OBJECTIVE:To determine the spectrum of phenotypes linked to the ABO blood group system, using genetic determinants of the ABO blood group system.
APPROACH AND RESULTS:We assessed the risk of 41 ...health and disease outcomes, and 36 linear traits associated with the ABO blood group system in the UK Biobank cohort. A total of 406 755 unrelated individuals were included in this study. Blood groups A, B, and O were determined based on allele combinations of previously established single-nucleotide polymorphisms rs8176746, rs8176719 in the ABO gene. Group AB was excluded because of its relative small sample size. Overall, 187 387 (46%) were male with a mean (SD) age of 57±8.1 years and a median total exposure of 64 person-years (interquartile range, 57–70). Of 406 755 individuals, 182 621 (44.9%) participants had blood group O, 182 786 (44.9%) had blood group A, and 41 348 (10.2%) had blood group B. ABO blood groups were associated with 11 health and disease outcomes (P<2.19×10). ABO blood groups were primarily associated with cardiovascular outcomes. Compared with individuals with blood group O, blood groups A and B were associated with increased odds of up to 1.56 (95% CI, 1.43–1.69) for thromboembolic events and decreased odds for hypertension (0.94 95% CI, 0.92–0.97).
CONCLUSIONS:The ABO blood group system is associated with several parameters of healthy aging and disease development. Knowledge of ABO blood groups might be of interest for more personalized approaches towards health maintenance and the prevention of diseases.
Periodic repolarization dynamics (PRD) is an electrocardiographic biomarker that quantifies low-frequency (LF) instabilities of repolarization. PRD is a strong predictor of mortality in patients with ...ischaemic and non-ischaemic cardiomyopathy. Until recently, two methods for calculating PRD have been proposed. The wavelet analysis has been widely tested and quantifies PRD in deg
units by application of continuous wavelet transformation (PRD
). The phase rectified signal averaging method (PRD
) is an algebraic method, which quantifies PRD in deg. units. The correlation, as well as a conversion formula between the two methods remain unknown.
The first step for quantifying PRD is to calculate the beat-to-beat change in the direction of repolarization, called dT°. PRD is subsequently quantified by means of either wavelet or PRSA-analysis. We simulated 1.000.000 dT°-signals. For each simulated signal we calculated PRD using the wavelet and PRSA-method. We calculated the ratio between PRD
and PRD
for different values of dT° and RR-intervals and applied this ratio in a real-ECG validation cohort of 455 patients after myocardial infarction (MI). We finally calculated the correlation coefficient between real and calculated PRD
. PRD
was dichotomized at the established cut-off value of ≥5.75 deg
.
The ratio between PRD
and PRD
increased with increasing heart-rate and mean dT°-values (p < 0.001 for both). The correlation coefficient between PRD
and PRD
in the validation cohort was 0.908 (95% CI 0.891-0.923), which significantly (p < 0.001) improved to 0.945 (95% CI 0.935-0.955) after applying the formula considering the ratio between PRD
and PRD
obtained from the simulation cohort. The calculated PRD
correctly classified 98% of the patients as low-risk and 87% of the patients as high-risk and correctly identified 97% of high-risk patients, who died within the follow-up period.
This is the first analytical investigation of the different methods used to calculate PRD using simulated and clinical data. In this article we propose a novel algorithm for converting PRD
to the widely validated PRD
, which could unify the calculation methods and cut-offs for PRD.
La enfermedad renal diabética es la principal causa de enfermedad renal crónica (ERC) en el mundo y tanto la diabetes mellitus (DMT2) como la ERC son importantes factores de riesgo para mortalidad. ...Sin embargo, se desconoce si la presencia simultánea de ambas enfermedades modifica el riesgo de muerte.
Evaluar la presencia de interacción entre DMT2 y estadio ERC respecto a la mortalidad en una población representativa de un país latinoamericano.
Estudio analítico en dos cohortes de pacientes con diagnóstico de ERC con cuatro años de seguimiento entre 2004 y 2008. Se calculó la tasa de incidencia, progresión, supervivencia (Kaplan-Meier), interacción (aditiva y multiplicativa) e impacto de la presencia de los diferentes estadios de ERC en pacientes con y sin DMT2 mediante un análisis de riesgos proporcionales de Cox.
En esta población de estudio de 5.663 pacientes, tanto la DMT2 como el estadio de ERC son factores de riesgo para mortalidad (p < 0,001). La diferencia en la supervivencia entre diabéticos y no diabéticos en estadios 3 – 4 – 5 fue estadísticamente significativa (Log-rank p = 0,0076). Se encontró una interacción estadísticamente significativa en las escalas aditiva y multiplicativa entre la presencia de DMT2 y el estadio de ERC, con respecto a la mortalidad (p = 0,005). Se confirmó el impacto de la diabetes como factor de riesgo de mortalidad (Hazard Ratio 1,61 p < 0,001), pero en los pacientes con DMT2 solamente la edad, la dislipidemia y los nefroprotectores estuvieron asociados significativamente con la mortalidad.
La interacción entre ERC y DMT2 modifica de forma negativa el riesgo de muerte de ambas enfermedades. Es decir que el efecto conjunto observado es menor al esperado.
Diabetic kidney disease is the main cause of chronic kidney disease (CKD) worldwide. Both CKD and diabetes mellitus (DMT2) are important risk factors for mortality. However, it is still unknown if the risk of death is modified by the simultaneous presence of these diseases.
To evaluate the presence of an interaction between DMT2 and CKD for mortality in a representative population of a Latin American country.
It is an analytical cohort study of patients with CKD, who were followed for 4 years (between 2004 and 2009). We calculated the incidence rate, progression, survival (using Kaplan–Meier curves), interaction (on the additive and multiplicative scales) and impact of the different stages of CKD in patients with and without DMT2 (using a cox proportional hazards model).
In this population of 5663 individuals, both DMT2 and CKD are risk factors for mortality (P < 0.001). We found a statistically significant difference in mortality between individuals with and without DMT2, who also had CKD stages 3 – 4 – 5 (Log-rank P = 0.0076). Additionally, we found a statistically significant interaction for mortality in both the additive and multiplicative scales between DMT2 and CKD (P = 0.005). DMT2 was found to be a risk factor for mortality (Hazard Ratio 1.61 P < 0.001), but in individuals with DMT2, the only risks significantly associated with mortality, were age, dyslipidemia and nephroprotective drugs.
The interaction between CKD and DMT2 negatively modifies the risk of death of both diseases. This means that when the two diseases are present, the risk of mortality is lower than expected.
Diabetic kidney disease is the main cause of chronic kidney disease (CKD) worldwide. Both CKD and diabetes mellitus (DMT2) are important risk factors for mortality. However, it is still unknown if ...the risk of death is modified by the simultaneous presence of these diseases.
To evaluate the presence of an interaction between DMT2 and CKD for mortality in a representative population of a Latin American country.
It is an analytical cohort study of patients with CKD, who were followed for 4 years (between 2004 and 2009). We calculated the incidence rate, progression, survival (using Kaplan-Meier curves), interaction (on the additive and multiplicative scales) and impact of the different stages of CKD in patients with and without DMT2 (using a cox proportional hazards model).
In this population of 5663 individuals, both DMT2 and CKD are risk factors for mortality (P < 0.001). We found a statistically significant difference in mortality between individuals with and without DMT2, who also had CKD stages 3 - 4 - 5 (Log-rank P = 0.0076). Additionally, we found a statistically significant interaction for mortality in both the additive and multiplicative scales between DMT2 and CKD (P = 0.005). DMT2 was found to be a risk factor for mortality (Hazard Ratio 1.61 P < 0.001), but in individuals with DMT2, the only risks significantly associated with mortality, were age, dyslipidemia and nephroprotective drugs. CONCLUSIóN: The interaction between CKD and DMT2 negatively modifies the risk of death of both diseases. This means that when the two diseases are present, the risk of mortality is lower than expected.
Diabetic kidney disease is the main cause of chronic kidney disease (CKD) worldwide. Both CKD and diabetes mellitus (DMT2) are important risk factors for mortality. However, it is still unknown if ...the risk of death is modified by the simultaneous presence of these diseases.
To evaluate the presence of an interaction between DMT2 and CKD for mortality in a representative population of a Latin American country.
It is an analytical cohort study of patients with CKD, who were followed for 4 years (between 2004 and 2009). We calculated the incidence rate, progression, survival (using Kaplan–Meier curves), interaction (on the additive and multiplicative scales) and impact of the different stages of CKD in patients with and without DMT2 (using a cox proportional hazards model).
In this population of 5663 individuals, both DMT2 and CKD are risk factors for mortality (p<0.001). We found a statistically significant difference in mortality between individuals with and without DMT2, who also had CKD stages 3–4 –5 (Log-rank p=0.0076). Additionally, we found a statistically significant interaction for mortality in both the additive and multiplicative scales between DMT2 and CKD (p=0.005). DMT2 was found to be a risk factor for mortality (Hazard Ratio 1.61 p<0.001), but in individuals with DMT2, the only risks significantly associated with mortality, were age, dyslipidemia and nephroprotective drugs.
The interaction between CKD and DMT2 negatively modifies the risk of death of both diseases. This means that when the two diseases are present, the risk of mortality is lower than expected.
La enfermedad renal diabética es la principal causa de enfermedad renal crónica (ERC) en el mundo y tanto la diabetes mellitus (DMT2) como la ERC son importantes factores de riesgo para mortalidad. Sin embargo, se desconoce si la presencia simultánea de ambas enfermedades modifica el riesgo de muerte.
Evaluar la presencia de interacción entre DMT2 y estadio ERC respecto a la mortalidad en una población representativa de un país latinoamericano.
Estudio analítico en dos cohortes de pacientes con diagnóstico de ERC con cuatro años de seguimiento entre 2004 y 2008. Se calculó la tasa de incidencia, progresión, supervivencia (Kaplan-Meier), interacción (aditiva y multiplicativa) e impacto de la presencia de los diferentes estadios de ERC en pacientes con y sin DMT2 mediante un análisis de riesgos proporcionales de Cox.
En esta población de estudio de 5.663 pacientes, tanto la DMT2 como el estadio de ERC son factores de riesgo para mortalidad (p<0,001). La diferencia en la supervivencia entre diabéticos y no diabéticos en estadios 3 – 4 – 5 fue estadísticamente significativa (Log-rank p=0,0076). Se encontró una interacción estadísticamente significativa en las escalas aditiva y multiplicativa entre la presencia de DMT2 y el estadio de ERC, con respecto a la mortalidad (p=0,005). Se confirmó el impacto de la diabetes como factor de riesgo de mortalidad (Hazard Ratio 1,61 p<0,001), pero en los pacientes con DMT2 solamente la edad, la dislipidemia y los nefroprotectores estuvieron asociados significativamente con la mortalidad.
La interacción entre ERC y DMT2 modifica de forma negativa el riesgo de muerte de ambas enfermedades. Es decir que el efecto conjunto observado es menor al esperado.
Objetivo: describir las características demográficas, clínicas, terapéuticas y microbiológicas de los pacientes con malignidad hematológica en quimioterapia que desarrollan neutropenia febril durante ...el tratamiento, así como la mortalidad al egreso.
Métodos: estudio de cohorte retrospectivo en pacientes con neoplasia hematológica que desarrollaron neutropenia febril evaluados en un hospital universitario de Medellín.
Resultados: se obtuvieron registros de 110 episodios de neutropenia febril. Media de edad 45 años. En el 55,4% se obtuvo diagnostico microbiológico, la bacteriemia fue documentada en el 83,8% de ellos. Los microorganismos más comunes fueron K. pneumoniae (30%) y E. coli (18%). La resistencia a antibióticos por presencia de BLEE o carbapenemasas en bacilos gram negativos fue del 33%. La mortalidad ocurrió en el 17% de los pacientes. La leucemia linfoide aguda (LLA) y leucemia mieloide aguda (LMA) fueron los diagnósticos de base más prevalentes, el foco clínico más prevalente fue bacteriemia (24,5%).
Conclusión: En nuestra serie de casos, hay diferencias significativas en cuanto al porcentaje de pacientes con bacteriemia, así como en la mortalidad global respecto al resto de cohortes de la región, es necesario desarrollar un nuevo trabajo de investigación que permita aclarar el origen de estas diferencias.
En este trabajo se comparó la efectividad de la vacuna contra la COVID-19 (EV) durante agosto de 2021, en personas nacidas entre 1962
y 1971 y vacunadas durante junio, según la marca utilizada. La ...protección frente a infección por SARS-CoV-2 sintomática fue menor
para la vacuna de Janssen (56%; IC95%: 53-59) y AstraZeneca Vaxzevria (68%; IC95%: 65-70), en comparación con Pfizer Comirnaty
(78%; IC95%: 77-78), AZ/Pfizer (86%; IC95%: 80-90) y Moderna Spikevax (89%; IC95%: 88-90). La EV contra la hospitalización
osciló entre el 86% de Janssen y el 97%-98% de las demás vacunas.
In this paper we compared brand-specific COVID-19 vaccine effectiveness (VE) during August 2021 in persons born 1962-1971 and vaccinated
during June. For SARS-CoV-2 symptomatic infection, protection was lower for Janssen (56%; CI95%: 53-59) or AstraZeneca Vaxzevria
(68%; CI95%: 65-70), compared to Pfizer-BioNTech Comirnaty (78%; CI95%: 77-78), AstraZeneca/Pfizer (86%; CI95%: 80-90) or Moderna
Spikevax (89%; CI95%: 88-90). VE against hospitalization was ranged 86% for Janssen to 97%-98% for other vaccines.
Objetivo: describir las caracteristicas demograficas, clinicas, terapeuticas y microbiologicas de los pacientes con malignidad hematologica en quimioterapia que desarrollan neutropenia febril durante ...el tratamiento, asi como la mortalidad al egreso. Metodos: estudio de cohorte retrospectivo en pacientes con neoplasia hematologica que desarrollaron neutropenia febril evaluados en el Hospital Universitario San Vicente Fundacion de Medellin. Resultados: se obtuvo el registro de 110 episodios de neutropenia febril. Media de edad 45 anos. En 55.4% se obtuvo diagnostico microbiologico, la bacteriemia fue documentada en 83.8% de ellos. Los microorganismos mas comunes fueron K. pneumoniae (30%) y E. coli (18%). La resistencia a antibioticos por presencia de BLEE o carbapenemasas en bacilos gram negativos fue de 33%. La mortalidad ocurrio en 17% de los pacientes. La leucemia linfoide aguda (LLA) y leucemia mieloide aguda (LMA) fueron los diagnosticos de base mas prevalentes, el foco clinico mas prevalente fue bacteriemia (24.5%). Conclusion: en nuestra cohorte se encontro diferencias significativas en cuanto al porcentaje de pacientes con bacteriemia, asi como en la mortalidad global respecto al resto de cohortes de la region, es necesario desarrollar un nuevo trabajo de investigacion que permita aclarar el origen de estas diferencias. (Acta Med Colomb 2020; 45. DOI: Palabras clave: neutropenia, quimioterapia, microbiologia. Objective: to describe the demographic, clinical, therapeutic and microbiological characteristics of patients with hematological malignancies undergoing chemotherapy who develop febrile neutropenia during treatment, as well as the mortality at discharge. Methods: a retrospective cohort study of patients with hematologic neoplasms who developed febrile neutropenia and were seen at the Hospital Universitario San Vicente Fundacion in Medellin. Results: records of 110 episodes of febrile neutropenia were obtained. The mean age was 45 years. In 55.4%, a microbiological diagnosis was obtained; bacteremia was documented in 83.8% of these. The most common microorganisms were K. pneumoniae (30%) and E. coli (18%). Antibiotic resistance due to ESBLs or carbapenemases in gram negative bacilli was 33%. Death occurred in 17% of patients. Acute lymphocytic leukemia (ALL) and acute myeloid leukemia (AML) were the most prevalent underlying diagnoses; the most prevalent clinical focus was bacteremia (24.5%). Conclusion: in our case series, there are significant differences in the percentage of patients with bacteremia, as well as in global mortality, compared to the rest of the cohorts in the region. A new research study needs to be carried out to clarify the source of these differences. (Acta Med Colomb 2020; 45. DOI: Key words: neutropenia, chemotherapy, microbiology.
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