Lp(a) Levels in Relatives of Patients with Acute Coronary Syndrome and Elevated Lp(a): HER(a) Study.

Background: Lipoprotein(a) [Lp(a)] is a proatherogenic particle associated with increased cardiovascular risk. It is mainly genetically determined; so, the aim of our study is to evaluate the levels of Lp(a) in the relatives of a prospective cohort of patients who have suffered from an acute coronary syndrome (ACS) with Lp(a) ≥ 50 mg/dL. Methods: We conducted a multicenter prospective study, in which consecutive patients who had suffered from an ACS and presented Lp(a) ≥ 50 mg/dL and their first-degree relatives were included. Results: We included 413 subjects, of which 56.4% were relatives of the patients. Family history of early ischemic heart disease was present in 57.5%, and only 20.6% were receiving statin treatment. The family cohort was younger (37.5 vs. 59.1 years; p < 0.001), and 4% had ischemic heart disease and fewer cardiovascular risk factors. Mean Lp(a) levels were 64.9 mg/dL, 59.4% had levels ≥ 50 mg/dL, and 16.1% had levels ≥ 100 mg/dL. When comparing the patients with respect to their relatives, the mean level of Lp(a) was lower but without significant differences regarding the levels of LDLc, ApoB, and non-HDL. However, relatives with Lp(a) ≥ 50 mg/dL, had values similar to the group of patients with ACS (96.8 vs. 103.8 mg/dL; p = 0.18). No differences were found in Lp(a) levels in relatives based on the other lipid parameters. Conclusions: Overall, 59.4% of the first-degree relatives of patients who suffered from an ACS with Lp(a) ≥ 50 mg/dL also had elevated levels. Relatives with elevated Lp(a) had similar levels as patients.

[Usefulness of COVID-19 patients first analysis made at the Emergency Department as a prediction tool for mortality (PMCovid Score).] / Utilidad de la primera analítica de Urgencias realizada en pacientes con COVID-19 como predictora de mortalidad (PMCOVID SCORE).

OBJECTIVE: The COVID-19 pandemic has generated a high demand for hospital resources taking the national health system to its limit. In order to reduce this over burden and to avoid a potential system collapse, it would be beneficial to generate scientific evidence for the prognosis of the disease and to count with models that are able to forecast the mortality and progression of the disease. Identify mortality risk factors in COVID-19 patients from analytic data obtained from the Emergency Service at our hospital and to elaborate a prognostic score for predicting 30-day mortality (PMCovid Score) that will be included in the report submitted by the Emergency Clinic Laboratory. METHODS: Transversal descriptive study in a population that came to the Emergency Service at the University Hospital of Jaén between March 8th and April 7th 2020. We obtained the variables for the prognosis by a univariate data analysis. On this basis, we applied a multivariate analysis of the logistical regression of the mortality after 30 days in order to generate a prognostic score which was validated subsequently by the TRIPOD method. RESULTS: 298 patients were included. PMCovid Score assigns 1 point to patients age ≥77 years old; 1 point to patients with a urea level ≥49 mg/dL, 1 point to erythrocyte values <4.6x106/µL, 2 points to platelet values <165x103/µL; 1 point to patients with a percentage of lymphocytes below 18.1%; 1 point to those with a % of monocytes <6.8% and 2 points if the % of eosinophils is <0.4%.Our score had a predictive accuracy of 88.6% (AUC 0.886 IC at 95%; 0.842-0.931), with a sensibility of 91.7% (IC at 95% 82.810-100) and a specificity of 69.7% (IC at 95% 63.840-75.680). CONCLUSIONS: PMCovid Score provides the doctor with information on the prognosis of the positive COVID-19 patient along with the usual first analysis data, the necessary parameters for the calculations are available at all Emergency Laboratory Clinics. This information can be very useful for the management of this kind of patients and their classification based on the risk supplied by the PMCovid Score.

OBJETIVO: La pandemia por COVID-19 ha generado una alta demanda de recursos hospitalarios llevando al límite al sistema nacional de salud. Es por ello que para reducir dicha sobrecarga y el posible colapso del sistema, sería beneficioso generar evidencia científica sobre el pronóstico de la enfermedad y disponer de modelos que permitan predecir la mortalidad y la progresión de la enfermedad. El objetivo de este trabajo fue identificar factores de riesgo de mortalidad en pacientes COVID-19 a partir de los datos analíticos solicitados por el Servicio de Urgencias del hospital y elaborar un score pronóstico de mortalidad a 30 días. METODOS: Estudio transversal descriptivo en pacientes con COVID-19 que acudieron al Servicio de Urgencias del Hospital Universitario de Jaén entre el 8 de marzo y el 7 de abril de 2020. Las variables con utilidad para el pronóstico se obtuvieron mediante un análisis univariante de los datos, a partir de ellas se aplicó un análisis multivariante de regresión logística de mortalidad a los 30 días para generar el score pronóstico que posteriormente fue validado mediante el método TRIPOD. RESULTADOS: Se incluyeron 298 pacientes. PMCovid Score asigna 1 punto a pacientes con edad ≥77 años; 1 punto a los pacientes con niveles de urea ≥49 mg/dL, 1 punto a valores de hematíes <4,6x106/µL, 2 puntos a valores de plaquetas <165x103/µL; 1 punto a pacientes con un porcentaje de linfocitos inferior al 18,1%; 1 punto a los que tenga un porcentaje de monocitos menores a 6,8% y 2 puntos si el porcentaje de eosinófilos es menor del 0,4%. La capacidad pronóstica de nuestro score fue del 88,6% (AUC 0,886 IC al 95%; 0,842-0,931), con una sensibilidad del 91,7% (IC al 95% 82,810-100) y una especificidad del 69,7% (IC al 95% 63,840-75,680). CONCLUSIONES: PMCovid Score proporciona al clínico información acerca del pronóstico del paciente con COVID-19 positivo con los datos habituales de la primera analítica, los parámetros necesarios para el cálculo están disponibles en la totalidad de los Laboratorios Clínicos de Urgencias.

Analysis of HLA-ABC locus-specific transcription in normal tissues.

We developed a novel human leukocyte antigen HLA-ABC locus-specific quantitative real-time polymerase chain reaction (PCR) to determine the locus-specific gene expression of HLA-ABC in peripheral blood leukocytes (PBLs, n = 53), colon mucosa (n = 15), and larynx mucosa (n = 15). Laser-assisted tissue microdissection allowed us to study the selected cells without interference from surrounding stroma. We report evidence on the specificity of the technique, describing the HLA-ABC locus-specific gene expression patterns found in the PBLs and two solid tissues studied. PBLs showed a higher gene expression of HLA-B than of HLA-A or HLA-C (p = 4.7 × 10(-10) and p = 1.6 × 10(-6), respectively). In solid tissue, HLA-A and HLA-B gene expressions were similar and HLA-C expression lower. In particular, in larynx mucosa, significant differences were found between HLA-A and HLA-C expressions and between HLA-B and HLA-C expressions (p = 6.5 × 10(-4) and p = 8.1 × 10(-4), respectively). The same differences were observed in colon mucosa, but significance was not reached (p = 0.08 and p = 0.06, respectively). Differences in locus-specific regulation may be related to the control of cytotoxic responses of NK and CD8 positive T cells. Gene expression of HLA-ABC specific locus showed no intra-individual variability, but there was a high inter-individual variability. This may result from differences in the expression of common regulatory factors that control HLA-ABC constitutive expression.