Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 20 de 70.916
Filtrar
1.
J Infect Chemother ; 29(1): 7-14, 2023 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-36089256

RESUMEN

BACKGROUND: Cefmetazole is used as the first-line treatment for intra-abdominal infections. However, only a few studies have investigated the risk factors for cefmetazole treatment failure. AIMS: This study aimed to develop a decision tree-based predictive model to assess the effectiveness of cefmetazole in initial intra-abdominal infection treatment to improve the clinical treatment strategies. METHODS: This retrospective cohort study included adult patients who were unexpectedly hospitalized due to intra-abdominal infections between 2003 and 2020 and initially treated with cefmetazole. The primary outcome was clinical intra-abdominal infection improvement. The chi-square automatic interaction detector decision tree analysis was used to create a predictive model for clinical improvement after cefmetazole treatment. RESULTS: Among 2,194 patients, 1,807 (82.4%) showed clinical improvement post-treatment; their mean age was 48.7 (standard deviation: 18.8) years, and 1,213 (55.3%) patients were men. The intra-abdomせinal infections were appendicitis (n = 1,186, 54.1%), diverticulitis (n = 334, 15.2%), and pancreatitis (n = 285, 13.0%). The chi-square automatic interaction detector decision tree analysis identified the intra-abdominal infection type, C-reactive protein level, heart rate, and body temperature as predictive factors by categorizing patients into seven groups. The area under the receiver operating characteristic curve was 0.71 (95% confidence interval: 0.68-0.73). CONCLUSION: This predictive model is easily understandable visually and may be applied in clinical practice.


Asunto(s)
Cefmetazol , Infecciones Intraabdominales , Adulto , Masculino , Humanos , Persona de Mediana Edad , Femenino , Cefmetazol/uso terapéutico , Estudios Retrospectivos , Árboles de Decisión , Infecciones Intraabdominales/tratamiento farmacológico , Curva ROC
2.
J Environ Manage ; 325(Pt A): 116450, 2023 Jan 01.
Artículo en Inglés | MEDLINE | ID: mdl-36228397

RESUMEN

Modelling flood susceptibility is an indirect way to reduce the loss from flood disaster. Now, flood susceptibility modelling based on data driven model is state-of-the-art method such as ensemble learning and deep learning. However, the effect of deep learning coupling with ensemble learning models in flood susceptibility modelling is still unknown. Therefore, the aim of this paper is to propose three deep learning coupling with ensemble learning models by combining the deep learning (DL) with Filtered Classifier (FC), Rotation forest (RF) and Random Subspace (RSS) and explore the effect of coupling method for modelling flood susceptibility. The key step of this paper is as following: firstly, a Dingnan County which is lied in the Jiangxi Province of China is chosen as a case study, single flood event point and random sampling method was applied to generate the flood and non-flood data, respectively, then frequency ratio was utilized to analyze the relationship between each influencing factor and flood occurrence, based on the value of VIF, Spearman's correlation and One R classifier, the result show that there is no multicollinearity between each influencing factor, ten influencing factors have contribution to the flood occurrence and all of them are applied to construct the coupling model. Finally, the DL, FC-DL, RF-DL and RSS-DL were applied to produce flood susceptibility maps. Then, several statistical indexes such as area under the curve (AUC), Kappa index, accuracy (ACC), and F-measure were used to assess the accomplishment of these coupling models. For the train data, the FC-DL model acquired the highest AUC value (0.996), followed by RF-DL (0.944), RSS-DL (0.934), and DL (0.934). For the validation data, the result showed that all models have a good accomplishment (AUC>0.8). In a word, the deep learning coupling with ensemble learning models demonstrates the more reliable and excellent performance. Hence, the proposed new method will help the government for land use planning and can be applied in other area around the world.


Asunto(s)
Aprendizaje Profundo , Desastres , Curva ROC , Inundaciones , Bosques
3.
Biosensors (Basel) ; 12(11)2022 Oct 28.
Artículo en Inglés | MEDLINE | ID: mdl-36354448

RESUMEN

More than half of all pleural effusions are due to malignancy of which lung cancer is the main cause. Pleural effusions can complicate the course of pneumonia, pulmonary tuberculosis, or underlying systemic disease. We explore the application of label-free surface-enhanced Raman spectroscopy (SERS) as a point of care (POC) diagnostic tool to identify if pleural effusions are due to lung cancer or to other causes (controls). Lung cancer samples showed specific SERS spectral signatures such as the position and intensity of the Raman band in different wave number region using a novel silver coated silicon nanopillar (SCSNP) as a SERS substrate. We report a classification accuracy of 85% along with a sensitivity and specificity of 87% and 83%, respectively, for the detection of lung cancer over control pleural fluid samples with a receiver operating characteristics (ROC) area under curve value of 0.93 using a PLS-DA binary classifier to distinguish between lung cancer over control subjects. We have also evaluated discriminative wavenumber bands responsible for the distinction between the two classes with the help of a variable importance in projection (VIP) score. We found that our label-free SERS platform was able to distinguish lung cancer from pleural effusions due to other causes (controls) with higher diagnostic accuracy.


Asunto(s)
Neoplasias Pulmonares , Derrame Pleural Maligno , Derrame Pleural , Humanos , Derrame Pleural Maligno/diagnóstico , Derrame Pleural Maligno/etiología , Derrame Pleural Maligno/patología , Neoplasias Pulmonares/complicaciones , Neoplasias Pulmonares/diagnóstico , Derrame Pleural/complicaciones , Derrame Pleural/diagnóstico , Curva ROC , Aprendizaje Automático
4.
Front Public Health ; 10: 972797, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36339155

RESUMEN

Background: In recent years, the number of elderly patients undergoing cardiac surgery has rapidly increased and is associated with poor outcomes. However, there is still a lack of adequate models for predicting the risk of death after cardiac surgery in elderly patients. This study sought to identify independent risk factors for 1-year all-cause mortality in elderly patients after cardiac surgery and to develop a predictive model. Methods: A total of 3,752 elderly patients with cardiac surgery were enrolled from the Medical Information Mart for Intensive Care III (MIMIC-III) dataset and randomly divided into training and validation sets. The primary outcome was the all-cause mortality at 1 year. The Least absolute shrinkage and selection operator (LASSO) regression was used to decrease data dimensionality and select features. Multivariate logistic regression was used to establish the prediction model. The concordance index (C-index), receiver operating characteristic curve (ROC), and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram. Results: Our results demonstrated that age, sex, Sequential Organ Failure Assessment (SOFA), respiratory rate (RR), creatinine, glucose, and RBC transfusion (red blood cell) were independent factors for elderly patient mortality after cardiac surgery. The C-index of the training and validation sets was 0.744 (95%CI: 0.707-0.781) and 0.751 (95%CI: 0.709-0.794), respectively. The area under the curve (AUC) and decision curve analysis (DCA) results substantiated that the nomogram yielded an excellent performance predicting the 1-year all-cause mortality after cardiac surgery. Conclusions: We developed a novel nomogram model for predicting the 1-year all-cause mortality for elderly patients after cardiac surgery, which could be an effective and useful clinical tool for clinicians for tailored therapy and prognosis prediction.


Asunto(s)
Procedimientos Quirúrgicos Cardíacos , Nomogramas , Humanos , Anciano , Pronóstico , Curva ROC , Factores de Riesgo
5.
Hematology ; 27(1): 1230-1236, 2022 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-36373698

RESUMEN

OBJECTIVES: Sysmex® XN series hematopoietic progenitor cell (XN-HPC) is a sensitive, fast, and economic analytical method for predicting the yields of peripheral blood stem cell enumeration and products, and does not require a sophisticated or expensive workflow. However, various studies have shown that the characteristics of its diagnostic performance were non-uniform. METHODS: We performed a systematic inquiry using PubMed, Embase, and Cochrane Library, to comprehensively search for studies published before November 21, 2021. The pooled specificity (SPE), sensitivity (SEN), negative likelihood ratio (NLR), positive likelihood ratio (PLR), diagnostic odds ratio (DOR) and receiver operating characteristic (ROC) curves were summarized to appraise the diagnostic merit of XN-HPC. A forest plot was used to research the sensitivities and specificities of XN-HPC performance. Subgroup analysis was performed to investigate heterogeneity where of importance. RESULTS: Our research included four studies that assessed the diagnostic performance of XN-HPC in hematopoietic progenitor cell collection. The pooled accuracy was 95.4% (95% CI, 94.3-96.3), SPE was 0.81 (95% CI, 0.71-0.88), SEN was 0.95 (95% CI, 0.75-0.99), NLR was 0.06 (95% CI, 0.01-0.37), PLR was 5.0 (95% CI, 3.0-8.5), DOR was 78 (95% CI, 9-707) and the summary of the area under the ROC was 0.90 (95% CI, 0.87-0.92). Forest plot of sensitivities and specificities from XN-HPC test accuracy studies indicated the existence of high heterogeneity. We deduced that the patients were the source of heterogeneity via subgroup analysis. CONCLUSIONS: XN-HPC is an excellent diagnostic marker for quantitative detection of peripheral blood hematopoietic progenitor cells.


Asunto(s)
Células Madre Hematopoyéticas , Inmunoterapia , Humanos , Biomarcadores , Curva ROC , Sensibilidad y Especificidad
6.
Korean J Intern Med ; 37(6): 1176-1185, 2022 11.
Artículo en Inglés | MEDLINE | ID: mdl-36375488

RESUMEN

BACKGROUND/AIMS: Acute upper gastrointestinal (UGI) bleeding is a significant emergency situation with a mortality rate of 2% to 10%. Therefore, initial risk stratification is important for proper management. We aimed to evaluate the role of contrast-enhanced multidetector computed tomography (MDCT) for risk stratification in patients with acute UGI bleeding in the emergency room (ER). METHODS: This retrospective study included patients with UGI bleeding in the ER. Glasgow-Blatchford risk score-computed tomography (GBS-CT) was assessed using a combination of GBS and the MDCT scan scoring system. RESULTS: Of the 297 patients with UGI bleeding, 124 (41.8%) underwent abdominal MDCT. Among them, 90.3% were classified as high-risk by GBS, and five patients died (4.0%). Rebleeding occurred in nine patients (7.3%). The high-risk GBS-CT group had significantly higher in-hospital mortality (10.5% in high-risk vs. 1.4% in moderate risk vs. 0% in low-risk, p = 0.049), transfusion amount (p < 0.001), and endoscopic hemostasis (p < 0.001) compared to the moderate- and low-risk groups. CONCLUSION: Adding MDCT scans to the existing validated prognosis model when predicting the risk of UGI bleeding in patients in the ER plays a significant role in determining in-hospital mortality, transfusions, and the need for endoscopic hemostasis.


Asunto(s)
Servicio de Urgencia en Hospital , Hemorragia Gastrointestinal , Humanos , Estudios Retrospectivos , Medición de Riesgo/métodos , Índice de Severidad de la Enfermedad , Hemorragia Gastrointestinal/diagnóstico por imagen , Hemorragia Gastrointestinal/etiología , Hemorragia Gastrointestinal/terapia , Enfermedad Aguda , Factores de Riesgo , Pronóstico , Tomografía Computarizada por Rayos X , Tomografía , Curva ROC
7.
Braz J Med Biol Res ; 55: e12109, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36350970

RESUMEN

PREDICT is a tool designed to estimate the benefits of adjuvant therapy and the overall survival of women with early breast cancer. The model uses clinical, histological, and immunohistochemical variables. This study aimed to evaluate the model's performance in a Brazilian population. We assessed the discrimination and calibration of the PREDICT model to estimate overall survival (OS) in five and ten years of follow-up in a cohort of 873 women with early breast cancer diagnosed from January 2001 to December 2016. A total of 743 patients had estrogen receptor (ER)-positive and 130 had ER-negative tumors. The area under the receiver operating characteristic (ROC) curve (AUC) for discrimination was 0.72 (95%CI: 0.66-0.78) at five years and 0.67 (95%CI: 0.61-0.72) at ten years for women with ER-positive tumors. The AUC was 0.72 (95%CI: 0.62-0.81) at five years and 0.67 (95%CI: 0.54-0.77) at ten years for women with ER-negative tumors. The predicted survival in ER-positive tumors was 91.0% (95%CI: 90.2-91.6%) at five years and 79.3% (95%CI: 77.7-81.0%) at ten years, and the observed survival 90.7% (95%CI: 88.6-92.9%) and 77.2% (95%CI: 73.4-81.4%), respectively. The predicted survival in ER-negative tumors was 84.5% (95%CI: 82.5-86.6%) at five years and 75.0% (95%CI: 71.6-78.5%) at ten years, and the observed survival 76.3% (95%CI: 69.1-84.3%) and 67.9% (95%CI: 58.6-78.6%), respectively. In conclusion, PREDICT was accurate to estimate OS in women with ER-positive tumors and overestimated the OS in women with ER-negative tumors.


Asunto(s)
Neoplasias de la Mama , Humanos , Femenino , Neoplasias de la Mama/tratamiento farmacológico , Brasil/epidemiología , Estudios de Cohortes , Curva ROC
8.
Braz J Med Biol Res ; 55: e12347, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36350973

RESUMEN

Severe pneumonia related to human adenoviruses (HAdVs) has a high lethality rate in children and its early diagnosis and treatment remain a major challenge. Circular RNAs (circRNAs) are novel long noncoding RNAs that play important roles in gene regulation and disease pathogenesis. To investigate the roles of circRNAs in HAdV pneumonia, we analyzed the circRNA profiles of healthy children and children with HAdV pneumonia, including both mild and severe cases, and identified 139 significantly upregulated circRNAs in children with HAdV pneumonia vs healthy controls and 18 significantly upregulated circRNAs in children with severe HAdV pneumonia vs mild HAdV pneumonia. In particular, hsa_circ_0002171 was differentially expressed in both groups and might thus be useful as a diagnostic biomarker of HAdV pneumonia and severe HAdV pneumonia. To identify the underlying mechanisms of circRNAs in HAdV pneumonia, we analyzed the transcriptome of children with HAdV pneumonia and established a circRNA-mRNA regulatory network. Enrichment analysis of differentially expressed target mRNAs demonstrated that the differentially expressed genes between healthy controls and HAdV pneumonia patients were mainly involved in RNA splicing while the differentially expressed genes between children with mild and severe HAdV pneumonia were mainly involved in regulating lymphocyte activation. Receiver operating characteristic (ROC) curve analysis suggested that hsa_circ_0002171 had a significant value in the diagnosis of HAdV pneumonia and of severe HAdV pneumonia. Taken together, the circRNA expression profile was altered in children with HAdV pneumonia. These results demonstrated that hsa_circ_0002171 is a potential diagnostic biomarker of HAdV pneumonia.


Asunto(s)
Adenovirus Humanos , Neumonía , Niño , Humanos , ARN Circular/genética , Adenovirus Humanos/genética , Adenovirus Humanos/metabolismo , Biomarcadores , Curva ROC , ARN Mensajero/genética , ARN/genética
9.
Sci Rep ; 12(1): 19518, 2022 Nov 14.
Artículo en Inglés | MEDLINE | ID: mdl-36376428

RESUMEN

To establish the severity of pancreatitis, there are many scoring systems, the most used are the Marshall and APACHE II systems, each one has advantages and disadvantages; but with good relation regarding mortality and prediction of complications. In populations with low barometric pressures produced by a decrease in atmospheric pressure, there is a decrease in partial pressure of oxygen, in these cases scores which take arterial oxygen partial pressure as one of their variables, may be overestimated. A diagnostic trial study was designed to evaluate the performance of APACHE II, Marshall and BISAP in a city 2640 m above sea level. A ROC analysis was performed to estimate the AUC of each of the scores, to evaluate the performance in predicting unfavorable outcomes (defined as the need for percutaneous drainage, surgery, or mortality) and a non-parametric comparison was made between the AUC of each of the scores with the DeLong test. From January 2018 to December 2019, data from 424 patients living in Bogota, with a diagnosis of gallstone pancreatitis was collected consecutively in a hospital in Bogota, Colombia. The ROC analysis showed AUC for predicting adverse outcomes for APACHE II in 0.738 (95% CI 0.647-0.829), Marshall in 0.650 (95% CI 0.554-0.746), and BISAP in 0.744 (95% CI 0.654-0.835). The non-parametric comparison to assess whether there were differences between the different AUC of the different scores showed that there is a statistically significant difference between Marshall and BISAP AUC to predict unfavorable outcomes (p=0.032). The mortality in the group of patients studied was 5.8%. We suggest the use of BISAP to predict clinical outcomes in patients with a diagnosis of biliary pancreatitis in populations with decreased atmospheric pressure because it is an easy-to-use tool and does not require arterial oxygen partial pressure for its calculation.


Asunto(s)
Oxígeno , Pancreatitis , Humanos , Valor Predictivo de las Pruebas , Índice de Severidad de la Enfermedad , Enfermedad Aguda , Estudios Retrospectivos , Pancreatitis/diagnóstico , Curva ROC , Presión Atmosférica , Pronóstico
10.
Sci Rep ; 12(1): 19499, 2022 Nov 14.
Artículo en Inglés | MEDLINE | ID: mdl-36376523

RESUMEN

Although many studies have been conducted on machine learning (ML) models for Parkinson's disease (PD) prediction using neuroimaging and movement analyses, studies with large population-based datasets are limited. We aimed to propose PD prediction models using ML algorithms based on the National Health Insurance Service-Health Screening datasets. We selected individuals who participated in national health-screening programs > 5 times between 2002 and 2015. PD was defined based on the ICD-code (G20), and a matched cohort of individuals without PD was selected using a 1:1 random sampling method. Various ML algorithms were applied for PD prediction, and the performance of the prediction models was compared. Neural networks, gradient boosting machines, and random forest algorithms exhibited the best average prediction accuracy (average area under the receiver operating characteristic curve (AUC): 0.779, 0.766, and 0.731, respectively) among the algorithms validated in this study. The overall model performance metrics were higher in men than in women (AUC: 0.742 and 0.729, respectively). The most important factor for predicting PD occurrence was body mass index, followed by total cholesterol, glucose, hemoglobin, and blood pressure levels. Smoking and alcohol consumption (in men) and socioeconomic status, physical activity, and diabetes mellitus (in women) were highly correlated with the occurrence of PD. The proposed health-screening dataset-based PD prediction model using ML algorithms is readily applicable, produces validated results, and could be a useful option for PD prediction models.


Asunto(s)
Enfermedad de Parkinson , Humanos , Masculino , Femenino , Enfermedad de Parkinson/diagnóstico , Enfermedad de Parkinson/epidemiología , Aprendizaje Automático , Redes Neurales de la Computación , Algoritmos , Curva ROC
11.
BMC Psychiatry ; 22(1): 701, 2022 11 14.
Artículo en Inglés | MEDLINE | ID: mdl-36376898

RESUMEN

BACKGROUND: The 14-item Short Health Anxiety Inventory (SHAI-14) is a common measure of health anxiety but its screening properties have not been studied. The aims of this study were to evaluate the SHAI-14 as a screening instrument, identify cut-offs for clinically significant health anxiety and investigate which scores correspond to different severity levels. METHOD: The study included 1729 psychiatric patients and 85 healthy controls. Participants completed the SHAI-14 and underwent a diagnostic interview. Cut-off scores were evaluated in three scenarios to approximate screening 1) in a psychiatric clinic, 2) in a low prevalence setting and, 3) of healthy volunteers (cut-off for remission). Receiver operating characteristics were used. Classification of severity was based on the distribution of SHAI-14 scores reported by patients with clinically significant health anxiety. RESULTS: The area under the curve (AUC) values were high in all scenarios (above 0.95). The optimal cut-off scores on the SHAI-14 were 22 in the psychiatric context, 29 in a setting with low prevalence of psychiatric disorders and 18 versus healthy controls. SHAI-14 scores of 0-27 represented no or mild health anxiety, 28-32 moderate health anxiety and 33-42 substantial health anxiety. CONCLUSION: Brief self-report measures used as screening instruments are a simple way of gathering information about the presence of specific symptoms and thus a way to detect the likelihood of a diagnosis. The SHAI-14 shows evidence of good diagnostic utility in both clinical and non-clinical settings. However, which cut-off score is to be used, depends on the intended purpose and the setting where the cut-off is used.


Asunto(s)
Trastornos de Ansiedad , Ansiedad , Humanos , Psicometría , Suecia , Trastornos de Ansiedad/diagnóstico , Trastornos de Ansiedad/psicología , Ansiedad/diagnóstico , Ansiedad/psicología , Tamizaje Masivo , Curva ROC , Escalas de Valoración Psiquiátrica , Reproducibilidad de los Resultados , Sensibilidad y Especificidad
12.
Wiad Lek ; 75(9 pt 2): 2244-2251, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36378703

RESUMEN

OBJECTIVE: The aim: To evaluate the possibility of using screening markers of coagulation to the assessment of severity and predict short-term outcomes in patients with small bowel obstruction. PATIENTS AND METHODS: Materials and methods: The study was based on the results of treatment of 71 patients 18-60 years old in 2019-2021. Patients were divided into two groups: in the 1st included those with a positive outcome (90.1%), and in the 2nd those with adverse outcomes (9.9%). RESULTS: Results: Only the laparoscopy approach has been in 12.5%, the laparotomy in 78.9%, and the hybrid in 9.9% of patients. There were no significant differences in screening tests of coagulation function indicators, including D-dimer, fibrinogen, Activated Partial Thromboplastin, International Normalised Ratio levels, and the International Society on Thrombosis and Hemostasis Criteria (ISTHC) score in two groups of patients before surgery. The predictive value of preoperative Sequential Organ Failure Assessment (SOFA) data (AUC = 0.844), serum lactate (AUC = 0.805), and systolic blood pressure (SPB) data (AUC = 0.808) before surgery were significant. The SOFA (AUC = 0.844) and APACHE II scores (AUC = 0.802), serum lactate (AUC = 0.884), D-dimer (AUC = 0.812), Antithrombin (AUC = 0.815), and CRP (AUC = 0.856) levels, SPB (0.856) within the first 72 hours after surgery were also good predictors of short-term outcomes (P = 0.000). CONCLUSION: Conclusions: It was confirmed that three parameters were predictors of early mortality before surgery, none of them included parameters of coagulation and seven parameters via 72 hours after surgery, which had included some parameters of coagulation.


Asunto(s)
Sepsis , Adulto , Humanos , Adolescente , Adulto Joven , Persona de Mediana Edad , Estudios Retrospectivos , Curva ROC , Pronóstico , Sepsis/diagnóstico , Biomarcadores , Lactatos
14.
BMC Bioinformatics ; 23(1): 469, 2022 Nov 08.
Artículo en Inglés | MEDLINE | ID: mdl-36348271

RESUMEN

Early detection of cancers has been much explored due to its paramount importance in biomedical fields. Among different types of data used to answer this biological question, studies based on T cell receptors (TCRs) are under recent spotlight due to the growing appreciation of the roles of the host immunity system in tumor biology. However, the one-to-many correspondence between a patient and multiple TCR sequences hinders researchers from simply adopting classical statistical/machine learning methods. There were recent attempts to model this type of data in the context of multiple instance learning (MIL). Despite the novel application of MIL to cancer detection using TCR sequences and the demonstrated adequate performance in several tumor types, there is still room for improvement, especially for certain cancer types. Furthermore, explainable neural network models are not fully investigated for this application. In this article, we propose multiple instance neural networks based on sparse attention (MINN-SA) to enhance the performance in cancer detection and explainability. The sparse attention structure drops out uninformative instances in each bag, achieving both interpretability and better predictive performance in combination with the skip connection. Our experiments show that MINN-SA yields the highest area under the ROC curve scores on average measured across 10 different types of cancers, compared to existing MIL approaches. Moreover, we observe from the estimated attentions that MINN-SA can identify the TCRs that are specific for tumor antigens in the same T cell repertoire.


Asunto(s)
Neoplasias , Redes Neurales de la Computación , Humanos , Aprendizaje Automático , Curva ROC , Receptores de Antígenos de Linfocitos T , Atención , Neoplasias/diagnóstico
15.
PLoS One ; 17(11): e0273786, 2022.
Artículo en Inglés | MEDLINE | ID: mdl-36350840

RESUMEN

BACKGROUND: Poorly controlled blood glucose is prevalent and contributes to the huge burden of diabetes related morbidity, and central obesity has a great role in the pathogenesis of diabetes and its adverse complications, which could predict such risks, yet evidence is lacking. Hence, this paper is to evaluate the predictive performance of central obesity indices for glycemic control among adult patients with diabetes in eastern Ethiopia. METHODS: A survey of 432 randomly chosen patients with diabetes was conducted using a pretested questionnaire supplemented by chart review, anthropometrics, and biomarkers by trained data collectors. The poor glycemic control was assessed using a fasting blood glucose (FBS) level of above 130 and/or an HgA1c level above 7%. Weight, height, waist circumference (WC), and hip circumference (HC) were measured under standard procedures and we calculated waist-to-hip circumference ratio (WHR) and waist-to-height ratio (WHtR). The receiver operating characteristics curve was used to assess the predictive performance of obesity indices for glycemic control using area under the curve (AUC) and corresponding validity measures. RESULTS: A total of 432 (92%) patients with diabetes were enrolled with a mean age of 49.6 (±12.4) years. The mean fasting blood glucose level was 189 (±72) mg dl-1 where 330 (76.4%) (95% CI: 74.4-78.4%) and 93.3% of them had poor glycemic control based on FBS and HgA1c, respectively. WC (AUC = 0.90; 95% CI: 0.85-0.95), WHR (AUC = 0.64; 95% CI: 0.43-0.84), and WHtR (AUC = 0.87; 95% CI: 0.83-0.94) have a higher predictive performance for poor glycemic control at cut-off points above 100 cm, 0.95, and 0.62, respectively. However, obesity indices showed a lower predictive performance for poor glycemic control based on FBS. Body mass index (BMI) had a poor predictive performance for poor glycemic control (AUC = 0.26; 95% CI: 0.13-0.40). CONCLUSIONS: Poor glycemic control is a public health concern and obesity indicators, typically WC, WHR, and WHtR, have a better predictive performance for poor glycemic control than BMI.


Asunto(s)
Diabetes Mellitus , Hiperglucemia , Adulto , Humanos , Persona de Mediana Edad , Circunferencia de la Cintura , Índice de Masa Corporal , Curva ROC , Obesidad Abdominal , Control Glucémico , Glucemia , Etiopía/epidemiología , Relación Cintura-Estatura , Relación Cintura-Cadera , Obesidad/complicaciones , Diabetes Mellitus/epidemiología , Factores de Riesgo
16.
Physiol Rep ; 10(21): e15494, 2022 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-36353917

RESUMEN

Acute respiratory distress syndrome (ARDS) is a lethal disease with severe forms conferring a mortality rate approaching 40%. The initial phase of ARDS results in acute lung injury (ALI) characterized by a severe inflammatory response and exudative alveolar flooding due to pulmonary capillary leak. Timely therapies to reduce ARDS mortality are limited by the lack of laboratory-guided diagnostic biomarkers for ARDS. The purpose of this study was to evaluate the prognostic role of circulating microvesicles (MVs)-containing miR-223 (MV-miR-223) if indicate more severe lung injury and worse outcomes in ARDS patients. Human plasma samples from one hundred ARDS patients enrolled in Albuterol to Treat Acute Lung Injury (ALTA) trial were compared to a control group of twenty normal human plasma specimens. The amount of MV-miR-223 was measured using absolute real-time polymerase chain reaction (PCR) with a standard curve. Mann-Whitney-Wilcoxon, Spearman correlation, Chi-squared tests, and Kaplan-Meier curves were computed to assess different variables and survival. Plasma levels of MV-miR-223 were significantly higher in ARDS patients compared to normal control subjects. Upon receiver operator characteristic (ROC) analysis of MV-miR-223 in relation to 30-day mortality, MV-miR-223 had an area under the curve (AUC) of 0.7021 with an optimal cut-off value of 2.413 pg/ml. Patients with high MV-miR-223 had higher 30-day mortality than subjects with low MV-miR-223 levels. MV-miR-223 was negatively correlated with ICU-free days, ventilator-free days, and organ failure-free days. Patients with high MV-miR-223 levels had higher 30 and 90-day mortality. MV-miR-223 was associated with 28-day clinical outcomes of ALTA trial including ICU-free days, ventilator-free days, and organ failure-free days. Thus, circulating MV-miR-223 may be a potential biomarker in prognosticating patient-centered outcomes and predicting mortality in ARDS.


Asunto(s)
Lesión Pulmonar Aguda , MicroARNs , Síndrome de Dificultad Respiratoria , Humanos , Curva ROC , Síndrome de Dificultad Respiratoria/diagnóstico , MicroARNs/genética , Biomarcadores
17.
Transl Vis Sci Technol ; 11(11): 7, 2022 Nov 01.
Artículo en Inglés | MEDLINE | ID: mdl-36355387

RESUMEN

Purpose: To predict demographic characteristics from anterior segment optical coherence tomography (AS-OCT) images of eyes using a Vision Transformer (ViT) model. Methods: A total of 2970 AS-OCT images were used to train, validate, and test a ViT to predict age and sex, and 2616 images were used for height, weight, and body mass index (BMI). The main outcome measure was the area under the receiver operating characteristic curve (AUC) of the ViT. Results: The ViT achieved the largest AUC (0.910) for differentiating age ≤75 versus >75 years, followed by age ≤60 versus 60-75 versus >75 years (AUC, 0.844), and for discriminating sex (AUC, 0.665). The prediction abilities for the other demographic characteristics were lower: an AUC of 0.521 for classifying height ≤170 versus >170 cm in males and ≤155 versus >155 cm in females; 0.522 for weight <70 versus ≥70 kg in males and 0.503 for <55 versus ≥55 kg in females, and 0.517 for BMI <23 versus 23-25 versus ≥25 kg/m2. Heatmaps highlighted the area of the iridocorneal angle for its contribution to the prediction of age ≤75 versus >75 years. Conclusions: Although the ViT demonstrated a good ability to classify age from AS-OCT images, it performed poorly for sex, height, weight, and BMI. The heatmap obtained of the prediction will provide clues to understanding the age-related anterior segment changes in eyes. Translational Relevance: The ViT can determine age-related anterior segment structural changes using AS-OCT images, which will aid clinicians in the management of ocular diseases.


Asunto(s)
Segmento Anterior del Ojo , Tomografía de Coherencia Óptica , Masculino , Femenino , Humanos , Anciano , Segmento Anterior del Ojo/diagnóstico por imagen , Tomografía de Coherencia Óptica/métodos , Curva ROC , Cara , Demografía
18.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 34(9): 915-920, 2022 Sep.
Artículo en Chino | MEDLINE | ID: mdl-36377443

RESUMEN

OBJECTIVE: To evaluate the effect of 2019 novel coronavirus inactivated vaccine on the disease severity of patients with Delta variant of coronavirus disease 2019. METHODS: A retrospective analysis was performed on 704 patients with coronavirus disease 2019 infected with Delta variant who were older than 18 years old and admitted in the coronavirus disease 2019 designated hospital of Yangzhou (Subei Hospital New Area Branch) from July 2021 to September 2021. They were divided into severe (severe, critical) group and non-severe (light, ordinary) group according to the clinical characteristics of patients. According to the vaccination status, they were divided into 0-dose group, 1-dose group and 2-dose group. We evaluated the effects of vaccination on the severity of the disease and the production of antibodies, and analyzed the influencing factors leading to the severe group of coronavirus disease 2019. RESULTS: The proportion of severe group in the 2-dose vaccinated group was significantly lower than that in the 1-dose vaccinated group and 0-dose vaccinated group [3.02% (7/232) vs. 9.48% (22/232), 15.83% (38/240), P < 0.05]. The time from onset to admission (day: 1.97±1.66 vs. 2.66±2.70), age (years: 45.3±12.2 vs. 63.6±17.0), direct bilirubin [DBil (µmol/L): 3.70±1.83 vs. 5.30±5.13], lactate dehydrogenase [LDH (U/L): 240.69±74.29 vs. 256.30±85.18], creatinine [SCr (µmol/L): 63.38±19.86 vs. 70.23±25.43], interleukin-6 [IL-6 (ng/L): 7.32 (1.54, 17.40) vs. 18.38 (8.83, 33.43)], creatine kinase [CK (U/L): 66.00 (43.00, 99.75) vs. 78.00 (54.50, 144.00)] and D-dimer [mg/L: 0.30 (0.08, 0.49) vs. 0.41 (0.23, 0.69)] of patients in the 2-dose group were significantly lower than those in the 0-dose group (all P < 0.05), while platelet [PLT (×109/L): 176.69±60.25 vs. 149.25±59.07], white blood cell count [WBC (×109/L): 5.43±1.77 vs. 5.03±1.88] and lymphocyte [LYM (×109/L): 1.34±0.88 vs. 1.17±0.50] were significantly higher than those in the 0-dose group (all P < 0.05). The titer of immunoglobulin G (IgG) in the 2-dose group was significantly higher than those in the 1-dose group and 0-dose group on the 10th day after admission [U/L: 130.94 (92.23, 326.31), 113.18 (17.62, 136.20), 117.85 (33.52, 156.73), both P < 0.05], and higher than 0-dose group on the 16th day [U/L: 156.12 (120.32, 167.76) vs. 126.52 (61.34, 149.57), P < 0.05]. The proportion of complete 2-dose vaccination [10.45% (7/67) vs. 35.32% (225/637)], LYM (×109/L: 1.09±0.32 vs. 1.25±0.56) and PLT (×109/L: 138.55±68.03 vs. 166.93±59.70) in the severe group were significantly lower than those in the non-severe group (P < 0.05), while the time from onset to admission (day: 3.01±2.99 vs. 2.25±2.09), the length of hospital stay (day: 28±18 vs. 16±6), male proportion [77.61% (52/67) vs. 34.54% (220/637)], age (years: 69.13±12.63 vs. 52.28±16.53), DBil [µmol/L: 4.20 (3.18, 6.65) vs. 3.60 (2.80, 4.90], LDH (U/L: 310.61±98.33 vs. 238.19±72.14), SCr (µmol/L: 85.67±38.25 vs. 65.98±18.57), C-reactive protein [CRP (µmol/L): 28.12 (11.32, 42.23) vs. 8.49 (2.61, 17.58)], IL-6 [ng/L: 38.38 (24.67, 81.50) vs. 11.40 (4.60, 22.07)], CK [U/L: 140.00 (66.00, 274.00) vs. 72.80 (53.00, 11.00)] and the D-dimer [mg/L: 0.46 (0.29, 0.67) vs. 0.35 (0.19, 0.57)] in the severe group were significantly higher than those in the non-severe group (all P < 0.05). Multivariate regression analysis showed that the odds ratio (OR) of severe group was 0.430 (P = 0.010) in the 1-dose group and the 2-dose group compared with the 0-dose group. However, the risk of severe group was 0.381-fold in the 2-dose group compared with the 0-dose group [OR = 0.381, 95% confidence interval (95%CI) was 0.121-1.199] which was not statistically significant, when the age was included in the regression analysis (P > 0.05). PLT (OR = 0.992, 95%CI was 0.986-0.998) were protective factors, but older than 60 years old (OR = 3.681, 95%CI was 1.637-8.278), CK (OR = 1.001, 95%CI was 1.000-1.001), IL-6 (OR = 1.006, 95%CI was 1.002-1.010), SCr (OR = 1.020, 95%CI was 1.007-1.033) were risk factors for severe group (all P < 0.05). CONCLUSIONS: Compared with the 0-dose vaccinated patients, the coronavirus disease 2019 patients infected with delta variant and fully vaccinated with 2-dose 2019 novel coronavirus inactivated vaccine had lower level of IL-6, SCr, CK and D-dimer, and higher PLT, LYM and IgG titer, who were not easy to develop into the severe condition.


Asunto(s)
COVID-19 , Humanos , Masculino , Adolescente , Persona de Mediana Edad , SARS-CoV-2 , Estudios Retrospectivos , Interleucina-6 , Curva ROC , Pronóstico , Índice de Severidad de la Enfermedad , Vacunación , Inmunoglobulina G , Vacunas de Productos Inactivados
19.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 34(9): 921-926, 2022 Sep.
Artículo en Chino | MEDLINE | ID: mdl-36377444

RESUMEN

OBJECTIVE: To explore the value of monocyte subsets and CD64 expression in the diagnosis and prognosis of sepsis. METHODS: A prospective case-control study was designed. 30 septic patients and 30 non-septic patients who were admitted to the intensive care unit (ICU) of the PLA Army Characteristic Medical Center from March 2021 to March 2022 were enrolled. After 1, 3, and 5 days of ICU admission, peripheral blood samples were taken from patients. Flow cytometry was used to detect the proportion of monocyte subsets and the expression level of CD64 on the surface, and the difference of expression between patients in two group was analyzed. The risk variables for sepsis were analyzed using single-factor and multi-factor Logistic regression. The diagnostic efficacy of each risk factor for sepsis was determined using the receiver operator characteristic curve (ROC curve). RESULTS: One day after ICU admission, the proportions of monocytes and classic monocytes in white blood cells (WBC) of septic patients were significantly lower than those of non-septic patients [proportion of monocytes to WBC: (4.13±2.03)% vs. (6.53±3.90)%, proportion of classic monocytes to WBC: 1.97 (1.43, 2.83)% vs. 3.37 (1.71, 5.98)%, both P < 0.05]. The proportion of non-classical monocytes in monocytes was significantly higher in septic patients than that in non-septic patients [(11.42±9.19)% vs. (6.57±4.23)%, P < 0.05]. The levels of CD64 expression in monocytes, classic monocytes, intermediate monocytes and non-classic monocytes were significantly higher in sepsis patients than those in non-septic patients [mean fluorescence intensity (MFI): 13.10±6.01 vs. 9.84±2.83 for monocytes, 13.58±5.98 vs. 10.03±2.84 for classic monocytes, 13.48±6.35 vs. 10.22±2.99 for intermediate monocytes, 8.21±5.52 vs. 5.79±2.67 for non-classic monocytes, all P < 0.05]. Multivariate Logistic regression research showed that CD64 in typical monocytes [odds ratio (OR) = 1.299, 95% confidence interval (95%CI) was 1.027-1.471, P = 0.025] and the proportion of non-typical monocytes in monocytes (OR = 1.348, 95%CI was 1.034-1.758, P = 0.027) were the independent risk factors for sepsis. ROC curve showed that the area under the ROC curve (AUC) of CD64 expression of classical monocytes, the fraction of non-classical monocytes in monocytes, and procalcitonin (PCT) in the diagnosis of sepsis was 0.871. A correlation analysis revealed a negative relationship between the acute physiology and chronic health status evaluation II (APACHE II) on the first, third, and fifth days following ICU admission and the expression level of CD64 in patients' classic monocytes (r values were -0.264, -0.428 and -0.368, respectively, all P < 0.05). CONCLUSIONS: Combining the proportion of non-classical monocytes in monocytes, the level of plasma PCT, and the CD64 expression of classic monocytes in peripheral blood has good efficacy in identifying sepsis and assessing its severity.


Asunto(s)
Monocitos , Sepsis , Humanos , Estudios de Casos y Controles , Curva ROC , Sepsis/diagnóstico , Pronóstico , Polipéptido alfa Relacionado con Calcitonina , Unidades de Cuidados Intensivos , Estudios Retrospectivos
20.
Zhonghua Wei Zhong Bing Ji Jiu Yi Xue ; 34(9): 935-940, 2022 Sep.
Artículo en Chino | MEDLINE | ID: mdl-36377447

RESUMEN

OBJECTIVE: To construct and verify the nomogram prediction model based on inflammatory indicators, underlying diseases, etiology and the British Thoracic Society modified pneumonia score (CURB-65 score) in adults with severe community acquired pneumonia (CAP). METHODS: The clinical data of 172 adult inpatients first diagnosed as CAP at Taikang Xianlin Drum Tower Hospital from January 2018 to December 2021 were divided into severe and non-severe diseases groups according to the severity of their conditions. The baseline conditions (including gender, age, past history, comorbidities and family history), clinical data (including chief symptoms, onset time, CURB-65 score), first laboratory results on admission (including whole blood cell count, liver and kidney function, blood biochemistry, coagulation function, microbiological culture results) and whether the antimicrobial therapy was adjusted according to the microbiological culture results were recorded in both groups. Univariate analysis was used to screen for differential indicators between severe and non-severe patients. After covariate analysis, multi-factor Logistic regression analysis was performed based on the Aakaike information criterion (AIC) forward stepwise regression method to rigorously search for risk factors for constructing the model. Based on the results of the multi-factor analysis, a nomogram prediction model was constructed, and the discriminatory degree and calibration degree of the model were assessed using the receiver operator characteristic curve (ROC curve) and calibration curve. RESULTS: A total of 172 adult CAP patients were included, 48 in severe group and 124 in non-severe group. The median age was 74 (57, 83) years old, onset time was 5.0 (3.0, 10.0) days, total number of comorbidities was 3 (2, 5), including 58 cases (33.7%) with hypertension and 17 (9.9%) with heart failure, 113 (65.7%) with CURB-65 score ≤ 1, 34 cases (19.8%) had a CURB-65 score = 2 and 25 cases (14.5%) had a CURB-65 score ≥ 3. Univariate analysis showed that there were statistically significant differences between the two groups in age, smoking history, CURB-65 score, heart rate, onset time, total comorbidity, pathogenic microorganisms, fibrinogen (FIB), D-dimer, C-reactive protein (CRP), procalcitonin (PCT), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Multi-factor Logistic regression analysis showed that hypertension [odds ratio (OR) = 3.749, 95% confidence interval (95%CI) 1.411 to 9.962], heart failure (OR = 4.616, 95%CI was 1.116 to 19.093), co-infection (OR = 2.886, 95%CI was 1.073 to 7.760), history of smoking (OR = 8.268, 95%CI was 2.314 to 29.537), moderate to high CURB-65 score (OR = 4.833, 95%CI was 1.892 to 12.346), CRP (OR = 1.012, 95%CI was 1.002 to 1.022), AST (OR = 1.015, 95%CI was 1.001 to 1.030) were risk factors for severe CAP (all P < 0.05). The filtered indicators were included in the nomogram model, and the results showed that the area under the ROC curve (AUC) for the model to identify patients with severe adult CAP was 0.896, 95%CI was 0.840 to 0.937 (P < 0.05), and the calibration curve showed that the predicted probability of severe CAP was in good agreement with the observed probability (Hosmer-Lemeshow test: χ2 = 6.088, P = 0.665). CONCLUSIONS: The nomogram model has a good ability to identify patients with severe adult CAP and can be used as a comprehensive and reliable clinical diagnostic tool to provide a evidence for timely intervention in the treatment of adults with severe CAP.


Asunto(s)
Infecciones Comunitarias Adquiridas , Insuficiencia Cardíaca , Hipertensión , Neumonía , Humanos , Adulto , Anciano , Anciano de 80 o más Años , Nomogramas , Estudios Retrospectivos , Pronóstico , Infecciones Comunitarias Adquiridas/diagnóstico , Neumonía/diagnóstico , Proteína C-Reactiva/análisis , Curva ROC
SELECCIÓN DE REFERENCIAS
DETALLE DE LA BÚSQUEDA
...