A non-invasive laboratory panel as a diagnostic and prognostic biomarker for thrombotic microangiopathy: development and application in a Chinese cohort study

The Effects of Exercise Training on Recovery of Biochemical and Hematological Outcomes in Patients Surviving COVID-19: A Randomized Controlled Assessor-Blinded Trial

BACKGROUND

No previous research has investigated the direct effects of exercise interventions on COVID-19 outcomes. The aim is to investigate the effect of 8 weeks of home-based moderate-intensity continuous training (MICT), resistance training (RT), and combined aerobic and resistance training (CET) on biochemical and hematologic markers associated with COVID-19 symptoms and severity in COVID-19 survivors.

METHODS

A total of 547 male and female COVID-19 survivors were screened, and 296 (aged 20-93 years) were randomly assigned in a 1:1:1:1 ratio to one of four groups: MICT (n = 74), RT (n = 74), CET (n = 74), or non-exercise (NON-EX, n = 74). Blood samples were taken at baseline, at week 4, and week 8 after training.

RESULTS

After the intervention, compared with the NON-EX group, all 3 MICT, RT, and CET interventions caused significant improvements in the levels of creatine kinase (CK), lactate dehydrogenase (LDH), C-reactive protein (CRP), troponin-I, d-dimer, creatinine, urea, potassium (K), sodium (Na), white blood cell (WBC), neutrophils, lymphocytes, red blood cells (RBC), platelets, hemoglobin, and hematocrit concentrations (P < 0.05). CET was effectively superior to MICT and RT in the improvements in the biochemical and hematological variables studied (P < 0.05).

CONCLUSIONS

Overall, the present study demonstrates that long-term MICT plus RT interventions have a synergistic effect in accelerating and enhancing the recovery in patients surviving COVID-19. Trial registration IRCT20160605028270N3, 6 September 2020.

Prognostic Value of Routine Blood Parameters in Intensive Care Unit COVID-19 Patients

INTRODUCTION

Laboratory medicine has an important role in the management of COVID-19. The aim of this study was to analyze routinely available blood parameters in intensive care unit COVID-19 patients and to evaluate their prognostic value.

PATIENTS AND METHODS

This is a retrospective, observational, single-center study including consecutive severe COVID-19 patients who were admitted into the intensive care unit of Ben Arous Regional Hospital in Tunisia from 28 September 2020 to 31 May 2021. The end point of the study was either hospital discharge or in-hospital death. We defined two groups based on the outcome: survivors (Group 1) and non-survivors (Group 2). Demographical, clinical, and laboratory data on admission were collected and compared between the two groups. Univariate and multivariate logistic regression analysis were performed to determine the predictive factors for COVID-19 disease mortality.

RESULTS

A total of 150 patients were enrolled. Eighty patients (53.3%) died and 70 (46.7%) survived during the study period. Based on statistical analysis, median age, Simplified Acute Physiology Score (SAPS II) with the serum levels of urea, creatinine, total lactate dehydrogenase (LDH), creatine kinase, procalcitonin and hs-troponin I were significantly higher in non-survivors compared to survivors. On multivariate analysis, LDH activity ≥ 484 U/L (OR=17.979; 95%CI [1.119-2.040]; p = 0.09) and hs-troponin I ≥ 6.55 ng/L (OR=12.492; 95%CI [1.691-92.268]; p = 0.013) independently predicted COVID-19 related mortality.

CONCLUSION

Total LDH and hs-troponin I were independent predictors of death. However, further clinical investigations with even larger number of patients are needed for the evaluation of other laboratory biomarkers which could aid in assessing the prediction of mortality.

Assessment of some Physiological Biomarkers in COVID-19 Patients in Thi-Qar, Iraq

It is believed that many biomarkers and factors could be linked to the prognosis of coronavirus disease 2019 (COVID-19). Therefore, this study aimed to evaluate the association of lactate dehydrogenase (LDH), D-Dimer, vitamin D, and ferritin statuses with the prognosis of COVID-19; moreover, it was attempted to investigate its prevalence according to age, employment status, body mass index (BMI), and place of residency in a population sample of hospitalized patients in Thi-Qar, Iraq. This study evaluated 200 COVID-19 patients and 100 controls. The BMI of all individuals was calculated, and such demographic characteristics as age, gender, place of residency, and occupational status were collected from all participants. Blood samples were taken and used to estimate D-Dimer, LDH, vitamin D, ferritin, oxygen, and pulse rate. The mean age of the patients approached the fifth decade, and 72% of the cases were more than 40 years of age. In addition, 60% of the patients were living in the countryside, and 52% of the participants were employed, compared to only 8% of the cases who were students. The BMI of the patients was obtained at 31.44±10.2 kg/m²; accordingly, 47% and 40% of the cases were obese and overweight, respectively, compared to only 12% of the patients who had normal weight (P˂0.05). There were significantly lower vitamin D levels in the patients; however, the concentrations of LDH, serum ferritin, and D-Dimer were significantly higher in the patients, compared to the control group (P˂0.05). Not only age and body weight but also employment status and place of residency maybe also the important risk factors for COVID-19 distribution. LDH, D-dimer, vitamin D, and ferritin statuses could be used as good biomarkers for this disease and its severity.

Predicting Severe Disease and Critical Illness on Initial Diagnosis of COVID-19: Simple Triage Tools

Rationale

This study was conducted to develop, validate, and compare prediction models for severe disease and critical illness among symptomatic patients with confirmed COVID-19.

Methods

For development cohort, 433 symptomatic patients diagnosed with COVID-19 between April 15th 2020 and June 30th, 2020 presented to Tawam Public Hospital, Abu Dhabi, United Arab Emirates were included in this study. Our cohort included both severe and non-severe patients as all cases were admitted for purpose of isolation as per hospital policy. We examined 19 potential predictors of severe disease and critical illness that were recorded at the time of initial assessment. Univariate and multivariate logistic regression analyses were used to construct predictive models. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC). Calibration and goodness of fit of the models were assessed. A cohort of 213 patients assessed at another public hospital in the country during the same period was used to validate the models.

Results

One hundred and eighty-six patients were classified as severe while the remaining 247 were categorized as non-severe. For prediction of progression to severe disease, the three independent predictive factors were age, serum lactate dehydrogenase (LDH) and serum albumin (ALA model). For progression to critical illness, the four independent predictive factors were age, serum LDH, kidney function (eGFR), and serum albumin (ALKA model). The AUC for the ALA and ALKA models were 0.88 (95% CI, 0.86–0.89) and 0.85 (95% CI, 0.83–0.86), respectively. Calibration of the two models showed good fit and the validation cohort showed excellent discrimination, with an AUC of 0.91 (95% CI, 0.83–0.99) for the ALA model and 0.89 (95% CI, 0.80–0.99) for the ALKA model. A free web-based risk calculator was developed.

Conclusions

The ALA and ALKA predictive models were developed and validated based on simple, readily available clinical and laboratory tests assessed at presentation. These models may help frontline clinicians to triage patients for admission or discharge, as well as for early identification of patients at risk of developing critical illness.

Clinical Characteristics and Predictors of Mortality in Minority Patients Hospitalized with COVID-19 Infection

Objectives

To identify the early mortality predictors in minority patients hospitalized with coronavirus disease 2019 (COVID-19).

Design

Demographics, presenting characteristics, admission laboratory data, ICU admission, and mortality data were collected from 200 consecutively hospitalized patients with COVID-19.

Results

The mean (SD) age was 58.9 (15.1) years, 121(60.5%) were men, 143 (71.5%) were African Americans, and 33 (16.5%) were Latino. Common presenting symptoms were cough 130 (65.0%), shortness of breath 129 (64.5%), and fever 121 (60.5%). One or more comorbid illness occurred in 171 (85.5%) and common comorbidities were hypertension (130 (65.2%)), diabetes (100 (50.0%)) and chronic kidney disease (60 (30.0%)). Of the 200 patients, 71 (35.5%) were treated in the ICU, 47 (24.2%) received mechanical ventilation, 45 (22.5%) died, and 155(77.5%) patients discharged home alive. The non-survivors were significantly older and had elevated markers of inflammation, coagulation, and acute organ damage on presentation. Age ≥ 65 years (odds ratio (OR), 3.78; 95% CI, 1.74–8.22; P = .001), lactate dehydrogenase level > 400 IU/L (OR, 9.1; 95% CI, 2.97–28.1; p < 0.001), C-reactive protein > 20 mg/dl (OR, 5.56; 95%CI, 1.84–16.8; p < 0.001), ferritin > 2000 ng/ml (OR, 5.42; 95%CI, 1.63–17.9; p = 0.006), creatinine kinase > 1000 iu/l (OR, 3.57; 95% CI, 1.23 10.3; p = 0.019), procalcitonin > 2.5 ng/ml (OR, 4.21; 95% CI, 1.47–12.0; p = 0.007), D-dimer level > 3.0 μg/ml (OR,10.9; 95% CI, 3.33–36.2; p = < 0.001), creatinine > 2 mg/dl (OR, 4.5; 95% CI, 1.29–15.8; P = 0.018) at admission were associated independently with increases risk of in-hospital mortality.

Conclusion

Patients of advanced age that present with elevated biomarkers of inflammation, coagulation, and end-organ damage were at higher risk of mortality.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40615-020-00961-x.

Lactate dehydrogenase levels predict coronavirus disease 2019 (COVID-19) severity and mortality: A pooled analysis

Coronavirus disease 2019 (COVID-19) infection has now reached a pandemic state, affecting more than a million patients worldwide. Predictors of disease outcomes in these patients need to be urgently assessed to decrease morbidity and societal burden. Lactate dehydrogenase (LDH) has been associated with worse outcomes in patients with viral infections. In this pooled analysis of 9 published studies (n = 1532 COVID-19 patients), we evaluated the association between elevated LDH levels measured at earliest time point in hospitalization and disease outcomes in patients with COVID-19. Elevated LDH levels were associated with a ~6-fold increase in odds of developing severe disease and a ~16-fold increase in odds of mortality in patients with COVID-19. Larger studies are needed to confirm these findings.

Profiles of Coagulation and Fibrinolysis Activation-Associated Molecular Markers of Atypical Hemolytic Uremic Syndrome in the Acute Phase

Aim: Atypical hemolytic uremic syndrome (aHUS), characterized by thrombotic microangiopathy (TMA), is a genetic, life-threatening disease which needs many differential diagnoses. This study aimed to reveal coagulation and fibrinolysis profiles in aHUS and secondary TMA patients. Furthermore, we investigated whether aHUS patients progress to, and meet, disseminated intravascular coagulation (DIC) criteria.

Methods: The acute phase samples were available in 15 aHUS and 20 secondary TMA patients. We measured PT-ratio, activated partial thromboplastin time (APTT), fibrinogen, fibrin degradation product (FDP), fibrin monomer complex (FMC), antithrombin (AT), plasmin-α2 plasmin inhibitor complex (PIC), and von Willebrand factor antigen (VWF:Ag). We examined and compared these tests among aHUS, secondary TMA patients, and healthy volunteer (HV), and evaluated whether patients with aHUS and secondary TMA met DIC criteria.

Results: PT-ratio, APTT, FDP, FMC and PIC in patients with aHUS and secondary TMA were higher than those in HV. Fibrinogen and AT showed no significant difference among three groups. VWF:Ag was higher in only aHUS patients. No tests showed significant difference between aHUS and secondary TMA patients. Three aHUS patients out of 15 met DIC criteria.

Conclusion: We revealed the profiles and distributions of coagulation and fibrinolysis tests of aHUS and secondary TMA patients. All tests were enhanced compared to HV; however, our results showed the no specificities in distinguishing aHUS from secondary TMA patients. We also clarified that some aHUS patients fulfilled DIC diagnostic criteria, indicating that DIC itself cannot be an exclusion criterion of aHUS.