Escala predictiva de mortalidad por afección cardiovascular en adultos mayores del municipio de Santiago de Cuba / Predictive scale of mortality due to cardiovascular affection in elderly from Santiago de Cuba municipality i: en

Introducción: En el contexto del envejecimiento saludable, la prevención de las enfermedades cardiovasculares es un desafío. Objetivo: Diseñar una escala, basada en factores de riesgo identificados, para la predicción de la mortalidad por afección cardiovascular en ancianos. Métodos: Se realizó un estudio analítico, observacional y retrospectivo, de tipo caso-control, que incluyó a 536 ancianos mayores de 60 años de edad pertenecientes a 3 áreas de salud (policlínicos Ramón López Peña, Municipal y 28 de Septiembre) del municipio de Santiago de Cuba, durante el 2021. La escala se derivó del análisis de regresión logística binaria de los factores de riesgo cardiovascular identificados. Resultados: En la medida que aumentó el puntaje de la escala, se incrementó el porcentaje de pacientes fallecidos. El área bajo la curva fue de 0,836 (p= 0,000) y en la prueba de bondad de ajuste de Hosmer-Lemeshow se obtuvo p= 1,000. Conclusiones: La escala propuesta permitió predecir la mortalidad por afección cardiovascular en adultos mayores, con muy buena capacidad de discriminación y calibración.

Introduction: In the context of healthy aging, the prevention of cardiovascular diseases is a challenge. Objective: To design a scale, based on identified risk factors, for predicting mortality due to cardiovascular affection in elderly. Methods: An analytic, observational and retrospective case-control study was carried out that included 536 elderly over 60 years, belonging to 3 health areas (Ramón López Peña, Municipal and 28 de Septiembre polyclinics) from Santiago de Cuba municipality, during 2021. The scale was derived from the analysis of binary logistical regression of the identified cardiovascular risk factors. Results: As the score of the scale increased, the percentage of dead patients increased. The area under the curve was of 0.836 (p = 0.000) and in the Hosmer-Lemeshow test was obtained p = 1.000. Conclusions: The proposed scale allowed predicting mortality due to cardiovascular affection in elderly, with very good discrimination capacity and calibration.

Predictive value of Post-stroke Depression Prediction Scale combined with the Early Symptom Measurement of Post-Stroke Depression-Short Form for post-stroke depression / 中国实用护理杂志

Objective:To analyze the efficacy of the Post-stroke Depression Prediction Scale (DePreS) combined with the Early Symptom Measurement of Post-Stroke Depression-Short Form (ESMPSD-SF) in predicting post stroke depression (PSD).Methods:This study was a cross-sectional survey, using convenience sampling method to select 185 stroke patients admitted to Henan Provincial People′s Hospital from June 2019 to May 2021 as the research subjects. The DePreS, ESMPSD-SF, and general information questionnaire were used to investigate them.Results:The incidence of PSD was 36.76% (68/185). The DePreS and ESMPSD-SF scores in the PSD patients were (6.29 ± 8.77), (33.83 ± 6.78) points, respectively, significantly higher than those in the non-PSD patients (-2.05 ± 5.70), (26.51 ± 5.56) points, with statistically significant differences ( t=7.06, 7.97, both P<0.05). Logistic regression analysis showed that DePreS and ESMPSD-SF scores, marital status, and the number of comorbidities were predictive factors for PSD occurrence ( P<0.05). The AUC of DePreS for diagnosing PSD was 0.777, with an optimal diagnostic point of 2 points, a sensitivity of 59.42%, and a specificity of 80.71%; the AUC of the ESMPSD-SF for diagnosing PSD was 0.792, with an optimal diagnostic point of 28 points, a sensitivity of 78.26%, and a specificity of 74.14%. The sensitivity, specificity, and AUC of DePreS combined with ESMPSD-SF in the diagnosis of PSD were 82.61%, 83.62%, and 0.886, respectively. The differences were statistically significant compared to the AUC evaluated separately by DePreS or ESMPSD-SF ( Z=3.21, 3.49, both P<0.05). Conclusions:The combination of DePreS and ESMPSD-SF had a higher detection efficiency for PSD, and the combination of the two is more suitable for assessing PSD risk in stroke patients.

Prediction scale of cerebrovascular disease subtypes for high-risk population / 中南大学学报(医学版)

Objective: Cerebrovascular disease can be roughly divided into 2 subtypes: Cerebral ischemia (CI) and cerebral hemorrhage (CH). No scale currently exist that can predict the subtypes of cerebrovascular diseases. This study aims to establish a prediction scale for the subtypes of cerebrovascular diseases. Methods:A total of 1200 cerebrovascular disease patients were included in this study, data from 1081 (90％) patients were used to establish the CI-CH risk scale, and data from 119 (10％) patients were used to test it. Risk factors for the CI-CH risk scale were identified by 2 screens, with two-tailed student ' s t-test and two-tailed Fisher ' s exact test preliminarily and with logistic regression analysis further. The scores of each risk factor for CI-CH risk scale were determined according to the odds rate, and the cut-off point was determined by Youden index. Results: Nine risk factors were ultimately selected for score system, including age (≥75 years old was ?1, <75 years old was 0), BMI (<24 kg/m2 was 0, 24?28 kg/m2 was ?1,>28 kg/m2 was?2), hypertension grade (grade 1 was 1, grade 2 was 2, and grade 3 was 3), diabetes status (no was 0, yes was?1), antihypertensive drug use (no was 0, yes was?2), alcohol consumption (<60 g/d was 1, ≥60 g/d was 2), uric acid (less than normal was 0, normal was?1, high than normal was?2), LDL cholesterol (<2 mmol/L was 0, 2?4 mmol/L was?1, and>4 mmol/L was?2), and HDL cholesterol (<1.55 mmol/L was 0,≥1.55 mmol/L was 2). Patients with a score more than 0 were classified as the CH group, Conversely, they were assigned to the CI group;its sensitivity, specificity, and accuracy were 74.5％, 77.9％, and 76.4％, respectively. Conclusion: The CI-CH risk scale can help the clinician predict the subtypes of cerebrovascular diseases.