory findings, radiological investigations, and therapy that could correlate with varying degree of COVID-19 or adverse outcomes, and fatality. However, the studies published earlier have highlighted the significance of some important biomarkers and clinical features in diagnosis, prognosis and management of mild to severe COVID-19.

METHODOLOGY
In the present work, we aim to identify key players of the disease and summarize important findings from already published studies on diverse clinical aspects of COVID-19. The search terms 'COVID-19', 'SARS-CoV-2', 'clinical predictors', 'signs and symptoms' were used individually or in appropriate combinations and only the 'systematic reviews and/or metaanalysis' articles that were published until February, 2021 were included for the present work. We carefully studied 20 systematic review/meta-analysis/meta-regression articles ( Table 1A) that spanned the global population.
Apart from the above-mentioned somewhat obvious comorbidities, obesity emerged as another major condition that would worsen the outcomes in COVID-19 patients (Földi et al., 2020;Poly et al., 2021). A meta-analysis involving 2770 patients revealed that obesity was a significant risk factor associated with admission to critical care units (OR= 1.21, 95% CI 1.002-1.46) (Földi et al., 2020). Also, the requirement of invasive mechanical ventilation (IMV) was more (up to 78%) for obese patients as analyzed in 509 subjects. A body-mass-index (BMI) of ≥ 25 was a significant risk factor for IMV requirement (OR= 2.63, 95% CI 1.64-4.22) (Földi et al., 2020). Like obesity, psychiatric comorbidities (like anxiety and depression) must also be considered during COVID-19 management. Potential bi-directional associations between psychiatric comorbidities and sleep have been reported (Jahrami et al., 2021), amounting to sleep problems during COVID-19. This may impact the recovery from the disease.
A systematic review and meta-analysis of 36 studies involving more than 20000 patients demonstrated important findings (Del Zompo et al., 2020). With an intent to correlate liver injury with clinical outcomes in COVID-19 patients, the researchers found that nearly 47% of COVID-19 cases had abnormal LFT. They also found that the laboratory tested AST, ALT and total bilirubin were independent predictors of COVID-19 severity and in-hospital mortality ( Table 2) (Del Zompo et al., 2020). However, there was insufficient information on the etiology of pre-existing liver injury in COVID-19 patients at the time of hospitalization. Hence, further prospective cohort studies would be essential to validate these findings.
Other noteworthy biochemical findings are elevated levels of BUN and serum creatinine (SCr) (Shao et al., 2020). A robust meta-analysis recorded significant (p< 0.00001) rise in levels of BUN and SCr in severe COVID-19 cases and non-survivors (Table 1B) (Shao et al., 2020). Increased SCr and BUN values were identified as independent biomarkers for COVID-19 related severity and in-hospital mortality early during the pandemic (Chen et al., 2020;Cheng et al., 2020). However, the rate of severe and fatal cases in the study by Shao et al. was quite high, which could be due to the fact that the studies analyzed represented majorly poor COVID-19 outcomes (Shao et al., 2020). Hence, over-estimation of severity and fatality rate may be a limitation to this otherwise crucial set of findings.

CONCLUSIONS
Identification of high-risk clinical and laboratory features contribute to early prediction, diagnosis and efficient treatment of patients (Li et al., 2021). A fatality rate of 7.7% with about 8% of the COVID-19 patients being asymptomatic was observed during the early pandemic period (Jutzeler et al., 2020). Since, it is difficult to record the exact number of asymptomatic cases, owing to obvious reasons (like no hospital/clinic visit, hence no medical record; or lack of awareness that a potentially fatal disease can be asymptomatic in some patients) such value is deemed to be 6-to 10-fold higher (Jutzeler et al., 2020). Hence, more aggressive antigen detection, as well as serological surveillance of contacts of confirmed COVID-19 patients, is necessary to enable screening and identification of asymptomatic COVID-19 patients. Further, prospective well-planned cohort studies would be necessary to enable further characterization of the overall, genderspecific and/or geographical location-based risk factors. It is imperative to categorize COVID-19 patients based on their comorbidities, like impaired kidney or liver functions or cardiac injury, etc. As discussed in the present work, AKI is a critical complication of COVID-19 and calls for immediate care and monitoring (Shao et al., 2020) to minimize the risk of severity and poor prognosis. Similarly, abnormal LFTs are important early predictors of COVID-19 severity and in-hospital mortality (Del Zompo et al., 2020). Also, pre-existing chronic liver disease, especially cirrhosis, is an indicator of a high risk of mortality. Hence, aggressive interventions for such cases must be exercised. This would enable better patient management and may improve the disease outcome. Measurement of anthropometric parameters, especially BMI, is also recommended for COVID-19 patient management, importantly for patients who are or above 65 years of age (Földi et al., 2020;Poly et al., 2021). Basic hematological screening that can be done with minimal resources can be a lifesaver. The findings that lymphopenia and neutrophilia at the time of hospital admission indicate poor COVID-19 outcome call for routine hematological monitoring. It would enable an early careful intervention in such patients enabling better patient care. Such regular monitoring may also aid in the stratification and the management of risk associated with COVID-19 . Further, it is also important to stratify epidemiological data based on demographic characteristics and risk factors for adverse COVID-19 outcomes, to enable exact and aggressive patient care (Mesas et al., 2020). Based on the analysis in this work, we can conclude that careful monitoring of clinical data, risk factors and disease biomarkers (Israfil et al., 2021) may enable early determination of COVID-19-led severity. Such an early estimate would be helpful in efficient patient management and possibly minimize the related mortality.

AUTHOR CONTRIBUTIONS
JS conceptualized the study, retrieved the articles, analyzed the data and guided inclusion of specific information, drafted and proof-read the manuscript. RR reviewed the data, analyzed the information, tabulated findings, drafted and proof-read the manuscript. MB helped in information retrieval and inclusion of findings. PA provided intellectual inputs and proof-read the manuscript. VS conceived the study, provided intellectual inputs, guided the inclusion of information, proof-read and approved the final version of the manuscript. All authors contributed to the article and approved the submitted version.

FUNDING
JS received institutional support from AIIMS, Bathinda, Punjab, India. RR is presently an independent research fellow (Research Associate) of the Council of Scientific and Industrial Research (CSIR), Government of India. VS received financial support (Faculty Recharge Programme) from the University Grants Commission (UGC), Govt. of India.