{"id":50621,"date":"2023-09-30T10:58:54","date_gmt":"2023-09-30T10:58:54","guid":{"rendered":"https:\/\/biomedpharmajournal.org\/?p=50621"},"modified":"2023-10-07T11:07:06","modified_gmt":"2023-10-07T11:07:06","slug":"analysis-of-clotting-factors-in-covid-19-a-study-in-indian-patients-in-a-tertiary-hospital","status":"publish","type":"post","link":"https:\/\/biomedpharmajournal.org\/staging\/vol16no3\/analysis-of-clotting-factors-in-covid-19-a-study-in-indian-patients-in-a-tertiary-hospital\/","title":{"rendered":"Analysis of Clotting Factors in Covid 19: A Study in Indian Patients in a Tertiary Hospital"},"content":{"rendered":"\n

Introduction<\/strong><\/p>\n\n\n\n

Coronaviruses are enveloped nonsegmented positive stranded RNA viruses belonging to the family Coronaviridae and the order Nidovirales.4 <\/sup>The virus spreads through direct contact of infected surfaces or through human to human contact through air borne droplet spread.5,6 <\/sup>The virus has mean incubation period of 5.2 days.7 <\/sup>Most common symptoms include nausea, vomiting, fever, fatigue, dry cough, dyspnoea, myalgia, diarrhea, sore throat, rhinorrhea and chest pain.8,9,10<\/sup>Increased mortality in COVID patients is related to severe symptoms like pneumonia, acute respiratory distress syndrome and multi organ failure.11,12<\/sup> In severe cases, patients may develop acute respiratory distress syndrome (ARDS), with coagulation predominant-type coagulopathy. 13<\/sup><\/p>\n\n\n\n

The\ncoronavirus causing COVID-19 may trigger coagulation dysfunction because it\ninduces abundant release of pro-inflammatory cytokines in various tissues,\nwhich can lead to systemic inflammatory response syndrome that damages the\nmicrovascular system and thereby activates the coagulation system, leading to\ngeneralised small vessel vasculitis and extensive microthrombosis1.14,15<\/sup>\nPatients with severe COVID-19 may be at high risk of venous thromboembolism,\nwhich may be present in up to 25% of such patients.16<\/sup>\nRisk may be exacerbated by the dehydration due to fever and diarrhea,\nhypotension, and prolonged bed rest characteristic of the disease, all of which\nare risk factors for coagulation.17<\/sup>Chinese studies have revealed markedly\nprolonged PT\/APTT and elevated D dimer in nonsurvivors in comparision to COVID\n19 survivors.13,18<\/sup> The coagulation parameters \nhave not been completely reported in patients with and without SARS in\nIndian literature so far. Hence this research project was undertaken to\nascertain the differences in coagulation parameters in symptomatic patients\nwith and without SARI.<\/p>\n\n\n\n

Aims and Objectives<\/strong><\/p>\n\n\n\n

To evaluate the basic coagulation parameters in symptomatic patients with  and without SARI  <\/p>\n\n\n\n

To study the prognostic role of the basic coagulation parameters in both the clinical forms of disease.<\/p>\n\n\n\n

Materials and Methods<\/strong><\/p>\n\n\n\n

This\nstudy was a prospective comparative cross sectional study which was undertaken\nin COVID patients admitted to Father Muller Medical College Hospital over a\nperiod of one year from April 2020- April 2021. The Institutional Ethics Committee\nclearance and prior written informed consent was obtained from the study\nparticipants.<\/p>\n\n\n\n

The\nsample size was 96 (48 in each group)<\/p>\n\n\n\n

Inclusion Criteria<\/strong><\/p>\n\n\n\n

Adult COVID patients admitted to ward and ICU of this hospital with symptoms of nausea, vomiting, fever, fatigue, dry cough, dyspnoea, myalgia, diarrhea, sore throat, rhinorrhea and chest pain.<\/p>\n\n\n\n

Exclusion Criteria<\/strong><\/p>\n\n\n\n

Asymptomatic COVID patients, pregnant COVID patients and paediatric COVID patients. <\/p>\n\n\n\n

At the\ntime of admission to the hospital, blood sample was   collected for platelets, prothrombin time (PT),\nactivated thromboplastin time (APTT), fibrinogen and D dimer. Demographic characteristics,\ndetailed medical history and basic coagulation was recorded and was analysed. Platelet\nanalysis was done in Beckman Coulter LH 750. PT, APTT and fibrinogen was\nanalysed in ACL TOP 500 and ACL TOP 300.D dimer was analysed by an automated latex\nenhanced immunoassay on the ACL TOP.<\/p>\n\n\n\n

The COVID patients was divided into 2 groups according to presence or absence of  severe SARI requiring ICU care  The clotting factors was compared between these 2 groups of patients and also survivors and non survivors . The case definition of severe SARI was defined as those patients requiring ICU care with saturation less than 90 % on room air requiring non-invasive or invasive ventilation.<\/p>\n\n\n\n

Statistical Analysis<\/strong><\/p>\n\n\n\n

The sample size of 96 was calculated based on the standard\ndeviation 151 of fibrinogen in admitted COVID patients and standard deviation\nof 83 in outpatient (in reference to previously done study), mean difference of\n70, alpha error 5% for 80% power, 2 sided test, sample size required for each\ngroup is 48.19<\/sup> This was calculated using Master 2 software,\nCMC, Vellore. <\/p>\n\n\n\n

Data was analysed using unpaired t test if the results follow normal distribution or else Mann Whitney test will be used. P<0.05 is considered to be significant. Data was analysed using SPSS version 20.<\/p>\n\n\n\n

Statistical analysis<\/strong><\/p>\n\n\n\n

Continuous variables were expressed as mean and SD or median and\nIQR The independent group t test was used to analyse normally distributed\ncontinuous variables, and the Mann-Whitney U test was used to analyse\nnon-normally distributed continuous variables. Categorical variables were\npresented as frequency rates and percentages and analysed using \u03c7\u00b2 test or\nFisher\u2019s exact test as appropriate. Receiver Operative characteristic curves\nwere plotted for significant variables to obtain area under curve.<\/p>\n\n\n\n

Results<\/strong><\/p>\n\n\n\n

Table 1: Group Statistics<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

Moderate Vs Severe Cases<\/strong><\/p>\n<\/td>\n

\n

N<\/strong><\/p>\n<\/td>\n

\n

Mean<\/strong><\/p>\n<\/td>\n

\n

Std. Deviation<\/strong><\/p>\n<\/td>\n

\n

Std. Error Mean<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

12.8417<\/p>\n<\/td>\n

\n

3.37190<\/p>\n<\/td>\n

\n

.48669<\/p>\n<\/td>\n<\/tr>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

21.3104<\/p>\n<\/td>\n

\n

31.41860<\/p>\n<\/td>\n

\n

4.53488<\/p>\n<\/td>\n<\/tr>\n

\n

INR<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

1.1438<\/p>\n<\/td>\n

\n

.29556<\/p>\n<\/td>\n

\n

.04266<\/p>\n<\/td>\n<\/tr>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

1.8483<\/p>\n<\/td>\n

\n

2.72371<\/p>\n<\/td>\n

\n

.39313<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

37.8875<\/p>\n<\/td>\n

\n

35.36448<\/p>\n<\/td>\n

\n

5.10442<\/p>\n<\/td>\n<\/tr>\n

\n

 <\/p>\n<\/td>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

42.3188<\/p>\n<\/td>\n

\n

38.89234<\/p>\n<\/td>\n

\n

5.61363<\/p>\n<\/td>\n<\/tr>\n

\n

Fibrinogen<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

458.1667<\/p>\n<\/td>\n

\n

166.26732<\/p>\n<\/td>\n

\n

23.99862<\/p>\n<\/td>\n<\/tr>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

621.4583<\/p>\n<\/td>\n

\n

286.98869<\/p>\n<\/td>\n

\n

41.42325<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

265770.8333<\/p>\n<\/td>\n

\n

124442.9699<\/p>\n<\/td>\n

\n

17961.79554<\/p>\n<\/td>\n<\/tr>\n

\n

 <\/p>\n<\/td>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

198958.3333<\/p>\n<\/td>\n

\n

130473.9247<\/p>\n<\/td>\n

\n

18832.28889<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

382.5417<\/p>\n<\/td>\n

\n

492.35197<\/p>\n<\/td>\n

\n

71.06489<\/p>\n<\/td>\n<\/tr>\n

\n

 <\/p>\n<\/td>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

2168.2083<\/p>\n<\/td>\n

\n

3320.43931<\/p>\n<\/td>\n

\n

479.26413<\/p>\n<\/td>\n<\/tr>\n

\n

CRP<\/p>\n<\/td>\n

\n

Moderate<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

46.6608<\/p>\n<\/td>\n

\n

60.04235<\/p>\n<\/td>\n

\n

8.66637<\/p>\n<\/td>\n<\/tr>\n

\n

Severe<\/p>\n<\/td>\n

\n

48<\/p>\n<\/td>\n

\n

112.7206<\/p>\n<\/td>\n

\n

123.35552<\/p>\n<\/td>\n

\n

17.80484<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 2: Group Statistics Continue<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

Non Survivor Vs Survivor<\/strong><\/p>\n<\/td>\n

\n

N<\/strong><\/p>\n<\/td>\n

\n

Mean<\/strong><\/p>\n<\/td>\n

\n

Std. Deviation<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT (survivor Vs Nopn Survivor)<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

14.6100<\/p>\n<\/td>\n

\n

13.11189<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

29.4063<\/p>\n<\/td>\n

\n

46.29603<\/p>\n<\/td>\n<\/tr>\n

\n

INR (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

1.2924<\/p>\n<\/td>\n

\n

1.13967<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

2.5144<\/p>\n<\/td>\n

\n

4.01809<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

35.7925<\/p>\n<\/td>\n

\n

27.59943<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

61.6563<\/p>\n<\/td>\n

\n

63.9037<\/p>\n<\/td>\n<\/tr>\n

\n

Fibinogen (Survivor vs Non Survivor)<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

518.4875<\/p>\n<\/td>\n

\n

227.27500<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

646.4375<\/p>\n<\/td>\n

\n

317.42106<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet (Survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

237600.0000<\/p>\n<\/td>\n

\n

130760.2502<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

206187.50000<\/p>\n<\/td>\n

\n

134452.5784<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer (survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

927.4875<\/p>\n<\/td>\n

\n

2344.09279<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

3014.8125<\/p>\n<\/td>\n

\n

2755.96904<\/p>\n<\/td>\n<\/tr>\n

\n

CRP (Suvivor vs Non Survivors<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

80<\/p>\n<\/td>\n

\n

62.1549<\/p>\n<\/td>\n

\n

78.14500<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

16<\/p>\n<\/td>\n

\n

167.3700<\/p>\n<\/td>\n

\n

154.77387<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 3: Group statistics <\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

Non Survivor Vs Survivor<\/strong><\/p>\n<\/td>\n

\n

Std. Error Mean<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT (survivor Vs Nopn Survivor)<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

1.46595<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

11.57401<\/p>\n<\/td>\n<\/tr>\n

\n

INR (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

.12742<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

1.00452<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

3.08571<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

15.97509<\/p>\n<\/td>\n<\/tr>\n

\n

Fibinogen (Survivor vs Non Survivor)<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

25.41012<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

79.35526<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet (Survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

14619.44041<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

33613.14460<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer (survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

262.07754<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

688.99226<\/p>\n<\/td>\n<\/tr>\n

\n

CRP (Suvivor vs Non Survivors<\/p>\n<\/td>\n

\n

Survivors<\/p>\n<\/td>\n

\n

8.73688<\/p>\n<\/td>\n<\/tr>\n

\n

Non Survivors<\/p>\n<\/td>\n

\n

38.69347<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 4<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

Levene\u2019s Test for Equality of Variances<\/strong><\/p>\n<\/td>\n

\n

t-test Equality of Means<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

F<\/strong><\/p>\n<\/td>\n

\n

Sig<\/strong><\/p>\n<\/td>\n

\n

t<\/strong><\/p>\n<\/td>\n

\n

Df<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

7.767<\/p>\n<\/td>\n

\n

.006<\/p>\n<\/td>\n

\n

-1.857<\/p>\n

-1.857<\/p>\n<\/td>\n

\n

94<\/p>\n

48.083<\/p>\n<\/td>\n<\/tr>\n

\n

INR<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

7.531<\/p>\n<\/td>\n

\n

.007<\/p>\n<\/td>\n

\n

-1.782<\/p>\n

-1.782<\/p>\n<\/td>\n

\n

94<\/p>\n

48.107<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.815<\/p>\n<\/td>\n

\n

.369<\/p>\n<\/td>\n

\n

-.584<\/p>\n

-.584<\/p>\n<\/td>\n

\n

94<\/p>\n

93.163<\/p>\n<\/td>\n<\/tr>\n

\n

Fibrinogen<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

12.653<\/p>\n<\/td>\n

\n

.001<\/p>\n<\/td>\n

\n

-3.411<\/p>\n

-3.411<\/p>\n<\/td>\n

\n

94<\/p>\n

75.356<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

1.092<\/p>\n<\/td>\n

\n

.299<\/p>\n<\/td>\n

\n

2.567<\/p>\n

2.567<\/p>\n<\/td>\n

\n

94<\/p>\n

93.790<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

18.579<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

-3.686<\/p>\n

-3.686<\/p>\n<\/td>\n

\n

94<\/p>\n

49.066<\/p>\n<\/td>\n<\/tr>\n

\n

CRP<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

4.957<\/p>\n<\/td>\n

\n

.028<\/p>\n<\/td>\n

\n

-3.336<\/p>\n

-3.336<\/p>\n<\/td>\n

\n

94<\/p>\n

68.087<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 5<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

t-test Equality of Means<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Sig.(2-tailed)<\/strong><\/p>\n<\/td>\n

\n

Mean<\/strong><\/p>\n

Difference<\/strong><\/p>\n<\/td>\n

\n

Std. Error Difference<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.066<\/p>\n

.069<\/p>\n<\/td>\n

\n

-8.46875<\/p>\n

-8.46875<\/p>\n<\/td>\n

\n

4.56093<\/p>\n

4.56093<\/p>\n<\/td>\n<\/tr>\n

\n

INR<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.078<\/p>\n

.081<\/p>\n<\/td>\n

\n

-.70458<\/p>\n

-.70458<\/p>\n<\/td>\n

\n

.39544<\/p>\n

.39544<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.561<\/p>\n

.561<\/p>\n<\/td>\n

\n

-4.43125<\/p>\n

-4.43125<\/p>\n<\/td>\n

\n

7.58735<\/p>\n

7.58735<\/p>\n<\/td>\n<\/tr>\n

\n

Fibrinogen<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.001<\/p>\n

.001<\/p>\n<\/td>\n

\n

-163.29167<\/p>\n

-163.29167<\/p>\n<\/td>\n

\n

47.87295<\/p>\n

47.87295<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.012<\/p>\n

.012<\/p>\n<\/td>\n

\n

66812.50000<\/p>\n

66812.50000<\/p>\n<\/td>\n

\n

26024.62687<\/p>\n

26024.62687<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.000<\/p>\n

.001<\/p>\n<\/td>\n

\n

-1785.66667<\/p>\n

-1785.66667<\/p>\n<\/td>\n

\n

484.50421<\/p>\n

484.50421<\/p>\n<\/td>\n<\/tr>\n

\n

CRP<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

.001<\/p>\n

.001<\/p>\n<\/td>\n

\n

-66.05979<\/p>\n

-66.05979<\/p>\n<\/td>\n

\n

19.80197<\/p>\n

19.80197<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 6<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

 <\/p>\n<\/td>\n

\n

 <\/p>\n<\/td>\n

\n

t-test for Equality of Means<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

95% Confidence Interval of the Difference <\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Lower <\/strong><\/p>\n<\/td>\n

\n

Upper <\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-17.52458<\/p>\n

-17.63870<\/p>\n<\/td>\n

\n

.58708<\/p>\n

.70120<\/p>\n<\/td>\n<\/tr>\n

\n

INR<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-1.488974<\/p>\n

-1.49963<\/p>\n<\/td>\n

\n

.08058<\/p>\n

.09046<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-19.49612<\/p>\n

-19.49788<\/p>\n<\/td>\n

\n

10.63362<\/p>\n

10.63538<\/p>\n<\/td>\n<\/tr>\n

\n

Fibrinogen<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-258.34453<\/p>\n

-258.65208<\/p>\n<\/td>\n

\n

-68.23880<\/p>\n

-67.93125<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

15139.99328<\/p>\n

15138.48669<\/p>\n<\/td>\n

\n

118485.0067<\/p>\n

118486.5133<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-2747.66113<\/p>\n

-27759.28132<\/p>\n<\/td>\n

\n

-823.67221<\/p>\n

-812.05201<\/p>\n<\/td>\n<\/tr>\n

\n

CRP<\/p>\n<\/td>\n

\n

Equal Variances assumed Equal Variances  not assumed<\/p>\n<\/td>\n

\n

-105.37707<\/p>\n

-105.57310<\/p>\n<\/td>\n

\n

-26.74251<\/p>\n

-26.54648<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

In our study the values\nof the levels of all five parameters were elevated in non survivors as compared\nto survivors.<\/p>\n\n\n\n

PT<\/strong><\/p>\n\n\n\n

On admission the mean level\nof PT in patients with and without SARI 12.8s and 21.3s. When interpreted with\nINR the mean values were 1.1 and 1.8. The difference in the mean values apart\nfrom being statistically significant (p=0.006) and also clinically different\nwith moderate patients having a mean value within normal range for our laboratory(10-13s) and the\nsevere cases well above that. Our finding is similar to Song JC15<\/sup> et al who hypothesized that these are due\nto liver involvement as there was significant abnormality in the liver enzymes\nof patients with COVID. <\/p>\n\n\n\n

The average PT for\nsurvivors was 14.6 and the non survivors was 29.4s and the difference was\nstatistically significant.  Area under\nthe curve for PT (survivors non survivor)was 0.751 and at a cut off value of\n13s PT alone had a sensitivity of 75 % and a specificity of 62.5% for\npredicting those with severe covid. A cut off value of 16s had sensitivity to\n39.6%. specificity of 95.8 % in predicting death This finding is similar to\nthose described by Cui S et al16<\/sup> in whose study the multivariate regression analysis showed the\ndifference in PT inpatients with SARI who survived and did not survive was not\nsignificant.<\/p>\n\n\n\n\n\n
\"\"<\/td>\n\n

Graph 1: Roc Curve<\/strong><\/p>\n

<\/p>\n

Click here to view Graph<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Table 7<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

t-test Result Variable(s)<\/strong><\/p>\n<\/td>\n

\n

Area<\/strong><\/p>\n<\/td>\n

\n

a<\/strong><\/p>\n<\/td>\n

\n

Asymptotic<\/strong><\/p>\n

Sig.b<\/strong><\/p>\n<\/td>\n

\n

Asymptotic 95% confidence Interval<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

Std  Error<\/strong><\/p>\n<\/td>\n

\n

Lower Bound<\/strong><\/p>\n<\/td>\n

\n

Upper Bound<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT<\/p>\n<\/td>\n

\n

.735<\/p>\n<\/td>\n

\n

.051<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.635<\/p>\n<\/td>\n

\n

.835<\/p>\n<\/td>\n<\/tr>\n

\n

INR<\/p>\n<\/td>\n

\n

.724<\/p>\n<\/td>\n

\n

.052<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.623<\/p>\n<\/td>\n

\n

.825<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT<\/p>\n<\/td>\n

\n

.535<\/p>\n<\/td>\n

\n

.059<\/p>\n<\/td>\n

\n

.558<\/p>\n<\/td>\n

\n

.418<\/p>\n<\/td>\n

\n

.651<\/p>\n<\/td>\n<\/tr>\n

\n

Fibrinogen<\/p>\n<\/td>\n

\n

.667<\/p>\n<\/td>\n

\n

.055<\/p>\n<\/td>\n

\n

.005<\/p>\n<\/td>\n

\n

.559<\/p>\n<\/td>\n

\n

.775<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet<\/p>\n<\/td>\n

\n

.350<\/p>\n<\/td>\n

\n

.057<\/p>\n<\/td>\n

\n

.011<\/p>\n<\/td>\n

\n

.239<\/p>\n<\/td>\n

\n

.461<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer<\/p>\n<\/td>\n

\n

.852<\/p>\n<\/td>\n

\n

.039<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.775<\/p>\n<\/td>\n

\n

.928<\/p>\n<\/td>\n<\/tr>\n

\n

CRP<\/p>\n<\/td>\n

\n

.740<\/p>\n<\/td>\n

\n

.051<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.639<\/p>\n<\/td>\n

\n

.840<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n
\"\"<\/td>\n\n

Graph 2: Roc Curve<\/strong><\/p>\n

<\/p>\n

Click here to view Graph<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

Area Under the Curve<\/strong><\/p>\n\n\n\n

Table 8<\/strong><\/p>\n\n\n\n\n\n\n\n\n\n\n\n\n
\n

Test Result Variables<\/strong><\/p>\n<\/td>\n

\n

Area<\/strong><\/p>\n<\/td>\n

\n

Std. Error<\/strong><\/p>\n<\/td>\n

\n

Asymptotic sig.<\/strong><\/p>\n<\/td>\n

\n

Asymptotic 95% Confidence<\/strong><\/p>\n<\/td>\n<\/tr>\n

\n

PT (survivor vs Non survivor)<\/p>\n<\/td>\n

\n

.751<\/p>\n<\/td>\n

\n

.073<\/p>\n<\/td>\n

\n

.002<\/p>\n<\/td>\n

\n

.607<\/p>\n<\/td>\n<\/tr>\n

\n

INR (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

.738<\/p>\n<\/td>\n

\n

.073<\/p>\n<\/td>\n

\n

.003<\/p>\n<\/td>\n

\n

.506<\/p>\n<\/td>\n<\/tr>\n

\n

aPTT (Survivor Vs Non Survivor<\/p>\n<\/td>\n

\n

.705<\/p>\n<\/td>\n

\n

.069<\/p>\n<\/td>\n

\n

.010<\/p>\n<\/td>\n

\n

.570<\/p>\n<\/td>\n<\/tr>\n

\n

Fibinogen (Survivor vs Non Survivor)<\/p>\n<\/td>\n

\n

.615<\/p>\n<\/td>\n

\n

.087<\/p>\n<\/td>\n

\n

.147<\/p>\n<\/td>\n

\n

.445<\/p>\n<\/td>\n<\/tr>\n

\n

Platelet (Survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

.448<\/p>\n<\/td>\n

\n

.090<\/p>\n<\/td>\n

\n

.513<\/p>\n<\/td>\n

\n

.272<\/p>\n<\/td>\n<\/tr>\n

\n

DDimer (survivor vs Non Survivor )<\/p>\n<\/td>\n

\n

.644<\/p>\n<\/td>\n

\n

.057<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.732<\/p>\n<\/td>\n<\/tr>\n

\n

CRP (Suvivor vs Non Survivors<\/p>\n<\/td>\n

\n

.784<\/p>\n<\/td>\n

\n

.064<\/p>\n<\/td>\n

\n

.000<\/p>\n<\/td>\n

\n

.658<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n

The prolongation of PT is understandable. One of the mechanisms of COVID induced coagulopathy (CIC) is the over expression of tissue factor (TF) by the endothelial cells secondary to the cytokine release. Binding activation and consumption of factor VII by TF is probably the main reason for this. It can be inferred that the consumption of factor VII occurs more severely in SARI than in non SARI cases due to stronger cytokine response in them.<\/p>\n\n\n\n

aPTT<\/strong><\/p>\n\n\n\n

The\ndifference in aPTT among the moderate and sever cases was not statistically\nsignificant. This finding is similar to other studies. However the difference\nwas significant when aPTT was survivors was compared with non survivors. (p=0.003)\nThe median value for non survivors was 35.5 (IQR 32.5-42.1) and for survivors\nit was 31.9 (IQR 29.5-35.7) This finding is similar to that of study done by   Huang C 11<\/sup> et al.<\/p>\n\n\n\n

It\nhas been suggested that CIC be categorized into three stages beginning with\nstage of high d-dimer and nerar normal PT and aPTT, followed by increasing PT\nand aPTT with high dDimer and finally with features of Classic DIC as described\nby International Society of Thrombosis and Hemostasis (ISTH) It is possible\nthat the non survivors in our case had progressed to  second stage as compared to our survivors .\nIt is interesting to note that the difference in the aPTT between survivors\nwith and without SARI was also not significant as well as between the SARI\nsurvivors and non survivors. <\/p>\n\n\n\n

33.9 cut off  21 severe patients and 18  moderate  patients <\/p>\n\n\n\n

>33.9s  in 11\/16  non survivors(68.5%)  36.2 5% (of survivors 29\/80)<\/p>\n\n\n\n

D\nDimer (D-DU) (non survivor vs survivor and Non Sari vs Sari).  The mean values of D dimer for patients without\nand with SARI as 384 and 2168 mcg\/ml and the difference was highly significant.\nThe IQR of D dimer in survivors and non survivors was 196-817 and 1043-4961 and\nthe median was 352 and 2080 between survivors and non survivors difference was\nstatistically significant ( p<0.001)<\/p>\n\n\n\n

The\nD Dimer test was the single most important test distinguishing survivors and\nnon Survivors with an AUC of. 0.844. At values if 382 the sensitivity and\nspecificity was 93.8 and 51, 2. A cut off of 1000 ensured a 81.3 and 81.2%\nspecificity. At 1711 it was 56.3 and 90% respectively. Our findings is similar\nto Gao Y.D. et al 20<\/sup> also  is\nthe most common hematological abnormality reported in COVID-19 in a study done Asakura\nH, Ogawa H21<\/sup> . Elevated D-dimer level is a sign of excessive\ncoagulation activation and hyperfibrinolysis which is a significant predictor\nof mortality due to venous thromboembolism both of the deep veins and in the\npulmonary circulation the prevalence of which ranges from 0-54% as shown in a\nstudy by Suh et al22<\/sup><\/p>\n\n\n\n

The  mean  levels of fibrinogen values in our study in\nmoderate and severe cases was 458 and 621 respectively and the difference\nwas  significant  (p =. 001) .The CRP The levels of fibrinogen\nand CRP was higher in patients with severe COVID and the difference was\nstatistically significant whereas platelet values were lower but difference was\nnot significant<\/p>\n\n\n\n

Discussion <\/strong><\/p>\n\n\n\n

The\naim of the cross-sectional study was to analyze the association between the\ncoagulation parameters on admission with the severity and survival of adult<\/p>\n\n\n\n

COVID patients as thromboembolism and disseminated Intravascular Coagulation are an important cause of morbidity and mortality among COVID patients.<\/p>\n\n\n\n

Early on it was discovered that the mechanism for development of DIC in patients with COVID differed from those commonly encountered during sepsis. It is believed that the release of cytokines especially the Interleukin -6(IL-6) is major contributor for development of macrovascular as well as microvascular thrombosis. The mechanism appears to be dual:1. IL -6 increases the endothelial expression of Tissue Factor, ii) Sars Co-V 2 by itself produces widespread endothelitis and also pyroptosis and apoptosis of endothelial cells.<\/p>\n\n\n\n

The\ncoagulation cascade activation that occurs I Covid can be identified by\nprolongation of Prothrombin Time, Activated Partial Thromboplastin Time (aPTT).\nThe fibrinolysis that follows is represented by increased levels of D- Dimer\nand Fibrin Split Products (FSP). The other conventional laboratory parameters\nthat are useful in monitoring of Covid patients is levels of Lactate\nDehydrogenase (LDH ), Serum Ferritin, C- Reactive Protein(CRP) and Interleukin\n6 levels. <\/p>\n\n\n\n

In\nour study the values of the levels of all five parameters were elevated in non\nsurvivors as compared to survivors<\/p>\n\n\n\n

On\nadmission the mean level of PT in patients with and without SARI 12.8s and\n21.3s. When interpreted with INR the mean values were 1.1 and 1.8. The\ndifference in the mean values apart from being statistically significant\n(p=0.006) also clinically different with moderate patients having a mean value\nwithin normal range for our laboratory (10-13s) and the severe cases well above\nthat. Our finding is similar to Zhang et al23<\/sup> who hypothesized that\nthese are due to liver involvement as there was significant abnormality in the\nliver enzymes of patients with COVID.<\/p>\n\n\n\n

The levels of fibrinogen and CRP was higher in patients with severe covid and the difference was statistically significant whereas platelet values were lower but difference was not significant. <\/p>\n\n\n\n

Platelet\nvalues are known to be lower in patients with severe Covid and multiple\nmechanisms are proposed beginning with suppression of bone marrow to increased\nconsumption. Lower platelet counts are associated with more severe disease and\nare useful if monitored serially24<\/sup>. Since we did not follow up platelet\ncounts and it may be the reason that it was not statistically significant. In\nour study 20 severe and 6 moderate cases had levels below 1,50,000<\/p>\n\n\n\n

Both\nfibrinogen and CRP elevation can be explained by the fact that they are acute\nphase reactants. Elevation of fibrinogen could also be an indicator of\nprothrombotic state as shown in study done by Thachil J25<\/sup> and in\nconjunction with elevated CRP gives credence to the connection between\ninflammation and coagulation.<\/p>\n\n\n\n

Conclusion<\/strong><\/p>\n\n\n\n

Basic coagulation markers may have a\nprognostic implication in the treatment of Covid patients with and without SARI.<\/p>\n\n\n\n

Acknowledgement<\/strong><\/p>\n\n\n\n

The authors would like to acknowledge\nFather Muller Medical College hospital , Mangalore to allow us to carry out the\npresent study .<\/p>\n\n\n\n

Conflicting of Interests <\/strong><\/p>\n\n\n\n

There are no conflict of interest.<\/p>\n\n\n\n

Funding Sources<\/strong><\/p>\n\n\n\n

Father muller research grant ,Father Muller  Medical College , Mangalore -575002 grant number FMRC\/FMMC\/06\/2020.<\/p>\n\n\n\n

References<\/strong><\/p>\n\n\n\n

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     CrossRef <\/a><\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

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