, a cumulative total of over 23 million cases of coronavirus disease 2019 (COVID-19) infections and 800,000 related deaths has been reported [1]. Although most infected people present with mild-tomoderate symptoms, about one-third require hospitalization [2] (Last accessed 27 Aug 2020). Identification of valid prognostic factors for patients with COVID-19 might be helpful in the early diagnosis of "high-risk" individuals [3]. Some demographic and clinical variablesnotably age, male sex, smoking or comorbidities such as cardiovascular disease, obesity or diabeteshave been associated with a worse prognosis [4]. By contrast, while some potential blood biomarkers (e.g., lactate dehydrogenase [LDH], C-reactive protein, coagulation parameters or lymphopenia) are emerging [4, 5], the evidence remains scarce and validation using advanced analyses in different cohorts is needed. The use of artificial intelligence (e.g., artificial neural network [ANN]) as a form of predictive analysis could help in this regard, and its combination with standard observation at triage might help to correctly identify those patients at a higher risk [6]. We have studied the prognostic value (in terms of survival) of potential "early" routine biochemistry and hematological biomarkers in patients with COVID-19. This is a retrospective study of all admitted patients diagnosed with COVID-19 (by polymerase chain reaction) in a large public Hospital of Madrid, Spain (Hospital 12 de Octubre) from February 28 to March 30. The protocol was approved by the Ethics Committee of the aforementioned institution (reference #20/222) and adhered to the Declaration of Helsinki. The predictive value (i.e., odds of dying in the hospital versus discharge) of routine serum biochemistry (Cobas 8000 platform; Roche Diagnostics, Risch-Rotkreuz, Switzerland) and hematological parameters (DxH 900 hematology analyzer, Beckman Coulter, Alejandro Santos-Lozano and Fernando Calvo-Boyero contributed equally to this work.
Objectives We aimed to determine whether the plasma profile of lactate dehydrogenase (LDH) isoenzymes is altered in patients with COVID-19, and whether this is attributable to a specific release of LDH-3, the main LDH isoenzyme expressed in lungs. Design and Methods : We collected fresh plasma aliquots from 17 patients (LDH range, 281 to 822 U/L) and seven controls (LDH < 230 U/L). In-gel relative activity of the different LDH isoenzymes was determined by electrophoresis and densitometric analysis. Results Despite the expected higher total LDH activity levels in patients (p<0.001), the in-gel relative activities of LDH isoenzymes did not differ between patients and controls (all p>0.05). We found no correlation between total plasma LDH activity and the in-gel relative activities of the different LDH isoenzymes, including LDH-3. Likewise, there was no correlation between LDH-3 and various routine haematological and serum parameters that have been previously reported to be altered in COVID-19 (such as lymphocyte count, albumin, alanine and aspartate aminotransferase, creatinine, C-reactive protein, or ferritin). Conclusions Our findings suggest that elevation of plasma LDH activity in patients with COVID-19 is not associated to a specific release of LDH-3 into the bloodstream, and do not support the use of LDH as a specific biomarker for lung affectation in patients with COVID-19.
BackgroundPreeclampsia (PE) is a specific pregnancy syndrome that affects 2–5% of healthy women. This risk increases up to 10–30% in patients with autoimmune diseases such as Systemic Lupus Erythematosus (SLE) and/or Antiphospholipid Syndrome (APS). Differential diagnosis between PE and disease flare during pregnancy is often difficult. Pulsatility index of uterine arteries (mPI-UtA), serum levels of endoglin and the ratio tyrosine kinase-like soluble receptor/ placental growth factor (sFlt-1/PlGF) are useful markers for early diagnosis of PE, even in asymptomatic women.ObjectivesTo analyse the utility of these markers among pregnant patients with SLE/APS.MethodsWe included patients consecutively followed in our high-risk pregnancy clinic from 2008 to the present. These patients had diagnosis of SLE (ACR criteria 1987), LES-like (<4 ACR-SLE 1987 criteria), APS (Sydney criteria) or antiphospholipid antibodies without fulfilling criteria APS (aPL). PE and its severity were diagnosed according to the International Society for the Study of Hypertension in Pregnancy criteria (ISSHP). Lupus activity was assessed with moderate considering SLEPDAI index ≥6 and APS according to the clinical activity. Follow-up visits were performed at 11–13, 22, 28 and 32 weeks and postpartum. We collected clinical data about autoimmune disease and pregnancy, treatments, toxic and cardiovascular risk factors, analytical data including endoglin and ratio and Doppler ultrasound (mPI-UtA). We performed a descriptive analysis, Chi-square or t-Student tests according to the type of variable. Odds ratio and confidence intervals were calculated by using simple logistic regression.ResultsWe analysed 58 pregnancies. Lupus activity during pregnancy was detected in 6 patients (10.3%), 5 with SLE and one with LES-like diagnosis. Two patients developed moderate to severe activity (SLEPDAI 25 and 12, respectively) with worsening since 24th week (33.3%). Two patients with SLE +/− APS developed PE (3.4%). We found statistically significant association between PlGF and ratio values in week 32 and development of PE [(mean 151.76±118.85 with p=0.023) and (89.62±114.70 with p=0.020), respectively)]. In addition, the values of endoglin, ratio and mPI-UtA were higher in PE than in normal pregnancy or flares since 24 week (see Table). On the other hand, there not seems to be differences in scores between patients with lupus activity and normal development of pregnancy.ConclusionsDespite the limited number of patients who develop complications in our cohort, it seems that the mPI-UtA, endoglin and ratio in patients with SLE and/or APS behaves as in the general population and may help in the differential diagnosis of preeclampsia and disease activity.Disclosure of InterestNone declared
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.