In-birth CPR in neonates; Predictable or Unpredictable?

Abstract Background: Anticipating on in-birth Cardiopulmonary Resuscitation(CPR) in neonates is very important and complex. Timely identification and rapid CPR in neonates in the delivery room significantly affect reducing the mortality and other neurological disabilities. The aim of this study is to create a prediction system for identifying the need to in-birth CPR in neonates based on Machine Learning(ML) algorithms.Methods: In this study, 3882 neonatal medical records were retrospectively reviewed. Records were extracted from the maternal, fetal, and neonatal registry of Valiasr hospital in Tehran. A total of 60 risk factors were extracted, and five ML algorithms including J48, Naïve Bayesian, Multilayer Perceptron (MLP)، Support Vector Machine (SVM) and Random Forest were compared to predict the need to in-birth CPR in neonates. Also, using 10 feature selection algorithms, the features were ranked based on the importance, and using the ML algorithms, the important risk factors were identified. Results: In order to predict the need to in-birth CPR in neonates, SVM using all risk factors reached the accuracy of 88.43% and F-measure of 88.4%, while MLP using the 15 first important features reached the accuracy of 90.86% and the F-measure of 90.8%. The most important risk factors included gestational age, delivery type, presentation, steroid administration, macrosomia, prenatal care, infant number and rank, mother addiction, maternal chronic disease history, fetal hydrops, amniotic fluid, gestational hypertension, infertility and placental abruption. Conclusions: The proposed system can be useful in predicting the need to CPR in neonates in the delivery room.

Download Full-text

A novel method detecting the key clinic factors of portal vein system thrombosis of splenectomy & cardia devascularization patients for cirrhosis & portal hypertension

BMC Bioinformatics ◽

10.1186/s12859-019-3233-3 ◽

2019 ◽

Vol 20 (S22) ◽

Cited By ~ 1

Author(s):

Mingzhao Wang ◽

Linglong Ding ◽

Meng Xu ◽

Juanying Xie ◽

Shengli Wu ◽

...

Keyword(s):

Risk Factors ◽

Support Vector Machine ◽

Portal Hypertension ◽

Portal Vein ◽

Dimensional Space ◽

Risk Indicators ◽

Support Vector ◽

Antiplatelet Aggregation ◽

Sensitivity Specificity ◽

F Measure

Abstract Background Portal vein system thrombosis (PVST) is potentially fatal for patients if the diagnosis is not timely or the treatment is not proper. There hasn’t been any available technique to detect clinic risk factors to predict PVST after splenectomy in cirrhotic patients. The aim of this study is to detect the clinic risk factors of PVST for splenectomy and cardia devascularization patients for liver cirrhosis and portal hypertension, and build an efficient predictive model to PVST via the detected risk factors, by introducing the machine learning method. We collected 92 clinic indexes of splenectomy plus cardia devascularization patients for cirrhosis and portal hypertension, and proposed a novel algorithm named as RFA-PVST (Risk Factor Analysis for PVST) to detect clinic risk indexes of PVST, then built a SVM (support vector machine) predictive model via the detected risk factors. The accuracy, sensitivity, specificity, precision, F-measure, FPR (false positive rate), FNR (false negative rate), FDR (false discovery rate), AUC (area under ROC curve) and MCC (Matthews correlation coefficient) were adopted to value the predictive power of the detected risk factors. The proposed RFA-PVST algorithm was compared to mRMR, SVM-RFE, Relief, S-weight and LLEScore. The statistic test was done to verify the significance of our RFA-PVST. Results Anticoagulant therapy and antiplatelet aggregation therapy are the top-2 risk clinic factors to PVST, followed by D-D (D dimer), CHOL (Cholesterol) and Ca (calcium). The SVM (support vector machine) model built on the clinic indexes including anticoagulant therapy, antiplatelet aggregation therapy, RBC (Red blood cell), D-D, CHOL, Ca, TT (thrombin time) and Weight factors has got pretty good predictive capability to PVST. It has got the highest PVST predictive accuracy of 0.89, and the best sensitivity, specificity, precision, F-measure, FNR, FPR, FDR and MCC of 1, 0.75, 0.85, 0.92, 0, 0.25, 0.15 and 0.8 respectively, and the comparable good AUC value of 0.84. The statistic test results demonstrate that there is a strong significant difference between our RFA-PVST and the compared algorithms, including mRMR, SVM-RFE, Relief, S-weight and LLEScore, that is to say, the risk indicators detected by our RFA-PVST are statistically significant. Conclusions The proposed novel RFA-PVST algorithm can detect the clinic risk factors of PVST effectively and easily. Its most contribution is that it can display all the clinic factors in a 2-dimensional space with independence and discernibility as y-axis and x-axis, respectively. Those clinic indexes in top-right corner of the 2-dimensional space are detected automatically as risk indicators. The predictive SVM model is powerful with the detected clinic risk factors of PVST. Our study can help medical doctors to make proper treatments or early diagnoses to PVST patients. This study brings the new idea to the study of clinic treatment for other diseases as well.

Download Full-text

Assessment of Risk Factors for Severe Coronavirus Disease 2019 among Iranian Patients

10.32592/ircmj.2020.22.9.72 ◽

2020 ◽

Keyword(s):

Risk Factors ◽

Immune System ◽

Medical Records ◽

Critical Role ◽

Diabetic Patients ◽

Medication History ◽

Epidemiological Features ◽

Hookah Smoking ◽

And Behavior ◽

Iranian Patients

Background: The outbreak of Coronavirus Disease 2019 (COVID-19) has led to a major concern for those who are more vulnerable to infections. Objectives: This study aimed to evaluate the most important risk factors for severe COVID-19 pneumonia. Methods: This retrospective study included information on clinical and epidemiological features of 105 patients with severe COVID-19 pneumonia hospitalized in Tajrish Hospital, Tehran, Iran. Initially, the medical records of the patients were investigated, and an interview was conducted based on a pre-prepared checklist to seek information about symptoms, past medical history, medication history, and behavior before hospitalization. Results: Out of 105 participants, 76 (72.5%) cases were male, and 54 (51.4%) patients were older than 54 years old. The majority of the patients (n=18; 17.1%) had both hypertension and diabetes (n=12; 11.4%). Metformin (n=36; 34.3%) was the most used medication amongst the studied patient. In addition, 24 (22.9%) patients were recreational hookah smokers, and the majority (75%) of them were under the age of 46 years old. Eventually, 19 patients were excluded from the study, of whom 11 individuals had diabetes, and 10 cases were using metformin. Conclusion: Apparently, hookah smoking played a critical role in the spread of COVID-19 in Iran and has made younger people more susceptible. In addition to older age, the immunosuppressive effects of Metformin seem to make diabetic patients with an impaired immune system more vulnerable to severe COVID-19 pneumonia. More studies on the immune system of vulnerable individuals by identifying their differences can help to protect them.

Download Full-text

Preterm Delivery; Who Is at Risk?

Journal of Clinical Medicine ◽

10.3390/jcm10112279 ◽

2021 ◽

Vol 10 (11) ◽

pp. 2279

Author(s):

Dvora Kluwgant ◽

Tamar Wainstock ◽

Eyal Sheiner ◽

Gali Pariente

Keyword(s):

Risk Factors ◽

Preterm Birth ◽

Prenatal Care ◽

Recurrent Pregnancy Loss ◽

Placental Abruption ◽

Placenta Previa ◽

Population Based ◽

Perinatal Morbidity ◽

Multiple Gestations ◽

Extremely Preterm

Preterm birth (PTB) is the leading cause of perinatal morbidity and mortality. Adverse effects of preterm birth have a direct correlation with the degree of prematurity, in which infants who are born extremely preterm (24–28 weeks gestation) have the worst outcomes. We sought to determine prominent risk factors for extreme PTB and whether these factors varied between various sub-populations with known risk factors such as previous PTB and multiple gestations. A population-based retrospective cohort study was conducted. Risk factors were examined in cases of extreme PTB in the general population, as well as various sub-groups: singleton and multiple gestations, women with a previous PTB, and women with indicated or induced PTB. A total of 334,415 deliveries were included, of which 1155 (0.35%) were in the extreme PTB group. Placenta previa (OR = 5.8, 95%CI 4.14–8.34, p < 0.001), multiple gestations (OR = 7.7, 95% CI 6.58–9.04, p < 0.001), and placental abruption (OR = 20.6, 95%CI 17.00–24.96, p < 0.001) were the strongest risk factors for extreme PTB. In sub-populations (multiple gestations, women with previous PTB and indicated PTBs), risk factors included placental abruption and previa, lack of prenatal care, and recurrent pregnancy loss. Singleton extreme PTB risk factors included nulliparity, lack of prenatal care, and placental abruption. Placental abruption was the strongest risk factor for extreme preterm birth in all groups, and risk factors did not differ significantly between sub-populations.

Download Full-text

Endometriosis and Risk of Adverse Pregnancy Outcome: A Systematic Review and Meta-Analysis

Journal of Clinical Medicine ◽

10.3390/jcm10040667 ◽

2021 ◽

Vol 10 (4) ◽

pp. 667

Author(s):

Kjerstine Breintoft ◽

Regitze Pinnerup ◽

Tine Brink Henriksen ◽

Dorte Rytter ◽

Niels Uldbjerg ◽

...

Keyword(s):

Preterm Birth ◽

Cesarean Section ◽

Placental Abruption ◽

Gestational Hypertension ◽

Adverse Pregnancy Outcome ◽

Placenta Previa ◽

Meta Analysis ◽

Increased Risk ◽

Spontaneous Hemoperitoneum ◽

In Pregnancy

Background: This systematic review and meta-analysis summarizes the evidence for the association between endometriosis and adverse pregnancy outcome, including gestational hypertension, pre-eclampsia, low birth weight, and small for gestational age, preterm birth, placenta previa, placental abruption, cesarean section, stillbirth, postpartum hemorrhage, spontaneous hemoperitoneum in pregnancy, and spontaneous bowel perforation in pregnancy. Methods: We performed the literature review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), by searches in PubMed and EMBASE, until 1 November 2020 (PROSPERO ID CRD42020213999). We included peer-reviewed observational cohort studies and case-control studies and scored them according to the Newcastle–Ottawa Scale, to assess the risk of bias and confounding. Results: 39 studies were included. Women with endometriosis had an increased risk of gestational hypertension, pre-eclampsia, preterm birth, placenta previa, placental abruption, cesarean section, and stillbirth, compared to women without endometriosis. These results remained unchanged in sub-analyses, including studies on spontaneous pregnancies only. Spontaneous hemoperitoneum in pregnancy and bowel perforation seemed to be associated with endometriosis; however, the studies were few and did not meet the inclusion criteria. Conclusions: The literature shows that endometriosis is associated with an increased risk of gestational hypertension, pre-eclampsia, preterm birth, placenta previa, placental abruption, cesarean section, and stillbirth.

Download Full-text

Maternal Risk Factors Associated with Limb Reduction Defects: Data from the Polish Registry of Congenital Malformations (PRCM)

Children ◽

10.3390/children8020138 ◽

2021 ◽

Vol 8 (2) ◽

pp. 138

Author(s):

Anna Materna-Kiryluk ◽

Katarzyna Wisniewska ◽

Barbara Wieckowska ◽

Jolanta Wierzba ◽

Anna Jazdzewska ◽

...

Keyword(s):

Risk Factors ◽

Congenital Malformations ◽

Gestational Hypertension ◽

First Trimester ◽

Smoking History ◽

Upper Respiratory Tract ◽

Maternal Risk ◽

Limb Reduction ◽

Integral Role ◽

Tract Infections

Data from the Polish Registry of Congenital Malformations (PRCM) suggest that the prevalence of limb reduction defects (LRDs) in some Polish regions is significantly higher in comparison to that reported in the European Surveillance of Congenital Anomalies (EUROCAT) registry, but specific risk factors are still unknown. The objectives of this study were two-fold: to detect risk factors linked to isolated LRDs among Polish natives and to search for geospatial clusters of isolated LRDs to identify high-risk areas across the country. Among the 2,939,001 births accounted for in the PRCM, we determined that there were 852 children with distinct LRDs. Our data demonstrate that lower birth weight, prematurity, and maternal smoking history are strongly associated with isolated LRDs. Furthermore, our investigation pointed to various additional risk factors for isolated LRDs, including paternal education, gestational hypertension, upper respiratory tract infections, and exposure to anti-inflammatory drugs in the first trimester of pregnancy. We did not recognize statistically significant spatial or spatiotemporal clusters over the area of Poland using Kulldorff’s scan. Our study strengthens the hypothesis that maternal factors have an integral role in the etiology of isolated LRDs.

Download Full-text

Post-Operative Dysphagia in Anterior Cervical Discectomy and Fusion

Annals of Otology Rhinology & Laryngology ◽

10.1177/00034894211015582 ◽

2021 ◽

pp. 000348942110155

Author(s):

Leonard Haller ◽

Khush Mehul Kharidia ◽

Caitlin Bertelsen ◽

Jeffrey Wang ◽

Karla O’Dell

Keyword(s):

Risk Factors ◽

Medical Records ◽

Assessment Tool ◽

Demographic Data ◽

Anterior Cervical Discectomy ◽

Cervical Discectomy ◽

Long Term Follow Up

Objective: We sought to identify risk factors associated with long-term dysphagia, characterize changes in dysphagia over time, and evaluate the incidence of otolaryngology referrals for patients with long-term dysphagia following anterior cervical discectomy with fusion (ACDF). Methods: About 56 patients who underwent ACDF between May 2017 to February 2019 were included in the study. All patients were assessed for dysphagia using the Eating Assessment Tool (EAT-10) survey preoperatively and late postoperatively (≥1 year). Additionally, 28 patients were assessed for dysphagia early postoperatively (2 weeks—3 months). Demographic data, medical comorbidities, intraoperative details, and post-operative otolaryngology referral rates were collected from electronic medical records. Results: Of the 56 patients enrolled, 21 patients (38%) had EAT-10 scores of 3 or more at long-term follow-up. None of the demographics, comorbidities, or surgical factors assessed were associated with long-term dysphagia. Patients who reported no long-term dysphagia had a mean EAT-10 score of 6.9 early postoperatively, while patients with long-term symptoms had a mean score of 18.1 ( P = .006). Of the 21 patients who reported persistent dysphagia symptoms, 3 (14%) received dysphagia testing or otolaryngology referrals post-operatively. Conclusion: Dysphagia is a notable side effect of ACDF surgery, but there are no significant demographics, comorbidities, or surgical risk factors that predict long-term dysphagia. Early postoperative characterization of dysphagia using the EAT-10 questionnaire can help predict long-term symptoms. There is inadequate screening and otolaryngology follow-up for patients with post-ACDF dysphagia.

Download Full-text

Effect of Instruction on Preventing Delayed Bleeding after Colorectal Polypectomy and Endoscopic Mucosal Resection

Journal of Clinical Medicine ◽

10.3390/jcm10050928 ◽

2021 ◽

Vol 10 (5) ◽

pp. 928

Author(s):

Takuya Okugawa ◽

Tadayuki Oshima ◽

Keisuke Nakai ◽

Hirotsugu Eda ◽

Akio Tamura ◽

...

Keyword(s):

Risk Factors ◽

Medical Records ◽

Colorectal Polyp ◽

Control Group ◽

Single Center ◽

Antithrombotic Agents ◽

Delayed Bleeding ◽

Factors Associated ◽

Independent Risk Factors ◽

Continuous Use

Background: The frequency of delayed bleeding after colorectal polypectomy has been reported as 0.6–2.8%. With the increasing performance of polypectomy under continuous use of antithrombotic agents, care is required regarding delayed post-polypectomy bleeding (DPPB). Better instruction to educate endoscopists is therefore needed. We aimed to evaluate the effect of instruction and factors associated with delayed bleeding after endoscopic colorectal polyp resection. Methods: This single-center, retrospective study was performed to assess instruction in checking complete hemostasis and risk factors for onset of DPPB. The incidence of delayed bleeding, comorbidities, and medications were evaluated from medical records. Characteristics of historical control patients and patients after instruction were compared. Results: A total of 3318 polyps in 1002 patients were evaluated. The control group comprised 1479 polyps in 458 patients and the after-instruction group comprised 1839 polyps in 544 patients. DPPB occurred in 1.1% of polyps in control, and 0.4% in after-instruction. Instruction significantly decreased delayed bleeding, particularly in cases with antithrombotic agents. Hot polypectomy, clip placement, and use of antithrombotic agents were significant independent risk factors for DPPB even after instruction. Conclusion: The rate of delayed bleeding significantly decreased after instruction to check for complete hemostasis. Even after instruction, delayed bleeding can still occur in cases with antithrombotic agents or hot polypectomy.

Download Full-text

Risk Factors for Fall-Related Serious Injury among Korean Adults: A Cross-Sectional Retrospective Analysis

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18031239 ◽

2021 ◽

Vol 18 (3) ◽

pp. 1239

Author(s):

Moon-Sook Kim ◽

Hyun-Myung Jung ◽

Hyo-Yeon Lee ◽

Jinhyun Kim

Keyword(s):

Risk Factors ◽

Fall Prevention ◽

Medical Records ◽

Brain Injuries ◽

Tertiary Hospital ◽

Antiplatelet Drugs ◽

Cross Sectional ◽

Complete Survey ◽

Serious Injury ◽

Serious Injuries

The purpose of this study was to identify the risk factors of serious fall-related injuries by analyzing the differences between two fall groups: one with serious fall-related injuries and one without such injuries. Applying a retrospective, descriptive investigation study design, we analyzed the degree of fall-related injury and the risk factors related to serious falls by conducting a complete survey of the medical records of fall patients reported throughout one full year, 2017, at a tertiary hospital in Seoul, Korea. Among the patients with reported falls, 188 sustained no injury (63.1%), 72 sustained minor injury (24.2%), and 38 patients sustained serious injury (12.8%). The serious fall-related injuries included eight lacerations requiring suture (2.7%), 23 fractures (7.7%), five brain injuries (1.7%), and two deaths (0.7%). Analysis results indicated that taking anticoagulants/antiplatelet drugs (p = 0.016) and having a fall history (p = 0.038) were statistically significant in the differences between the group with serious injury related to falls and the group without serious injury. Logistic regression revealed that taking anticoagulant/antiplatelet drugs was the factor most significantly correlated with serious injuries related to falls (OR = 2.299, p = 0.022). Results show that it is necessary to develop a patient-tailored fall prevention activity program.

Download Full-text

Early Detection of Red Palm Weevil, Rhynchophorus ferrugineus (Olivier), Infestation Using Data Mining

Plants ◽

10.3390/plants10010095 ◽

2021 ◽

Vol 10 (1) ◽

pp. 95

Author(s):

Heba Kurdi ◽

Amal Al-Aldawsari ◽

Isra Al-Turaiki ◽

Abdulrahman S. Aldawood

Keyword(s):

Data Mining ◽

Plant Size ◽

Support Vector ◽

Classification Algorithms ◽

Palm Tree ◽

Rhynchophorus Ferrugineus ◽

Red Palm Weevil ◽

Palm Weevil ◽

Using Data ◽

F Measure

In the past 30 years, the red palm weevil (RPW), Rhynchophorus ferrugineus (Olivier), a pest that is highly destructive to all types of palms, has rapidly spread worldwide. However, detecting infestation with the RPW is highly challenging because symptoms are not visible until the death of the palm tree is inevitable. In addition, the use of automated RPW weevil identification tools to predict infestation is complicated by a lack of RPW datasets. In this study, we assessed the capability of 10 state-of-the-art data mining classification algorithms, Naive Bayes (NB), KSTAR, AdaBoost, bagging, PART, J48 Decision tree, multilayer perceptron (MLP), support vector machine (SVM), random forest, and logistic regression, to use plant-size and temperature measurements collected from individual trees to predict RPW infestation in its early stages before significant damage is caused to the tree. The performance of the classification algorithms was evaluated in terms of accuracy, precision, recall, and F-measure using a real RPW dataset. The experimental results showed that infestations with RPW can be predicted with an accuracy up to 93%, precision above 87%, recall equals 100%, and F-measure greater than 93% using data mining. Additionally, we found that temperature and circumference are the most important features for predicting RPW infestation. However, we strongly call for collecting and aggregating more RPW datasets to run more experiments to validate these results and provide more conclusive findings.

Download Full-text