Mean platelet volume as a prognostic factor for venous thromboembolic disease.

BACKGROUND: Mean platelet volume (MPV) is a risk factor for cardiovascular and inflammatory diseases. AIM: To evaluate the association between high MPV and 90-day mortality after an episode of venous thromboembolism (VTE). MATERIAL AND METHODS: Retrospective cohort of 594 patients with a median age of 73 years (58% women) with a first episode VTE, included in an institutional Thromboembolic Disease registry between 2014 and 2015. MPV values were obtained from the automated blood cell count measured at the moment of VTE diagnosis. Volumes ≥ 11 fL were classified as high. All patients were followed for 90 days to assess survival. RESULTS: The main comorbidities were cancer in 221 patients (37%), sepsis in 172 (29%) and coronary artery disease in 107 (18%). Median MPV was 8 fl (8-9), brain natriuretic peptide 2,000 pg/ml (1,025-3,900) and troponin 40 pg/ml (19.5-75). Overall mortality was 20% (121/594) during the 90 days of follow-up. Thirty three deaths occurred within 7 days and 43 within the first month. The loss of patients from follow-up was 5% (28/594) at 90 days. Mortality among patients with high MP was 36% (23/63). The crude mortality hazard ratio (HR) for high MPV was 2.2 (95% confidence intervals (CI) 1.4-3.5). When adjusted for sepsis, oncological disease, heart disease, kidney failure and surgery, the mortality HR of high MPV was 2.4 (CI95% 1.5-3.9) in the VTE group, 2.3 (CI95% 1.5-4.4) in the deep venous thrombosis group, and 2.9 (CI95% 1.6 -5.6) in the pulmonary embolism group. CONCLUSIONS: High MPV is an independent risk factor for mortality following an episode of VTE.

Mean platelet volume as a prognostic factor for venous thromboembolic disease / Volumen plaquetario medio como factor pronóstico de la enfermedad tromboembólica venosa

ABSTRACT Background: Mean platelet volume (MPV) is a risk factor for cardiovascular and inflammatory diseases. Aim: To evaluate the association between high MPV and 90-day mortality after an episode of venous thromboembolism (VTE). Material and Methods: Retrospective cohort of 594 patients with a median age of 73 years (58% women) with a first episode VTE, included in an institutional Thromboembolic Disease registry between 2014 and 2015. MPV values were obtained from the automated blood cell count measured at the moment of VTE diagnosis. Volumes ≥ 11 fL were classified as high. All patients were followed for 90 days to assess survival. Results: The main comorbidities were cancer in 221 patients (37%), sepsis in 172 (29%) and coronary artery disease in 107 (18%). Median MPV was 8 fl (8-9), brain natriuretic peptide 2,000 pg/ml (1,025-3,900) and troponin 40 pg/ml (19.5-75). Overall mortality was 20% (121/594) during the 90 days of follow-up. Thirty three deaths occurred within 7 days and 43 within the first month. The loss of patients from follow-up was 5% (28/594) at 90 days. Mortality among patients with high MP was 36% (23/63). The crude mortality hazard ratio (HR) for high MPV was 2.2 (95% confidence intervals (CI) 1.4-3.5). When adjusted for sepsis, oncological disease, heart disease, kidney failure and surgery, the mortality HR of high MPV was 2.4 (CI95% 1.5-3.9) in the VTE group, 2.3 (CI95% 1.5-4.4) in the deep venous thrombosis group, and 2.9 (CI95% 1.6 −5.6) in the pulmonary embolism group. Conclusions: High MPV is an independent risk factor for mortality following an episode of VTE.

Antecedentes: El volumen plaquetario medio (VPM) es un factor de riesgo de complicaciones cardiovasculares y enfermedades inflamatorias. Objetivo: Evaluar la asociación entre VPM alto y la mortalidad a los 90 días después de un episodio de tromboembolismo venoso (ETV). Material y Métodos: Cohorte retrospectiva de 594 pacientes adultos con una edad media de 73 años (58% mujeres) con un primer episodio de ETV incluidos en un registro de enfermedad tromboembólica institucional entre 2014 y 2015. Se obtuvieron valores de VPM desde el hemograma tomado en el momento del diagnóstico de ETV y un volumen ≥ 11 fL fue clasificado como alto. Todos los pacientes fueron seguidos durante 90 días para determinar sobrevida. Resultados: Las comorbilidades fueron cáncer en 221 pacientes (37%), sepsis en 172 (29%) y enfermedad coronaria en 107 (18%). La mediana de VPM fue 8 fl (89), el péptido natriurético cerebral fue de 2.000 pg/ml (1.025-3.900) y la troponina fue de 40 pg/ml (19,5-75). La mortalidad global a 90 días fue 20% (121/594). Treinta y tres muertes ocurrieron dentro de los 7 días y 43 en el primer mes. La pérdida de seguimiento de pacientes fue de 5% (28/594) a los 90 días. La mortalidad en el grupo con VPM alto fue 36% (23/63). La razón de riesgo (HR) cruda de la mortalidad para un VPM alto fue de 2,2 (intervalos de confianza (IC) de 95% 1,4-3,5). Cuando se ajustó por sepsis, enfermedad oncológica, enfermedad cardíaca, insuficiencia renal y cirugía, la HR de muerte para un VPM alto fue de 2,4 (IC95% 1,5-3,9) en el grupo de ETV; 2,3 (IC95% 1,5-4,4) en el grupo de trombosis venosa profunda; y 2,9 (CI95% 1,6 −5,6) en el grupo de embolia pulmonar. Conclusiones: Un VPM alto es un factor de riesgo independiente de mortalidad después de un episodio de ETV.

Statistical Process Control: A Quality Tool for a Venous Thromboembolic Disease Registry.

OBJECTIVE: We aim to describe Statistical Control Process as a quality tool for the Institutional Registry of Venous Thromboembolic Disease (IRTD), a registry developed in a community-care tertiary hospital in Buenos Aires, Argentina. METHODS: The IRTD is a prospective cohort. The process of data acquisition began with the creation of a computerized alert generated whenever physicians requested imaging or laboratory study to diagnose venous thromboembolism, which defined eligible patients. The process then followed a structured methodology for patient's inclusion, evaluation, and posterior data entry. To control this process, process performance indicators were designed to be measured monthly. These included the number of eligible patients, the number of included patients, median time to patient's evaluation, and percentage of patients lost to evaluation. Control charts were graphed for each indicator. RESULTS: The registry was evaluated in 93 months, where 25,757 patients were reported and 6,798 patients met inclusion criteria. The median time to evaluation was 20 hours (SD, 12) and 7.7% of the total was lost to evaluation. Each indicator presented trends over time, caused by structural changes and improvement cycles, and therefore the central limit suffered inflexions. CONCLUSION: Statistical process control through process performance indicators allowed us to control the performance of the registry over time to detect systematic problems. We postulate that this approach could be reproduced for other clinical registries.