Vascular compression syndromes: the value of Doppler ultrasonography.

Vascular compression syndromes arise when a vessel in a tight anatomic space is entrapped by another structure, resulting in diverse symptoms for which different imaging tests are used to diagnose. Radiologists need to be familiar with vascular compression syndromes and to be able to identify their most representative findings. This paper aims to review the principal symptoms of vascular compression, describing and illustrating the key findings on Doppler ultrasonography that enable accurate diagnosis and guide further workup, avoiding unnecessary invasive tests and pointing to the appropriate treatment.

Síndromes de compresión vascular. Valor de la ecografía Doppler / Vascular compression syndromes: the value of Doppler ultrasonography

Los síndromes de compresión vascular consisten en el atrapamiento de un vaso por otra estructura en un espacio anatómico reducido, lo que provoca sintomatología diversa y para cuyo diagnóstico se emplean diferentes pruebas de imagen. Es importante familiarizarse con este tipo de patología y ser capaces de identificar sus hallazgos más representativos. El objetivo de este artículo es revisar los principales síndromes de compresión vascular, aportando datos clave de hallazgos en la ecografía Doppler que permitan establecer un diagnóstico acertado, evitar otras pruebas más agresivas o seleccionar aquellos pacientes que las requieran y orientar el tratamiento adecuado.(AU)

Vascular compression syndromes arise when a vessel in a tight anatomic space is entrapped by another structure, resulting in diverse symptoms for which different imaging tests are used to diagnose. Radiologists need to be familiar with vascular compression syndromes and to be able to identify their most representative findings. This paper aims to review the principal symptoms of vascular compression, describing and illustrating the key findings on Doppler ultrasonography that enable accurate diagnosis and guide further workup, avoiding unnecessary invasive tests and pointing to the appropriate treatment.(AU)

Effect of DPYD, MTHFR, ABCB1, XRCC1, ERCC1 and GSTP1 on chemotherapy related toxicity in colorectal carcinoma.

ABCB1, DPYD, MHTFR, XRCC1, ERCC1, GSTP1 and UGT1A1 genetic variants affect proteins related to CRC chemotherapy toxicity. A retrospective cohort study was conducted in 194 CRC patients. In first line treatment, DPYD rs17376848 AG genotype was associated with hematological toxicity (OR = 4.85; p = 0.03); GSTP1 G-allele (OR = 3.01; p = 0.005) and MTHFR rs1801133 T allele (OR = 2.51; p = 0.03) with respiratory toxicity; GSTP1 G-allele with cardiovascular toxicity (OR = 4.05; p = 0.01); ERCC1 rs11615 GG genotype with neurological toxicity (OR = 3.98; p = 0.01) and with asthenia (OR = 2.91; p = 0.08); XRCC1 rs1799782 T allele (OR = 0.31; p = 0.03) and GSTP1 G-allele (OR = 1.81; p = 0.01) with cutaneous toxicity. In second line treatment, XRCC1 rs1799782 T-allele was associated with asthenia (OR = 0.17; p = 0.03) and XRCC1 rs25487 T-allele with gastrointestinal toxicity (OR = 3.03; p = 0.005). After stratifying by treatment, in the 5-Fluorouracil group, the DPYD rs17376848 AG genotype was associated with hematological toxicity (OR = 2.76; p = 0.003), ABCB1 rs1045642 T-allele with the need of treatment adjustment due to toxicity (OR = 3.06; p = 0.01), and rs1045642 CC genotype with gastrointestinal toxicity (OR = 5.80; p = 0.03). In the capecitabine group, the MTHFR rs1801131 CC genotype was associated with asthenia (OR = 3.48; p = 0.009). In the oxaliplatin group, rs1045642 TT genotype was associated with the need to adjust treatment (OR = 0.32; p = 0.02), ERCC1 rs11615 GG genotype with asthenia (OR = 3.01; p = 0.01) and rs1615 GSTP1 GG genotype with respiratory toxicity (OR = 5.07; p = 0.009). ABCB1 rs1045642 T-allele reduces the need for treatment modification with both 5FU and oxaliplatin. Although several biomarkers predicted different toxic effects, they cannot be considered as risk factors for severe toxicity.

Análisis modal de fallos y efectos en las prescripciones farmacológicas informatizadas / Failure mode and effects analysis on computerized drug prescriptions

Objetivo. Determinar y analizar los errores en las prescripciones farmacológicas de pacientes asistidos en un hospital de alta resolución mediante la aplicación de un análisis modal de fallos y efectos (AMFE). Material y métodos. Un grupo multidisciplinar de distintas especialidades médicas y de enfermería analizó historias clínicas, en las que las prescripciones farmacológicas se realizaban en formato de texto libre. Se desarrolló un AMFE en el que el índice de prioridad de riesgos (IPR) se obtuvo a partir de un estudio observacional transversal, mediante una auditoría de historias clínicas realizada en 2 fases: 1) verificación previa a la intervención y 2) evaluación de las acciones de mejora después del primer análisis. El tamaño muestral auditable, calculado con técnica de muestreo estratificado y selección aleatoria de episodios clínicos, fue de 679 historias clínicas. Resultados. Se incluyó a 2.096 pacientes. Los errores de prescripción respecto del total de prescripciones descendieron en la segunda fase un 22,2%. En las variables con IPR mayor («vía de administración no especificada» y «dosificación no especificada») no se observaron descensos significativos en la segunda fase, durante la cual no se detectó «pauta horaria incorrecta», «contraindicación del fármaco por alergia», «paciente incorrecto» ni «duplicidad de prescripción», lo que redundó en la mejora de las prescripciones. Conclusiones. Se han determinado y analizado errores de prescripciones farmacológicas mediante la metodología AMFE, mejorando la seguridad clínica de dichas prescripciones. La herramienta permite monitorizar actualizaciones del sistema de prescripción electrónica. Para evitar dichos errores se requeriría que todos los apartados de una prescripción fueran de registro obligado (AU)

Objective. To identify and analyze errors in drug prescriptions of patients treated in a «high resolution» hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Results. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in «unspecified route of administration» and «dosage unspecified», with no significant decreases observed in the second phase, although it did detect, «incorrect dosing time», «contraindication due to drug allergy», «wrong patient» or «duplicate prescription», which resulted in the improvement of prescriptions. Conclusions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription (AU)

[Failure mode and effects analysis on computerized drug prescriptions]. / Análisis modal de fallos y efectos en las prescripciones farmacológicas informatizadas.

OBJECTIVE: To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. RESULTS: Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. CONCLUSIONS: Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription.

[Utilization of a post-anesthetic recovery index]. / Utilización de un índice de recuperación postanestésica.

OBJECTIVES: 1. To introduce use of the postanesthesia recovery score (assessing consciousness, mobility, ventilation, hemodynamics and blood analysis) as a good method for evaluating and classifying recovery from anesthesia in the postoperative care unit. 2. To determine overall patient progress and assess the influence of various patient, anesthetic and surgical factors. PATIENTS AND METHODS: This was a multicenter study of 1,227 patients. We excluded all patients who were to be transferred to intensive care units after surgery. A score of 10 or more, with no single item score equal to 0, was considered optimal for discharge from the postanesthesia care unit. RESULTS: The lowest score upon admission to the unit was among patients who had undergone high abdominal surgery (16.4%). Scores over 9 belonged to patients who had undergone lower abdominal and perineal surgery (87.5 and 95.3%, respectively). Scores were < or = 9 in patients who received inhaled anesthetics (42%). Intravenous anesthesia patients (84.4%) had scores over 9. The local-regional anesthetic procedures with the best scores were axilar blocks and local infiltrations. Patients staying longer in the recovery unit were those classified as ASA III, those whose procedures lasted longer than 120 minutes, those undergoing surgery on the upper abdomen or on extremities, those receiving isoflurane and pancuronium, and those suffering adverse events during and after the procedure. Factors influencing perioperative events were age, duration of procedure and history of intraoperative events.