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1.
Cir. Esp. (Ed. impr.) ; 101(1): 51-54, en. 2023. ilus
Article in Spanish | IBECS | ID: ibc-226687

ABSTRACT

Las resecciones sublobares anatómicas mínimamente invasivas han ganado relevancia durante los últimos años gracias al avance de las técnicas de imagen, los programas de cribado y el aumento de segundas neoplasias. La identificación precisa del bronquio segmentario o subsegmentario objeto de resección es vital para obtener resultados óptimos en segmentectomías y subsegmentectomías. Dada la complejidad y la posibilidad de variaciones anatómicas, varios autores han publicado distintos métodos para identificar el bronquio objetivo de la resección. Sin embargo, estos métodos tienen ciertas limitaciones. El presente artículo describe una nueva técnica rápida, efectiva, con bajo riesgo de complicaciones y sin coste adicional para la identificación de los bronquios segmentarios en segmentectomías mínimamente invasivas. (AU)


Minimally invasive anatomical sublobar resections have gained relevance in recent years mainly due to advances in imaging techniques, screening programs and the increase in second neoplasms. Accurate identification of the segmental or subsegmental bronchus is vital to guarantee optimal results in segmentectomies and subsegmentectomies. Given the complexity and the possibility of anatomical variations, several authors have published different methods to identify the target bronchus. However, these methods have certain limitations. This article describes a new rapid and effective technique, with a low risk of complications and without additional cost, for the identification of segmental bronchi in minimally invasive segmentectomies. (AU)


Subject(s)
Humans , Male , Female , Middle Aged , Aged , Fluorescence , Bronchi , Lung Neoplasms , Infrared Rays , Adenocarcinoma , Robotics
2.
Cir. Esp. (Ed. impr.) ; 101(1): 51-54, en. 2023. ilus
Article in Spanish | IBECS | ID: ibc-EMG-427

ABSTRACT

Las resecciones sublobares anatómicas mínimamente invasivas han ganado relevancia durante los últimos años gracias al avance de las técnicas de imagen, los programas de cribado y el aumento de segundas neoplasias. La identificación precisa del bronquio segmentario o subsegmentario objeto de resección es vital para obtener resultados óptimos en segmentectomías y subsegmentectomías. Dada la complejidad y la posibilidad de variaciones anatómicas, varios autores han publicado distintos métodos para identificar el bronquio objetivo de la resección. Sin embargo, estos métodos tienen ciertas limitaciones. El presente artículo describe una nueva técnica rápida, efectiva, con bajo riesgo de complicaciones y sin coste adicional para la identificación de los bronquios segmentarios en segmentectomías mínimamente invasivas. (AU)


Minimally invasive anatomical sublobar resections have gained relevance in recent years mainly due to advances in imaging techniques, screening programs and the increase in second neoplasms. Accurate identification of the segmental or subsegmental bronchus is vital to guarantee optimal results in segmentectomies and subsegmentectomies. Given the complexity and the possibility of anatomical variations, several authors have published different methods to identify the target bronchus. However, these methods have certain limitations. This article describes a new rapid and effective technique, with a low risk of complications and without additional cost, for the identification of segmental bronchi in minimally invasive segmentectomies. (AU)


Subject(s)
Humans , Male , Female , Middle Aged , Aged , Fluorescence , Bronchi , Lung Neoplasms , Infrared Rays , Adenocarcinoma , Robotics
3.
Cir Esp (Engl Ed) ; 101(1): 51-54, 2023 Jan.
Article in English | MEDLINE | ID: mdl-35905869

ABSTRACT

Minimally invasive anatomical sublobar resections have gained relevance in recent years mainly due to advances in imaging techniques, screening programs and the increase in second neoplasms. Accurate identification of the segmental or subsegmental bronchus is vital to guarantee optimal results in segmentectomies and subsegmentectomies. Given the complexity and the possibility of anatomical variations, several authors have published different methods to identify the target bronchus. However, these methods have certain limitations. This article describes a new rapid and effective technique, with a low risk of complications and without additional cost, for the identification of segmental bronchi in minimally invasive segmentectomies.


Subject(s)
Pneumonectomy , Robotic Surgical Procedures , Humans , Pneumonectomy/methods , Mastectomy, Segmental , Fluorescence , Bronchi/diagnostic imaging , Bronchi/surgery , Robotic Surgical Procedures/methods
8.
Arch. bronconeumol. (Ed. impr.) ; 57(10): 625-629, Oct. 2021. tab, graf
Article in English | IBECS | ID: ibc-212170

ABSTRACT

Introduction: Failure to rescue (FTR), defined as the mortality rate among patients suffering from postoperative complications, is considered an indicator of the quality of surgical care. The aim of this study was to investigate the risk factors associated with FTR after anatomical lung resections.Method: Patients undergoing anatomical lung resection at our center between 1994 and 2018 were included in the study. Postoperative complications were classified as minor (grade I and II) and major (grade IIIA to V), according to the standardized classification of postoperative morbidity. Patients who died after a major complication were considered FTR. A stepwise logistic regression model was created to identify FTR predictors. Independent variables included in the multivariate analysis were age, body mass index, cardiac, renal, and cerebrovascular comorbidity, ppoFEV1%, VATS approach, extended resection, pneumonectomy, and reintervention. A non-parametric ROC curve was constructed to estimate the predictive capacity of the model.Results: A total of 2.569 patients were included, of which 223 (8.9%) had major complications and 49 (22%) could not be rescued. Variables associated with FTR were: age (OR: 1.07), history of cerebrovascular accident (OR: 3.53), pneumonectomy (OR: 6.67), and reintervention (OR: 12.26). The area under the ROC curve was 0.82 (95% CI: 0.77–0.88).Conclusions: Overall, 22% of patients with major complications following anatomical lung resection in this series did not survive until discharge. Pneumonectomy and reintervention are the most significant risk factors for FTR. (AU)


Introducción: El fallo en el rescate (FTR) definido como la tasa de fallecimientos entre los pacientes que sufren una complicación postoperatoria, es considerado un indicador de la calidad de los cuidados quirúrgicos. El objetivo de este estudio es investigar los factores de riesgo asociados al FTR después de resecciones pulmonares anatómicas.Método: Se incluyeron en el estudio pacientes sometidos a resección pulmonar anatómica en nuestro centro entre 1994 y 2018. Las complicaciones postoperatorias se clasificaron en menores (grados I y II) y mayores (grados IIIa a V) según la clasificación estandarizada de morbilidad postoperatoria. Los casos que fallecieron tras una complicación mayor fueron considerados FTR. Se creó un modelo de regresión logística por pasos para identificar los factores predictores de FTR. Se consideraron variables independientes en el análisis multivariante la edad, índice de masa corporal, comorbilidad cardiaca, renal, cerebrovascular, VEF1ppo%, abordaje VATS, resección extendida, neumonectomía y reintervención. Se construyó una curva ROC no paramétrica para estimar la capacidad predictiva del modelo.Resultados: Se analizaron 2.569 pacientes. En total, 223 casos (8,9%) tuvieron complicaciones mayores y 49 (22%) no pudieron ser rescatados. Las variables asociadas con FTR fueron: edad (OR: 1,07), antecedente de ACV (OR: 3,53), neumonectomía (OR: 6,67) y reintervención (OR: 12,26). El área bajo la curva de la curva ROC fue 0,82 (IC 95%: 0,77–0,88).Conclusiones: 22% de los pacientes que presentan complicaciones mayores tras la resección pulmonar anatómica en esta serie no sobreviven al alta. La neumonectomía y la reintervención son los factores de riesgo más potentes para FTR. (AU)


Subject(s)
Humans , Male , Female , Middle Aged , Aged , Pneumonectomy , Failure to Rescue, Health Care , Postoperative Complications/mortality , Retrospective Studies , Quality Indicators, Health Care , Risk Factors
9.
Cir. Esp. (Ed. impr.) ; 99(6): 421-427, jun.- jul. 2021. ilus, graf, tab
Article in Spanish | IBECS | ID: ibc-218164

ABSTRACT

Introducción: La cirugía robótica se ha convertido en una vía de abordaje segura y efectiva para el tratamiento de la patología quirúrgica pulmonar. Sin embargo, la adopción de nuevas técnicas quirúrgicas requiere de la evaluación de la curva de aprendizaje. El objetivo de este estudio es analizar la curva de aprendizaje de las resecciones pulmonares anatómicas por vía robótica. Métodos: Análisis retrospectivo de todas las resecciones pulmonares anatómicas por vía robótica realizadas por un mismo cirujano entre junio de 2018 y marzo de 2020. La curva de aprendizaje se evaluó utilizando gráficas CUSUM para estimar los cambios en la tendencia del tiempo y los fallos quirúrgicos y la aparición de complicaciones cardiorrespiratorias postoperatorias a lo largo de la secuencia de casos. Resultados: El estudio incluyó un total de 73 casos. La mediana de duración de todas las intervenciones fue de 120min (rango intercuartílico: 90-150min), la prevalencia de fallo quirúrgico fue del 23,29%, mientras que 4/73 pacientes presentaron alguna complicación cardiorrespiratoria postoperatoria. Con base en el análisis CUSUM, la curva de aprendizaje fue dividida en 3 fases diferentes: fase i (desde la primera hasta la 14.a intervención), fase ii (entre la 15.a y la 30.a intervención) y fase iii (a partir de la 31.a intervención). Conclusiones: La curva de aprendizaje para las resecciones pulmonares anatómicas por vía robótica puede dividirse en 3 fases. La competencia técnica que asegura resultados perioperatorios satisfactorios se consiguió en la fase iii, a partir de la 31.a intervención. (AU)


Introduction: Robotic surgery has become a safe and effective approach for the treatment of pulmonary surgical pathology. However, the adoption of new surgical techniques requires the evaluation of the learning curve. The objective of this study is to analyze the learning curve of robotic anatomical lung resections. Methods: Retrospective analysis of all robotic anatomical lung resections performed by the same surgeon between June 2018 and March 2020. The learning curve was evaluated using CUSUM charts to estimate trend changes in surgical time, surgical failure and the occurrence of post-operative cardiorespiratory complications throughout the sequence of cases. Results: The study included a total of 73 cases. The median duration of all complications was 120min (interquartile range: 90-150min), the prevalence of surgical failure was 23.29%, while 4/73 patients had any postoperative cardiorespiratory complication. Based on the CUSUM analysis, the learning curve was divided into 3 different phases: phase i (from the first to the 14th intervention), phase ii (between the 15th and 30th intervention) and phase iii (from the 31st intervention). Conclusions: The learning curve for robotic anatomical lung resections can be divided into 3 phases. The technical competence that guarantees satisfactory perioperative outcomes was achived in phase iii from the 31st intervention. (AU)


Subject(s)
Humans , Male , Female , Middle Aged , Aged , Thoracic Surgery , Robotic Surgical Procedures , Learning Curve , Lung/pathology , Lung/surgery
10.
Cir Esp (Engl Ed) ; 99(6): 421-427, 2021.
Article in English | MEDLINE | ID: mdl-34099400

ABSTRACT

INTRODUCTION: Robotic surgery has become a safe and effective approach for the treatment of pulmonary surgical pathology. However, the adoption of new surgical techniques requires the evaluation of the learning curve. The objective of this study is to analyze the learning curve of robotic anatomical lung resections. METHODS: Retrospective analysis of all robotic anatomical lung resections performed by the same surgeon between June 2018 and March 2020. The learning curve was evaluated using CUSUM charts to estimate trend changes in surgical time, surgical failure and the occurrence of post-operative cardiorespiratory complications throughout the sequence of cases. RESULTS: The study included a total of 73 cases. The median duration of all complications was 120 min (interquartile range: 90-150 min), the prevalence of surgical failure was 23.29%, while 4/73 patients had any postoperative cardiorespiratory complication. Based on the CUSUM analysis, the learning curve was divided into 3 different phases: phase i (from the first to the 14th intervention), phase ii (between the 15th and 30th intervention) and phase iii (from the 31st intervention). CONCLUSIONS: The learning curve for robotic anatomical lung resections can be divided into 3 phases. The technical competence that guarantees satisfactory perioperative outcomes was achived in phase iii from the 31st intervention.


Subject(s)
Learning Curve , Robotic Surgical Procedures , Humans , Lung/surgery , Operative Time , Retrospective Studies , Robotic Surgical Procedures/adverse effects
12.
Arch Bronconeumol ; 57(10): 625-629, 2021 Oct.
Article in English | MEDLINE | ID: mdl-35702903

ABSTRACT

INTRODUCTION: Failure to rescue (FTR), defined as the mortality rate among patients suffering from postoperative complications, is considered an indicator of the quality of surgical care. The aim of this study was to investigate the risk factors associated with FTR after anatomical lung resections. METHOD: Patients undergoing anatomical lung resection at our center between 1994 and 2018 were included in the study. Postoperative complications were classified as minor (grade I and II) and major (grade IIIA to V), according to the standardized classification of postoperative morbidity. Patients who died after a major complication were considered FTR. A stepwise logistic regression model was created to identify FTR predictors. Independent variables included in the multivariate analysis were age, body mass index, cardiac, renal, and cerebrovascular comorbidity, ppoFEV1%, VATS approach, extended resection, pneumonectomy, and reintervention. A non-parametric ROC curve was constructed to estimate the predictive capacity of the model. RESULTS: A total of 2.569 patients were included, of which 223 (8.9%) had major complications and 49 (22%) could not be rescued. Variables associated with FTR were: age (OR: 1.07), history of cerebrovascular accident (OR: 3.53), pneumonectomy (OR: 6.67), and reintervention (OR: 12.26). The area under the ROC curve was 0.82 (95% CI: 0.77-0.88). CONCLUSIONS: Overall, 22% of patients with major complications following anatomical lung resection in this series did not survive until discharge. Pneumonectomy and reintervention are the most significant risk factors for FTR.


Subject(s)
Pneumonectomy , Postoperative Complications , Humans , Logistic Models , Lung , Pneumonectomy/adverse effects , Postoperative Complications/epidemiology , Postoperative Complications/etiology , Retrospective Studies , Risk Factors
13.
Rev. ORL (Salamanca) ; 11(3): 383-388, jul.-sept. 2020. ilus
Article in Spanish | IBECS | ID: ibc-197906

ABSTRACT

INTRODUCCIÓN Y OBJETIVO: La prevalencia de paratiroides ectópicas oscila entre el 6.3 % y el 26 % en pacientes intervenidos por hiperparatiroidismo y la exploración mediastínica es necesaria en alrededor del 1-2 % de los pacientes con paratiroides ectópica. El objetivo del presente artículo es describir las particularidades del tratamiento quirúrgico de las paratiroides mediastínicas. SÍNTESIS: La localización preoperatoria de paratiroides ectópicas es fundamental para asegurar el éxito de la intervención; la gamma-grafía de doble fase con 99mTc-metoxi-isobutil-isonitrilo (99mTc-MIBI) se considera la técnica gold estándar para su localización. La navegación intraoperatoria radioguiada con sonda gamma y la monitorización intraoperatoria de la PTH son útiles para reducir el tiempo quirúrgico y evitar re-exploraciones innecesarias. Los abordajes mínimamente invasivos (VATS o cirugía robótica) para la exploración y extirpación de lesiones presentes en mediastino ofrecen ventajas sobre los abordajes abiertos convencionales como son la magnificación y mejor visión de las estructuras y la maniobrabilidad. CONCLUSIONES: El éxito de la extirpación quirúrgica de las paratiroides ectópicas se basa en la adecuada localización preoperatoria. La navegación radioguiada con sonda gamma y la monitorización de la PTH intraoperatorias son útiles para asegurar la adecuada resección de la paratiroides. Los abordajes mínimamente invasivos (VATS o cirugía robótica) han reducido la necesidad de esternotomía o toracotomía


Introduction and objective: The prevalence of ectopic parathyroids ranges from 6.3 % to 26 % in patients undergoing surgery due to hyperparathyroidism and mediastinal exploration is necessary in about 1-2 % of patients with ectopic parathyroid. The objective of this article is to describe the particularities of surgical treatment of mediastinal parathyroids. SYNTHESIS: Preoperative localization of ectopic parathyroids is essential to ensure the success of the intervention; dual phase scintigraphy with 99mTc-methoxy-isobutyl-isonitrile (99mTc-MIBI) is considered the gold standard technique for its location. Intraoperative radioguided navigation with a gamma probe and intraoperative monitoring of PTH are useful for reducing surgical time and avoiding unnecessary re-examinations. Minimally invasive approaches (VATS or robotic surgery) for the exploration and removal of mediastinal lesions offer advantages over conventional open approaches such as magnification and better vision of structures and maneuverability. CONCLUSIONS: The success of surgical removal of ectopic parathyroids is based on the appropriate preoperative location. Radio-guided navigation with gamma probe and intraoperative PTH monitoring are useful to ensure adequate parathyroid resection. Minimally invasive approaches (VATS or robotic surgery) have reduced the need for sternotomy or thoracotomy


Subject(s)
Humans , Thoracic Surgery/methods , Parathyroid Glands/surgery , Thoracic Surgery, Video-Assisted/trends , Parathyroid Diseases/surgery , Radionuclide Imaging , Tomography, Emission-Computed , Tomography, X-Ray Computed
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