Factors Relating to Preventive Practices of Health Science Students during the Early Stage of the COVID-19 Pandemic

Objectives: We assessed the factors relating to the prevention of the Novel Coronavirus Disease (COVID-19) for students at the University of Medicine and Pharmacy at Ho Chi Minh City, Vietnam. Methods: A cross-sectional study was performed in February and March 2020. A 21 item self-administered questionnaire on the knowledge, attitude, and practices regarding COVID-19 was collected from students of the first to the sixth year using the strategy of simple random sampling. The aim was to establish factors that relate to practices using Odds ratio (OR) and 95% confidence interval (95% CI) which were estimated by the logistic regression model, p-value <0.05 shows a significant difference. Results: Of the 551 students, 41.0% recorded responses indicating good practices toward prevention measures, while around half the students reported that they did not wash their hands for 20 full seconds (50.5%). The overall rate of good knowledge and positive attitude was 49.0% and 26.1%, respectively. When adjusted for all variables in the logistic regression model, a positive overall attitude was associated with good overall preventive practice; AOR = 1.72 (95% CI: 1.16 – 2.55). Furthermore, students mainly accessed information via social media and television (95.8% and 85.8%, respectively). Conclusions: There were only 41.0% recorded responses indicating good practices toward prevention measures. Besides, knowledge and attitudes about COVID-19 among students were inadequate. Further health education interventions should be focused to change bad hand-washing habits via mass media messages.

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Association between Attention Deficit Hyperactivity Disorder and Suicide Attempts in Patients with Bipolar Disorder

Iranian Journal of Psychiatry ◽

10.18502/ijps.v14i3.1341 ◽

2019 ◽

Author(s):

Jafar Fili ◽

Marzieh Nojomi ◽

Katayoon Razjouyan ◽

Mojgan Kahdemi ◽

Rozita Davari- Ashtiani

Keyword(s):

Bipolar Disorder ◽

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Suicide Attempts ◽

P Value ◽

Hyperactivity Disorder ◽

Significant Difference ◽

Chi Squared ◽

History Of

Objective: The present study aimed to examine the association between ADHD and suicide attempts among adolescents with bipolar disorder. Method: Participants were 168 adolescents who fulfilled DSM-IV-TR criteria for bipolar disorder. They were divided into 2 groups: The first group of patients with bipolar disorder with a history of suicide attempts (n = 84) and the second group without a history of suicide attempts (n = 84). ADHD and other variables were analyzed using a chi-squared test and logistic regression model. Results: No significant difference was observed between the 2 groups in comorbidity of ADHD and other psychiatric disorders (P value > 0/05). In the logistic regression model, and after controlling for other factors, gender (OR = 3.9, CI 95%: 1.5-9.6) and history of sexual abuse (OR = 3.4; CI 95%: 1.06-11.3) were the only 2 factors associated with a history of suicide attempts. Conclusion: No significant association was found between ADHD and suicide attempts in adolescents with bipolar disorder.

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Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus in Uganda: report of a scoring system that predicts success

Journal of Neurosurgery Pediatrics ◽

10.3171/2009.9.peds09196 ◽

2010 ◽

Vol 5 (2) ◽

pp. 143-148 ◽

Cited By ~ 94

Author(s):

Benjamin C. Warf ◽

John Mugamba ◽

Abhaya V. Kulkarni

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Endoscopic Third Ventriculostomy ◽

Successful Outcome ◽

Third Ventriculostomy ◽

P Value ◽

Training Set ◽

Childhood Hydrocephalus ◽

Validation Set

Object In Uganda, childhood hydrocephalus is common and difficult to treat. In some children, endoscopic third ventriculostomy (ETV) can be successful and avoid dependence on a shunt. This can be especially beneficial in Uganda, because of the high risk of infection and long-term failure associated with shunting. Therefore, the authors developed and validated a model to predict the chances of ETV success, taking into account the unique characteristics of a large sub-Saharan African population. Methods All children presenting with hydrocephalus at CURE Children's Hospital of Uganda (CCHU) between 2001 and 2007 were offered ETV as first-line treatment and were prospectively followed up. A multivariable logistic regression model was built using ETV success at 6 months as the outcome. The model was derived on 70% of the sample (training set) and validated on the remaining 30% (validation set). Results Endoscopic third ventriculostomy was attempted in 1406 patients. Of these, 427 were lost to follow-up prior to 6 months. In the remaining 979 patients, the ETV was aborted in 281 due to poor anatomy/visibility and in 310 the ETV failed during the first 6 months. Therefore, a total of 388 of 979 (39.6% and [55.6% of completed ETVs]) procedures were successful at 6 months. The mean age at ETV was 12.6 months, and 57.8% of cases were postinfectious in origin. The authors' logistic regression model contained the following significant variables: patient age at ETV, cause of hydrocephalus, and whether choroid plexus cauterization was performed. In the training set (676 patients) and validation set (303 patients), the model was able to accurately predict the probability of successful ETV (Hosmer-Lemeshow p value > 0.60 and C statistic > 0.70). The authors developed the simplified CCHU ETV Success Score that can be used in the field to predict the probability of ETV success. Conclusions The authors' model will allow clinicians to accurately identify children with a good chance of successful outcome with ETV, taking into account the unique characteristics and circumstances of the Ugandan population.

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Determinants of acute respiratory infection among under-five children in rural Ethiopia

BMC Infectious Diseases ◽

10.1186/s12879-021-06864-4 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Amanuel Mengistu Merera

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Regression Model ◽

Respiratory Infection ◽

Acute Respiratory Infection ◽

Logistic Regression Model ◽

P Value ◽

Under Five ◽

Under Five Children ◽

Rural Ethiopia

Abstract Introduction In low- and middle-income nations, acute respiratory infection (ARI) is the primary cause of morbidity and mortality. According to some studies, Ethiopia has a higher prevalence of childhood acute respiratory infection, ranging from 16 to 33.5%. The goal of this study was to determine the risk factors for acute respiratory infection in children under the age of five in rural Ethiopia. Methods A cross-sectional study involving 7911 children under the age of five from rural Ethiopia was carried out from January 18 to June 27, 2016. A two stage cluster sampling technique was used recruit study subjects and SPSS version 20 was used to extract and analyze data. A binary logistic regression model was used to identify factors associated with a childhood acute respiratory infection. The multivariable logistic regression analysis includes variables with a p-value less than 0.2 during the bivariate logistic regression analysis. Adjusted odds ratios were used as measures of effect with a 95% confidence interval (CI) and variables with a p-value less than 0.05 were considered as significantly associated with an acute respiratory infection. Results The total ARI prevalence rate among 7911 under-five children from rural Ethiopia was 7.8%, according to the findings of the study. The highest prevalence of ARI was found in Oromia (12.8%), followed by Tigray (12.7%), with the lowest frequency found in Benishangul Gumuz (2.4%). A multivariable logistic regression model revealed that child from Poor household (AOR = 2.170, 95% CI: 1.631–2.887), mother’s no education (AOR = 2.050,95% CI: 1.017–4.133), mother’s Primary education (AOR = 2.387, 95% CI:1.176–4.845), child had not received vitamin A (AOR = 1.926, 95% CI:1.578–2.351), child had no diarrhea (AOR = 0.257, 95% CI: 0.210–0.314), mothers not working (AOR = 0.773, 95% CI:0.630–0.948), not stunted (AOR = 0.663, 95% CI: 0.552–0.796), and not improved water source (AOR = 1.715, 95% CI: 1.395–2.109). Similarly, among under-five children, the age of the child, the month of data collection, anemia status, and the province were all substantially linked to ARI. Conclusions Childhood ARI morbidity is a serious health challenge in rural Ethiopia, according to this study, with demographic, socioeconomic, nutritional, health, and environmental factors all having a role. As a result, regional governments, healthcare staff, and concerned groups should place a priority on reducing ARI, and attempts to solve the issue should take these variables into account.

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Determinants of Acute Respiratory Infection among Under-Five Children in Rural Ethiopia

10.21203/rs.3.rs-811643/v1 ◽

2021 ◽

Author(s):

Amanuel Mengistu Merera

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Regression Model ◽

Respiratory Infection ◽

Acute Respiratory Infection ◽

Logistic Regression Model ◽

P Value ◽

Under Five ◽

Under Five Children ◽

Rural Ethiopia

Abstract Introduction: In low- and middle-income nations, acute respiratory infection (ARI) is the primary cause of morbidity and mortality. According to some studies, Ethiopia has a higher prevalence of childhood acute respiratory infection, ranging from 16 % to 33.5 %. The goal of this study was to determine the risk factors for acute respiratory infection in children under the age of five in rural Ethiopia. Methods: A cross-sectional study involving 7,911 children under the age of five from rural Ethiopia was carried out from January 18 to June 27, 2016. A two stage cluster sampling technique was used recruit study subjects and SPSS version 20 was used to extract and analyze data. A binary logistic regression model was used to identify factors associated with a childhood acute respiratory infection. The multivariable logistic regression analysis includes variables with a p-value less than 0.2 during the bivariate logistic regression analysis. Adjusted odds ratios were used as measures of effect with a 95% confidence interval (CI) and variables with a p-value less than 0.05 were considered as significantly associated with an acute respiratory infection. Results: The total ARI prevalence rate among 7,911 under-five children from rural Ethiopia was 7.8%, according to the findings of the study. The highest prevalence of ARI was found in Oromia (12.8 %), followed by Tigray (12.7 %), with the lowest frequency found in Benishangul Gumuz (2.4 %). A multivariable logistic regression model revealed that child from Poor household (AOR=2.170, 95% CI: 1.631-2.887), mother’s no education (AOR=2.050,95% CI: 1.017-4.133), mother’s Primary education (AOR=2.387, 95% CI:1.176-4.845), child had not received vitamin A (AOR=1.926, 95% CI:1.578-2.351), child had no diarrhea (AOR=0.257, 95% CI: 0.210-0.314), mothers not working (AOR=0.773, 95% CI:0.630-0.948), not stunted (AOR=0.663, 95% CI: 0.552-0.796), and not improved water source (AOR=1.715, 95% CI: 1.395-2.109). Similarly, among under-five children, the age of the child, the month of data collection, anemia status, and the province were all substantially linked to ARI. Conclusions: Childhood ARI morbidity is a serious health challenge in rural Ethiopia, according to this study, with demographic, socioeconomic, nutritional, health, and environmental factors all having a role. As a result, regional governments, healthcare staff, and concerned groups should place a priority on reducing ARI, and attempts to solve the issue should take these variables into account.

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Forecasting Of Content Ca 125 Endometriosis Using Logistic Regression Model

International Journal of Human and Health Sciences (IJHHS) ◽

10.31344/ijhhs.v5i1.232 ◽

2020 ◽

Vol 5 (1) ◽

pp. 47

Author(s):

Sardjana Atmadja ◽

Gulam Gumilar

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Measurement Model ◽

Ca 125 ◽

P Value ◽

Primary Dysmenorrhoea ◽

Lemeshow Test ◽

Main Factors ◽

Blood Loss Volume

Objective : This study is to prove that there is a significant relationship between the absence of students participating in activities at school / on campus and the symptoms of primary dysmenorrhoea experienced during menstruation. Endometriosis is characterized as pain under the abdomen during menstruation. In addition, this study is also to obtain a profile of students and factors that influence primary dysmenorrhoea. A logistic regression model has been used to assess the main factors of dysmenorrhoea among these students.Methods : The study was conducted at the RSK Permata Hati Malang. A total of 123 students were randomly selected in this study. The factors observed were menarche, menstruation, menstruation period and blood loss volume and CA 125 level. From the logistic regression model, it was found that there were three factors that influence the occurrence of dysmenorrhoea among students, namely menarche, menstruation period and menstrual blood volume.Results: The Hosmer and Lemeshow test showed that the measurement model of CA 125 levels in endometriosis was appropriate (Chi squar test value was 2.847 with p-value = 0.416). Instead of Press. (3) and Eq. (4), it was found that the contributors to dismenortea were menstrual length, menstrual discharge and the beginning of menarche. By looking at the odds ratio it is found that the risk of students experiencing dysmenorrhoea is (i) 2.5 times higher for those with longer menstrual periods (ii) 3.7 times higher for those who have menstrual expenditure which is a little and (iii) three times higher for those who have mined it for more than 13 years.Conclusion: Significant CA 125 levels were obtained for students and students suffering from dysmenorrhoea. The study also found that the risk of getting dysmenorrhoea increased if students and students had menstrual periods longer than 35 days, menstrual expenditure levels were small and menarche was more than 13 years old.International Journal of Human and Health Sciences Vol. 05 No. 01 January’21 Page: 47-49

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The applicability of basic preventive measures of the pandemic COVID-19 and associated factors among residents in Guraghe Zone

PLoS ONE ◽

10.1371/journal.pone.0256598 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0256598

Author(s):

Samuel Dessu ◽

Tadesse Tsehay ◽

Tadele Girum ◽

Abebe Timerga ◽

Mamo Solomon ◽

...

Keyword(s):

Public Health ◽

Logistic Regression ◽

Regression Model ◽

Family Size ◽

Associated Factors ◽

Logistic Regression Model ◽

Preventive Measures ◽

P Value ◽

Multivariable Logistic Regression Model ◽

Poor Knowledge

Introduction Internationally, countries have reacted to the COVID-19 outbreak by introducing key public health non-pharmaceutical interventions to protect vulnerable population groups. In response to COVID-19, the Government of Ethiopia has been taking a series of policy actions beyond public health initiatives alone. Therefore, this study was aimed to assess the applicability of basic preventive measures of the pandemic COVID-19 and associated factors among the residents of Guraghe Zone from 18th to 29th September, 2020. Methods Community based cross sectional study was conducted at Guraghe Zone from 18th to 29th September, 2020. Systematic random sampling method was applied among the predetermined 634 samples. Variables which had p-value less than 0.25 in bivariate analysis were considered as candidate for multivariable logistic regression model. P-value <0.05 was used as a cutoff point to determine statistical significance in multiple logistic regressions for the final model. Result In this study, 17.7% (95% CI: 14.7, 20.5) of the respondents apply the basic preventive measures towards the prevention of the pandemic COVID-19. In addition, being rural resident (AOR: 4.78,; 95%CI: 2.50, 8.90), being studied grade 1–8 (AOR: 3.70; 95%CI: 1.70, 7.90), being a farmer (AOR: 4.10; 95%CI: 1.25, 13.35), currently not married (AOR: 2.20, 95%CI: 1.24, 4.06), having family size 1-3(AOR: 6.50; 95%CI: 3.21, 3.35), have no diagnosed medical illness (AOR: 6.40; 95%CI: 3.85, 10.83) and having poor knowledge (AOR: 3.50; 95%CI: 1.60, 7.40) were factors which are statistically significant in multivariable logistic regression model. Conclusion Despite the application of preventive measures and vaccine delivery, the applicability of the pandemic COVID-19 preventive measures was too low, which indicate that the Zone is at risk for the infection. Rural residents, those who have lower educational level, farmers, non-marrieds, those who have lower family size, those who have diagnosed medical illnesses and those who have poor knowledge were prone to the infection with the pandemic COVID-19 due to the lower practice of applying the basic preventive measures. In addition, awareness creation should be in practice at all levels of the community especially lower educational classes and rural residents.

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Έκφραση και κλινική σημασία των Claudin77, PDL-1, PTEN, C-KIT, C-MET, CMYC, ALK, CK5/6, CK17, P53, EGFR, KI67 και P63 στον τριπλά αρνητικό καρκίνο του μαστού

10.12681/eadd/48147 ◽

2018 ◽

Author(s):

Χλόη Κωνσταντίνου

Keyword(s):

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Tissue Microarrays ◽

P Value ◽

Exact Test ◽

Fisher's Exact Test ◽

Backward Elimination ◽

Fisher’S Exact Test ◽

Elimination Of Variables

Ο τριπλά αρνητικός καρκίνος του μαστού (TNBC) αντιπροσωπεύει το 10-15% των καρκίνωντου μαστού και ορίζεται ανοσοΐστοχημικά από την έλλειψη έκφρασης των ER, PR και HER2.Χαρακτηρίζεται από υψηλότερη θνησιμότητα σε σχέση με τους άλλους υποτύπους λόγω τηςεπιθετικής κλινικής συμπεριφοράς του, της κακής πρόγνωσης του και της έλλειψης στοχευμένων θεραπειών. Σκοπός της παρούσας μελέτης ήταν η αξιολόγηση προγνωστικών δεικτών για τους TNBCs -p53, p63, C-KIT, Ki67, cMet, claudin 7, CK 5/6, CK17, AR, PTEN, EGFR, ALK, PDL-1 και cMYC - σε σχέση με τον υψηλότερο βαθμό κακοήθειας, θετικούς λεμφαδένες, την λεμφαγγειακήδιήθηση (LVI), τοπική υποτροπή, μεταστάσεις, την ελεύθερη νόσου επιβίωση (DFS) καθώς και την συνολική επιβίωση (OS). Υλικό-Μέθοδοι: Διενεργήθηκε απλή ανοσοϊστοχημεία έναντι των 14 αντιγόνων σε 84 ασθενείς με τριπλά αρνητικό διηθητικό καρκίνωμα του μαστού. Επιλέγηκαν κατάλληλοι κύβοι παραφίνης για την δημιουργία ιστικών μικροσυστοιχιών (Tissue MicroArrays-TMA). Η ανοσοϊστοχημική διερεύνηση εφαρμόσθηκε σε τομές πάχους 3 μm, από τους τρεις ΤΜΑ κύβους παραφίνης. Αποτελέσματα: Μονοπαραγοντική ανάλυση με το Fisher’s exact test εδειξε στατιστικάσημαντική σχέση μεταξύ του βαθμού κακοήθειας του όγκου και της CLAUDIN 7 (pvalue=0.004), των θετικών λεμφαδένων και της πρωτεΐνης p53 (p-value=0.015), της λεμφαγγειακής διήθησης και της CLAUDIN 7 (p-value=0.032), καθώς και μεταξύ των μοριακών δεικτών ckit και των ck5/6 (p-value=0.022), ckit και EGFR (p-value=0.055), AR και cΜet (p-value=0.041), CK5/6 και EGFR (p-value=0.004), CK17 και Ki67 (p-value=0.041), Ki67 και cΜet (p-value=0.002). Η σημασία αυτής της συσχέτισης μεταξύ των δεικτών δεν έχει διερευνηθεί. Πολυπαραγοντική ανάλυση με logistic regression model with stepwise backward elimination of variables with a p-value=0.05 για τον βαθμό κακοήθειας έδειξε: Υψηλότερη έκφραση της cl7 ( OR=65.8, 95%CI=4.35-995.19, p-value=0.003), χαμηλότερη έκφραση της ckit (OR=0.14, 95%CI=0.025-0.793, p-value=0.026) αλλά και της πρωτεΐνης p63 (OR=0.18 95%CI=0.035-0.978, p-value=0.047) σχετίζονταν με υψηλότερο βαθμό κακοήθειας του όγκου. Παρατηρήθηκε υψηλότερη έκφραση του AR (OR=13.44, 95%CI=1.28-141.56, pvalue=0.031) και χαμηλότερη έκφραση των CK5/6 OR=0.072, 95%CI=0.007-0.732, (pvalue=0.026) σε ασθενείς με θετική LVI. Σύμφωνα με το Α-rank B, μόνο το Κi67 απεδείχθη στατιστικά σημαντικό για την OS (pvalue=0.0186) και για την DFS (p-alue=0.0378).Συμπέρασμα: Υψηλή έκφραση της claudin-7 και χαμηλή έκφραση της c-kit και της πρωτεΐνης p63 σχετίζονταν με υψηλότερο βαθμό κακοήθειας του όγκου. Υψηλότερη έκφραση του AR, και χαμηλότερη έκφραση των CK5/6 φαίνεται να σχετίζονται με θετικό LVI. Αυτά τα ευρήματα εισηγούνται ότι αυτοί οι μοριακοί δείκτες μπορεί να χρησιμοποιηθούν ως προγνωστικοί δείκτεςγια τους TNBCς.

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Application of the Preoperative Assistant System Based on Machine Learning in Hepatocellular Carcinoma Resection

Journal of Healthcare Engineering ◽

10.1155/2021/4757668 ◽

2021 ◽

Vol 2021 ◽

pp. 1-6

Author(s):

Shouyun Lv ◽

Shizong Li ◽

Zhiwei Yu ◽

Kaiqiong Wang ◽

Xin Qiao ◽

...

Keyword(s):

Machine Learning ◽

Hepatocellular Carcinoma ◽

Logistic Regression ◽

Regression Model ◽

Logistic Regression Model ◽

Liver Volume ◽

Surgical Margin ◽

Extensive Hepatectomy ◽

Significant Difference ◽

Logistic Regression Algorithm

To conduct better research in hepatocellular carcinoma resection, this paper used 3D machine learning and logistic regression algorithm to study the preoperative assistance of patients undergoing hepatectomy. In this study, the logistic regression model was analyzed to find the influencing factors for the survival and recurrence of patients. The clinical data of 50 HCC patients who underwent extensive hepatectomy (≥4 segments of the liver) admitted to our hospital from June 2020 to December 2020 were selected to calculate the liver volume, simulated surgical resection volume, residual liver volume, surgical margin, etc. The results showed that the simulated liver volume of 50 patients was 845.2 + 285.5 mL, and the actual liver volume of 50 patients was 826.3 ± 268.1 mL, and there was no significant difference between the two groups (t = 0.425; P > 0.05). Compared with the logistic regression model, the machine learning method has a better prediction effect, but the logistic regression model has better interpretability. The analysis of the relationship between the liver tumour and hepatic vessels in practical problems has specific clinical application value for accurately evaluating the volume of liver resection and surgical margin.

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A Machine-Learning Model Based on Morphogeometric Parameters for RETICS Disease Classification and GUI Development

Applied Sciences ◽

10.3390/app10051874 ◽

2020 ◽

Vol 10 (5) ◽

pp. 1874 ◽

Cited By ~ 2

Author(s):

José M. Bolarín ◽

F. Cavas ◽

J.S. Velázquez ◽

J.L. Alió

Keyword(s):

Machine Learning ◽

Logistic Regression ◽

Regression Model ◽

Web Application ◽

High Performance ◽

Logistic Regression Model ◽

Early Stage ◽

Disease Classification ◽

Multivariate Logistic Regression Model ◽

Detection Model

This work pursues two objectives: defining a new concept of risk probability associated with suffering early-stage keratoconus, classifying disease severity according to the RETICS (Thematic Network for Co-Operative Research in Health) scale. It recruited 169 individuals, 62 healthy and 107 keratoconus diseased, grouped according to the RETICS classification: 44 grade I; 18 grade II; 15 grade III; 15 grade IV; 15 grade V. Different demographic, optical, pachymetric and eometrical parameters were measured. The collected data were used for training two machine-learning models: a multivariate logistic regression model for early keratoconus detection and an ordinal logistic regression model for RETICS grade assessments. The early keratoconus detection model showed very good sensitivity, specificity and area under ROC curve, with around 95% for training and 85% for validation. The variables that made the most significant contributions were gender, coma-like, central thickness, high-order aberrations and temporal thickness. The RETICS grade assessment also showed high-performance figures, albeit lower, with a global accuracy of 0.698 and a 95% confidence interval of 0.623–0.766. The most significant variables were CDVA, central thickness and temporal thickness. The developed web application allows the fast, objective and quantitative assessment of keratoconus in early diagnosis and RETICS grading terms.

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Risk assessment of severe tricyclic antidepressant overdose

Human & Experimental Toxicology ◽

10.1177/0960327109106970 ◽

2009 ◽

Vol 28 (8) ◽

pp. 511-519 ◽

Cited By ~ 11

Author(s):

Florian Eyer ◽

Jochen Stenzel ◽

Tibor Schuster ◽

Norbert Felgenhauer ◽

Rudi Pfab ◽

...

Keyword(s):

Risk Assessment ◽

Logistic Regression ◽

Regression Model ◽

Clinical Characteristics ◽

Logistic Regression Model ◽

Early Stage ◽

Statistical Significance ◽

Time Lag ◽

Tricyclic Antidepressant ◽

Multivariable Logistic Regression Model

Prognostic factors for severe complications in tricyclic antidepressant (TCA) overdose remain unclear. We therefore evaluated the value of clinical characteristics and electrocardiograph (ECG) parameters to predict serious events (seizures, arrhythmia, death) in severe TCA overdose of 100 patients using logistic regression models for risk assessment. The overall fatality rate was 6%, arrhythmia occurred in 21% and 31% of the patients developed seizures. Using an univariable logistic regression model, the maximal QRS interval (OR 1.22; 95% CI 1.06-1.41; p = .005), the time lag between ingestion and occurrence of first symptoms of overdose (OR 1.13; 95% CI 0.99-1.29; p = .072) and the age (OR 0.73; 95% CI 0.55-0.98; p = .038) were determined as the solely predictive parameters. In the multivariable logistic regression model, the QRS interval could not be established as independent predictor, however, the terminal 40-ms frontal plane QRS vector (T40) reached statistical significance regarding prediction of serious events (odds ration [OR] 1.70; 95% confidence interval [CI] 1.02-2.84; p = .041), along with age and time lag between ingestion and onset of symptoms of overdose with a sensitivity and specificity of 71% and 70%, respectively. Evaluation of both clinical characteristics and ECG-parameters in the early stage of TCA overdose may help to identify those patients who urgently need further aggressive medical observation and management.

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