Analysis in calculating Osseo dental discrepancy manually and in I Model Analysis 2 application

Objetivo: determinar si existe diferencia entre el cálculo de la discrepancia oseodentaria de forma ma-nual y utilizando la aplicación iModelanalisys2. Materiales y método: Se conformó una muestra por conveniencia de 120 modelos de estudio pretratamiento de ortodoncia. Se procedió a realizar la me-dición de todos los órganos dentarios tanto de la arcada superior como inferior, así como la longitud total de ambos arcos con un calibrador digital y calculadora. Posteriormente se realizó el calculo de la discrepancia oseodental introduciendo los datos obtenidos en la aplicación iModelAnalysis2, en un Smartphone. Resultados: El promedio de edad de la muestra fue de 17 años. En el maxilar la media de la discrepancia ósea dentaria al calcularlo de forma manual fue de -3.7mm y al calcularla con el progra-ma iModelAnalysis2 el promedio de la discrepancia óseo dentaria fue de -3.22mm. En la mandíbula, la diferencia entre utilizar la aplicación y hacerlo de forma manual presentó una discrepancia de 0.5mm. Al realizar la comparación de los resultados mediante pruebas de t de Student, no se encontraron dife-rencias estadísticamente significativas. Conclusiones: realizar el calculo de la discrepancia osea dentaria en forma manual o utilizando la aplicación para smartphone iModelanalisys2 no alterará el diagnóstico.Objective: Determine whether there is a difference between the calculation of the discrepancy osseoden-tal manually and using the iModelanalisys2 application. Materials and method: A convenience sample of 120 models pretreatment orthodontic study was formed. We proceeded to perform the measurement of all dental organs of the upper and lower arch, and the total length of both arches with a digital caliper and calculator. Subsequently, the calculation discrepancy oseodental entering the data obtained in the iModelAnalysis2 application in a smartphone. Results: The average age of the sample was 17 years. In the maxillary average dental bone discrepancy to manually calculate it was -3.7mm and calculate the average program iModelAnalysis2 dental bone discrepancy was -3.22mm. In the mandible, the diffe-rence between using the application and do it manually discrepancy of 0.5mm. When comparing the results using Student’s t test, no statistically significant differences were found. Conclusions: Realising the calculation of the osseodental discrepancy manually or using the smartphone application iModela-nalisys2 not alter jthe diagnosis

La renovación de la palabra en el bicentenario de la Argentina : los colores de la mirada lingüística

El libro reúne trabajos en los que se exponen resultados de investigaciones presentadas por investigadores de Argentina, Chile, Brasil, España, Italia y Alemania en el XII Congreso de la Sociedad Argentina de Lingüística (SAL), Bicentenario: la renovación de la palabra, realizado en Mendoza, Argentina, entre el 6 y el 9 de abril de 2010. Las temáticas abordadas en los 167 capítulos muestran las grandes líneas de investigación que se desarrollan fundamentalmente en nuestro país, pero también en los otros países mencionados arriba, y señalan además las áreas que recién se inician, con poca tradición en nuestro país y que deberían fomentarse. Los trabajos aquí publicados se enmarcan dentro de las siguientes disciplinas y/o campos de investigación: Fonología, Sintaxis, Semántica y Pragmática, Lingüística Cognitiva, Análisis del Discurso, Psicolingüística, Adquisición de la Lengua, Sociolingüística y Dialectología, Didáctica de la lengua, Lingüística Aplicada, Lingüística Computacional, Historia de la Lengua y la Lingüística, Lenguas Aborígenes, Filosofía del Lenguaje, Lexicología y Terminología

Necesidad de tratamiento ortodóntico utilizando el Índice Estética Dental (DAI) en una población de Guadalajara, Jalisco, México

El Índice de Estética Dental, DAI, permite determinar la severidad de las maloclusiones, con lo que se puede priorizar la necesidad de tratamiento ortodóncico de los pacientes. Material y Métodos: la muestra fue de 123 modelos de estudio pretratamiento de ortodoncia, se valoraron los modelos de estudio con el Índice de Estética Dental, se tabuló y calculó la estadística descriptiva con programa Microsoft Office Excel 2007. Resultados: El promedio del DAI fue de 39.84, el 53% de la población presentó una maloclusión muy severa con necesidad de tratamiento obligatorio, el 17.9% con maloclusión severa con necesidad de tratamiento deseable por el paciente, la categoría de maloclusión definitiva, que requiere tratamiento, se presentó en el 17.1% y solo el 11.4% presentó una oclusión normal sin necesidad de tratamiento. Conclusión: En la población de estudio fue mayor el porcentaje de maloclusión muy severa, las otras tres categorías del índice presentaron valores del 17% al 11%. Las mujeres que acudieron a atención con el ortodoncista presentaron mayor porcentaje de severidad de maloclusión que los hombres. Estos porcentajes demuestran que los pacientes que acuden, o son remitidos al ortodoncista, presentan maloclusiones severas

Global variation in postoperative mortality and complications after cancer surgery: a multicentre, prospective cohort study in 82 countries

© 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: 80% of individuals with cancer will require a surgical procedure, yet little comparative data exist on early outcomes in low-income and middle-income countries (LMICs). We compared postoperative outcomes in breast, colorectal, and gastric cancer surgery in hospitals worldwide, focusing on the effect of disease stage and complications on postoperative mortality. Methods: This was a multicentre, international prospective cohort study of consecutive adult patients undergoing surgery for primary breast, colorectal, or gastric cancer requiring a skin incision done under general or neuraxial anaesthesia. The primary outcome was death or major complication within 30 days of surgery. Multilevel logistic regression determined relationships within three-level nested models of patients within hospitals and countries. Hospital-level infrastructure effects were explored with three-way mediation analyses. This study was registered with ClinicalTrials.gov, NCT03471494. Findings: Between April 1, 2018, and Jan 31, 2019, we enrolled 15 958 patients from 428 hospitals in 82 countries (high income 9106 patients, 31 countries; upper-middle income 2721 patients, 23 countries; or lower-middle income 4131 patients, 28 countries). Patients in LMICs presented with more advanced disease compared with patients in high-income countries. 30-day mortality was higher for gastric cancer in low-income or lower-middle-income countries (adjusted odds ratio 3·72, 95% CI 1·70–8·16) and for colorectal cancer in low-income or lower-middle-income countries (4·59, 2·39–8·80) and upper-middle-income countries (2·06, 1·11–3·83). No difference in 30-day mortality was seen in breast cancer. The proportion of patients who died after a major complication was greatest in low-income or lower-middle-income countries (6·15, 3·26–11·59) and upper-middle-income countries (3·89, 2·08–7·29). Postoperative death after complications was partly explained by patient factors (60%) and partly by hospital or country (40%). The absence of consistently available postoperative care facilities was associated with seven to 10 more deaths per 100 major complications in LMICs. Cancer stage alone explained little of the early variation in mortality or postoperative complications. Interpretation: Higher levels of mortality after cancer surgery in LMICs was not fully explained by later presentation of disease. The capacity to rescue patients from surgical complications is a tangible opportunity for meaningful intervention. Early death after cancer surgery might be reduced by policies focusing on strengthening perioperative care systems to detect and intervene in common complications. Funding: National Institute for Health Research Global Health Research Unit

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licenseBackground: Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide. Methods: A multimethods analysis was performed as part of the GlobalSurg 3 study—a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital. Findings: Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3·85 [95% CI 2·58–5·75]; p<0·0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63·0% vs 82·7%; OR 0·35 [0·23–0·53]; p<0·0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer. Interpretation: Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised. Funding: National Institute for Health and Care Research