Printed from acutecaretesting.org
Evidence of a potential role for D-dimer and Procalcitonin testing used to assess comorbidities of patients hospitalized with COVID-19
Summarized from Zhou F., Yu T., Du R et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet 2020 published on line March 9th 2020 (available at: https://doi.org/10.1016/S0140-6736(20)30566-3) AND: Lippi G., Plebani M. Procalcitonin in patients with severe coronavirus disease 2019 (COVID-19): A meta-analysis. Clin Chim Acta. 2020; 505:190-191.
Coronavirus disease 2019 (COVID-19), which is caused by the recently identified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was officially declared a pandemic disease by the World Health Organisation (WHO) on the 11th March. Since the first cases (then of unknown aetiology) were reported in Wuhan, China towards the end of December 2019, the disease has spread rapidly both within China and beyond to 150 countries on all continents except Antarctica. By mid-March, when the epicenter of the disease had moved from China to Europe, around 220,000 cases worldwide had been reported; the death toll at this point was close to 9,000.
Median incubation period (i.e. time from viral exposure to onset of symptoms) is currently estimated to be 5 days with an upper 97.5% limit of 11 days. Clinical manifestation spectrum of COVID-19 is wide, ranging from asymptomatic infection, through the most common presentation, relatively mild self-limiting infection (fever, persistent—usually dry—cough, malaise), to more serious respiratory illness—viral pneumonia, respiratory failure—requiring hospitalization. A small proportion (current estimates around 3-4%) do not survive the infection.
While the laboratory has a clear role in diagnosis of COVID-19 (i.e. confirming the presence of SARS-CoV-2 RNA in throat swabs) and monitoring viral shedding, it remains less clear at the present time how other laboratory testing can contribute. Results from these two highlighted (very different) studies suggest measurement of D-dimer and procalcitonin concentrations are helpful in the early assessment of COVID-19 patients with comorbidities such as e.g. coronary heart disease, coagulopathy, and co-infection who require hospitalization.
The first highlighted paper is the report of a retrospective study of patients hospitalized for laboratory-confirmed COVID-19 in Wuhan China - the primary epicenter of the disease. The study provides detail of the clinical course of COVID-19, including patient laboratory test results and has allowed identification of risk factors for severe disease and death following COVID-19 infection.
Among many other findings, results of the study indicate that D-dimer measurement, as a part of the routine blood examinations at the time of hospital admission, can help the clinicians to identify COVID-19 patients at risk of having a poor prognosis. The theory behind their result is given in the discussion and involves a previous investigation  showing that 90 % of inpatients with pneumonia had increased coagulation activity, marked by increased D-dimer concentrations.
During the first month of the COVID-19 outbreak, December 29th to January 30th, 813 adult patients with COVID-19 were admitted to one or other of two Wuhan hospitals. Of these 813 patients, 191 had either died in hospital or recovered and been discharged from hospital by January 30th. These 191 patients, with definite outcome, are the object of this retrospective cohort study. Of the 191 patients, 54 died in hospital (non-survivors) and 137 were discharged from hospital (survivors).
Researchers compared demographic data, clinical records, course of symptoms treatment data, and laboratory results of survivors versus non-survivors.
Median age of non-survivors was 69 years (Interquartile range, IQR 63-76 years) significantly higher than survivors 52 years (IQR 45-58 years). Both survivors and non-survivors were admitted to hospital around 11 days after onset of illness (range 8-14 days). There was no significant difference between survivors and non-survivors with regard to symptoms at admission; the two most common being fever (present in 94% of both groups) and cough (present in 72% of non-survivors and 82% of survivors). Less common symptoms included fatigue and sputum (both present in around 23% of both groups), myalgia (present in around 15% of both groups) and gastrointestinal symptoms (nausea, vomiting and diarrhoea) - present in just 5% of both groups. Increased respiratory rate (>24 breaths/min) was present in 63% of non-survivors at admission but only 16% of survivors.
Not unexpectedly, given the age of the study cohort, around half (48%) had at least one co-morbidity, the most common co-morbidities were hypertension (30% of total cohort), diabetes (19%) and coronary heart disease (8%). While all these comorbidities were more prevalent among non-survivors than survivors, the difference was not statistically significant, except in the case of coronary heart disease: 24% of non-survivors had a history of coronary heart disease, this compared with just 1% of survivors.
Assessment at admission included laboratory and clinical measurements required to calculate Sequential Organ Failure Assessment (SOFA) score. The SOFA score, which is a widely-used tool to assess and predict outcome of critically ill patients, is based on the degree of dysfunction of six organ systems. Median SOFA score at admission among non-survivors was 4.5 (range 4.0-6.0), significantly higher than among survivors, whose median score was 1.0 (range 1.0-2.0).
The authors provide detail of a range of laboratory test results used to assess study patients status. The following laboratory test parameters were significantly more frequently abnormal at the time of admission in non-survivors than in survivors: total white blood count (WBC), lymphocyte count, platelet count, alanine transferase (ALT); lactate dehydrogenase (LD); creatine kinase (CK), cardiac troponin I (cTnI), ferritin, Interleukin-6 (IL-6), procalcitonin (PCT) and D-dimer.
So far as D-dimer results are concerned, the median (IQR) D-dimer concentration at admission among survivors was 0.6 (0.3-1.0) µg/ml, this compared with 5.2 (1.5 – 21.1) µg/ml among non-survivors; the difference is statistically significant (p value <0.0001). Univariate analysis revealed that risk factors for increased odds for in-hospital death was e.g. diabetes and coronary heart disease, together with age and elevated laboratory tests as mentioned above.
In addition to data relating to laboratory parameters at the time of hospital admission outlined above, the authors also provide detail of temporal change in some of these laboratory parameters (including D-dimer) over the period of hospital stay, prior to death or discharge, which on average was 22 days for survivors and 19 days for non-survivors. This reveals that median D-dimer concentration of non-survivors increased progressively to 42.2 µg/ml at death. By comparison, median D-dimer of survivors remained essentially unchanged (0.5-1.0 µg/ml) for the duration of their stay in hospital.
Of five admission variables chosen for multivariate logistic regression analysis, three: increasing age; high SOFA score; and D-dimer >1 µg/ml were found to be independently predictive of in-hospital death. Of these, D-dimer > 1µg/ml was the best predictor. Odds Ratio (OR) of in-hospital death associated with increasing age was 1.10 (95% CI 0.3-1.17, p=0.0043)) per year increase; OR for in-hospital death associated with higher SOFA score was 5.65 (95% CI 2.61-12.23, p=<0.0001) and OR for in hospital death associated with D-dimer > 1µg/ml was 18.42 (95% CI 2.64-128.55, p=0.0033). The data suggests assessing the patient’s comorbidities e.g. coagulopathy at admission to the hospital is valuable for predicting the outcome among patients with COVID-19.
The second highlighted paper is a very brief report (letter to the editor) of a meta-analysis study aimed at determining if measurement of procalcitonin may play a role in distinguishing patients with severe COVID-19 from those with non-severe COVID-19 disease. For the purposes of the study severe disease was defined as needing admission to intensive care unit or use of mechanical ventilation.
Investigators searched medical literature databases using the following search terms “procalcitonin” AND “2019 novel coronavirus” OR “2019 nCoV” OR “COVID-19”. The search revealed 4 studies of COVID-19 patients judged suitable for inclusion in the meta-analysis; they all reported procalcitonin concentration values in those with severe disease as well as those with non-severe disease. The meta-analysis involved calculating the individual and pooled odds ratio (OR) for predicting that raised procalcitonin (above the upper limit of the reference range) is associated with severe COVID-19.
The result of the meta-analysis (pooled OR 4.76 95% CI 2.74-8.29) indicates that raised procalcitonin is associated with a nearly five-fold increased risk of severe COVID-19. The authors conclude that “serial procalcitonin measurement may play a role for predicting evolution towards a more severe form of disease”.
In discussion of their findings the authors reflect that procalcitonin is usually used as a biomarker of bacterial infection; in general, viral infections are not associated with increased procalcitonin concentration. They speculate that the increased procalcitonin values seen in those with severe COVID might indicate that bacterial-coinfection is a feature of severe COVID-19, a notion that, as they imply, can only be confirmed with further study.
1. Milbrandt EB, Reade MC, Lee M, et al. Prevalence and significance of coagulation abnormalities in community-acquired pneumonia. Mol Med 2009; 15: 438–45.
May contain information that is not supported by performance and intended use claims of Radiometer's products. See also Legal info.