Predictors of perioperative atrial fibrillation in non cardiac elective surgery: the Hart score

EP Europace ◽  
2021 ◽  
Vol 23 (Supplement_3) ◽  
Author(s):  
G Stronati ◽  
C Mondelli ◽  
S Principi ◽  
M Silenzi ◽  
A Urbinati ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
High Risk ◽  
Risk Score ◽  
Primary Endpoint ◽  
Thyroid Dysfunction ◽  
Previous History ◽  
Internal Validation ◽  
Old Patients ◽  
Multivariable Logistic Regression

Abstract Funding Acknowledgements Type of funding sources: None. BACKGROUND  Postoperative atrial fibrillation (POAF) is defined as de novo onset of atrial fibrillation in the post operative period, in patients with no previous history of atrial fibrillation. It affects almost 3% of all over 45 year old patients undergoing non cardiovascular surgery and is associated with a higher risk of stroke and mortality. PURPOSE  To assess independent predictors of POAF in elective non-cardiac surgery.  METHODS  Retrospective observational database including all patients attending a cardiological preoperative assessment from the 1st of January 2016 to the 31st of December 2019. The primary endpoint was the occurrence of POAF. Individual predictors of the primary endpoint were tested through a series of multivariable logistic regression models, including only those variables with a p<.01 in the univariable models. Independent predictors were entered into a score, and assigned points according to their odd ratios. Performance of the risk score was tested with the receiver operating characteristic  curve. A bootstrap procedure was employed for internal validation of both the multivariable logistic regression model and the risk score, using 10000 bootstrap samples and bias-corrected and accelerated confidence intervals. RESULTS  A total of 2048 patients were enrolled (1350 men, age 71 ± 12 years). Fourty-four patients experienced POAF (2.1%) – median 3 days (1st-3rd quartile 2-3 days). Age (OR 1.03 for each year; 95% CI 1.01-1.07), hypertension (OR 3.43; 95% CI 1.22-9.63), thyroid dysfunction (OR 2.70; 95% CI 1.35-5.42) and intermediate or high risk surgery (OR 18.28; 95% CI 2.51-33.09) resulted as independent predictors of POAF (all p < 0.05). We therefore created the HART score according to Table 1 (OR 2.59 for each point; 95% CI 1.79-3.75; p > 0.001). A cut-off score ≥ 5 has a 70% sensitivity and a 72% specificity in detecting POAF in our population (AUC 0.74). Bootstrapping for internal validation confirmed the overall results. CONCLUSIONS A four items point-based risk score such as the HART score, could be effective in implementing effective POAF screening and improve management. The HART score Variable Points H Hypertension 1 point A Age (65-74 years) 1 point Age (75+ years) 2 points R Intermediate Risk surgery 3 points High Risk surgery 3 points T Thyroid dysfunction 1 point

scholarly journals Development of a new sternal dehiscence prediction scale for decision making in sternal closure techniques after cardiac surgery

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Ehab Nooh ◽  
Colin Griesbach ◽  
Johannes Rösch ◽  
Michael Weyand ◽  
Frank Harig
Keyword(s):  
Logistic Regression ◽  
Risk Score ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Individual Risk ◽  
Dependent Diabetes Mellitus ◽  
Analysis Model ◽  
Multivariable Logistic Regression Model ◽  
Sternal Dehiscence ◽  
Multivariable Logistic Regression

Abstract Background After sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an appropriate sternal osteosynthesis technique that is risk- adjusted as well as cost-effective. Methods Data from 7.173 patients operated via sternotomy for all cardiovascular indications from 2008 until 2017 were retrospectively analyzed. Sternal dehiscence occurred in 2.5% of patients (n = 176). A multivariable analysis model examined pre- and intraoperative factors. A multivariable logistic regression model and a backward elimination based on the Akaike Information Criterion (AIC) a logistic model were selected. Results The model showed good sensitivity and specificity (area under the receiver-operating characteristic curve, AUC: 0.76) and several predictors of sternal instability could be evaluated. Multivariable logistic regression showed the highest Odds Ratios (OR) for reexploration (OR 6.6, confidence interval, CI [4.5–9.5], p < 0.001), obesity (body mass index, BMI > 35 kg/m2) (OR 4.23, [CI 2.4–7.3], p < 0.001), insulin-dependent diabetes mellitus (IDDM) (OR 2.2, CI [1.5–3.2], p = 0.01), smoking (OR 2.03, [CI 1.3–3.08], p = 0.001). After weighting the probability of sternum dehiscence with each factor, a risk score model was proposed scaling from − 1 to 5 points. This resulted in a risk score ranging up to 18 points, with an estimated risk for sternum complication up to 74%. Conclusions A weighted scoring system based on individual risk factors was specifically created to predict sternal dehiscence. High-scoring patients should receive additive closure techniques.

scholarly journals Prediction of Shoulder Pain in Youth Competitive Swimmers: The Development and Internal Validation of a Prognostic Prediction Model

2020 ◽  
Vol 49 (1) ◽  
pp. 154-161
Author(s):  
Stef Feijen ◽  
Thomas Struyf ◽  
Kevin Kuppens ◽  
Angela Tate ◽  
Filip Struyf
Keyword(s):  
Logistic Regression ◽  
Shoulder Pain ◽  
Muscle Endurance ◽  
Internal Validation ◽  
Competitive Swimming ◽  
Final Model ◽  
Shoulder Muscle ◽  
Multivariable Logistic Regression ◽  
Posterior Shoulder ◽  
Competitive Swimmers

Background: Knowledge of predictors for shoulder pain in swimmers can assist professionals working with the athlete in developing optimal prevention strategies. However, study methodology and limited available data have constrained a comprehensive understanding of which factors cause shoulder pain. Purpose: To investigate risk factors and develop and internally validate a multivariable prognostic model for the prediction of shoulder pain in swimmers. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 201 pain-free club- to international-level competitive swimmers were followed for 2 consecutive seasons. The cohort consisted of 96 male (mean ± SD age, 13.9 ± 2.2 years) and 105 female (13.9 ± 2.2 years) swimmers. Demographic, sport-specific, and musculoskeletal characteristics were assessed every 6 months. Swim-training exposure was observed prospectively. Shoulder pain interfering with training was the primary outcome. Multiple imputation was used to cope with missing data. The final model was estimated using multivariable logistic regression. We applied bootstrapping to internally validate the model and correct for overoptimism. Results: A total of 42 new cases of shoulder pain were recorded during the study. Average duration of follow-up was 1.1 years. Predictors included in the final model were acute:chronic workload ratio (odds ratio [OR], 4.31; 95% CI, 1.00-18.54), competitive level (OR, 0.19; 95% CI, 0.06-0.63), shoulder flexion range of motion, posterior shoulder muscle endurance (OR, 0.96; 95% CI, 0.92-0.99), and hand entry position error (OR, 0.37; 95% CI, 0.16-0.91). After internal validation, this model maintained good calibration and discriminative power (area under the receiver operating characteristic curve, 0.71; 95% CI, 0.60-0.94). Conclusion: Our model consists of parameters that are readily measurable in a swimming setting, allowing the identification of swimmers at risk for shoulder pain. Multivariable logistic regression showed the strongest predictors for shoulder pain were regional competitive swimming level, acute:chronic workload ratio, posterior shoulder muscle endurance, and hand entry error.

Multicentre validation of the Geneva Risk Score for hospitalised medical patients at risk of venous thromboembolism

2014 ◽  
Vol 111 (03) ◽  
pp. 531-538 ◽  
Author(s):  
Drahomir Aujesky ◽  
Daniel Hayoz ◽  
Jürg Beer ◽  
Marc Husmann ◽  
Beat Frauchiger ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
High Risk ◽  
Risk Score ◽  
Primary Endpoint ◽  
Low Risk ◽  
Prediction Score ◽  
Medical Patients ◽  
Cumulative Rate ◽  
Patients At Risk ◽  
Risk Patients

SummaryThere is a need to validate risk assessment tools for hospitalised medical patients at risk of venous thromboembolism (VTE). We investigated whether a predefined cut-off of the Geneva Risk Score, as compared to the Padua Prediction Score, accurately distinguishes low-risk from high-risk patients regardless of the use of thromboprophylaxis. In the multicentre, prospective Explicit ASsessment of Thromboembolic RIsk and Prophylaxis for Medical PATients in SwitzErland (ESTIMATE) cohort study, 1,478 hospitalised medical patients were enrolled of whom 637 (43%) did not receive thromboprophylaxis. The primary endpoint was symptomatic VTE or VTE-related death at 90 days. The study is registered at ClinicalTrials.gov, number NCT01277536. According to the Geneva Risk Score, the cumulative rate of the primary endpoint was 3.2% (95% confidence interval [CI] 2.2–4.6%) in 962 high-risk vs 0.6% (95% CI 0.2–1.9%) in 516 low-risk patients (p=0.002); among patients without prophylaxis, this rate was 3.5% vs 0.8% (p=0.029), respectively. In comparison, the Padua Prediction Score yielded a cumulative rate of the primary endpoint of 3.5% (95% CI 2.3–5.3%) in 714 high-risk vs 1.1% (95% CI 0.6–2.3%) in 764 lowrisk patients (p=0.002); among patients without prophylaxis, this rate was 3.2% vs 1.5% (p=0.130), respectively. Negative likelihood ratio was 0.28 (95% CI 0.10–0.83) for the Geneva Risk Score and 0.51 (95% CI 0.28–0.93) for the Padua Prediction Score. In conclusion, among hospitalised medical patients, the Geneva Risk Score predicted VTE and VTE-related mortality and compared favourably with the Padua Prediction Score, particularly for its accuracy to identify low-risk patients who do not require thromboprophylaxis.

scholarly journals Impella use in real-world cardiogenic shock patients: Sobering outcomes

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0247667
Author(s):  
Khaled Q. A. Abdullah ◽  
Jana V. Roedler ◽  
Juergen vom Dahl ◽  
Istvan Szendey ◽  
Hendrik Haake ◽  
...  
Keyword(s):  
Logistic Regression ◽  
High Risk ◽  
Hospital Mortality ◽  
Cardiogenic Shock ◽  
Patient Selection ◽  
Primary Endpoint ◽  
Real World ◽  
Risk Group ◽  
Low Risk ◽  
Medium Risk

Background Critically ill patients with cardiogenic shock could benefit from ventricular assist device support using the Impella microaxial blood pump. However, recent studies suggested Impella not to improve outcomes. We, therefore, evaluated outcomes and predictors in a real-world scenario. Methods In this retrospective single-center trial, 125 patients suffering from cardiac arrest/cardiogenic shock between 2008 and 2018 were analyzed. 93 Patients had a prior successful cardiopulmonary resuscitation. The primary endpoint was hospital mortality. Associations of covariates with the primary endpoint were assessed by univariable and multivariable logistic regression. Adjusted odds ratios (aOR) and optimal cut-offs (using Youden index) were obtained. Results Hospital mortality was high (81%). Baseline lactate was 4.7mmol/L [IQR = 7.1mmol/L]. In multivariable logistic regression, only age (aOR 1.13 95%CI 1.06–1.20; p<0.001) and lactate (aOR 1.23 95%CI 1.004–1.516; p = 0.046) were associated with hospital mortality, and the respective optimal cut-offs were >3.3mmol/L and age >66 years. Patients were retrospectively stratified into three risk groups: Patients aged ≤66 years and lactate ≤3.3mmol (low-risk; n = 22); patients aged >66 years or lactate >3.3mmol/L (medium-risk; n = 52); and patients both aged >66 years and lactate >3.3mmol/L (high-risk, n = 51). Risk of death increased from 41% in the low-risk group, to 79% in the medium risk group and 100% in the high-risk group. The predictive abilities of this model were high (AUC 0.84; 95% 0.77–0.92). Conclusion Mortality was high in this real-world collective of severely ill cardiogenic shock patients. Better patient selection is warranted to avoid unethical use of Impella. Age and lactate might help to improve patient selection.

scholarly journals Increased baseline ECG R-R dispersion predicts improvement in systolic function after atrial fibrillation ablation

Open Heart ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. e000958
Author(s):  
Ryan J Koene ◽  
Eric Buch ◽  
Young-Ji Seo ◽  
Jian-Ming Li ◽  
Mackenzi Mbai ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Systolic Function ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Baseline Heart Rate ◽  
Absolute Increase ◽  
Ventricular Ejection Fraction ◽  
Af Ablation ◽  
Multivariable Logistic Regression

BackgroundAtrial fibrillation (AF) is associated with left ventricular (LV) systolic dysfunction which may improve after AF ablation. We hypothesised that increased ventricular irregularity, as measured by R-R dispersion on the baseline ECG, would predict improvement in the left ventricular ejection fraction (LVEF) after AF ablation.MethodsPatients with LVEF <50% at two US centres (2007–2016), having both a preablation and postablation echocardiogram or cardiac MRI, were included. LVEF improvement was defined as absolute increase in LVEF by >7.5%. Multivariable logistic regression (restricted to echocardiographic/ECG variables) was performed to evaluate predictors of LVEF improvement.ResultsFifty-two patients were included in this study. LVEF improved in 30 patients (58%) and was unchanged/worsened in 22 patients (42%). Those with versus without LVEF improvement had an increased baseline R-R dispersion (645±155 ms vs 537±154 ms, p=0.02, respectively). The average baseline heart rate in all patients was 93 beats per minute. After multivariable logistic regression, increased R-R dispersion (OR 1.59, 95% CI 1.00 to 2.55, p=0.03) predicted LVEF improvement.ConclusionsIncreased R-R dispersion on ECG was independently associated with improved systolic function after AF ablation. This broadens the existing knowledge of arrhythmia-induced cardiomyopathy, demonstrating that irregular electrical activation (as measured by increased R-R dispersion on ECG) is associated with a cardiomyopathy capable of improving after AF ablation.

scholarly journals Risk for Depressive Symptoms among Hospitalized Women in High-Risk Pregnancy Units during the COVID-19 Pandemic

2020 ◽  
Vol 9 (8) ◽  
pp. 2449 ◽  
Author(s):  
Shanny Sade ◽  
Eyal Sheiner ◽  
Tamar Wainstock ◽  
Narkis Hermon ◽  
Shimrit Yaniv Salem ◽  
...  
Keyword(s):  
Logistic Regression ◽  
High Risk ◽  
Medical Center ◽  
Depression Scale ◽  
High Risk Pregnancy ◽  
Multivariable Logistic Regression ◽  
Risk Pregnancy ◽  
Increased Risk ◽  
Isolation Period ◽  
Risk For Depression

Objective: Higher rates of mental disorders, specifically depression, were found among affected people in previous epidemiological studies taken after disasters. The aim of the current study was to assess risk for depression among pregnant women hospitalized during the “coronavirus disease 2019” (COVID-19) pandemic, as compared to women hospitalized before the COVID-19 pandemic. Study design: A cross-sectional study was performed among women hospitalized in the high-risk pregnancy units of the Soroka University Medical Center (SUMC). All participating women completed the Edinburgh Postnatal Depression Scale (EPDS), and the results were compared between women hospitalized during the COVID-19 strict isolation period (19 March 2020 and 26 May 2020) and women hospitalized before the COVID-19 pandemic. Multivariable logistic regression models were constructed to control for potential confounders. Results: Women hospitalized during the COVID-19 strict isolation period (n = 84) had a comparable risk of having a high (>10) EPDS score as compared to women hospitalized before the COVID-19 pandemic (n = 279; 25.0% vs. 29.0%, p = 0.498). These results remained similar in the multivariable logistic regression model, while controlling for maternal age, ethnicity and known mood disorder (adjusted odds ratio (OR) 1.0, 95% CI 0.52–1.93, p = 0.985). Conclusion: Women hospitalized at the high-risk pregnancy unit during the COVID-19 strict isolation period were not at increased risk for depression, as compared to women hospitalized before the COVID-19 pandemic.

scholarly journals P827 Left atrial contractile function is the main correlate of atrial fibrillation in patients with hypertrophic cardiomyopathy

2020 ◽  
Vol 21 (Supplement_1) ◽  
Author(s):  
M Rosca ◽  
L Mandes ◽  
D Ciuperca ◽  
A Calin ◽  
C C Beladan ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Hypertrophic Cardiomyopathy ◽  
Logistic Regression Analysis ◽  
Left Atrial ◽  
Contractile Function ◽  
Multivariable Logistic Regression Analysis ◽  
Multivariable Logistic Regression ◽  
And Function

Abstract Background Given the negative impact of atrial fibrillation (AF) in patients (pts) with hypertrophic cardiomyopathy (HCM), finding new and better predictors of AF is clinically important, especially for patients considered at low or intermediate risk based on current recommendations (i.e. left atrial diameter, LAD &lt;45 mm). Purpose To assess the relationship between left atrial (LA) remodelling (size and function) and the presence of paroxysmal AF in HCM patients with and without increased LAD. Methods A comprehensive echocardiogram was performed in 110 consecutive pts (52 ± 17 years, 50 men) with HCM, in sinus rhythm. Indexed LA volume (LAVi), maximum left ventricular wall thickness (LVWT), LV ejection fraction, E/e’ ratio were determined. Global longitudinal LV strain (GLS) and LA strain parameters (LAɛ, SSr, ASr) were assessed by speckle tracking echocardiography. Patients were divided into two groups according to the presence (30 pts) or absence (80 pts) of documented paroxysmal AF (24/48 h ambulatory ECG recordings) Results Patients with AF were older than pts without AF (p &lt; 0.001). LAD, LAVi, E/e’ were significantly higher, while LAɛ, ESr, ASr were significantly lower in pts with AF compared to pts without AF (p &lt; 0.05 for all). There were no significant differences between pts with and without AF regarding: gender, LVWT, GLS, the presence and severity of LV outflow tract obstruction (p &gt; 0.05 for all). The correlates of AF in the whole HCM study population were: age (OR = 1.05, p = 0.001), ASr (OR = 10.1, p &lt; 0.001), LAVi (OR = 1.03, p = 0.004), LAD (OR = 1.2, p = 0.001), E/e’(OR = 1.05, p = 0.02) and mitral regurgitation degree (OR = 1.6, p = 0.04). ASr had the best area under the curve (AUC: 0.74) with a cutoff of -0.88 s-1 for identifying HCM patients with AF (sensitivity: 80%, specificity: 65%). At multivariable logistic regression analysis, age, LAVi and ASr emerged as the only independent correlates of AF. 14 of the 71 patients with a LAD &lt; 45 mm had paroxysmal AF. In this selected population, pts with AF were older (p = 0.001), had higher values for E/e’ (p = 0.04) and lower values for ASr (p = 0.02) than pts without AF. Moreover, in this subgroup of pts, at multivariable logistic regression analysis, ASr correlated with AF independently of age, LA dimensions, LV hypertrophy or E/e’ (OR = 10.008, 95% CI 1.297-77.219, p = 0.02). Conclusions In pts with HCM, age, LAVi and ASr, were independently related to the presence of AF, while LAD was not. Moreover, in the subgroup of HCM pts with LAD &lt; 45 mm, ASr (reflecting LA contractile function) was the only LA remodelling parameter correlated with the presence of AF. The assessment of LA volume and function can provide further insights into the risk stratification of pts with HCM, especially in pts considered at lower risk for AF based on the assessment of classical risk parameters, such as LAD.

Developing a Cerebral Palsy Risk Score for Newborns

2021 ◽  
Vol 104 (2) ◽  
pp. 240-246
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cerebral Palsy ◽  
High Risk ◽  
Risk Score ◽  
Low Birthweight ◽  
Prediction Score ◽  
University Hospital ◽  
P Value ◽  
Close Monitoring

Background: Cerebral palsy (CP) causes developmental delays, affecting quality of life. Many risk factors are theorized however, no total risks summary exists, nor a CP prediction score for newborns. The result is under surveillance, treatment delays, and non-rectifiable complications. Objective: To establish total risk factors and create a prediction score for assessing CP neonatal risk before discharge. A prediction score has great utility for medical professionals and parents in screening high-risk patients and developing adequate monitoring systems. Materials and Methods: Using a case-controlled retrospect of children aged 0 to 2 years, born at Thammasat University Hospital, Thailand between 2005 and 2014, prenatal, perinatal, and postnatal risks were compared between children without CP as control, and those diagnosed with CP as case, by multivariable logistic regression. Predictors were assessed with area under the receiver operating characteristic (AuROC), odds ratio (OR), 95% confidence interval (CI), p-value, and clinical predisposition. Logistic regression was applied, including calibration, validation, and categorization of risk. Results: Cerebral and non-cerebral malformations, multi-fetal gestation, low birthweight, and neonatal sepsis were found as potential predictors, scoring 3, 1.5, 1, 2, 2.5, respectively, AuROC being 0.86 (95% CI 0.79 to 0.92). Low, moderate, and high-risk groups were set with scores of less than 1, 1.5 to 3, and more than 3.5, respectively. Conclusion: The present predictive CP risks and scoring system shows excellent discrimination power. If newborns were categorized in the highrisk group, close monitoring and surveillance are needed. Keywords: Cerebral palsy, Risk score, Prenatal, Perinatal, Postnatal

scholarly journals Development of a New Sternal Dehiscence Prediction Scale for Decision Making in Sternal Closure Techniques After Cardiac Surgery

2020 ◽  
Author(s):  
Frank Harig ◽  
Ehab Nooh ◽  
Colin Griesbach ◽  
Michael Weyand ◽  
Johannes Rösch
Keyword(s):  
Logistic Regression ◽  
Risk Score ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Individual Risk ◽  
Dependent Diabetes Mellitus ◽  
Analysis Model ◽  
Multivariable Logistic Regression Model ◽  
Sternal Dehiscence ◽  
Multivariable Logistic Regression

Abstract BackgroundAfter sternotomy, the spectrum for sternal osteosynthesis comprises standard wiring and more complex techniques, like titanium plating. The aim of this study is to develop a predictive risk score that evaluates the risk of sternum instability individually. The surgeon may then choose an appropriate sternal osteosynthesis technique that is risk- adjusted as well as cost-effective.MethodsData from 7.173 patients operated via sternotomy for all cardiovascular indications from 2008 until 2017 were retrospectively analyzed. Sternal dehiscence occurred in 2.5% of patients (n=176). A multivariable analysis model examined pre- and intraoperative factors. A multivariable logistic regression model and a backward elimination based on the Akaike Information Criterion (AIC) a logistic model were selected.ResultsThe model showed good sensitivity and specificity (area under the receiver-operating characteristic curve, AUC: 0.76) and several predictors of sternal instability could be evaluated. Multivariable logistic regression showed the highest Odds Ratios (OR) for reexploration (OR 6.6, confidence interval, CI [4.5-9.5], p <0.001), obesity (body mass index, BMI >35kg/m²) (OR 4.23, [CI 2.4-7.3], p<0.001), insulin-dependent diabetes mellitus (IDDM) (OR 2.2, CI [1.5-3.2], p=0.01), smoking (OR 2.03, [CI 1.3-3.08], p=0.001). After weighting the probability of sternum dehiscence with each factor, a risk score model was proposed scaling from -1 to 5 points. This resulted in a risk score ranging up to 18 points, with an estimated risk for sternum complication up to 74%.ConclusionsA weighted scoring system based on individual risk factors was specifically created to predict sternal dehiscence. High-scoring patients should receive additive closure techniques.

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