Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers

Objective: This study examines factors predicting self-reported voice symptoms in call center workers. Methods: Multivariate analysis and predictive modeling assess personal, work-related, acoustic, and behavioral factors. Generalized Linear Models (GLMs) and Receiver Operating Characteristic (ROC) curves are employed. Results: Age and sleep patterns impacted voice quality and effort, while workplace factors influenced symptom perception. Unhealthy vocal behaviors related to tense voice and increased effort, while hydration was protective. Voice acoustics showed diagnostic potential, supported by ROC data. These findings emphasize voice symptom complexity in call center professionals, necessitating comprehensive assessment. Limitations: This study recognizes its limitations, including a moderate-sized convenience sample and reliance on PROM metrics. Future research should incorporate more objective measures in addition to self-reports and acoustic analysis. Value: This research provides novel insights into the interplay of personal, occupational, and voice-related factors in developing voice symptoms among call center workers. Predictive modeling enhances risk assessment and understanding of individual susceptibility to voice disorders. Conclusion: Results show associations between various factors and self-reported voice symptoms. Protective factors include sleeping more than six hours and consistent hydration, whereas risk factors include working conditions, such as location and behaviors like smoking. Diagnostic models indicate good accuracy for some voice symptom PROMs, emphasizing the need for comprehensive models considering work factors, vocal behaviors, and acoustic parameters to understand voice issues complexity.

Objetivo: Este estudio examina los factores que predicen los síntomas de voz en los trabajadores de call centers. Métodos: Se utilizan análisis multivariados y modelos predictivos para evaluar factores personales, laborales, acústicos y de comportamiento. Se emplean Modelos Lineales Generalizados (GLM) y curvas ROC. Resultados: La edad y los patrones de sueño afectaron la calidad vocal y el esfuerzo, mientras que los factores laborales influyeron en la percepción de síntomas. Los comportamientos vocales no saludables se relacionaron con voz tensa y mayor esfuerzo, mientras que la hidratación fue protectora. Los parámetros acústicos de voz mostraron potencial diagnóstico respaldado por datos de ROC. Los hallazgos subrayan complejidad de síntomas vocales en profesionales de centros de llamadas, requiriendo una evaluación integral. Limitaciones: Este estudio reconoce sus limitaciones, que incluyen una muestra de conveniencia de tamaño moderado y la dependencia de medidas PROMs. Futuras investigaciones deberían incorporar medidas objetivas, además de los autorreportes y análisis acústico. Importancia: Esta investigación aporta nuevos conocimientos sobre factores personales, laborales y síntomas de voz en trabajadores de call centers. El modelado predictivo mejora la evaluación de riesgos y la comprensión de la susceptibilidad individual a trastornos de la voz. Conclusión: Los resultados muestran asociaciones entre diversos factores y los síntomas vocales reportados. Los factores de protección incluyen dormir más de seis horas y una hidratación constante; los factores de riesgo incluyen las condiciones de trabajo, como la ubicación y comportamientos como fumar. Los modelos de diagnóstico indican una buena precisión para algunas PROMs de síntomas de la voz, lo que subraya la necesidad de modelos integrales que tengan en cuenta los factores laborales, los comportamientos vocales y los parámetros acústicos para comprender la complejidad de los problemas de la voz.

Development and validation of a clinical prediction model for prognostic factors in patients with primary pontine hemorrhage

Abstract We aimed to develop a prognostic model for primary pontine hemorrhage (PPH) patients and validate the predictive value of the model for a good prognosis at 90 days. A total of 254 PPH patients were included for screening of the independent predictors of prognosis, and data were analyzed by univariate and multivariable logistic regression tests. The cases were then divided into training cohort (n=219) and validation cohort (n=35) based on the two centers. A nomogram was developed using independent predictors from the training cohort to predict the 90-day good outcome and was validated from the validation cohort. Glasgow Coma Scale score, normalized pixels (used to describe bleeding volume), and mechanical ventilation were significant predictors of a good outcome of PPH at 90 days in the training cohort (all P<0.05). The U test showed no statistical difference (P=0.892) between the training cohort and the validation cohort, suggesting the model fitted well. The new model showed good discrimination (area under the curve=0.833). The decision curve analysis of the nomogram of the training cohort indicated a great net benefit. The PPH nomogram comprising the Glasgow Coma Scale score, normalized pixels, and mechanical ventilation may facilitate predicting a 90-day good outcome.

Variáveis Clínicas e Laboratoriais na Admissão Hospitalar são Preditores de Fibrilação Atrial Nova em Pacientes Internados com Pneumonia por COVID-19 / Clinical and Laboratory Data Up on Hospital Admission are Predictors of New-Onset Atrial Fibrillation in Patients Hospitalized Due to COVID-19 Pneumonia

Resumo Fundamento Fibrilação atrial nova (FAN) ocorre em pacientes internados por COVID-19. Há controvérsias quanto ao valor preditivo de dados clínicos e laboratoriais à admissão hospitalar para ocorrência de FAN. Objetivos Analisar, à admissão hospitalar, variáveis com potencial preditivo para ocorrência de FAN em pacientes com pneumonia por COVID-19. Método Estudo observacional, retrospectivo, caso-controle. Foram avaliados prontuários eletrônicos de pacientes consecutivos ≥ 60 anos, hospitalizados com pneumonia por COVID-19 entre 1º de março e 15 de julho de 2020. Comparações feitas pelos testes `t' de Student ou qui-quadrado. Foi empregado modelo de risco proporcional de Cox para identificação de preditores de FAN. Considerou-se o valor de p < 0,05 como estatisticamente significativo. Resultados Entre 667 pacientes internados por COVID-19, 201 (30,1%) foram incluídos. FAN foi documentada em 29 pacientes (14,4%) (grupo 1). Grupo 2 foi composto por 162 pacientes que não apresentaram FAN. Dez pacientes excluídos por estarem em FA na admissão hospitalar. Houve diferenças entre os grupos 1 e 2, respectivamente, no tempo de permanência em UTI (11,1±10,5 dias vs. 4,9±7,5 dias; p=0,004), necessidade de ventilação invasiva (82,9% e 32,7%; p<0,001) e mortalidade hospitalar (75,9% vs. 32,1%; p<0,001). No modelo de Cox, idade > 71 anos (hazard ratio [HR]=6,8; p<0,001), leucometria ≤ 7.720 cels.μL-1 (HR=6,6; p<0,001), natremia ≤ 137 mEq.L-1 (HR=5,0; p=0,001), escore SAPS3 > 55 (HR=5,6; p=0,002) e desorientação (HR=2,5; p=0,04) foram preditores independentes de FAN. Conclusões FAN é uma arritmia comum em idosos hospitalizados com pneumonia por COVID-19. Parâmetros clínicos e laboratoriais avaliados na admissão são preditores de FAN durante internação.

Abstract Background New-onset atrial fibrillation (NOAF) occurs in patients hospitalized due to COVID-19. It is still unknown whether clinical and laboratory data assessed upon hospital admission have predictive value for NOAF. Objectives To analyze, upon hospital admission, variables with predictive potential for the occurrence of NOAF in patients with COVID-19 pneumonia. Methods Observational, retrospective, case-control study. Electronic medical reports of consecutive patients, 60 years of age or older, hospitalized due to COVID-19 pneumonia between March 1st and July 15th, 2020, were reviewed. Non-paired Student or chi-squared tests compared variables. A Cox proportional hazard model was employed to identify independent predictors of NOAF. P value < 0.05 was considered statistically significant. Results Among 667 patients hospitalized due to COVID-19, 201 (30.1%) fulfilled the inclusion criteria. NOAF was documented in 29 patients (14.4%), composing group 1. Group 2 was composed of 162 patients without NOAF. Ten patients were excluded due to the AF rhythm upon hospital admission. In groups 1 and 2, there were differences in overall in-hospital survival rate (24.1 % vs. 67.9%; p<0.001), length of stay in ICU (11.1 ± 10.5 days vs. 4.9 ± 7.5 days; p=0.004) and need for mechanical ventilation rate (82.9% vs. 32.7%; p<0.001). In the Cox model, age > 71 y/o (HR=6.8; p<0.001), total leukocyte count ≤ 7,720 cels.μL-¹ (HR=6.6; p<0.001), serum [Na+] ≤ 137 mEq.L-¹ (HR=5.0; p=0.001), SAPS3 score > 55 (HR=5.6; p=0.002), and disorientation (HR=2.5; p=0.04) on admission were independent predictors of NOAF. Conclusion NOAF is a common arrhythmia in elderly hospitalized patients with COVID-19 pneumonia. Clinical and laboratory parameters evaluated on admission have a predictive value for the occurrence of NOAF during hospitalization.

Application progress of predictive models in the prevention and control of myopia in children and adolescents / 国际眼科杂志(Guoji Yanke Zazhi)

In medical research,predictive models have been widely used to predict disease progression and identify high-risk populations in advance, especially in the prevention and diagnosis of chronic diseases. In ophthalmology, the predictive and diagnostic models for fundus diseases such as age-related macular degeneration and diabetic retinopathy have demonstrated expert-level accuracy. However, the application of predictive models is still in the exploratory stage as for myopia prevention and control. The establishment of a predictive model is helpful to identify the high-risk myopic children in advance, so that preventive measures such as adequate outdoor activities and reducing near work can be taken in time, which is of great significance to prevent or slow down the occurrence and development of myopia. Because the mechanism of myopia has not been fully elucidated, there are still challenges and limitations in the selection of application objects, predictors and predictive outcomes. This paper reviews the research progress of different types of myopia predictive models in order to provide reference for further development and improvement.

Stellate Ganglion Block as an Adjunctive Intervention for Chronic Subjective Tinnitus： Efficacy and Predictive Indicators / 中山大学学报(医学科学版)

ObjectiveTo explore the efficacy and predictive indicators of stellate ganglion block （SGB） as an adjunctive intervention for chronic subjective tinnitus and accumulate experience for the application of SGB in the clinical treatment of tinnitus. MethodsA retrospective review was conducted on the data of chronic subjective tinnitus patients who received SGB intervention， with unsatisfactory outcomes otherwise. Pure tone audiometry （PTA）， tinnitus loudness evaluation and Pittsburgh sleep quality index （PSQI） were used. The tinnitus handicap inventory （THI） scores were compared before and after SGB intervention. Correlation analysis and linear regression equations were employed to identify the potential indicators predicting the effectiveness of SGB intervention. Statistical analysis was performed by SPSS 24.0 software. ResultsBy April 2023， a total of 107 patients with chronic subjective tinnitus had undergone SGB intervention， including 67 male and 40 female， with a mean age of （45.32±11.40） years old and an average tinnitus history of （20.32±24.64） months ［16 （12~20）］. Only 7 patients （6.54%） quitted the intervention for personal reasons， which demonstrated good compliance with the intervention. No patients experienced adverse reactions such as infection at the injection site， hematoma， nerve injury， local anesthetic intoxication and so on， which revealed good safety. After SGB intervention， THI scores decreased to below 36 points in 77 patients and decrease by 10 points or more in 12 of the remaining patients， with a total effective rate of 89%. A paired sample t-test showed a significant difference in THI scores before and after SGB intervention （t=15.575， P<0.001）， indicating good improvement. Pearson correlation analysis suggested that pre-intervention THI scores and subjective tinnitus loudness were significantly positively correlated with the improvement level of THI scores （P<0.05）. Further stepwise linear regression analysis found that "pre-intervention THI scores" had statistical significance （P<0.001）， with a regression coefficient of 0.308， predicting a 17.4% improvement level in THI scores. ConclusionsDue to its good and safe short-term effects， SGB intervention can be used as a supplementary option for chronic subjective tinnitus when other interventions are not ideal， especially for patients with higher THI scores. However， further research is needed to clarify the long-term efficacy and underlying mechanisms， in order to establish a more solid theoretical basis for SGB intervention in the treatment of subjective tinnitus.

Risk prediction models of dangerous behaviors among patients with severe mental disorder in community / 四川精神卫生

BackgroundThe occurrence rate of dangerous behaviors in patients with severe mental disorders is higher than that of the general population. In China， there is limited research on the prediction of dangerous behaviors in community-dwelling patients with severe mental disorders， particularly in terms of predicting models using data mining techniques other than traditional methods. ObjectiveTo explore the influencing factors of dangerous behaviors in community-dwelling patients with severe mental disorders and testing whether the classification decision tree model is superior to the Logistic regression model. MethodsA total of 11 484 community-dwelling patients with severe mental disorders who had complete follow-up records from 2013 to 2022 were selected on December 2023. The data were divided into a training set （n=9 186） and a testing set （n=2 298） in an 8∶2 ratio. Logistic regression and classification decision trees were separately used to establish predictive models in the training set. Model discrimination and calibration were evaluated in the testing set. ResultsDuring the follow-up period， 1 115 cases （9.71%） exhibited dangerous behaviors. Logistic regression results showed that urban residence， poverty， guardianship， intellectual disability， history of dangerous behaviors， impaired insight and positive symptoms were risk factors for dangerous behaviors （OR=1.778， 1.459， 2.719， 1.483， 3.890， 1.423， 2.528， 2.124， P<0.01）. Being aged ≥60 years， educated， not requiring prescribed medication and having normal social functioning were protective factors for dangerous behaviors （OR=0.594， 0.824， 0.422， 0.719， P<0.05 or 0.01）. The predictive effect in the testing set showed an area under curve （AUC） of 0.729 （95% CI： 0.692~0.766）， accuracy of 70.97%， sensitivity of 59.71%， and specificity of 72.05%. The classification decision tree results showed that past dangerous situations， positive symptoms， overall social functioning score， economic status， insight， household registration， disability status and age were the influencing factors for dangerous behaviors. The predictive effect in the testing set showed an AUC of 0.721 （95% CI： 0.705~0.737）， accuracy of 68.28%， sensitivity of 64.46%， and specificity of 68.60%. ConclusionThe classification decision tree does not have a greater advantage over the logistic regression model in predicting the risk of dangerous behaviors in patients with severe mental disorders in the community. ［Funded by Chengdu Medical Research Project （number， 2020052）］

Nomgram model for individual prediction of coronary heart disease with pulmonary hypertension / 公共卫生与预防医学

Objective To establish an individual Nomgram model for predicting the risk of coronary heart disease complicated with pulmonary hypertension. Methods From January 2017 to December 2021 , 352 patients with coronary heart disease (CHD) complicated with pulmonary hypertension in our hospital were selected, and 352 patients with coronary heart disease but without pulmonary hypertension were selected as the control group. The clinical baseline data of the two groups were analyzed first, and then logistics multivariate analysis was performed. To explore the risk factors of coronary heart disease complicated with pulmonary hypertension, the Nomgram model was established to predict the risk, and the predictive value of the model was tested by receiver characteristic curve (ROC). Results Logistics multivariate analysis showed that alcoholism, smoking, stroke history, hypertension course, CHD course, PASP, HCT, PaCO2, D-dimer, NIHSS score and low PaO2 were all independent risk factors for CHD complicated with pulmonary hypertension. Nomgram model prediction results for patients with coronary heart disease showed that Alcohol abuse, smoking, stroke history, duration of hypertension (5.66 years), duration of coronary heart disease (2.12 years), NIHSS (12.33 points), PASP (75.22mmHg), HCT (33.22%), PaCO2 (56.11mmHg), D-dimer (255.12μg/L), PaO2 (56.22mmHg) is a risk factor for coronary heart disease complicated with pulmonary hypertension. ROC curve showed that the area under the prediction curve of Nomgram model for coronary heart disease complicated with pulmonary hypertension was 0.675. Conclusion Nomgram model can predict pulmonary hypertension in patients with coronary heart disease to a certain extent.

Identificación con azul patente de ganglio centinela en cáncer de mama / Patent blue for identification of sentinel nodes in breast cancer

Resumen OBJETIVO: Describir las características sociodemográficas, clínicas y patológicas y los resultados obtenidos con la técnica de ganglio centinela con azul patente en la cirugía de cáncer de mama temprano. Además, reportar la experiencia en la identificación del ganglio centinela en cáncer de mama temprano con la técnica con azul patente al 2.5%. MATERIALES Y MÉTODOS: Estudio retrospectivo y analítico consistente en la evaluación de los expedientes clínicos de pacientes diagnosticadas con cáncer de mama temprano, sin sospecha clínica o radiológica de afectación axilar, atendidas entre junio de 2022 y junio de 2023 en el servicio de Ginecología Oncológica de la UMAE Hospital de Ginecoobstetricia, Centro Médico Nacional de Occidente del IMSS. El sitio de inyección del colorante fue subdérmico periareolar, los ganglios identificados se estudiaron en el transoperatorio. Se analizaron el porcentaje de identificación, las tasas de falsos negativos y el valor predictivo negativo del método. RESULTADOS: Se analizaron 95 procedimientos de biopsia de ganglio centinela. Solo se practicó la linfadenectomía axilar en las pacientes con metástasis en el ganglio centinela comprobada en el estudio transoperatorio y en las que no se identificaron ganglios teñidos por no migración del colorante. La edad promedio de las pacientes fue de 57.1 años límites 25 y 78 años. El tamaño del tumor fue menor a 3 cm. A 64 67% pacientes se les hizo la mastectomía en comparación con 31 a quienes se efectuó cirugía conservadora de mama 33%. Se estadificaron como IA 57 de las 95 pacientes; el subtipo molecular más frecuente fue compatible con luminal A en 49%. CONCLUSIONES: La biopsia del ganglio centinela, con azul patente, es una técnica rápida, sencilla, precisa y de bajo costo para identificar daño axilar en etapas tempranas del cáncer de mama. Lo aquí reportado son resultados que corresponden a una primera evaluación de la técnica en nuestro servicio.

Abstract OBJECTIVE: To describe the sociodemographic, clinical and pathological characteristics and results of the patent blue sentinel lymph node technique in early breast cancer surgery. And to report the experience in identifying the sentinel lymph node in early breast cancer using the 2.5% patent blue technique. MATERIALS AND METHODS: Retrospective and analytical study consisting of the evaluation of the clinical records of patients diagnosed with early breast cancer, without clinical or radiological suspicion of axillary involvement, seen between June 2022 and June 2023 at the Oncological Gynaecology Service of the UMAE Hospital de Ginecoobstetricia, Centro Médico Nacional de Occidente of the IMSS. The dye injection site was subdermal periareolar, and the identified lumps were examined in the transoperative period. The percentage of identification, false negative rates and negative predictive value of the method were analysed. RESULTS: Ninety-five sentinel node biopsies were analysed. Axillary lymphadenectomy was performed only in patients with sentinel lymph node metastasis confirmed at surgery and in those in whom no stained nodes were identified due to non-migration of the dye. The mean age of the patients was 57.1 years range 25 to 78 years. The tumour size was less than 3 cm. Sixty-four patients 67% underwent mastectomy, compared with 31 who underwent breast-conserving surgery 33%. Fifty-seven of the 95 patients were staged as AI; the most common molecular subtype was compatible with luminal A in 49%. CONCLUSIONS: Sentinel lymph node biopsy with patent blue is a rapid, simple, accurate and inexpensive technique for identifying axillary disease in early breast cancer. The results reported here represent an initial evaluation of the technique in our service.

Modelo predictivo del fracaso de la terapia eléctrica en la fibrilación auricular paroxística

Introducción: La fibrilación auricular es la arritmia recurrente más habitual en la práctica clínica. Su prevalencia se multiplica en la población actual y tiene diferentes causas fisiopatológicas que la convierten en una pandemia mundial. Objetivos: Diseñar un modelo predictivo de fracaso de la terapia eléctrica en pacientes con fibrilación auricular paroxística. Métodos: Se realizó un estudio de casos y controles, con 33 casos y 66 controles. Variables predictoras: edad, fracción de eyección ≤ 40 %, volumen de aurícula izquierda ≥ 34 mL/m2. A partir de la regresión logística se obtuvo un modelo en el que fueron incluidos el valor predictivo positivo, valor predictivo negativo, la sensibilidad y especificidad. Resultados: Los factores de riesgo predictores fueron: edad ≥ 55 años (p= 0,013; odds ratio (OR)= 3,58; intervalo de confianza -IC- 95 %: 1,33-9,67); la fracción de eyección del ventrículo izquierdo (FEVI) ≤ 40 % se observó en 20 pacientes (22,7 %) (p= 0,004; OR= 4,45; IC95 %: 1,54-12,8); presión de aurícula izquierda elevada, volumen de aurícula izquierda elevado (p= 0,004; OR= 3,11; IC95 %: 1,24-8,77), según el modelo de regresión logística. Se realizó la validación interna por división de datos; se confirmó que el modelo pronostica bien los que van a tener éxito en el resultado terapéutico. Conclusiones: El modelo predictivo elaborado está compuesto por los predictores edad > 55 años, FEVI; volumen de aurícula izquierda; presenta un buen ajuste y poder discriminante, sobre todo valor predictivo positivo.

Introduction: Atrial fibrillation is the most common recurrent arrhythmia in clinical practice. Its prevalence is multiplying in the current population and has different pathophysiological causes that make it a global pandemic. Objectives: To design a predictive model for failure of electrical therapy in patients with paroxysmal atrial fibrillation. Methods: A case-control study was carried out with 33 cases, and 66 controls. Predictor variables: age, ejection fraction ≤ 40%, left atrial volume ≥ 34 mL/m2. From logistic regression, a model was obtained in which the positive predictive value, negative predictive value, sensitivity and specificity were included. Results: The predictive risk factors were: age ≥ 55 years (p= 0.013; odds ratio (OR)= 3.58; 95% confidence interval -CI-: 1.33-9.67); left ventricular ejection fraction (LVEF) ≤ 40% was observed in 20 patients (22.7%) (p= 0.004; OR= 4.45; 95% CI: 1.54-12.8); elevated left atrial pressure, elevated left atrial volume (p= 0.004; OR= 3.11; 95% CI: 1.24-8.77), according to the logistic regression model. Internal validation was carried out by data division; It was confirmed that the model predicts very well those who will be successful in the therapeutic result. Conclusions: The predictive model developed is composed of the predictors age > 55 years, LVEF; left atrial volume; It presents a good fit and discriminating power, especially positive predictive value.

Are we ready to stratify BI-RADS 4 lesions observed on magnetic resonance imaging? A real-world noninferiority/equivalence analysis / Estamos prontos para estratificar lesões BI-RADS 4 na ressonância magnética? Uma análise de não inferioridade/equivalência do mundo real

Abstract Objective: To demonstrate that positive predictive values (PPVs) for suspicious (category 4) magnetic resonance imaging (MRI) findings that have been stratified are equivalent to those stipulated in the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) for mammography and ultrasound. Materials and Methods: This retrospective analysis of electronic medical records generated between January 4, 2016 and December 29, 2021 provided 365 patients in which 419 suspicious (BI-RADS category 4) findings were subcategorized as BI-RADS 4A, 4B or 4C. Malignant and nonmalignant outcomes were determined by pathologic analyses, follow-up, or both. For each subcategory, the level 2 PPV (PPV2) was calculated and tested for equivalence/noninferiority against the established benchmarks. Results: Of the 419 findings evaluated, 168 (40.1%) were categorized as malignant and 251 (59.9%) were categorized as nonmalignant. The PPV2 for subcategory 4A was 14.2% (95% CI: 9.3-20.4%), whereas it was 41.2% (95% CI: 32.8-49.9%) for subcategory 4B and 77.2% (95% CI: 68.4-84.5%) for subcategory 4C. Multivariate analysis showed a significantly different cancer yield for each subcategory (p < 0.001). Conclusion: We found that stratification of suspicious findings by MRI criteria is feasible, and malignancy probabilities for sub-categories 4B and 4C are equivalent to the values established for the other imaging methods in the BI-RADS. Nevertheless, low suspicion (4A) findings might show slightly higher malignancy rates.

Resumo Objetivo: Demonstrar que os valores preditivos positivos (VPPs) para lesões suspeitas (categoria 4) identificadas por ressonância magnética (RM) são equivalentes aos estipulados no ACR BI-RADS para mamografia e ultrassonografia. Materiais e Métodos: Análise retrospectiva de dados em prontuário eletrônico, entre 4 de janeiro de 2016 e 29 de dezembro de 2021, resultou em 365 pacientes elegíveis, com 419 lesões classificadas como BI-RADS 4A, 4B ou 4C. Desfechos malignos e não malignos foram determinados por estudo patológico e/ou acompanhamento. Realizamos o cálculo do VPP nível 2 (VPP2) para cada subcategoria e testamos para não inferioridade/equivalência em relação aos valores de referência. Resultados: Dos 419 achados, 168 (40,1%) foram malignos e 251 (59,9%), não malignos. O VPP2 para subcategoria 4A foi 14,2% (IC 95%: 9,3-20,4%), para 4B foi 41,2% (IC 95%:, 32,8-49,9%) e para 4C foi 77,2% (IC 95%: 68,4-84,5%). Análise multivariada demonstrou diferenças estatisticamente significantes entre as subcategorias (p < 0,001). Conclusão: A estratificação de achados suspeitos por RM é factível, sendo que a probabilidade de malignidade das subcategorias 4B e 4C é equivalente à estabelecida para outros métodos de imagem pelo BI-RADS. Contudo, lesões de baixa suspeição (4A) podem apresentar taxas mais altas de malignidade.

UDC- COVID 19: herramienta digital para predecir el retiro de la ventilación mecánica invasiva de pacientes con COVID-19

En diciembre de 2019 las Autoridades de la República Popular China, comunicaron a la OMS varios casos de neumonía de etiología desconocida en Wuhan, una ciudad situada en la provincia china de Hubei. Una semana más tarde confirmaron que se trataba de un nuevo coronavirus que fue denominado SARS-CoV-2, este virus causa diversas manifestaciones clínicas englobadas bajo el término COVID-19. El presente trabajo presenta un prototipo de aplicación con el nombre UDC-COVID19 que propone una herramienta digital sobre la base de una revisión actualizada de la evaluación ultrasonográfica del diafragma como elemento predictivo para retirar la ventilación mecánica invasiva en pacientes con COVID-19, proporcionando una excelente herramienta digital para la evaluación de la estructura y función dinámica diafragmática, es precisa, reproducible, sin radiación ionizante, fácil de realizar a la cabecera del paciente y costo efectiva en pacientes críticamente enfermos.

In December 2019, the Authorities of the People's Republic of China reported to the WHO several cases of pneumonia of unknown etiology in Wuhan, a city located in the Chinese province of Hubei. A week later, they confirmed that it was a new coronavirus called SARS-CoV-2, which causes various clinical manifestations encompassed under the term COVID-19. The present work presents an application prototype with the name UDC-COVID19 that proposes a digital tool based on an updated review of the ultrasonographic evaluation of the diaphragm as a predictive element to withdraw invasive mechanical ventilation in patients with COVID-19, providing an excellent digital tool for the evaluation of the diaphragmatic structure and dynamic function since it is precise, reproducible, without ionizing radiation, easy to perform at the patient's bedside and cost effective in critically ill patients; mechanical ventilation.

Alergia a la leche de vaca: ¿se pueden evitar las pruebas de provocación oral? Un análisis probabilístico basado en datos clínicos / Cow's milk allergy: Can oral food challenges be avoided? A probabilistic analysis based on clinical data

Introducción. La prueba de provocación oral (PPO) para el diagnóstico de alergia a las proteínas de la leche de la vaca (APLV) presenta riesgos y requiere de recursos. Nuestro objetivo fue evaluar condiciones y pruebas complementarias para identificar una alta probabilidad de APLV. Población y métodos. Análisis secundario sobre estudio de pacientes atendidos en una unidad de alergia entre 2015 y 2018. Se determinaron las probabilidades prepruebas asociadas a los síntomas y sus combinaciones, y las probabilidades pospruebas luego de realizadas pruebas cutáneas y determinación de inmunoglobulina E (IgE) sérica. Resultados. Se evaluó la información de 239 pacientes. Se observaron probabilidades mayores al 95 % en pacientes con angioedema y combinación de urticaria y vómitos. Usando puntos de corte propuestos por Calvani et al., la combinación de vómitos con rinitis, sin angioedema, también superó el 95 %. Conclusión. Se ofrece una metodología para identificar pacientes en los que puede diagnosticarse APLV sin realización de PPO.

Introduction. The oral food challenge (OFC) for the diagnosis of cow's milk protein allergy (CMPA) poses risks and requires resources. Our objective was to assess conditions and complementary tests used to identify a high probability of CMPA. Population and methods. Secondary analysis of a study of patients seen at a unit of allergy between 2015 and 2018. Pre-testing probabilities associated with symptoms and their combinations and post-testing probabilities after skin prick testing and serum immunoglobulin E (IgE) levels were determined. Results. The data from 239 patients were assessed. A probability greater than 95% was observed for angioedema and a combination of urticaria and vomiting. Based on the cut-off points proposed by Calvani et al., the combination of vomiting with rhinitis, without angioedema, also exceeded 95%. Conclusion. A methodology is provided to identify patients in whom CMPA may be diagnosed without an OFC.

Instrumentos para la evaluación del riesgo de lesiones por presión en adultos en estado crítico: scoping review / Risk assessment instruments for pressure ulcer in adults in critical situation: a scoping review / Instrumentos para a avaliação do risco de lesões por pressão para adultos em situação crítica: scoping review*

Objetivo: mapear los instrumentos para la evaluación del riesgo de lesiones por presión en adultos en situación crítica en una unidad de terapia intensiva; identificar los indicadores de desempeño de los instrumentos y la apreciación de los usuarios con respecto al uso/limitaciones de los instrumentos. Método: scoping review. Para redactar el estudio se utilizó la extensión Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. La investigación se realizó mediante la herramienta de búsqueda EBSCOhost en 8 bases de datos, resultando 1846 estudios, de los cuales 22 conforman la muestra. Resultados: se identificaron dos grandes grupos de instrumentos: los generalistas [Braden, Braden (ALB), Emina, Norton-MI, RAPS y Waterlow]; y los específicos (CALCULATE, Cubbin & Jackson, EVARUCI, RAPS-ICU, Song & Choi, Suriaidi y Sanada y el índice COMHON). En cuanto al valor predictivo, EVARUCI y CALCULATE mostraron los mejores resultados de indicadores de desempeño. En cuanto a las apreciaciones/limitaciones señaladas por los usuarios, destaca la escala CALCULATE, seguida de la EVARUCI y la RAPS-ICU, aunque aún necesitan ajustes futuros. Conclusión: el mapeo mostró que las evidencias son suficientes para indicar uno o más instrumentos para la evaluación del riesgo de lesiones por presión en adultos críticos en una unidad de cuidados intensivos.

Objective: to map the instruments for risk assessment of pressure ulcers in adults in critical situation in intensive care units; identify performance indicators of the instrument, and the appreciation of users regarding the instruments' use/limitations. Method: a scoping review. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews in the writing of the study. We carried out the searches in the EBSCOhost search tool for 8 databases, resulting in 1846 studies, of which 22 studies compose the sample. Results: we identified two big instrument groups: generalist [Braden, Braden (ALB), Emina, Norton-MI, RAPS, and Waterlow]; and specific (CALCULATE, Cubbin & Jackson, EVARUCI, RAPS-ICU, Song & Choi, Suriaidi and Sanada, and COMHON index). Regarding the predictive value, EVARUCI and CALCULATE presented better results for performance indicators. Concerning appreciation/limitations indicated by users, we highlight the CALCULATE scale, followed by EVARUCI and RAPS-ICU, although they still need future adjustments. Conclusion: the mapping of the literature showed that the evidence is sufficient to indicate one or more instruments for the risk assessment of pressure ulcers for adults in critical situation in intensive care units.

Objetivo: mapear os instrumentos para avaliação do risco de lesões por pressão nos adultos em situação crítica em unidade de cuidados intensivos; identificar os indicadores de desempenho dos instrumentos e a apreciação dos utilizadores quanto ao uso/às limitações dos instrumentos. Método: scoping review. O Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews foi utilizado para a redação do estudo. A pesquisa foi realizada na ferramenta de busca EBSCOhost em oito bases de dados, resultando em 1846 estudos, dos quais 22 compõem a amostra. Resultados: identificaram-se dois grandes grupos de instrumentos: os genéricos [Braden, Braden (ALB), Emina, Norton-MI, RAPS e Waterlow]; e os específicos (CALCULATE, Cubbin & Jackson, EVARUCI, RAPS-ICU, Song & Choi, Suriaidi e Sanada e o índice de COMHON). Quanto ao valor preditivo, a EVARUCI e a CALCULATE apresentaram os melhores resultados de indicadores de desempenho. Em relação à apreciação/às limitações apontadas pelos utilizadores, destacam-se a escala CALCULATE, seguindo-se da EVARUCI e da RAPS-ICU, embora ainda necessitem de ajustes futuros. Conclusão: o mapeamento mostrou que as evidências são suficientes para indicar um ou mais instrumentos para avaliação do risco de lesões por pressão nos adultos em situação crítica em unidade de cuidados intensivos.

Factores pronósticos de metástasis ósea en pacientes con cáncer de próstata / Predictive factors for bone metastasis in patients with prostate cancer i: en

El adenocarcinoma de próstata es considerado una de las neoplasias más frecuentes en hombres mayores de 60 años, y su metástasis ósea constituye una de las complicaciones de peor pronóstico. Objetivo: Estimar los factores pronósticos de metástasis ósea en pacientes con cáncer de próstata. Métodos: Se realizó un estudio analítico de 73 pacientes con cáncer de próstata, asistidos en el Hospital Oncológico Conrado Benítez de Santiago de Cuba en el período 2018-2022. Entre las variables analizadas figuraron: edad, color de la piel, manifestaciones clínicas, tiempo de aparición de la metástasis ósea, grado de diferenciación celular, nivel de antígeno prostático específico y diagnóstico imagenológico. Resultados: En la serie predominó el grupo etario de 60-69 años (50,7 %) y el promedio de edad fue de 67 años; asimismo, prevalecieron los pacientes de piel negra, el dolor óseo como síntoma más frecuente y el diagnóstico imagenológico de metástasis ósea por tomografía axial computarizada (48,0 %). Se observó un aumento proporcional de los valores del antígeno prostático específico y de la puntuación de Gleason en relación con la aparición de metástasis. Conclusiones: Los factores pronósticos que permiten estimar la presencia de metástasis ósea en pacientes con cáncer de próstata son la edad avanzada, el color negro de la piel y los valores de antígeno prostático específico por encima de 20 ng/mL.

Prostate adenocarcinoma is considered one of the most frequent neoplasms in men over 60 years, and bone metastasis constitutes one of the complications with the worst prognosis. Objective: Estimate the predictive factors for bone metastasis in patients with prostate cancer. Methods: An analytic study of 73 patients with prostate cancer was carried out. They were assisted at Conrado Benítez Cancer Hospital in Santiago de Cuba during 2018-2022. The variables analyzed included: age, skin color, clinical manifestations, onset time of bone metastasis, degree of cellular differentiation, prostate-specific antigen level and imaging diagnosis. Results: In the series there was a prevalence of the 60-69 age group (50.7%) and the average age was 67 years; also, dark skinned patients, bone pain as more frequent symptom and imaging diagnosis of bone metastasis by computerized axial tomography prevailed (48.0%). A proportional increase of prostate-specific antigen values and Gleason punctuation was observed in relation to the metastasis onset. Conclusions: The predictive factors for estimating the presence of bone metastasis in patients with prostate cancer are the advanced age, black skin color and prostate-specific antigen values above 20 ng/mL.

Prognostic predictive model for PONV in cesarean delivery

Introduction: Apfel simplified risk score for postoperative nausea and vomiting (PONV) has shown to be useful in anesthesia; however, since it has not been calibrated in regional anesthesia or in pregnant patients, its use in cesarean section is limited. Objective: To develop a prognostic predictive model for postoperative nausea and vomiting in pregnant patients undergoing cesarean section under spinal anesthesia. Methods: In a cohort of 703 term pregnant patients scheduled of cesarean section, 15 variables were prospectively assessed, to design a prognostic predictive model for the development of postoperative nausea and vomiting. A logistic regression analysis was used to construct the model and its calibration and discrimination were based on the Hosmer-Lemeshow test, the calibration curves, and C statistic. Additionally, the internal calibration was performed with the Bootstrap resampling method. Results: Postoperative nausea and vomiting were experienced by 27% of the patients during the first six hours after surgery. The model included as prognostic variables the development of intraoperative nausea and vomiting, age under 28 years, a history of PONV, the mother's BMI and the weight of the newborn baby. The model showed an adequate calibration (x2: 4.65 p: 0.5888), though a low discrimination (Statistic C = 0.68). Conclusions: A prognostic predictive model was created for the development of PONV in cesarean section. This model was used to build a prognostic scale for the classification of patients into risk groups.

Introducción: La escala de riesgo simplificada de Apfel para náuseas y vómito posoperatorio (NVPO) ha mostrado utilidad en anestesia; sin embargo, al no haber sido calibrada en anestesia regional o en pacientes embarazadas, su utilidad en cesárea es limitado. Objetivo: Desarrollar un modelo de predicción pronóstica para náuseas y vómito posoperatorios en pacientes embarazadas, llevadas a cesárea bajo anestesia espinal. Métodos: En una cohorte de 703 pacientes con embarazo a término programadas para cesárea, se evaluaron 15 variables de forma prospectiva para construir un modelo de predicción pronóstica para el desarrollo de náuseas y vómito posoperatorio. Se utilizó el análisis de regresión logística para la construcción del modelo y se calculó su calibración y discriminación con la prueba de Hosmer-Lemeshow, las curvas de calibración y el estadístico C. Además, se realizó la calibración interna con el método de remuestreo Bootstrap. Resultados: Las náuseas y vómito posoperatorio se presentaron en el 27% de las pacientes durante las primeras seis horas después de la cirugía. El modelo incluyó como variables pro-nósticas el desarrollo de náuseas y vómito en el intraoperatorio, edad menor de 28 años, antecedentes de NVPO, índice de masa corporal (IMC) de la madre y el peso del recién nacido. El modelo mostró una adecuada calibración (x2: 4,65 p: 0,5888), aunque una baja discriminación (Estadístico C = 0,68). Conclusiones: Se construyó un modelo de predicción pronóstica para el desarrollo de NVPO en cirugía cesárea, y con este se construyó una escala pronóstica que permite clasificar a las pacientes por grupos de riesgo.

Modelo predictivo de enfermedad cardiovascular basado en inteligencia artificial en la atención primaria de salud / A Predictive Model for Cardiovascular Disease based on Artificial Intelligence in Primary Health Care

Introducción: En Cuba y en el resto del mundo, las enfermedades cardiovasculares son reconocidas como un problema de salud pública mayúsculo y creciente, que provoca una alta mortalidad. Objetivo: Diseñar un modelo predictivo para estimar el riesgo de enfermedad cardiovascular basado en técnicas de inteligencia artificial. Métodos: La fuente de datos fue una cohorte prospectiva que incluyó 1633 pacientes, seguidos durante 10 años, fue utilizada la herramienta de minería de datos Weka, se emplearon técnicas de selección de atributos para obtener un subconjunto más reducido de variables significativas, para generar los modelos fueron aplicados: el algoritmo de reglas JRip y el meta algoritmo Attribute Selected Classifier, usando como clasificadores el J48 y el Multilayer Perceptron. Se compararon los modelos obtenidos y se aplicaron las métricas más usadas para clases desbalanceadas. Resultados: El atributo más significativo fue el antecedente de hipertensión arterial, seguido por el colesterol de lipoproteínas de alta densidad y de baja densidad, la proteína c reactiva de alta sensibilidad y la tensión arterial sistólica, de estos atributos se derivaron todas las reglas de predicción, los algoritmos fueron efectivos para generar el modelo, el mejor desempeño fue con el Multilayer Perceptron, con una tasa de verdaderos positivos del 95,2 por ciento un área bajo la curva ROC de 0,987 en la validación cruzada. Conclusiones: Fue diseñado un modelo predictivo mediante técnicas de inteligencia artificial, lo que constituye un valioso recurso orientado a la prevención de las enfermedades cardiovasculares en la atención primaria de salud(AU)

Introduction: In Cuba and in the rest of the world, cardiovascular diseases are recognized as a major and growing public health problem, which causes high mortality. Objective: To design a predictive model to estimate the risk of cardiovascular disease based on artificial intelligence techniques. Methods: The data source was a prospective cohort including 1633 patients, followed for 10 years. The data mining tool Weka was used and attribute selection techniques were employed to obtain a smaller subset of significant variables. To generate the models, the rule algorithm JRip and the meta-algorithm Attribute Selected Classifier were applied, using J48 and Multilayer Perceptron as classifiers. The obtained models were compared and the most used metrics for unbalanced classes were applied. Results: The most significant attribute was history of arterial hypertension, followed by high and low density lipoprotein cholesterol, high sensitivity c-reactive protein and systolic blood pressure; all the prediction rules were derived from these attributes. The algorithms were effective to generate the model. The best performance was obtained using the Multilayer Perceptron, with a true positive rate of 95.2percent and an area under the ROC curve of 0.987 in the cross validation. Conclusions: A predictive model was designed using artificial intelligence techniques; it is a valuable resource oriented to the prevention of cardiovascular diseases in primary health care(AU)

Aprendizaje automático aplicado a la predicción de diabetes mellitus, utilizando información socioeconómica y ambiental de usuarios del sistema de salud

Objetivo: Se propuso aplicar modelos basados en técnicas de aprendizaje automático como apoyo para el diagnóstico temprano de la diabetes mellitus, utilizando variables de datos ambientales, sociales, económicos y sanitarios, sin la dependencia de la toma de muestras clínicas. Metodología: Se utilizaron datos de 10 889 usuarios afiliados al régimen subsidiado de salud de la zona suroccidental en Colombia, diagnosticados con hipertensión y agrupados en usuarios sin (74,3 %) y con (25,7 %) diabetes mellitus. Se entrenaron modelos supervisados utilizando k vecinos más cercanos, árboles de decisión y bosques aleatorios, así como modelos basados en ensambles, aplicados a la base de datos antes y después de balancear el número de casos en cada grupo de diagnóstico. Se evalúo el rendimiento de los algoritmos mediante la división de la base de datos en datos de entreno y de prueba (70/30, respectivamente), y se utilizaron métricas de exactitud, sensibilidad, especificidad y área bajo la curva. Resultados: Los valores de sensibilidad aumentaron considerablemente al utilizar datos balanceados, pasando de valores máximos del 17,1 % (datos sin balancear) a valores de hasta 57,4 % (datos balanceados). El valor más alto de área bajo la curva (0,61) fue obtenido con los modelos de ensambles, al aplicar un balance en el número de datos por cada grupo y al codificar las variables categóricas. Las variables de mayor peso estuvieron asociadas con aspectos hereditarios (24,65 %) y con el grupo étnico (5.59 %), además de la dificultad visual, el bajo consumo de agua, una dieta baja en frutas y verduras, y el consumo de sal y azúcar. Conclusiones: Aunque los modelos predictivos, utilizando información socioeconómica y ambiental de las personas, surgen como una herramienta para el diagnóstico temprano de la diabetes mellitus, estos aún deben ser mejorados en su capacidad predictiva.

Objective: The objective was to apply models based on machine learning techniques to support the early diagnosis of diabetes mellitus, using environmental, social, economic and health data variables, without dependence on clinical sample collection. Methodology: Data from 10,889 users affiliated with the subsidized health system in the southwestern area of Colombia, diagnosed with hypertension and grouped into users without (74.3%) and with (25.7%) diabetes mellitus, were used. Supervised models were trained using k-nearest neighbors, decision trees, and random forests, as well as ensemble-based models, applied to the database before and after balancing the number of cases in each diagnostic group. The performance of the algorithms was evaluated by dividing the database into training and test data (70/30, respectively), and metrics of accuracy, sensitivity, specificity, and area under the curve were used. Results: Sensitivity values increased significantly when using balanced data, going from maximum values of 17.1% (unbalanced data) to values as high as 57.4% (balanced data). The highest value of area under the curve (0.61) was obtained with the ensemble models, by applying a balance in the amount of data for each group and by coding the categorical variables. The variables with the greatest weight were associated with hereditary aspects (24.65%) and with the ethnic group (5.59%), in addition to visual difficulty, low water consumption, a diet low in fruits and vegetables, and the consumption of salt and sugar. Conclusions: Although predictive models, using people's socioeconomic and environmental information, emerge as a tool for the early diagnosis of diabetes mellitus, their predictive capacity still needs to be improved.

Objetivo: Propôs-se aplicar modelos baseados em técnicas de aprendizagem automática como apoio para o diagnóstico precoce da diabetes mellitus, utilizando variáveis de dados ambientais, sociais, econômicos e sanitários, sem a dependência da coleta de amostras clínicas. Metodologia: Usaram-se dados de 10.889 usuários filiados ao regime subsidiado de saúde da zona sudoeste da Colômbia, diagnosticados com hipertensão e agrupados em usuários sem (74,3%) e com (25,7%) diabetes mellitus. Foram treinados modelos supervisionados utilizando k vizinhos mais próximos, árvores de decisão e florestas aleatórias, assim como modelos baseados em montagens, aplicados à base de dados antes de depois de equilibrar o número de casos em cada grupo de diagnóstico. Avaliou-se o desempenho dos algoritmos por meio da divisão da base de dados de treino e teste (70/30, respectivamente), e utilizaram-se métricas de exatidão, sensibilidade, especificidade e área sob a curva. Resultados: Os valores de sensibilidade aumentaram de maneira significativa ao utilizar dados equilibrados, passando de valores máximos de 17,1% (dados sem equilibrar) a valores de até 57,4% (dados equilibrados). O valor mais elevado de área sob a curva (0,61) foi obtido com os modelos de montagens, ao aplicar um balanço no número de dados por cada grupo e codificar as variáveis categóricas. As variáveis de maior peso estiveram associadas com fatores hereditários (24,65%) e com o grupo étnico (5,59%), além da dificuldade visual, o baixo consumo de água, um regime baixo em frutas e vegetais e o consumo de sal e açúcar. Conclusões: Embora os modelos preditivos, utilizando informação socioeconômica e ambiental das pessoas, surgem como uma ferramenta para o diagnóstico precoce da diabetes mellitus, ainda devem ser melhorados em sua capacidade preditiva.

Generación de un test predictivo para el diagnóstico de laetiología de la hemorragia digestiva alta variceal

Nuestro objetivo fue desarrollar un test diagnóstico para predecir la etiología de la Hemorragia Digestiva Alta Variceal (HDAV). Realizamos un estudio de cohorte retrospectivo. Se revisaron historias clínicas de pacientes mayores de 18 años con Hemorragia Digestiva Alta (HDA) que acudieron al servicio de emergencia del Hospital Cayetano Heredia (HCH) de Lima-Perú entre el 2019 a 2022, se recolectaron datos demográficos, de laboratorio y clínicos; posteriormente, se identificaron variables predictivas de HDAV mediante una regresión logística múltiple. A cada variable con capacidad predictiva se les asignó un puntaje con un punto de corte y sirvió para construir una escala predictiva de HDAV. Se incluyeron 197 historias clínicas de pacientes con HDA, de los cuales 127 (64%) tuvieron sangrado de causa no variceal, y, 70 (36%), variceal. Se identificaron 4 factores predictivos independientes: hematemesis (vómito rojo) (OR: 4,192, IC 95%: 1,586-11,082), recuento de plaquetas (OR: 3,786, IC 95%: 1,324-10,826), antecedente de HDA (OR: 2,634, IC 95%: 1,017-6,820), signos de enfermedad hepática crónica (OR: 11,244, IC 95%: 3,067-35,047), con los que se construyó una escala predictiva, con un punto de corte >7 y ≤7; que mostró una sensibilidad, especificidad, valor predictivo positivo, valor predictivo negativo, cociente de probabilidad positivo, y, negativo de 58,6%, 90,6%, 77,4%, 79,9%, 6,20, y 0,46 respectivamente. En conclusión, la escala predictiva con un punto de corte >7 es útil para predecir la presencia de la HDAV en pacientes que acuden a la emergencia por HDA.

Our objective was to develop a diagnostic test to predict the etiology of Variceal Upper Gastrointestinal Bleeding (VUGIB). We conducted a retrospective cohort study. Medical records of patients over 18 years of age with Upper Gastrointestinal Bleeding (UGIB) who attended the emergency service of Hospital Cayetano Heredia (HCH) in Lima-Peru between 2019 and 2022 were reviewed; demographic, laboratory and clinical data were collected. Subsequently, predictive variables of variceal upper gastrointestinal bleeding (VUGIB) were identified using multiple logistic regression. Each variable with predictive capacity was assigned a score with a cut-off point and served to build a predictive scale for VUGIB. 197 medical records of patients with UGIB were included, of which 127 (64%) had non-variceal bleeding, and 70 (36%), variceal. Four independent predictors were identified: hematemesis (red vomit) (OR: 4,192, 95% CI: 1.586-11.082), platelet count (OR: 3.786, 95% CI: 1.324-10.826), history of UGIB (OR: 2.634, 95% CI: 1.017-6.820), signs of chronic liver disease (OR: 11.244, 95% CI: 3.067-35.047), with which a predictive scale was constructed, with a cut-off point >7 and ≤7; which showed a sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative of 58.6%, 90.6%, 77.4%, 79.9%, 6.20, and 0.46 respectively. In conclusion, the predictive scale with a cut-off point >7 is useful for predicting the presence of VUGIB in patients who attend the emergency room for UGIB.

Factores predictivos de rotura de aneurismas intracraneales / Rupture Predictive Factors for Intracranial Aneurysms

Introducción: Un aneurisma intracraneal roto provoca una hemorragia subaracnoidea. La enfermedad presenta una alta mortalidad y morbilidad. Sin embargo, no todos se rompen. Mejorar la predicción de rotura permitirá un tratamiento quirúrgico preventivo en un grupo de pacientes y evitará una intervención quirúrgica con riesgos en otro grupo de enfermos. Es necesario identificar factores predictivos para mejorar la estratificación del riesgo de rotura y optimizar el tratamiento de los aneurismas intracraneales incidentales. Objetivo: Identificar factores predictivos de rotura de aneurismas intracraneales. Métodos: En una muestra de 152 pacientes espirituanos con aneurismas intracraneales saculares rotos (n = 138) y no rotos (n = 22) y 160 imágenes de angiografía por tomografía computarizada, se realizaron mensuraciones de los índices o factores morfológicos, los cuales se combinaron mediante análisis de regresión logística con variables demográficas y clínicas. Resultados: El grupo de edad con mayor frecuencia de presentación de aneurismas fue el de mayor de 65 años. La muestra estuvo representada, en su gran mayoría, por el sexo femenino. Se identificaron tres factores clínicos y cuatro factores morfológicos estadísticamente significativos, asociados con la rotura. El índice de no esfericidad (p = 0,002 y el sexo femenino (p = 0,02) fueron los de mayor significación estadística. Conclusiones: Se detectaron siete factores predictivos de rotura de aneurismas intracraneales estadísticamente significativos, de los cuales el índice de no esfericidad resultó el de mayor significación(AU)

Introduction: A ruptured intracranial aneurysm causes a subarachnoid hemorrhage. The disease has high mortality and morbidity. However, not all of them break. Improving the rupture prediction will allow preventive surgical treatment in a group of patients and it will avoid risky surgical intervention in another group of patients. It is necessary to identify predictive factors to improve rupture risk stratification and to optimize treatment of incidental intracranial aneurysms. Objective: To identify rupture predictive factors for intracranial aneurysms. Methods: Measurements of the morphological indices or factors were performed in a sample of 152 patients from Sancti Spiritus with ruptured (n = 138) and unruptured (n = 22) saccular intracranial aneurysms and 160 computed tomography angiography images. They were combined using logistic regression analysis with demographic and clinical variables. Results: The age group with the highest frequency of aneurysm presentation was older than 65. The sample was represented, in its vast majority, by the female sex. Three clinical factors and four statistically significant morphological factors associated with rupture were identified. The non-sphericity index (p = 0.002) and the female sex (p = 0.02) were the most statistically significant. Conclusions: Seven statistically significant predictors of intracranial aneurysm rupture were detected, the non-sphericity index being the most significant(AU)

Detección de novedad y codificación predictiva en el sistema auditivo: Impacto clínico en disfunciones auditivas y vestibulares. Revisión de la literatura / Deviance detection and predictive coding in the auditory system: Clinical impact in auditory and vestibular dysfunctions

Una propiedad fundamental de los sistemas sensoriales es su capacidad para detectar estímulos novedosos en el entorno. El sistema nervioso posee neuronas que disminuyen su respuesta a los estímulos sonoros que se repiten a lo largo del tiempo y otras neuronas que aumentan su frecuencia de disparo ante estímulos novedosos, siendo la diferencia entre ambas respuestas conocida como adaptación-específica a estímulos. En las últimas décadas, se ha propuesto que el cerebro establece, continuamente, predicciones de los estímulos novedosos y del entorno basándose en sus experiencias previas y en modelos de representación internos, teoría denominada codificación predictiva. En esta revisión, abordaremos algunos conceptos de la adaptación-específica a estímulos y codificación predictiva, centrándonos principalmente en el sistema auditivo. Por último, propondremos una explicación teórica basada en el marco de la codificación predictiva para algunas disfunciones neuropsiquiátricas, auditivas y vestibulares.

A fundamental property of sensory systems is their ability to detect novel stimuli in the environment. The nervous system possesses neurons that decrease their response to sound stimuli that are repeated over time and other neurons that increase their firing rate to novel stimuli, the difference between the two responses being known as stimulus-specific adaptation. In recent decades, it has been proposed that the brain continuously makes predictions of novel stimuli and the environment based on its previous experiences and internal representational models, a theory called predictive coding. In this review, we will address some concepts of stimulus-specific adaptation and predictive coding, focusing mainly on the auditory system. Finally, we will propose a theoretical explanation based on the predictive coding framework for some neuropsychiatric, auditory, and vestibular dysfunctions.