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BACKGROUND: We aimed to examine the relationship of 2 dietary scores [dietary inflammatory index (DII) and composite dietary antioxidant index (CDAI)] with frailty in elderly adults with diabetes. METHODS: Data were gathered from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2018. The frailty index was calculated using 49 deficits across various systems to define frailty. To examine the relationship of 2 dietary scores (DII and CDAI) with frailty in elderly adults with diabetes, multiple logistic regression analyses were performed. In logistic regression model, DII and CDAI were calculated as both continuous and tertiles. Subgroup analyses were performed to demonstrate stability of results. Restricted cubic splines were utilized to examine the non-linear correlations. RESULTS: A total of 2,795 elderly adults with diabetes were included in this study. In the multivariate logistic regression model, the odds ratio (OR) of DII for risk of frailty was 1.08 (95% CI 1.02-1.15) and the OR of CDAI for risk of frailty was 0.96 (95% CI 0.93-0.99). The ORs of DII for risk of frailty were 1.36 (95% CI 1.09-1.70) and 1.33 (95% CI 1.04-1.70) for tertiles 2 and 3, respectively (p for trend 0.027). The ORs of CDAI for risk of frailty were 0.94 (95% CI 0.75-1.17) and 0.75 (95% CI 0.58-0.98) for tertiles 2 and 3, respectively (p for trend 0.036). The subgroup analysis demonstrated reliable and enduring connections between 2 dietary scores and frailty (all p for interaction > 0.05). In the restricted cubic spline analyses, we discovered the non-linear relationship between DII and frailty (P for nonlinearity = 0.045) and linear relationship between CDAI and frailty (P for nonlinearity = 0.769). CONCLUSION: The research showed connections between 2 dietary scores (DII and CDAI) and frailty as measured by frailty index in elderly adults with diabetes.
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Antioxidantes , Diabetes Mellitus , Fragilidade , Inflamação , Humanos , Idoso , Masculino , Feminino , Fragilidade/epidemiologia , Antioxidantes/administração & dosagem , Inquéritos Nutricionais , Dieta , Idoso Fragilizado , Idoso de 80 Anos ou mais , Fatores de Risco , Pessoa de Meia-Idade , Modelos LogísticosRESUMO
Objective: Current scoring systems for short-term prognosis in patients with acute myocardial infarction (AMI) lack coverage of risk factors and have limitations in risk stratification. The aim of this study was to develop a novel assessment system based on laboratory indicators and frailty quantification to better infer short-term prognosis and risk indication in patients with AMI. Methods: A total of 365 patients with MI from January 2022 to June 2023 in Northern Jiangsu Province Hospital were included. The primary endpoint was all-cause mortality and major adverse cardiac events (MACE) during follow-up. A novel scoring model ranging from 0 to 12 was constructed, and the predictive ability of this scoring system was evaluated using the area under the receiver operating characteristic curve (AUC). Results: During follow-up, 68 patients experienced MACE. Five scoring indicators were selected through multivariate logistic regression analysis, resulting in a composite score with an AUC of 0.925, demonstrating good prognostic accuracy. Conclusion: The novel prognostic assessment system, which integrates age, Stress Hyperglycemia Ratio (SHR), Neutrophil to Lymphocyte Ratio (NLR), lactate, and frailty score, exhibits good predictive value for short-term MACE in patients with acute myocardial infarction and may enable more accurate risk classification for future use in MI patient risk management.
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Fragilidade , Infarto do Miocárdio , Curva ROC , Humanos , Masculino , Infarto do Miocárdio/sangue , Infarto do Miocárdio/diagnóstico , Infarto do Miocárdio/mortalidade , Feminino , Idoso , Estudos Retrospectivos , Fragilidade/diagnóstico , Prognóstico , Pessoa de Meia-Idade , Medição de Risco/métodos , Fatores de Risco , Neutrófilos , Idoso de 80 Anos ou mais , China , Modelos Logísticos , Ácido Láctico/sangueRESUMO
BACKGROUND: Endometriosis is intricately linked to metabolic health. The Cardiometabolic Index (CMI), a novel and readily accessible indicator, is utilized to evaluate metabolic status. This study seeks to investigate the potential correlation between CMI and endometriosis. METHODS: Data from four consecutive survey cycles of the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2006 were utilized. This included adult females with self-reported diagnoses of endometriosis and complete information required for calculating the CMI. The calculation formula for CMI is Triglycerides(TG) / High-density lipoprotein cholesterol (HDL-C) × WHtR (WHtR = waist circumference / height). A multivariable logistic regression model was employed to investigate the linear association between CMI and endometriosis. Subgroup analyses were performed to explore potential influencing factors. Additionally, the linear relationship was validated using restricted cubic spline (RCS) curve plotting and threshold effect analysis. RESULTS: This study, based on the National Health and Nutrition Examination Survey (NHANES), included a cohort of 2,224 adult women. The multivariable logistic regression analysis demonstrated that in the fully adjusted model, individuals with the highest CMI exhibited a 78% elevated likelihood of endometriosis compared to those with the lowest CMI (OR = 1.78; 95% CI, 1.02-3.11, P < 0.05). The subgroup analysis indicated that there were no significant interactions between CMI and specific subgroups (all interaction P > 0.05), except for the subgroup stratified by stroke status (P < 0.05). Additionally, the association between CMI and endometriosis was linear, with a 20% increase in the association for each unit increase in CMI when CMI > 0.67 (OR = 1.20; 95% CI, 1.05-1.37, P < 0.01). CONCLUSION: The study found that CMI levels are closely correlated with endometriosis, with this correlation increasing when the CMI exceeds 0.67. This finding implies that by regularly monitoring CMI levels, physicians may be able to screen women at risk for endometriosis at an earlier stage, thereby enabling the implementation of early interventions to slow the progression of the disease. To further validate these findings, larger-scale cohort studies are required to support the results of this research.
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HDL-Colesterol , Endometriose , Inquéritos Nutricionais , Triglicerídeos , Humanos , Feminino , Endometriose/sangue , Adulto , Estudos Transversais , Triglicerídeos/sangue , HDL-Colesterol/sangue , Circunferência da Cintura , Pessoa de Meia-Idade , Modelos Logísticos , Doenças Cardiovasculares/epidemiologiaRESUMO
OBJECTIVES: Previous research has extensively explored the factors associated with psychotic-like experiences (PLEs). However, the characteristics and associated factors of remitted PLEs, which refer to the absence of current PLEs following previous PLEs, remain unclear. Therefore, this study aims to describe the characteristics of adolescents who reported remitted PLEs. DESIGN: Cross-sectional study. SETTING: The survey was conducted from October to December 2020 in three colleges located in Guangzhou, China. PARTICIPANTS: A total of 4208 college freshmen aged from 15 to 24 participated in our survey. PRIMARY AND SECONDARY OUTCOME MEASURES: The 15-item positive subscale of the Community Assessment of the Psychic Experience was used to assess both lifetime and current PLEs. Multivariate logistic regression models were used to examine the associations between remitted PLEs and a range of demographic factors, lifestyle, psychosocial factors, lifetime affective symptoms and sleep problems. RESULTS: Three groups of PLEs were observed: non-PLEs (47.27% of the sample), remitted PLEs (40.42%) and current PLEs (12.31%). Several factors have been identified as shared correlates of remission and absence of PLEs, including fewer recent adverse life events, greater resilience, fewer symptoms of depression and anxiety, and early waking. Furthermore, higher levels of social support (OR 1.48, 95% CI 1.01 to 2.17; OR 1.53, 95% CI 1.18 to 1.97) was a specific factor associated with the remission of PLEs. Compared with individuals without PLEs, those with remitted PLEs were more likely to be female (OR 1.50, 95% CI 1.28 to 1.75), less likely to be younger (OR 0.88, 95% CI 0.81 to 0.95) and prone to have more chronic physical illness (OR 1.67, 95% CI 1.29 to 2.16), habitual alcohol intake (OR 1.85, 95% CI 1.19 to 2.88), more childhood trauma (OR for low vs high=0.72, 95% CI 0.57 to 0.91) and the sleep problems of waking up easily (OR 1.36, 95% CI 1.12 to 1.65). CONCLUSION: These findings suggest that remitted PLEs play a vital, unique role among three groups and provide preliminary targets for the intervention for adolescents at risk of mental health problems. Further investigation may shed light on the causality of the relationship between remitted PLEs and associated factors.
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Transtornos Psicóticos , Estudantes , Humanos , Estudos Transversais , Feminino , Masculino , China/epidemiologia , Adolescente , Estudantes/psicologia , Estudantes/estatística & dados numéricos , Adulto Jovem , Transtornos Psicóticos/epidemiologia , Universidades , Fatores de Risco , Inquéritos e Questionários , Modelos LogísticosRESUMO
BACKGROUND: A short cervix in mid-trimester pregnancy is a risk factor for spontaneous preterm birth. However, there is currently a lack of predictive models and classification systems for predicting spontaneous preterm birth in these patients, especially those without additional risk factors for spontaneous preterm birth. METHODS: A retrospective observational cohort study of low-risk singleton pregnant women with a short cervix (≤ 25 mm) measured by transvaginal ultrasonography between 22 and 24 weeks was conducted. A multivariate logistic regression model for spontaneous preterm birth < 32 weeks in low-risk pregnant women with a short cervix was constructed. Moreover, we developed a nomogram to visualize the prediction model and stratified patients into three risk groups (low-, intermediate-, and high-risk groups) based on the total score obtained from the nomogram model. RESULTS: Between 2020 and 2022, 213 low-risk women with a short cervix in mid-trimester pregnancy were enrolled in the study. Univariate logistic analysis revealed that a high body mass index, a history of three or more miscarriages, multiparity, a short cervical length, leukocytosis, and an elevated C-reactive protein level were associated with spontaneous preterm birth < 32 weeks, but multivariate analysis revealed that multiparity (OR, 3.31; 95% CI, 1.13-9.68), leukocytosis (OR, 3.96; 95% CI, 1.24-12.61) and a short cervical length (OR, 0.88; 95% CI, 0.82-0.94) were independent predictors of sPTB < 32 weeks. The model incorporating these three predictors displayed good discrimination and calibration, and the area under the ROC curve of this model was as high as 0.815 (95% CI, 0.700-0.931). Patients were stratified into low- (195 patients), intermediate- (14 patients) and high-risk (4 patients) groups according to the model, corresponding to patients with scores ≤ 120, 121-146, and > 146, respectively. The predicted probabilities of spontaneous preterm birth < 32 weeks for these groups were 6.38, 40.62, and 71.88%, respectively. CONCLUSIONS: A noninvasive and efficient model to predict the occurrence of spontaneous preterm birth < 32 weeks in low-risk singleton pregnant women with a short cervix and a classification system were constructed in this study and can provide insight into the optimal management strategy for patients with different risk stratifications according to the score chart.
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Medida do Comprimento Cervical , Colo do Útero , Nomogramas , Segundo Trimestre da Gravidez , Nascimento Prematuro , Humanos , Feminino , Gravidez , Estudos Retrospectivos , Nascimento Prematuro/epidemiologia , Adulto , Colo do Útero/diagnóstico por imagem , Colo do Útero/patologia , Fatores de Risco , Medição de Risco/métodos , Modelos Logísticos , Idade GestacionalRESUMO
BACKGROUND AND AIM: Colorectal cancer is a prevalent malignancy worldwide, and right hemicolectomy is a common surgical procedure for its treatment. However, postoperative incisional infections remain a significant complication, leading to prolonged hospital stays, increased healthcare costs, and patient discomfort. Therefore, this study aims to utilize machine learning models, including random forest, support vector machine, deep learning models, and traditional logistic regression, to predict factors associated with incisional infection following right hemicolectomy for colon cancer. METHODS: Clinical data were collected from 322 patients undergoing right hemicolectomy for colon cancer, including demographic information, preoperative chemotherapy status, body mass index (BMI), operative time, and other relevant variables. These data are divided into training and testing sets in a ratio of 7:3. Machine learning models, including random forest, support vector machine, and deep learning, were trained using the training set and evaluated using the testing set. RESULTS: The deep learning model exhibited the highest performance in predicting incisional infection, followed by random forest and logistic regression models. Specifically, the deep learning model demonstrated higher area under the receiver operating characteristic curve (ROC-AUC) and F1 score compared to other models. These findings suggest the efficacy of machine learning models in predicting risk factors for incisional infection following right hemicolectomy for colon cancer. CONCLUSIONS: Machine learning models, particularly deep learning models, offer a promising approach for predicting the risk of incisional infection following right hemicolectomy for colon cancer. These models can provide valuable decision support for clinicians, facilitating personalized treatment strategies and improving patient outcomes.
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Colectomia , Neoplasias do Colo , Aprendizado de Máquina , Infecção da Ferida Cirúrgica , Humanos , Colectomia/efeitos adversos , Neoplasias do Colo/cirurgia , Masculino , Feminino , Pessoa de Meia-Idade , Infecção da Ferida Cirúrgica/etiologia , Infecção da Ferida Cirúrgica/epidemiologia , Infecção da Ferida Cirúrgica/diagnóstico , Idoso , Fatores de Risco , Estudos Retrospectivos , Modelos Logísticos , Máquina de Vetores de SuporteRESUMO
BACKGROUND: Informal caregivers of older adults play a vital role in improving the degree to which older adults access community and healthcare services in a seamless and timely manner. They are fulfilling important navigation and support roles for their older care recipients. However, there is still little knowledge of the most significant facilitators and barriers to effective and efficient system navigation among caregivers. This paper aims to fill these knowledge gaps through investigation of the key factors (i.e., social capital/cohesion, caregiving supports, and utilization factors) affecting navigation difficulties faced by informal caregivers of older adults. METHODS: The Behavioural-Ecological Framework of Healthcare Access and Navigation (BEAN) model is used to frame the study. Using the General Social Survey on Caregiving and Care Receiving 2018, we analyzed 2,733 informal caregivers whose primary care recipients were aged 65 or older. Hierarchical logistic regression was conducted to identify the relationship between system navigation difficulties among informal caregivers and four sequentially ordered blocks of predictors: (1) sociodemographic (2), social capital/cohesion (3), caregiving supports, and (4) healthcare demand. RESULTS: The fully adjusted model showed that the probability of reporting navigation difficulties was lower for caregivers with social capital/cohesion compared to those without social capital/cohesion. In comparison, the probability of reporting navigation difficulties was higher among caregivers with caregiving support and among caregivers whose care receivers use a higher amount of health service use. Several sociodemographic covariates were also identified. CONCLUSION: Our findings support certain aspects of the BEAN model. This study extends our understanding of potential facilitators and barriers that informal caregivers of older adults face while navigating complex community and health systems. There is a need to implement coordinated schemes and health policies especially for older adults with mental/neurological issues to address the challenges of their caregivers given the specific vulnerability identified in this study. The need for further research using different approaches to examine the disproportionate impact of COVID-19 on caregivers' system navigation experience is crucial.
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Cuidadores , Capital Social , Apoio Social , Humanos , Cuidadores/psicologia , Cuidadores/estatística & dados numéricos , Idoso , Feminino , Masculino , Modelos Logísticos , Pessoa de Meia-Idade , Idoso de 80 Anos ou mais , Acessibilidade aos Serviços de Saúde , Navegação de PacientesRESUMO
BACKGROUND: Chronic abdominal pain is a potential symptom of lead poisoning, which is often challenging to diagnose. This case-control study aimed to evaluate blood lead levels in pediatric patients with chronic abdominal pain. METHODS: The case-control study was conducted on 190 pediatrics who presented to the Children's Medical Center Hospital clinics, Tehran between April 2021- 2023. The children were divided into two groups: the case group, consisting of 81 patients with chronic abdominal pain, and the matched control group; 109 children without any gastrointestinal symptoms. The statistical analysis of the data was performed using STATA 16. A multiple logistic regression model was used to assess the association of different independent variables with chronic abdominal pain. RESULTS: There was no significant difference between mean (± standard deviation [SD]) of age (8.80(2.7) years vs. control group: 9.23(3.9) years), sex, and BMI (16.55(4.6) vs. 17.32(4.7)) of the patients with chronic abdominal pain (case group) and the control group, whereas the mean weight was remarkably low in patients with chronic abdominal pain: 27.25(± 12.1) kg vs. 31.70(± 14.7) kg (P value = 0.028). Fifty-nine percent of children with chronic abdominal pain had serum lead levels ≥ 10 µg/dL. The mean (SD) of blood lead levels was statistically high in the case group: 11.09 (± 5.35) µg/dL vs. control group: 8.26 (± 5.01) µg/dL) (P value ≤ 0.05). The appetite level was significantly low in the case group: 3.8 (± 2.5) vs. control group 5.4 (± 1.3). CONCLUSIONS: Lead poisoning could be a possible cause of children's chronic abdominal pain. Regarding the high rate of lead poisoning in children exerting appropriate measures to reduce their exposure to lead is necessary.
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Dor Abdominal , Dor Crônica , Intoxicação por Chumbo , Chumbo , Humanos , Intoxicação por Chumbo/diagnóstico , Intoxicação por Chumbo/complicações , Intoxicação por Chumbo/sangue , Dor Abdominal/etiologia , Criança , Estudos de Casos e Controles , Masculino , Feminino , Irã (Geográfico) , Chumbo/sangue , Diagnóstico Diferencial , Adolescente , Pré-Escolar , Modelos LogísticosRESUMO
BACKGROUND: The comorbidity between obesity and smoking and its association with cardiometabolic risk factors has been little explored. OBJECTIVES: Describe the prevalence of such comorbidity and to explore its association with cardiometabolic risk factors. METHODS: The study was based on the 2016-2017 Chilean National Health Survey and included 6,233 participants. The independent variables were general obesity according to Body Mass Index (BMI), central obesity measured by Waist-to-Height Ratio (WTHR) and Waist Circumference (WC), and daily tobacco consumption (DTC). The dependent variables were blood lipids, fasting glucose and blood pressure. The association analysis was performed by multivariate logistic regression and excluded subjects with a medical record of hypertension, diabetes mellitus and dyslipidemia to avoid reverse causality. RESULTS: The prevalence of General obesity-DTC comorbidity was 7.7%, WTHR risk-DTC was 10.8% and elevated WC-DTC was 13.2%. A total of 3,132 participants were included in logistic regressions. General obesity alone, and DTC-general obesity comorbidity had statistically significant association with elevated triglycerides, decreased HDL, elevated non-HDL and total cholesterol, elevated fasting glucose, and elevated blood pressure. The comorbidities DTC-risk WTHR and DTC-increased WC were associated with increased triglycerides and non-HDL cholesterol. DTC alone was associated with elevated systolic blood pressure. CONCLUSION: DTC-general obesity comorbidity is more frequently associated with the cardiometabolic risk factors explored than DTC-central obesity comorbidity. Smoking cessation can be a cost-effective intervention in this risk comorbidity.
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Fatores de Risco Cardiometabólico , Comorbidade , Inquéritos Epidemiológicos , Obesidade , Fumar , Humanos , Masculino , Feminino , Chile/epidemiologia , Pessoa de Meia-Idade , Adulto , Obesidade/epidemiologia , Fumar/epidemiologia , Prevalência , Adulto Jovem , Índice de Massa Corporal , Circunferência da Cintura , Idoso , Adolescente , Doenças Cardiovasculares/epidemiologia , Doenças Cardiovasculares/etiologia , Estudos Transversais , Fatores de Risco , Modelos LogísticosRESUMO
ABASTRACT Background: To study the association between pain and depression, its characteristics and related factors in chilean older adults. METHODS: Cross-sectional analytical study of the National Survey of Dependence in Chilean older adults 2009, with a sample of 4766 people aged 60 years and older. Pain was described using a Likert scale from "no pain" to "very much pain". Depression was measured using the GDS-15 scale. Adjusted logistic regression analyses were performed to identify the association between pain and depression. RESULTS: 70% of the sample reported pain, 21.6% of high intensity. The screening was positive for depression in 23% of the sample, and 5% suspected severe depression. Both conditions were more frequent in women, subjects with low levels of schooling and rural residence. There was an association between pain and depression OR 3.46. The greater the intensity of pain, the greater the association OR 5.2 (95% CI 4.1-6.7) for depressive symptoms and OR 13.9 for suspected severe depression (95% CI 8.1-23.9). CONCLUSION: The association between pain and depression is high and is related to pain intensity, being higher in people with less education and physical dependency. The high frequency of both conditions in Chilean elderly people and their serious consequences make it an urgent public health problem, aggravated as a consequence of the prolonged isolation due to the COVID-19 pandemic.
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Depressão , Dor , Humanos , Chile/epidemiologia , Feminino , Masculino , Idoso , Estudos Transversais , Pessoa de Meia-Idade , Depressão/epidemiologia , Dor/epidemiologia , Dor/psicologia , Idoso de 80 Anos ou mais , Medição da Dor , Fatores de Risco , Fatores Socioeconômicos , Índice de Gravidade de Doença , Fatores Sociodemográficos , Modelos LogísticosRESUMO
Introduction: Intimate partner violence (IPV) is a human rights violation that often involves violence against women, which appears to be the most prevalent type of abuse. IPV is a global public health issue with major human rights violations. Pregnant women's IPV needs special consideration because of the possible harm that might happen to mothers and their fetuses. The enormous global public health issue of IPV affects physical, mental, and sexual transgressions. Even though there were studies conducted on IPV among women, few studies were conducted among pregnant women in sub-Saharan African countries. Therefore, this study revealed IPV and associated factors among pregnant women from the recent Demographic and Health Survey (DHS) in sub-Saharan African countries. Methods: Multilevel logistic regression analysis used data from the recent sub-Saharan African countries DHS was carried out using this secondary data. For this study, pregnant women between the ages of 15 and 49 were included; the total sample size was 17,672. Multilevel logistic regression models were calibrated to determine the associated factors at the individual and community level with IPV, with a 95% CI and AOR. Results: The prevalence of IPV among pregnant women in 23 sub-Saharan African countries was 41.94%, with a 95% CI of 40.82 to 43.06%. Poorer and poorest [AOR = 1.92; 95% CI: (1.01, 3.67)] and [AOR = 2.01; 95% CI:(1.02, 3.92)], partner alcohol drink [AOR = 3.37;95% CI:(2.21, 5.14)], and no partner education [AOR = 2.01;95% CI:(1.12, 3.63)] were statistically associated factors with IPV among pregnant women. Conclusion: The prevalence of IPV among pregnant women in sub-Saharan African countries was high (41.94%). Low economic status, partner drinking alcohol, and partner no education were the associated factors of IPV. This finding provides clues for policymakers and other organizations concerned about women.
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Inquéritos Epidemiológicos , Análise Multinível , Gestantes , Humanos , Feminino , África Subsaariana/epidemiologia , Adulto , Gravidez , Adolescente , Gestantes/psicologia , Prevalência , Adulto Jovem , Pessoa de Meia-Idade , Violência por Parceiro Íntimo/estatística & dados numéricos , Fatores de Risco , Modelos Logísticos , Violência Doméstica/estatística & dados numéricos , Fatores SocioeconômicosRESUMO
MOTIVATION: The association between weather conditions and stroke incidence has been a subject of interest for several years, yet the findings from various studies remain inconsistent. Additionally, predictive modelling in this context has been infrequent. This study explores the relationship of extremely high ischaemic stroke incidence and meteorological factors within the Slovak population. Furthermore, it aims to construct forecasting models of extremely high number of strokes. METHODS: Over a five-year period, a total of 52,036 cases of ischemic stroke were documented. Days exhibiting a notable surge in ischemic stroke occurrences (surpassing the 90th percentile of historical records) were identified as extreme cases. These cases were then scrutinized alongside daily meteorological parameters spanning from 2015 to 2019. To create forecasts for the occurrence of these extreme cases one day in advance, three distinct methods were employed: Logistic regression, Random Forest for Time Series, and Croston's method. RESULTS: For each of the analyzed stroke centers, the cross-correlations between instances of extremely high stroke numbers and meteorological factors yielded negligible results. Predictive performance achieved by forecasts generated through multivariate logistic regression and Random Forest for time series analysis, which incorporated meteorological data, was on par with that of Croston's method. Notably, Croston's method relies solely on the stroke time series data. All three forecasting methods exhibited limited predictive accuracy. CONCLUSIONS: The task of predicting days characterized by an exceptionally high number of strokes proved to be challenging across all three explored methods. The inclusion of meteorological parameters did not yield substantive improvements in forecasting accuracy.
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Previsões , AVC Isquêmico , Tempo (Meteorologia) , Humanos , Incidência , Previsões/métodos , AVC Isquêmico/epidemiologia , Masculino , Eslováquia/epidemiologia , Feminino , Conceitos Meteorológicos , Modelos Logísticos , IdosoRESUMO
INTRODUCTION: In the current study, we screened for highly sensitive and specific predictors of premature birth, with the aim to establish an sPTB prediction model that is suitable for women in China and easy to operate and popularize, as well as to establish a sPTB prediction scoring system for early, intuitive, and effective assessment of premature birth risk. METHODS: A total of 685 pregnant women with a single pregnancy during the second trimester (16-26 weeks) were divided into premature and non-premature delivery groups based on their delivery outcomes. Clinical and ultrasound information were collected for both groups, and risk factors that could lead to sPTB in pregnant women were screened and analyzed using a cut-off value. A nomogram was developed to establish a prediction model and scoring system for sPTB. In addition, 119 pregnant women who met the inclusion criteria for the modeling cohort were included in the external validation of the model. The accuracy and consistency of the model were evaluated using the area under the receiver operating characteristic (ROC) and C-calibration curves. RESULTS: Multivariate logistic regression analysis showed a significant correlation (P < 0.05) between the number of miscarriages in pregnant women, history of miscarriages in the first week of pregnancy, history of preterm birth, CL of pregnant women, open and continuous cervical opening, and the occurrence of sPTB in pregnant women. We drew a nomogram column chart based on the six risk factors mentioned above, obtained a predictive model for sPTB, and established a scoring system to divide premature birth into three risk groups: low, medium, and high. After validating the model, the Hosmer Lemeshow test indicated a good fit (p = 0.997). The modeling queue C calibration curve was close to diagonal (C index = 0.856), confirming that the queue C calibration curve was also close to diagonal (C index = 0.854). The AUCs of the modeling and validation queues were 0.850 and 0.881, respectively. CONCLUSION: Our predictive model is consistent with China's national conditions, as well as being intuitive and easy to operate, with wide applicability, thus representing a helpful tool to assist with early detection of sPTB in clinical practice, as well as for clinical management in assessing low, medium, and high risks of sPTB.
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Nomogramas , Nascimento Prematuro , Humanos , Feminino , Gravidez , Nascimento Prematuro/epidemiologia , Adulto , China/epidemiologia , Fatores de Risco , Medição de Risco/métodos , Segundo Trimestre da Gravidez , Curva ROC , Valor Preditivo dos Testes , Modelos Logísticos , Ultrassonografia Pré-NatalRESUMO
Automated screening for vertebral fractures could improve outcomes. We achieved an AUC-ROC = 0.968 for the prediction of moderate to severe fracture using a GAM with age and three maximal vertebral body scores of fracture from a convolutional neural network. Maximal fracture scores resulted in a performant model for subject-level fracture prediction. Combining individual deep learning vertebral body fracture scores and demographic covariates for subject-level classification of osteoporotic fracture achieved excellent performance (AUC-ROC of 0.968) on a large dataset of radiographs with basic demographic data. PURPOSE: Osteoporotic vertebral fractures are common and morbid. Automated opportunistic screening for incidental vertebral fractures from radiographs, the highest volume imaging modality, could improve osteoporosis detection and management. We consider how to form patient-level fracture predictions and summarization to guide management, using our previously developed vertebral fracture classifier on segmented radiographs from a prospective cohort study of US men (MrOS). We compare the performance of logistic regression (LR) and generalized additive models (GAM) with combinations of individual vertebral scores and basic demographic covariates. METHODS: Subject-level LR and GAM models were created retrospectively using all fracture predictions or summary variables such as order statistics, adjacent vertebral interactions, and demographic covariates (age, race/ethnicity). The classifier outputs for 8663 vertebrae from 1176 thoracic and lumbar radiographs in 669 subjects were divided by subject to perform stratified fivefold cross-validation. Models were assessed using multiple metrics, including receiver operating characteristic (ROC) and precision-recall (PR) curves. RESULTS: The best model (AUC-ROC = 0.968) was a GAM using the top three maximum vertebral fracture scores and age. Using top-ranked scores only, rather than all vertebral scores, improved performance for both model classes. Adding age, but not ethnicity, to the GAMs improved performance slightly. CONCLUSION: Maximal vertebral fracture scores resulted in the highest-performing models. While combining multiple vertebral body predictions risks decreasing specificity, our results demonstrate that subject-level models maintain good predictive performance. Thresholding strategies can be used to control sensitivity and specificity as clinically appropriate.
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Aprendizado Profundo , Fraturas por Osteoporose , Fraturas da Coluna Vertebral , Humanos , Fraturas por Osteoporose/diagnóstico por imagem , Fraturas por Osteoporose/epidemiologia , Fraturas da Coluna Vertebral/diagnóstico por imagem , Fraturas da Coluna Vertebral/epidemiologia , Masculino , Idoso , Pessoa de Meia-Idade , Estudos Retrospectivos , Idoso de 80 Anos ou mais , Vértebras Lombares/diagnóstico por imagem , Vértebras Lombares/lesões , Modelos Logísticos , Curva ROCRESUMO
BACKGROUND: In adult females, mycoplasma infection is common and challenging to diagnose. This study aimed to use retrospective laboratory data to construct a nomogram for predicting the mycoplasma infection of individuals with probable urogenital tract mycoplasma infection. METHODS: A total of 2,859 patients with suspected urogenital tract mycoplasma infection were retrospectively enrolled in this study. Demographics and routine examinations of leucorrhea were used to develop a nomogram for predicting mycoplasma infection. The least absolute shrinkage and selection operator (LASSO) method was applied to filter variables and select predictors, and multivariable logistic regression was used to construct a nomogram. The discriminatory ability of the model was determined by calculating the area under the curve (AUC). The performance and clinical utility of the nomogram were generated by using Harrell's concordance index, calibration curve, and decision curve analysis (DCA). RESULTS: By using the LASSO regression method, seven variables (age, white blood cell, epithetical cell, cleanliness, candidiasis vaginalis, sialidases, and leukocyte esterase) were chosen, and a nomogram was constructed using these variables. The prediction nomogram (0.676, 95% CI: 0.611 - 0.744) demonstrated a satisfactory performance. The prediction model's AUC was 0.679 (95% CI: 0.660 - 0.691). Furthermore, the DCA showed a good clinical net benefit based on the mycoplasma infection nomogram. CONCLUSIONS: A nomogram was created in this study, which included seven demographic and clinical characteristics of female patients. The nomogram could be of great value for the diagnosis of mycoplasma infection.
Assuntos
Infecções por Mycoplasma , Nomogramas , Humanos , Feminino , Infecções por Mycoplasma/diagnóstico , Infecções por Mycoplasma/microbiologia , Estudos Retrospectivos , Adulto , Pessoa de Meia-Idade , Modelos Logísticos , Adulto Jovem , Valor Preditivo dos Testes , Hidrolases de Éster CarboxílicoRESUMO
Cardiovascular Disease (CVD) is currently the major challenge to people's health and the world's top cause of death. In Tanzania, deaths due to CVD account for about 13% of the total deaths caused by the non-communicable diseases. This study examined the spatio-temporal clustering of CVDs from 2010 to 2019 in Tanzania for retrospective spatio-temporal analysis using the Bernoulli probability model on data sampled from four selected hospitals. Spatial scan statistics was performed to identify CVD clusters and the effect of covariates on the CVD incidences was examined using multiple logistic regression. It was found that there was a comparatively high risk of CVD during 2011-2015 followed by a decline during 2015-2019. The spatio-temporal analysis detected two high-risk disease clusters in the coastal and lake zones from 2012 to 2016 (p<0.001), with similar results produced by purely spatial analysis. The multiple logistic model showed that sex, age, blood pressure, body mass index (BMI), alcohol intake and smoking were significant predictors of CVD incidence.
Assuntos
Doenças Cardiovasculares , Análise Espaço-Temporal , Humanos , Tanzânia/epidemiologia , Doenças Cardiovasculares/epidemiologia , Masculino , Feminino , Pessoa de Meia-Idade , Estudos Retrospectivos , Incidência , Adulto , Fatores de Risco , Idoso , Modelos Logísticos , Índice de Massa Corporal , Fatores Sexuais , Fumar/epidemiologiaRESUMO
This study aimed to develop and validate a clinical model for predicting the risk of nonalcoholic fatty liver disease (NAFLD) by using data from a cross-sectional study. This investigation utilized data from the Dryad database and employed multivariable logistic regression analysis, restricted cubic spline, and nomogram analysis to achieve comprehensive insights. The discrimination and calibration of the nomogram were evaluated using the receiver operating characteristic curve and calibration plot. A total of 1072 patients were included in the study, including 456 with non-NAFLD and 616 with NAFLD. Significant differences were observed in terms of sex, body mass index (BMI), tobacco, hypertension, diabetes, alanine aminotransferase (ALT), aspartate aminotransferase (AST), ALT/AST ratio, uric acid (UA), fasting blood glucose (FBG), triglyceride (TG), high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, systolic blood pressure, and diastolic blood pressure (Pâ <â .05 for all comparisons). Multivariable logistic regression analysis indicated that sex, BMI, diabetes, ALT/AST ratio, UA, FBG, and TG were associated with an increased risk of NAFLD. Restricted cubic spline indicated a nonlinear relationship between the risk of NAFLD and variables including ALT/AST ratio, FPG, TG, and UA (P for nonlinearityâ <â .01). The variables in the nomogram included BMI, diabetes, ALT/AST ratio, UA, FBG, and TG. The value of area under the curve was 0.790, indicating that the nomogram prediction model exhibited significant discriminatory accuracy. A reliable clinical model for predicting the risk of NAFLD was developed using readily available clinical data. The model can assist clinicians in identifying individuals with an increased risk of NAFLD, enabling early interventions for preventing and managing this prevalent liver disease.
Assuntos
Nomogramas , Hepatopatia Gordurosa não Alcoólica , Humanos , Hepatopatia Gordurosa não Alcoólica/epidemiologia , Hepatopatia Gordurosa não Alcoólica/sangue , Masculino , Feminino , Estudos Transversais , Pessoa de Meia-Idade , Fatores de Risco , Medição de Risco/métodos , Adulto , Curva ROC , Modelos Logísticos , Índice de Massa Corporal , Alanina Transaminase/sangue , Aspartato Aminotransferases/sangue , IdosoRESUMO
Purpose: In recent times, growing uncertainty has emerged regarding the effectiveness of standard pressure ulcer (PU) risk assessment tools, which are suspected to be no better than clinical judgment, especially in the frail and comorbid elderly population. This study aimed to identify the primary clinical predictive variables for PU development and severity in hospitalized older adults, utilizing a multidimensional frailty assessment, and compare them with the Braden scale. Patients and methods: The population consisted of 316 patients, admitted to the Geriatric Unit and Transitional Care of San Bartolomeo Hospital in Sarzana (Italy) during the period 21/02/22-01/07/22. The collected information included both anamnestic and laboratory data. A comprehensive geriatric assessment was performed, including also anthropometric and physical performance measurements. Multivariate logistic analysis was used, both in a binary classification test and in the subsequent ordinal classification test of severity levels. The final performance of the model was assessed by ROC curve estimation and AUC comparison with the Braden scale. Results: Within the population, 152 subjects (48%) developed PU at different levels of severity. The results showed that age, Braden scale (subscales of mobility and friction/shear), Barthel scale, Mini Nutritional Assessment, hemoglobin, and albumin are predictors associated with the development of PU (AUC 85%). The result is an improvement over the use of the Braden scale alone (AUC 75%). Regarding the identification of predictive factors for PU severity, 4AT also emerges as potentially relevant. Conclusion: Assessing the subject's nutritional status, physical performance, and functional autonomies enables the effective integration of the Braden scale in identifying patients most susceptible to developing PU. Our findings support the integration of a comprehensive set of methodologically robust frailty determinants into traditional risk assessment tools. This integration reflects the mutual interplay between patients' frailty, skin frailty, and PU development in very old hospitalized patients.
Assuntos
Idoso Fragilizado , Avaliação Geriátrica , Hospitalização , Úlcera por Pressão , Índice de Gravidade de Doença , Humanos , Úlcera por Pressão/epidemiologia , Masculino , Feminino , Avaliação Geriátrica/métodos , Estudos Retrospectivos , Idoso de 80 Anos ou mais , Itália , Medição de Risco , Hospitalização/estatística & dados numéricos , Modelos Logísticos , Fatores de Risco , Curva ROC , Avaliação Nutricional , Análise Multivariada , IdosoRESUMO
Background: Major depressive disorder (MDD) is a prevalent mental disorder globally. Increasing evidence suggests that Environmental Metal (EM) play a crucial role in MDD. Therefore, this study investigated the roles of barium (Ba), cesium (Cs), nickel (Ni), manganese (Mn), lead (Pb), mercury (Hg), cadmium (Cd), and tin (Sn) in the etiology of MDD. Methods: The study included 72 MDD patients and 75 healthy controls (HCs) from the Second People's Hospital of Zhumadian, China. Inductively coupled plasma mass spectrometer (ICP-MS) measured the metal levels in serum and urine samples from both groups. Results: Significant differences in serum and urine levels of EMs were observed between MDD patients and HCs. After adjusting for age, gender, and BMI, logistic regression and quantile regression models revealed significant associations between EMs and MDD. In serum samples, higher Sn levels (OR = 1.22, p = 0.044) increased MDD risk, whereas higher Cs levels (OR = 0.02, p < 0.001), Cd (OR = 0.06, p = 0.047), and Mn (OR = 0.54, p = 0.016) decreased MDD risk. In urine samples, higher Ba levels (OR = 0.94, p = 0.015), Ni (OR = 0.87, p = 0.0024), Sn (OR = 1.62, p < 0.001), and Mn (OR = 0.77, p = 0.037) were significantly associated with MDD. Sn significantly positively predicted HAMD-24 scores at the 0.50 and 0.75 quantiles (ß = 0.96, p = 0.018; ß = 1.25, p = 0.008) as did Pb (ß = 5.15, p = 0.001; ß = 4.19, p = 0.004). Ba positively predicted depressive symptoms across all quantiles (all p < 0.05). Hg positively predicted HAMD-24 scores at the 0.50 quantile (ß = 9.20, p = 0.050). Conclusion: These findings underscore EMs' importance in depression, aiding in targeted interventions for varying degrees of depression and necessitating future studies to clarify causality and mechanisms.
Assuntos
Transtorno Depressivo Maior , Humanos , Transtorno Depressivo Maior/sangue , Transtorno Depressivo Maior/urina , Feminino , Masculino , Adulto , China , Modelos Logísticos , Pessoa de Meia-Idade , Estudos de Casos e Controles , Metais/sangue , Metais/urina , Exposição Ambiental/efeitos adversos , Poluentes Ambientais/sangue , Poluentes Ambientais/urinaRESUMO
BACKGROUND: For youths, abnormalities in ambulatory blood pressure (ABP) patterns are known to be associated with increased cardiovascular disease risk and potential target organ damage. Body composition, including indicators such as lean mass index (LMI), fat mass index (FMI), and visceral fat level (VFL), plays a significant role in blood pressure (BP) regulation. However, little is known about the association between these body composition indicators and ABP. Therefore, the present study examined the association between these body composition indicators and BP among Chinese youths. METHODS: A total of 477 college students aged 17 to 28 years old (mean ± Standard deviation = 18.96 ± 1.21) from a university in Changsha, Hunan Province, China, were included in this study. Body composition indicators were measured with a bioelectrical impedance body composition analyzer, and 24-hour ambulatory blood pressure monitoring (ABPM) was conducted. Multivariable logistic regression was performed to assess the relationship between body composition indicators and abnormal ABP. RESULTS: The prevalence of abnormal BP, including 24-hour BP, daytime BP, nighttime BP, and clinic BP, were 4.8%, 4.2%, 8.6%, and 10.9%, respectively. After adjusting for potential covariates, LMI [abnormal 24-hour BP (OR = 1.85, 95%CI:1.31, 2.62), abnormal daytime BP (OR = 1.76, 95%CI:1.21, 2.58), abnormal nighttime BP (OR = 1.64, 95%CI:1.25, 2.14), abnormal clinic BP (OR = 1.84, 95%CI:1.38, 2.45)], FMI [abnormal 24-hour BP (OR = 1.20, 95%CI:1.02, 1.41), abnormal daytime BP (OR = 1.30, 95%CI:1.07, 1.57), abnormal nighttime BP (OR = 1.24, 95%CI:1.10, 1.39), abnormal clinic BP (OR = 1.42, 95%CI:1.22, 1.65)], and VFL [abnormal 24-hour BP (OR = 1.22, 95%CI:1.06, 1.39), abnormal daytime BP (OR = 1.29, 95%CI:1.10, 1.51), abnormal nighttime BP (OR = 1.24, 95%CI:1.12, 1.39), abnormal clinic BP (OR = 1.38, 95%CI:1.21, 1.57)] are positively linked to abnormal BP. Additionally, there were significant sex differences in the association between body composition and abnormal BP. CONCLUSIONS: Our findings suggested maintaining an individual's appropriate muscle mass and fat mass and focusing on the different relations of males' and females' body composition is crucial for the achievement of appropriate BP profiles.