Aim
The objective was to assess the effect of three different surgical treatments for T1 rectal tumours, radical resection (RR), open local excision (open LE) and laparoscopic local excision ...(laparoscopic LE), on overall survival (OS).
Methods
Adults from the National Cancer Database (2008–2016) with a diagnosis of T1 rectal cancer were stratified by treatment type (LE vs RR). We assumed that laparoscopic LE equates to transanal minimally invasive surgery (TAMIS) or transanal endoscopic microsurgery. The primary outcome was 5‐year OS. Subgroup analyses of the LE group stratified by time period 2008–2010 (before TAMIS) vs 2011–2016 (after TAMIS) and approach (laparoscopic vs open) were performed.
Results
Among 10 053 patients, 6623 (65.88%) underwent LE (74.33% laparoscopic LE vs 25.67% open LE) and 3430 (34.12%) RR. The use of LE increased from 52.69% in 2008 to 69.47% in 2016, whereas RR decreased (P < 0.001). In unadjusted analysis, there was no significant difference in 5‐year OS between the LE and RR groups (P = 0.639) and between the two LE time periods (P = 0.509), which was consistent with the adjusted analysis (LE vs RR, hazard ratio 1.05, 95% CI 0.92–1.20, P = 0.468; 2008–2010 LE vs 2011–2016 LE, hazard ratio 1.09, 95% CI 0.92–1.29, P = 0.321). Laparoscopic LE was associated with improved OS in the unadjusted analysis only (P = 0.006), compared to the open LE group (hazard ratio 0.94, 95% CI 0.78–1.12, P = 0.495).
Conclusions
This study supports the use of a LE approach for T1 rectal tumours as a strategy to reduce surgical morbidity without compromising survival.
PurposeTo quantify early neuroretinal alterations in patients with type 1 diabetes mellitus (T1DM) and to assess whether glycemic variability contributes to alterations in neuroretinal structure or ...function.MethodsThirty patients with T1DM and 51 controls underwent comprehensive ophthalmic examination and assessment of retinal function or structure with frequency doubling perimetry (FDP), contrast sensitivity, dark adaptation, fundus photography, and optical coherence tomography (OCT). Diabetic participants wore a subcutaneous continuous glucose monitor for 5 days, from which makers of glycemic variability including the low blood glucose index (LGBI) and area under the curve (AUC) for hypoglycemia were derived.ResultsSixteen patients had no diabetic retinopathy (DR), and 14 had mild or moderate DR. Log contrast sensitivity for the DM group was significantly reduced (mean±SD=1.63±0.06) compared with controls (1.77±0.13, P<0.001). OCT analysis revealed that the inner temporal inner nuclear layer (INL) was thinner in patients with T1DM (34.9±2.8 μm) compared with controls (36.5±2.9 μm) (P=0.023), although this effect lost statistical significance after application of the Bonferroni correction for multiple comparisons. Both markers of glycemic variability, the AUC for hypoglycemia (R=-0.458, P=0.006) and LGBI (R=-0.473, P=0.004), were negatively correlated with inner temporal INL thickness.ConclusionsPatients with T1DM and no to moderate DR exhibit alterations in inner retinal structure and function. Increased glycemic variability correlates with retinal thinning on OCT imaging, suggesting that fluctuations in blood glucose may contribute to neurodegeneration.
Coaching your faculty and yourself Stem, Jonathan M.; Greenberg, Caprice C.
Surgery,
April 2024, 2024-Apr, 2024-04-00, 20240401, Volume:
175, Issue:
4
Journal Article
Peer reviewed
Surgical skills vary drastically among practicing surgeons. This variation in skill has been demonstrated to translate directly into patient outcomes, highlighting the importance of skill ...development. Despite this, directed efforts to improve surgical skills and performance among practicing surgeons remain limited. The development of surgical coaching programs offers an exciting opportunity for surgeon performance improvement and lifelong development. In this article, we will discuss the promise of surgical coaching programs, some of the challenges met when developing a program, and future avenues and opportunities for growth within the field.
Summary
Neoadjuvant therapy has proven to be effective in the reduction of locoregional recurrence and mortality for esophageal cancer. However, induction treatment has been reported to be associated ...with increased risk of postoperative complications. We therefore compared outcomes after esophagectomy for esophageal cancer for patients who underwent neoadjuvant therapy and patients treated with surgery alone. Using the American College of Surgeons National Surgical Quality Improvement Program database (2005–2011), we identified 1939 patients who underwent esophagectomy for esophageal cancer. Seven hundred and eight (36.5%) received neoadjuvant therapy, while 1231 (63.5%) received no neoadjuvant therapy within 90 days prior to surgery. Primary outcome was 30‐day mortality, and secondary outcomes included overall and serious morbidity, length of stay, and operative time. Patients who underwent neoadjuvant treatment were younger (62.3 vs. 64.7, P < 0.001), were more likely to have experienced recent weight loss (29.4% vs. 15.9%, P < 0.001), and had worse preoperative hematological cell counts (white blood cells <4.5 or >11 × 109/L: 29.3% vs. 15.0%, P < 0.001; hematocrit <36%: 49.7% vs. 30.0%, P < 0.001). On unadjusted analysis, 30‐day mortality, overall, and serious morbidity were comparable between the two groups, with the exception of the individual complications of venous thromboembolic events and bleeding transfusion, which were significantly lower in the surgery‐only patients (5.71% vs. 8.27%, P = 0.027; 6.89% vs. 10.57%, P = 0.004; respectively). Multivariable and matched analysis confirmed that 30‐day mortality, overall, and serious morbidity, as well as prolonged length of stay, were comparable between the two groups of patients. An increasing trend of preoperative neoadjuvant therapy for esophageal cancer was observed through the study years (from 29.0% in 2005–2006 to 44.0% in 2011, P < 0.001). According to our analysis, preoperative neoadjuvant therapy for esophageal cancer does not increase 30‐day mortality or the overall risk of postoperative complications after esophagectomy.
Surgical-site infection is a source of significant morbidity after colorectal surgery. Previous efforts to develop models that predict surgical-site infection have had limited accuracy. Machine ...learning has shown promise in predicting postoperative outcomes by identifying nonlinear patterns within large data sets.
This study aimed to seek usage of machine learning to develop a more accurate predictive model for colorectal surgical-site infections.
Patients who underwent colorectal surgery were identified in the American College of Surgeons National Quality Improvement Program database from years 2012 to 2019 and were split into training, validation, and test sets. Machine-learning techniques included random forest, gradient boosting, and artificial neural network. A logistic regression model was also created. Model performance was assessed using area under the receiver operating characteristic curve.
A national, multicenter data set.
Patients who underwent colorectal surgery.
The primary outcome (surgical-site infection) included patients who experienced superficial, deep, or organ-space surgical-site infections.
The data set included 275,152 patients after the application of exclusion criteria. Of all patients, 10.7% experienced a surgical-site infection. Artificial neural network showed the best performance with area under the receiver operating characteristic curve of 0.769 (95% CI, 0.762-0.777), compared with 0.766 (95% CI, 0.759-0.774) for gradient boosting, 0.764 (95% CI, 0.756-0.772) for random forest, and 0.677 (95% CI, 0.669-0.685) for logistic regression. For the artificial neural network model, the strongest predictors of surgical-site infection were organ-space surgical-site infection present at time of surgery, operative time, oral antibiotic bowel preparation, and surgical approach.
Local institutional validation was not performed.
Machine-learning techniques predict colorectal surgical-site infections with higher accuracy than logistic regression. These techniques may be used to identify patients at increased risk and to target preventive interventions for surgical-site infection. See Video Abstract at http://links.lww.com/DCR/C88 .
ANTECEDENTES:La infección del sitio quirúrgico es una fuente de morbilidad significativa después de la cirugía colorrectal. Los esfuerzos anteriores para desarrollar modelos que predijeran la infección del sitio quirúrgico han tenido una precisión limitada. El aprendizaje automático se ha mostrado prometedor en la predicción de los resultados posoperatorios mediante la identificación de patrones no lineales dentro de grandes conjuntos de datos.OBJETIVO:Intentamos utilizar el aprendizaje automático para desarrollar un modelo predictivo más preciso para las infecciones del sitio quirúrgico colorrectal.DISEÑO:Los pacientes que se sometieron a cirugía colorrectal se identificaron en la base de datos del Programa Nacional de Mejoramiento de la Calidad del Colegio Estadounidense de Cirujanos de los años 2012 a 2019 y se dividieron en conjuntos de capacitación, validación y prueba. Las técnicas de aprendizaje automático incluyeron conjunto aleatorio, aumento de gradiente y red neuronal artificial. También se creó un modelo de regresión logística. El rendimiento del modelo se evaluó utilizando el área bajo la curva característica operativa del receptor.CONFIGURACIÓN:Un conjunto de datos multicéntrico nacional.PACIENTES:Pacientes intervenidos de cirugía colorrectal.PRINCIPALES MEDIDAS DE RESULTADO:El resultado primario (infección del sitio quirúrgico) incluyó pacientes que experimentaron infecciones superficiales, profundas o del espacio de órganos del sitio quirúrgico.RESULTADOS:El conjunto de datos incluyó 275.152 pacientes después de la aplicación de los criterios de exclusión. El 10,7% de los pacientes presentó infección del sitio quirúrgico. La red neuronal artificial mostró el mejor rendimiento con el área bajo la curva característica operativa del receptor de 0,769 (IC del 95 %: 0,762 - 0,777), en comparación con 0,766 (IC del 95 %: 0,759 - 0,774) para el aumento de gradiente, 0,764 (IC del 95 %: 0,756 - 0,772) para conjunto aleatorio y 0,677 (IC 95% 0,669 - 0,685) para regresión logística. Para el modelo de red neuronal artificial, los predictores más fuertes de infección del sitio quirúrgico fueron la infección del sitio quirúrgico del espacio del órgano presente en el momento de la cirugía, el tiempo operatorio, la preparación intestinal con antibióticos orales y el abordaje quirúrgico.LIMITACIONES:No se realizó validación institucional local.CONCLUSIONES:Las técnicas de aprendizaje automático predicen infecciones del sitio quirúrgico colorrectal con mayor precisión que la regresión logística. Estas técnicas se pueden usar para identificar a los pacientes con mayor riesgo y para orientar las intervenciones preventivas para la infección del sitio quirúrgico. Consulte Video Resumen en http://links.lww.com/DCR/C88 . (Traducción-Dr Yolanda Colorado ).
IPAA is considered the procedure of choice for restorative surgery after total colectomy for ulcerative colitis. Previous studies have examined the rate of IPAA within individual states but not at ...the national level in the United States.
This study aimed to assess the rate of IPAA after total colectomy for ulcerative colitis in a national population and identify factors associated with IPAA.
This was a retrospective cohort study.
This study was performed in the United States.
Patients who were aged 18 years or older and who underwent total colectomy between 2009 and 2019 for a diagnosis of ulcerative colitis were identified within a commercial database. This database excluded patients with public insurance, including all patients older than 65 years with Medicare.
The primary outcome was IPAA. Multivariable logistic regression was used to assess the association between covariates and the likelihood of undergoing IPAA.
In total, 2816 patients were included, of whom 1414 (50.2%) underwent IPAA, 928 (33.0%) underwent no further surgery, and 474 (16.8%) underwent proctectomy with end ileostomy. Younger age, lower comorbidities, elective case, and laparoscopic approach in the initial colectomy were significantly associated with IPAA but socioeconomic status was not.
This retrospective study included only patients with commercial insurance.
A total of 50.2% of patients who had total colectomy for ulcerative colitis underwent IPAA, and younger age, lower comorbidities, and elective cases are associated with a higher rate of IPAA placement. This study emphasizes the importance of ensuring follow-up with colorectal surgeons to provide the option of restorative surgery, especially for patients undergoing urgent or emergent colectomies. See Video Abstract .
ANTECEDENTES:La anastomosis ileo-anal se considera el procedimiento de elección para la cirugía reparadora tras la colectomía total por colitis ulcerosa. Estudios previos han examinado la tasa de anastomosis ileo-anal dentro de los estados individuales, pero no a nivel nacional en los Estados Unidos.OBJETIVO:Evaluar la tasa de anastomosis bolsa ileal-anal después de la colectomía total para la colitis ulcerosa en una población nacional e identificar los factores asociados con la anastomosis bolsa ileal-anal.DISEÑO:Se trata de un estudio de cohortes retrospectivo.LUGAR:Este estudio se realizó en los Estados Unidos.PACIENTES:Los pacientes que tenían ≥18 años de edad que se sometieron a colectomía total entre 2009 y 2019 para un diagnóstico de colitis ulcerosa fueron identificados dentro de una base de datos comercial. Esta base de datos excluyó a los pacientes con seguro público, incluidos todos los pacientes >65 años con Medicare.MEDIDAS DE RESULTADO PRINCIPALES:El resultado primario fue la anastomosis ileal bolsa-anal. Se utilizó una regresión logística multivariable para evaluar la asociación entre las covariables y la probabilidad de someterse a una anastomosis ileal.RESULTADOS:En total, se incluyeron 2.816 pacientes, de los cuales 1.414 (50,2%) se sometieron a anastomosis ileo-anal, 928 (33,0%) no se sometieron a ninguna otra intervención quirúrgica y 474 (16,8%) se sometieron a proctectomía con ileostomía terminal. La edad más joven, las comorbilidades más bajas, el caso electivo, y el abordaje laparoscópico en la colectomía inicial se asociaron significativamente con la anastomosis ileal bolsa-anal, pero no el estatus socioeconómico.LIMITACIONES:Este estudio retrospectivo incluyó sólo pacientes con seguro comercial.CONCLUSIONES:Un 50,2% de los pacientes se someten a anastomosis ileo-anal y la edad más joven, las comorbilidades más bajas y los casos electivos se asocian con una mayor tasa de colocación de anastomosis ileo-anal. Esto subraya la importancia de asegurar el seguimiento con cirujanos colorrectales para ofrecer la opción de cirugía reparadora, especialmente en pacientes sometidos a colectomías urgentes o emergentes. (Traducción-Dr. Yolanda Colorado ).
Background
Ureteral injury (UI) is a rare but devastating complication during colorectal surgery. Ureteral stents may reduce UI but carry risks themselves. Risk predictors for UI could help target ...the use of stents, but previous efforts have relied on logistic regression (LR), shown moderate accuracy, and used intraoperative variables. We sought to use an emerging approach in predictive analytics, machine learning, to create a model for UI.
Methods
Patients who underwent colorectal surgery were identified in the National Surgical Quality Improvement Program (NSQIP) database. Patients were split into training, validation, and test sets. The primary outcome was UI. Three machine learning approaches were tested including random forest (RF), gradient boosting (XGB), and neural networks (NN), and compared with traditional LR. Model performance was assessed using area under the curve (AUROC).
Results
The data set included 262,923 patients, of whom 1519 (.578%) experienced UI. Of the modeling techniques, XGB performed the best, with an AUROC score of .774 (95% CI .742-.807) compared with .698 (95% CI .664-.733) for LR. Random forest and NN performed similarly with scores of .738 and .763, respectively. Type of procedure, work RVUs, indication for surgery, and mechanical bowel prep showed the strongest influence on model predictions.
Conclusions
Machine learning-based models significantly outperformed LR and previous models and showed high accuracy in predicting UI during colorectal surgery. With proper validation, they could be used to support decision making regarding the placement of ureteral stents preoperatively.
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