scholarly journals Predictive Biomarkers for Postmyocardial Infarction Heart Failure Using Machine Learning: A Secondary Analysis of a Cohort Study

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Feng Li ◽  
Jin-Yu Sun ◽  
Li-Da Wu ◽  
Qiang Qu ◽  
Zhen-Ye Zhang ◽  
...  
Keyword(s):  
Heart Failure ◽  
Cohort Study ◽  
Predictive Value ◽  
Transcriptional Profiling ◽  
Secondary Analysis ◽  
Area Under The Curve ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Postmyocardial Infarction

Background. There are few biomarkers with an excellent predictive value for postacute myocardial infarction (MI) patients who developed heart failure (HF). This study aimed to screen candidate biomarkers to predict post-MI HF. Methods. This is a secondary analysis of a single-center cohort study including nine post-MI HF patients and eight post-MI patients who remained HF-free over a 6-month follow-up. Transcriptional profiling was analyzed using the whole blood samples collected at admission, discharge, and 1-month follow-up. We screened differentially expressed genes and identified key modules using weighted gene coexpression network analysis. We confirmed the candidate biomarkers using the developed external datasets on post-MI HF. The receiver operating characteristic curves were created to evaluate the predictive value of these candidate biomarkers. Results. A total of 6,778, 1,136, and 1,974 genes (dataset 1) were differently expressed at admission, discharge, and 1-month follow-up, respectively. The white and royal blue modules were most significantly correlated with post-MI HF (dataset 2). After overlapping dataset 1, dataset 2, and external datasets (dataset 3), we identified five candidate biomarkers, including FCGR2A, GSDMB, MIR330, MED1, and SQSTM1. When GSDMB and SQSTM1 were combined, the area under the curve achieved 1.00, 0.85, and 0.89 in admission, discharge, and 1-month follow-up, respectively. Conclusions. This study demonstrates that FCGR2A, GSDMB, MIR330, MED1, and SQSTM1 are the candidate predictive biomarker genes for post-MI HF, and the combination of GSDMB and SQSTM1 has a high predictive value.

scholarly journals Development of caesarean section prediction models: secondary analysis of a prospective cohort study in two sub-Saharan African countries

2019 ◽  
Vol 16 (1) ◽  
Author(s):  
Hayala C. C. de Souza ◽  
Gleici S. C. Perdoná ◽  
Alessandra C. Marcolin ◽  
Lawal O. Oyeneyin ◽  
Olufemi T. Oladapo ◽  
...  
Keyword(s):  
Cohort Study ◽  
Caesarean Section ◽  
Prospective Cohort Study ◽  
Predictive Value ◽  
Prospective Cohort ◽  
Secondary Analysis ◽  
Area Under The Curve ◽  
World Health ◽  
African Countries ◽  
Sub Saharan

Abstract Background Caesarean section is recommended in situations in which vaginal birth presents a greater likelihood of adverse maternal or perinatal outcomes than normal. However, it is associated with a higher risk of complications, especially when performed without a clear medical indication. Since labour attendants have no standardised clinical method to assist in this decision, statistical tools developed based on multiple labour variables may be an alternative. The objective of this paper was to develop and evaluate the accuracy of models for caesarean section prediction using maternal and foetal characteristics collected at admission and through labour. Method This is a secondary analysis of the World Health Organization’s Better Outcomes in Labour Difficulty prospective cohort study in two sub-Saharan African countries. Data were collected from women admitted for labour and childbirth in 13 hospitals in Nigeria as well as Uganda between 2014 and 2015. We applied logistic regression to develop different models to predict caesarean section, based on the time when intrapartum assessment was made. To evaluate discriminatory capacity of the various models, we calculated: area under the curve, diagnostic accuracy, positive predictive value, negative predictive value, sensitivity and specificity. Results A total of 8957 pregnant women with 12.67% of caesarean births were used for model development. The model based on labour admission characteristics showed an area under the curve of 78.70%, sensitivity of 63.20%, specificity of 78.68% and accuracy of 76.62%. On the other hand, the models that applied intrapartum assessments performed better, with an area under the curve of 93.66%, sensitivity of 80.12%, specificity of 89.26% and accuracy of 88.03%. Conclusion It is possible to predict the likelihood of intrapartum caesarean section with high accuracy based on labour characteristics and events. However, the accuracy of this prediction is considerably higher when based on information obtained throughout the course of labour.

scholarly journals New screening approach to detecting congenital syphilis in China: a retrospective cohort study

2020 ◽  
pp. archdischild-2020-320549
Author(s):  
Fang Hu ◽  
Shuai-Jun Guo ◽  
Jian-Jun Lu ◽  
Ning-Xuan Hua ◽  
Yan-Yan Song ◽  
...  
Keyword(s):  
Predictive Value ◽  
Congenital Syphilis ◽  
Area Under The Curve ◽  
Diagnostic Tools ◽  
Operating Characteristics ◽  
Loss To Follow Up ◽  
Sensitivity Specificity ◽  
Mother To Child ◽  
Rule Out

BackgroundDiagnosis of congenital syphilis (CS) is not straightforward and can be challenging. This study aimed to evaluate the validity of an algorithm using timing of maternal antisyphilis treatment and titres of non-treponemal antibody as predictors of CS.MethodsConfirmed CS cases and those where CS was excluded were obtained from the Guangzhou Prevention of Mother-to-Child Transmission of syphilis programme between 2011 and 2019. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) using receiver operating characteristics (ROC) in two situations: (1) receiving antisyphilis treatment or no-treatment during pregnancy and (2) initiating treatment before 28 gestational weeks (GWs), initiating after 28 GWs or receiving no treatment for syphilis seropositive women.ResultsAmong 1558 syphilis-exposed children, 39 had confirmed CS. Area under the curve, sensitivity and specificity of maternal non-treponemal titres before treatment and treatment during pregnancy were 0.80, 76.9%, 78.7% and 0.79, 69.2%, 88.7%, respectively, for children with CS. For the algorithm, ROC results showed that PPV and NPV for predicting CS were 37.3% and 96.4% (non-treponemal titres cut-off value 1:8 and no antisyphilis treatment), 9.4% and 100% (non-treponemal titres cut-off value 1:16 and treatment after 28 GWs), 4.2% and 99.5% (non-treponemal titres cut-off value 1:32 and treatment before 28 GWs), respectively.ConclusionsAn algorithm using maternal non-treponemal titres and timing of treatment during pregnancy could be an effective strategy to diagnose or rule out CS, especially when the rate of loss to follow-up is high or there are no straightforward diagnostic tools.

scholarly journals Do patients have worse outcomes in heart failure than in cancer? A primary care-based cohort study with 10-year follow-up in Scotland

2017 ◽  
Vol 19 (9) ◽  
pp. 1095-1104 ◽  
Author(s):  
Mamas A. Mamas ◽  
Matthew Sperrin ◽  
Margaret C. Watson ◽  
Alasdair Coutts ◽  
Katie Wilde ◽  
...  
Keyword(s):  
Heart Failure ◽  
Primary Care ◽  
Cohort Study

Serum procalcitonin levels predict disseminated intravascular coagulation in patients with sepsis shock: A retrospective cohort study

2020 ◽  
Author(s):  
Guang Fu ◽  
Xi-si He ◽  
Hao-li Li ◽  
Hai-chao Zhan ◽  
Jun-fu Lu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Septic Shock ◽  
Cohort Study ◽  
Disseminated Intravascular Coagulation ◽  
Area Under The Curve ◽  
Multivariable Logistic Regression Model ◽  
Intravascular Coagulation ◽  
The Relationship ◽  
Conventional Risk Factors

Abstract Background Complication of disseminated intravascular coagulation (DIC) is a determinant of the prognosis in patients with sepsis shock. Procalcitonin (PCT) has been advocated as a marker of bacterial sepsis. The purpose of this study was to evaluate the relationship between serum PCT levels and DIC with sepsis shock Methods A cohort study was designed which included patients that admitted in intensive care unit (ICU) between January 1, 2015 and December 31, 2018 and the follow-up to discharge. 164 septic shock patients were divided into DIC and non-DIC groups according to international society of thrombosis and homeostasis (ISTH). PCT was measured at the admission to ICU, and all the participants received routine biochemical coagulation test subsequently. Results PCT levels were considerably higher in septic shock patients who developed DIC than those who did not (54.6[13.6–200]vs12.6[2.4–53.3]ng/ml), respectively, P < 0.001). Multivariable logistic regression model revealed that PCT level was significantly associated with risk of DIC independent of conventional risk factors. In addition, curve fitting showed a linear relationship between PCT and DIC score. The Receiver Operating characteristic(ROC) curve suggested that the optimal cut-off point for PCT to predicting DIC induced by septic shock was 42.0 ng/ml, and the area under the curve (AUC) was 0.701(95% CI [0.619–0.784], P < 0.001). More importantly, incorporating PCT with other risk factors into the prediction model significantly increased the AUC for prediction of DIC induced by sepsis shock (0.801vs 0.706; P = 0.012). Conclusions Our study suggests that PCT levels on admission is significantly and independently associated with DIC development subsequently with septic shock, combining PCT levels with other risk factors could significantly improve the prediction of DIC induced by sepsis shock.

scholarly journals Circulating miRNAs as a Predictive Biomarker of the Progression from Prediabetes to Diabetes: Outcomes of a 5-Year Prospective Observational Study

2020 ◽  
Vol 9 (7) ◽  
pp. 2184 ◽  
Author(s):  
Iwona Sidorkiewicz ◽  
Magdalena Niemira ◽  
Katarzyna Maliszewska ◽  
Anna Erol ◽  
Agnieszka Bielska ◽  
...  
Keyword(s):  
Pathway Analysis ◽  
Mirna Target ◽  
Target Genes ◽  
Quantitative Polymerase Chain Reaction ◽  
Area Under The Curve ◽  
Predictive Biomarkers ◽  
Predictive Biomarker ◽  
Circulating Mirnas ◽  
Serum Samples ◽  
Roc Curve Analysis

Due to a global increase in the prevalence of type 2 diabetes mellitus (T2DM), there is an urgent need for early identification of prediabetes, as these people have the highest risk of developing diabetes. Circulating miRNAs have shown potential as progression biomarkers in other diseases. This study aimed to conduct a baseline comparison of serum-circulating miRNAs in prediabetic individuals, with the distinction between those who later progressed to T2DM and those who did not. The expression levels of 798 miRNAs using NanoString technology were examined. Spearman correlation, receiver operating characteristic (ROC) curve analysis, and logistic regression modeling were performed. Gene ontology (GO) and canonical pathway analysis were used to explore the biological functions of the miRNA target genes. The study revealed that three miRNAs were upregulated in the serum samples of patients who later progressed to T2DM. Pathway analysis showed that the miRNA target genes were mainly significantly enriched in neuronal NO synthase (nNOS) signaling in neurons, amyloid processing, and hepatic cholestasis. ROC analysis demonstrated that miR-491-5p, miR-1307-3p, and miR-298 can be introduced as a diagnostic tool for the prediction of T2DM (area under the curve (AUC) = 94.0%, 88.0%, and 84.0%, respectively). Validation by real-time quantitative polymerase chain reaction (qRT-PCR) confirmed our findings. The results suggest that circulating miRNAs can potentially be used as predictive biomarkers of T2DM in prediabetic patients.

scholarly journals Malondialdehyde and Uric Acid as Predictors of Adverse Outcome in Patients with Chronic Heart Failure

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Ewa Romuk ◽  
Celina Wojciechowska ◽  
Wojciech Jacheć ◽  
Aleksandra Zemła-Woszek ◽  
Alina Momot ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Heart Failure ◽  
Uric Acid ◽  
Chronic Heart Failure ◽  
Predictive Biomarkers ◽  
Cox Regression Analysis ◽  
Risk Of Death ◽  
Increased Risk ◽  
Baseline Levels

In chronic heart failure (HF), some parameters of oxidative stress are correlated with disease severity. The aim of this study was to evaluate the importance of oxidative stress biomarkers in prognostic risk stratification (death and combined endpoint: heart transplantation or death). In 774 patients, aged 48-59 years, with chronic HF with reduced ejection fraction (median: 24.0 (20-29)%), parameters such as total antioxidant capacity, total oxidant status, oxidative stress index, and concentration of uric acid (UA), bilirubin, protein sulfhydryl groups (PSH), and malondialdehyde (MDA) were measured. The parameters were assessed as predictive biomarkers of mortality and combined endpoint in a 1-year follow-up. The multivariate Cox regression analysis was adjusted for other important clinical and laboratory prognostic markers. Among all the oxidative stress markers examined in multivariate analysis, only MDA and UA were found to be independent predictors of death and combined endpoint. Higher serum MDA concentration increased the risk of death by 103.0% (HR=2.103; 95% CI (1.330-3.325)) and of combined endpoint occurrence by 100% (HR=2.000; 95% CI (1.366-2.928)) per μmol/L. Baseline levels of MDA in the 4th quartile were associated with an increased risk of death with a relative risk (RR) of 3.64 (95% CI (1.917 to 6.926), p<0.001) and RR of 2.71 (95% CI (1.551 to 4.739), p<0.001) for the occurrence of combined endpoint as compared to levels of MDA in the 1st quartile. Higher serum UA concentration increased the risk of death by 2.1% (HR=1.021; 95% CI (1.005-1.038), p<0.001) and increased combined endpoint occurrence by 1.4% (HR=1.014; 95% CI (1.005-1.028), p<0.001), for every 10 μmol/L. Baseline levels of UA in the 4th quartile were associated with an increased risk for death with a RR of 3.21 (95% CI (1.734 to 5.931)) and RR of 2.73 (95% CI (1.560 to 4.766)) for the occurrence of combined endpoint as compared to the levels of UA in the 1st quartile. In patients with chronic HF, increased MDA and UA concentrations were independently related to poor prognosis in a 1-year follow-up.

scholarly journals Sleep Disturbance and the Risk of Cognitive Decline or Clinical Conversion in the ADNI Cohort

2018 ◽  
Vol 45 (3-4) ◽  
pp. 232-242 ◽  
Author(s):  
Adam P. Mecca ◽  
Hannah R. Michalak ◽  
Julia W. McDonald ◽  
Emily C. Kemp ◽  
Erika A. Pugh ◽  
...  
Keyword(s):  
Cohort Study ◽  
Cognitive Impairment ◽  
Cognitive Decline ◽  
Sleep Disturbance ◽  
Secondary Analysis ◽  
Study Results ◽  
Global Cognition ◽  
The Relationship ◽  
Normal Cognition

Background: We investigated the relationship between sleep disturbance and cognitive decline or clinical conversion in individuals with normal cognition (CN), as well as those with mild cognitive impairment (MCI) and dementia due to Alzheimer disease (AD-dementia). Methods: Secondary analysis of 1,629 adults between 48 and 91 years of age with up to 24 months of follow-up from the ADNI (Alzheimer’s Disease Neuroimaging Initiative), a longitudinal cohort study. Results: Sleep disturbance was not associated with decline in memory, executive function, or global cognition. The presence of sleep disturbance did not significantly increase the risk of diagnostic conversion in CN, early MCI, or late MCI participants. Conclusion: This study investigated the effect of sleep disturbance on cognitive decline using several outcomes and does not support the hypothesis that sleep disturbance predicts subsequent cognitive decline.

P6472Novel cardiac imaging prognostic markers of clinical outcome in patients with bicuspid aortic valve and chronic aortic regurgitation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
R Kockova ◽  
H Linkova ◽  
Z Hlubocka ◽  
A Praveckova ◽  
A Polednova ◽  
...  
Keyword(s):  
Heart Failure ◽  
Surgical Treatment ◽  
Disease Progression ◽  
Predictive Value ◽  
Area Under The Curve ◽  
Early Disease ◽  
Regurgitant Fraction ◽  
Cutoff Value ◽  
Vena Contracta ◽  
Chronic Aortic Regurgitation

Abstract Background Patients with chronic aortic regurgitation (AR) can have a substantial myocardial damage despite being asymptomatic. Early surgical strategy might be beneficial. Bicuspid aortic valve (BAV) is a congenital heart disease present in almost 30% of these patients. Purpose Identify novel imaging predictors of early disease progression. Methods Prospective three-centre study of patients with chronic AR of at least moderate to severe (3+) grade and BAV morphology. Patients without currently recognised indication for surgical treatment were enrolled. Baseline examination included echocardiography (ECHO) with 3-dimensional (3D) vena contracta area and magnetic resonance (MR) with regurgitant fraction measured from flow sequence. All imaging studies were analysed in CoreLab. The primary endpoint was defined as a combination of cardiovascular death, surgical treatment or hospitalization for heart failure. Results A total of 83 patients with BAV and at least 3+ AR were enrolled during 2015–2018. Median follow-up was 759±455 days, primary composite endpoint occurred in 13 patients who met criteria for surgical treatment, no patient died or was hospitalized for heart failure. Baseline parameters were compared between two groups: patients with and without endpoint. Clinical and laboratory data did not differ between the two groups. Left ventricular (LV) ejection fraction was normal in all patients. LV diameters and volumes were significantly larger in patients with primary endpoint. This was most pronounced in MR measured indexed volumes in end-diastole and end-systole, P=0.003 and P=0.003. Non-invasive markers of diffuse myocardial fibrosis (native T1 relaxation time and global longitudinal strain, P=0.614 and P=0.137 respectively) were not different. Novel markers of AR severity were significantly increased in surgically treated patients: 3D vena contracta 0.26±0.10 cm2 versus 0.38±0.11 cm2 (P<0.001), MR regurgitant fraction 33.9±15.4 versus 50.2±12.2% (P=0.001). Both 3D vena contracta with cutoff value ≥0.4 cm2 (sensitivity=85%, specificity=84%, area under the curve=0.85) and MR regurgitant fraction with cutoff value ≥34% (sensitivity=94%, specificity=58%, area under the curve=0.76) showed high accuracy to identify patients who require early surgical intervention. Adding 3D vena contracta and MR regurgitant fraction to indexed LV end-systolic volumetric parameters significantly increases the predictive value for early disease progression with p=0.001 and p=0.006 (Likelihood-ratio test). 3D vena contracta predictive value Conclusions Novel imaging parameters of AR severity such as 3D vena contracta and MR derived regurgitant fraction predict early disease progression in patients with BAV and at least 3+ chronic AR. These values significantly increase the predictive value of traditional parameters based on LV size measures.

scholarly journals Validation of the PredAHT-2 prediction tool for abusive head trauma

2020 ◽  
Vol 37 (3) ◽  
pp. 119-126 ◽  
Author(s):  
Helena Pfeiffer ◽  
Laura Elizabeth Cowley ◽  
Alison Mary Kemp ◽  
Stuart R Dalziel ◽  
Anne Smith ◽  
...  
Keyword(s):  
New Zealand ◽  
Head Trauma ◽  
Predictive Value ◽  
Head Injuries ◽  
Secondary Analysis ◽  
Area Under The Curve ◽  
Abusive Head Trauma ◽  
Long Bone ◽  
Prediction Tool ◽  
Zealand Population

ObjectiveThe validated Predicting Abusive Head Trauma (PredAHT) clinical prediction tool calculates the probability of abusive head trauma (AHT) in children <3 years of age who have sustained intracranial injuries (ICIs) identified on neuroimaging, based on combinations of six clinical features: head/neck bruising, seizures, apnoea, rib fracture, long bone fracture and retinal haemorrhages. PredAHT version 2 enables a probability calculation when information regarding any of the six features is absent. We aimed to externally validate PredAHT-2 in an Australian/New Zealand population.MethodsThis is a secondary analysis of a prospective multicentre study of paediatric head injuries conducted between April 2011 and November 2014. We extracted data on patients with possible AHT at five tertiary paediatric centres and included all children <3 years of age admitted to hospital who had sustained ICI identified on neuroimaging. We assigned cases as positive for AHT, negative for AHT or having indeterminate outcome following multidisciplinary review. The estimated probability of AHT for each case was calculated using PredAHT-2, blinded to outcome. Tool performance measures were calculated, with 95% CIs.ResultsOf 87 ICI cases, 27 (31%) were positive for AHT; 45 (52%) were negative for AHT and 15 (17%) had indeterminate outcome. Using a probability cut-off of 50%, excluding indeterminate cases, PredAHT-2 had a sensitivity of 74% (95% CI 54% t o89%) and a specificity of 87% (95% CI 73% to 95%) for AHT. Positive predictive value was 77% (95% CI 56% to 91%), negative predictive value was 85% (95% CI 71% to 94%) and the area under the curve was 0.80 (95% CI 0.68 to 0.92).ConclusionPredAHT-2 demonstrated reasonably high point sensitivity and specificity when externally validated in an Australian/New Zealand population. Performance was similar to that in the original validation study.Trial registration numberACTRN12614000463673.

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