Inflammation is an essential feature in the pathology of pneumonia [1] and Steroid benefits remains unclear [2, 3]. Pneumonias cause Hypoxia, respiratory failure and are associated with increased hospitalisation and Mortality [4, 5]. Meta analysis of Steroid use in pneumonias results in reduced mortality, decreased need for Mechanical ventilation and decreased length of Hospitalisation and RCTs for CAP shows steroids reduce treatment failure [6]. Understanding role of steroids in Pneumonia and its consequences yewande et al advised Biomarker informed concordant use associated if CRP is more than 150mg/l.

Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales [7]. CURB 65 identifies high probability of death but do not assess comorbidities and PSI underestimates risk of death in young. Both do not include host immune responses. Initial cytokine profile(IL-6,8,PCT and not CRP) and markers reflect severity and host immune response [8].CRP did not correlate with PSI and CURB [9] but the R Menendeze  study[7] confirms initial biomarkers correlation in the 30 day mortality and CRP improved diagnostic value of PSI and CURB 65 [7].

The Benefits of corticosteroids in community acquired pneumonia is documented many studies. The limited use and variable response in critically ill CAP and its inability to identify patients who benefit steroids form anti-inflammatory effects is unclear. Studies evaluating the role of biomarker-titrated adjuvant corticosteroid administration in COVID is lacking [12].

The COVID pandemic in 2019 due to COVID-19/SARS-Cov-2 caused highly infectious respiratory disease and with high case fatality in critically infected individuals [3].  The outcome of COVID is uncertain particularly in early days of the Pandemic because of the new outbreak of the disease and unexposed population to the novel corona virus infection. The pathological process, Diagnostic methods and the predictive outcome was still tentative and experimental. While outcome predication was uncertain RT-PCR, CT, CXR, Biomarkers were utilized in Diagnosis and predicting severity in the Routine clinical signs and symptoms. Mortality at 28 days in sever COVID was 61% as reported early by Yang et al [4]. Many mild COVID infections also had abrupt or rapid progression in late part of the disease and hence a simple and efficient predicator was needed to identify disease progression to reduce mortality.

The cytokine strom in COVID is responsible for the disease progression and can be identified by CBC,NLR,CRP,Procalcitonin and D-dimer. Studies showing CRP as prognostic markers of Mortality has been documented in Swedish multicentre study [5].Deregulation of Immune system in COVID and its clinical characteristics have been studied (6). Few studies valuated role of CRP in COVID include prognostic value of CRP by Xiamin luo (ref) and CRP in early COVID by l Wang [7].

• Retrospective single centre study.

• Period; September to October 2020.

All COVID patients meeting Criteria for COVID admissions were included and those requiring treatment with remdesivir was initiated as per guidelines of ICMR and the Institution protocols. Patients without CRP within 48 hours of admission were excluded. The outcome of the disease and other parameters were revived and recorded for analysis.

Data information of COVID patients were retrieved through case and Electronic records for Basic Epidemiological characteristics, age, sex, comorbidities, Personal habits, pervious history of illness and days of hospitalisation and outcomes. The outcomes of COVID disease is recorded as Cured/Recover, post discharge oxygen requirement, NIV support during hospitalisation, Death and Duration of stay. Secondary outcomes are category of disease and CXR scoring.

Laboratory results

CBC, NLR, PC, SII, D-dimer, Ferritin. 

Statistical Analysis

SPSS software, Categorical data presented as number and % and Compared by Chi-square test. The Normal distribution of continuous variables evaluated by Kolmogorm-Smirov test. Variables described as Mean/median.

All registered patients were analysed and 204 patients were identified for analysis during the period evaluated for the study. Criteria for COVID admissions were based on Guidelines and severity and patients requiring treatment with Remdesivir. Many were excluded due to lack of CRP at or within 48 hours of Admission.Males; 132 and Females: 72. Males had more COVID admissions.

Table 5 showed In Younger age group and age group between 45 to 60 cure rates is better-100% and in age >75 cure rates is only 86%. Table 7 showed Amount of Diabetes in COVID patients is 66 out of 204 (32%). Cure rates in Diabetes are 82% and is not significant Risk factor for cure outcome. Table 8 depicted that Number of hypertensions in covid patients is 55/204 (27%). cure rate in Hypertensive covid patients is 86% and is not significant risk factor for cure outcome. Table 9 depicted that Number of COPD in COVID patients is 15/204 (7%) cure rate in COPD patients are 100% and is not significant risk factor for cure outcome. Table 10 depicted that. Not cured and on ventilation, but initially on oxygen therapy is 7/26 (27%), not cured and not on ventilation is 19/26 (73%). Patients on supplemental oxygen and on ventilation the cure rate is 0, whereas patients not on supplemental oxygen and not on ventilation is 90%. Significant finding. Table 11 depicted that Patients on NIV and cured are 10/18 (56%).  Patients not on NIV and used supplemental oxygen are 157/167 (87%).  More cure rates among patients without NIV.

Table:1 Age Distribution of COVID pts

Table :2 Comorbidities Table in COVID pts

Table: 3 outcomes in COVID pts

Table: 4. Length of hospitalisation in COVID pts measured in terms of Outcome

Table 5: Cure rates in age subgroup population of COVID. 

Table 6:  Distribution of Cure rates in Gender division is not significant.

Table 7: Comorbidities and COVID

Table 8. Comobidities and covid.

Table 9: Comorbidities and COVID

Table 10: Comparison of cure and patients on supplemental oxygen therapy requiring ventilation.

Table 11: Comparision of cure and NIV out comes.

Table 12: Logistic regression of outcomes in COVID patients explains risk.

Table:13. Showing Initial characteristics in COVID pts with CRP more than 45

Table: 14 Showing outcomes in COVID pts with CRP more than 45.

Table: 15 Showing Initial characteristics in COVID pts with CRP less than 45.

Table 16: Showing outcomes in COVID pts with CRP less than 45

Presence of independent Risk factors is associated with adverse Clinical outcome as evidenced by increased WBC, Neutrophilic Count, NLR, SII, CRP, Procalcitonin and D-dimer and decreased RBC, lymphocyte count and platelet count in non survivors and severs COVID disease. (8, Xiaomin luo) 

Independent risk factors in COVID used as outcome predictors and discriminators of severity (8, Xiaomin Luo): such as NLR, SII, procalcitonin and D-dimer. But CRP is better and simple measure.

An CRP of 41.4 has Sensitivity (SN) of 90.5% and Specificity (SP) of 77.6% in predicating adverse outcome in COVID with positive predictive value (PPV) 61.3 and Negative predicative value(NPV) 95.4%.(8,9, Xiaomin Leo). An CRP of 81 has Sensitivity (SN) of 100% and Specificity (SP) of 95.6 % in predicating adverse outcome in Covid with positive predictive value (PPV) 40 and Negative predicative value (NPV) 100%. Median age in non survivors is--- and median age in survivors is-. Older individuals are more prone for severe Covid disease [10,11,12] and is associated with increased neutrophiic count (used as Moderate predictor), but difficult to rule out or attribute to secondary infections, stress, Glucocorticoids uses in disease progression. Decreased Lymphocyte count is critical factor associated with Severe COVID and increased mortality and Probably Cytokine storm (Mechanism- Decreases CD$ and CD* T cells due to ovr activation contribute to impaired immunity and disease progression).

NLR is an Inflammatory index and is increased in Sepsis, MODs (13) and also disease progression   predictor [14]. CRP is one of the typical acute phase reactants increased with inflammation, cell/tissue injury/damage. Inflammatory Pulmonary diseases raise CRP in response to cytokines (pro-inflammatory [21] IL-1,6, TNF-alpha [16,17]. Increased CRP predicts disease progression at time of admission and predicts risk of worsening COVID as per Sweeta Gupta study. Also, CRP exhibits anti-inflammatory effects and inhibits neutrophiic Chemotaxis [30].

CRP in ARDS/ALI [18,19]- Adults with high CRP in ARDS/ALI have favourable response [22] but elderly patients in ALI and High CRP have higher mortality [23] inmany studies with covid (xiamin Luo). Tissue damage and MODS in COVID cause increase Inflammatory response and progression of disease [20] contributing to Mortality and Morbidity.

1. Martinez, Martinez, R., et al. "Factors associated with inflammatory cytokine patterns in community-acquired pneumonia." European Respiratory Journal, vol. 37, no. 2, 2011, pp. 393–399.

2. Pastores, S.M., et al. "Guidelines for the diagnosis and management of critical illness-related corticosteroid insufficiency (CIRCI) in critically ill patients (Part II): Society of Critical Care Medicine (SCCM) and European Society of Intensive Care Medicine (ESICM) 2017." Critical Care Medicine, vol. 46, no. 1, 2018, pp. 146–148.

3. Metlay, J.P., et al. "Diagnosis and treatment of adults with community-acquired pneumonia: An official clinical practice guideline of the American Thoracic Society and Infectious Diseases Society of America." American Journal of Respiratory and Critical Care Medicine, vol. 200, no. 7, 2019, pp. e45–e67.

4. Restrepo, M.I., et al. "A comparative study of community-acquired pneumonia patients admitted to the ward and the ICU." Chest, vol. 133, no. 3, 2008, pp. 610–617.

5. De Pascale, G., et al. "Severe pneumonia in intensive care: Cause, diagnosis, treatment and management: A review of the literature." Current Opinion in Pulmonary Medicine, vol. 18, no. 3, 2012, pp. 213–221.

6. Torres, A., et al. "Effect of corticosteroids on treatment failure among hospitalized patients with severe community-acquired pneumonia and high inflammatory response: A randomized clinical trial." JAMA, vol. 313, no. 7, 2015, pp. 677–686.

7. Menéndez, R. "Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia." Thorax, https:// thorax. bmj.com/ content/ 64/ 7/ 587. Accessed 7 May 2025.

8. Menendez, R., et al. "Markers of treatment failure in hospitalised community acquired pneumonia." Thorax, vol. 63, 2008, pp. 447–452.

9. Christ-Crain, M., et al. "Pro-adrenomedullin to predict severity and outcome in community-acquired pneumonia [ISRCTN04176397]." Critical Care, vol. 10, 2006, Article ID R96.