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 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.

scholarly journals 62. Factors Associated with 30-Day ED Readmission Following Initial ED Discharge for Suspected Sepsis

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S51-S51
Author(s):  
Anna E Moscowitz ◽  
Esther Y Bae ◽  
Ricardo M La Hoz ◽  
James B Cutrell ◽  
Marguerite Monogue
Keyword(s):  
Logistic Regression ◽  
Medical Center ◽  
Multivariable Analysis ◽  
P Value ◽  
Multivariable Logistic Regression Model ◽  
Suspected Sepsis ◽  
Screening Criteria ◽  
Factors Associated ◽  
Multivariable Logistic Regression ◽  
Increased Risk

Abstract Background Given the increased mortality associated with delayed recognition of sepsis, emergency departments (ED) often use protocols to rapidly identify and treat suspected sepsis. However, screening criteria such as systemic inflammatory response syndrome (SIRS) lack specificity and may over-diagnose sepsis in patients otherwise stable for discharge. Our study describes outcomes and identifies factors associated with ED readmission in those initially discharged directly from the ED who met sepsis criteria. Methods This retrospective cohort study evaluated adult patients (≥ 18 years) seen in the ED at UTSW Medical Center from January to June 2018 who met all the following: ≥ 2 SIRS criteria; received ≥ 1 dose of intravenous (IV) broad-spectrum antibiotic(s) in the ED; were discharged home. A multivariable logistic regression model identified factors associated with 30-day re-admission to our ED, using clinically significant variables parsimoniously. A two-sided P value &lt; 0.05 was considered significant. Results A total of 179 patients were included. Forty-four patients (25%) returned to the ED within 30 days of their initial visit; of those 44, 63.6% (28) returned for issues related to their prior visit, and 50% (22) were admitted to the hospital. Table 1 compares baseline demographics of patients with suspected sepsis readmitted to the ED with those not readmitted within 30 days after initial ED discharge. In univariable analysis, quick Sequential Organ Failure Assessment (qSOFA), and length of antibiotic therapy (ED plus discharge antibiotics) were associated with ED re-admission (table 1). Receipt of antibiotics on discharge was not significant. In the final multivariable analysis (table 2), initial qSOFA ≥ 2 alone was associated with increased risk of ED re-admission (OR 7.5, p=0.01). Table 1. Baseline demographics of patients readmitted and not readmitted to the ED within 30 days after ED discharge with suspected sepsis Table 2. Multivariable logistic regression of risk factors for patients readmitted and not readmitted to the ED within 30 days after ED discharge with suspected sepsis Conclusion In this cohort, 25% of patients with suspected sepsis initially discharged from the ED were readmitted to our ED within 30 days. A qSOFA ≥ 2 at the initial ED visit was associated with increased risk of readmission, suggesting a potential use of qSOFA to triage those warranting admission or closer follow-up. Larger prospective studies are warranted in this understudied population of patients who meet screening sepsis criteria but are discharged from the ED. Disclosures All Authors: No reported disclosures

scholarly journals Risk score to stratify miscarriage risk levels in preconception women

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xin Hui Choo ◽  
Chee Wai Ku ◽  
Yin Bun Cheung ◽  
Keith M. Godfrey ◽  
Yap-Seng Chong ◽  
...  
Keyword(s):  
Risk Factors ◽  
Risk Score ◽  
Smoking Status ◽  
Characteristic Curve ◽  
Lifestyle Changes ◽  
Risk Scores ◽  
Risk Level ◽  
Multivariable Logistic Regression Model ◽  
Spontaneous Miscarriage ◽  
Risk Levels

AbstractSpontaneous miscarriage is one of the most common complications of pregnancy. Even though some risk factors are well documented, there is a paucity of risk scoring tools during preconception. In the S-PRESTO cohort study, Asian women attempting to conceive, aged 18-45 years, were recruited. Multivariable logistic regression model coefficients were used to determine risk estimates for age, ethnicity, history of pregnancy loss, body mass index, smoking status, alcohol intake and dietary supplement intake; from these we derived a risk score ranging from 0 to 17. Miscarriage before 16 weeks of gestation, determined clinically or via ultrasound. Among 465 included women, 59 had miscarriages and 406 had pregnancy ≥ 16 weeks of gestation. Higher rates of miscarriage were observed at higher risk scores (5.3% at score ≤ 3, 17.0% at score 4–6, 40.0% at score 7–8 and 46.2% at score ≥ 9). Women with scores ≤ 3 were defined as low-risk level (< 10% miscarriage); scores 4–6 as intermediate-risk level (10% to < 40% miscarriage); scores ≥ 7 as high-risk level (≥ 40% miscarriage). The risk score yielded an area under the receiver-operating-characteristic curve of 0.74 (95% confidence interval 0.67, 0.81; p < 0.001). This novel scoring tool allows women to self-evaluate their miscarriage risk level, which facilitates lifestyle changes to optimize modifiable risk factors in the preconception period and reduces risk of spontaneous miscarriage.

scholarly journals Development and validation of a clinical and genetic model for predicting risk of severe COVID-19

2021 ◽  
Author(s):  
Gillian S. Dite ◽  
Nicholas M. Murphy ◽  
Richard Allman
Keyword(s):  
Logistic Regression ◽  
Genetic Model ◽  
Characteristic Curve ◽  
Accurate Prediction ◽  
Training Dataset ◽  
Validation Dataset ◽  
Individual Risk ◽  
Prototype Model ◽  
List Type ◽  
New Model

SummaryClinical and genetic risk factors for severe COVID-19 are often considered independently and without knowledge of the magnitudes of their effects on risk. Using SARS-CoV-2 positive participants from the UK Biobank, we developed and validated a clinical and genetic model to predict risk of severe COVID-19. We used multivariable logistic regression on a 70% training dataset and used the remaining 30% for validation. We also validated a previously published prototype model. In the validation dataset, our new model was associated with severe COVID-19 (odds ratio per quintile of risk=1.77, 95% confidence interval [CI]=1.64, 1.90) and had excellent discrimination (area under the receiver operating characteristic curve=0.732, 95% CI=0.708, 0.756). We assessed calibration using logistic regression of the log odds of the risk score, and the new model showed no evidence of over- or under-estimation of risk (α=−0.08; 95% CI=−0.21, 0.05) and no evidence or over- or under-dispersion of risk (β=0.90, 95% CI=0.80, 1.00). Accurate prediction of individual risk is possible and will be important in regions where vaccines are not widely available or where people refuse or are disqualified from vaccination, especially given uncertainty about the extent of infection transmission among vaccinated people and the emergence of SARS-CoV-2 variants of concern.Key resultsAccurate prediction of the risk of severe COVID-19 can inform public heath interventions and empower individuals to make informed choices about their day-to-day activities.Age and sex alone do not accurately predict risk of severe COVID-19.Our clinical and genetic model to predict risk of severe COVID-19 performs extremely well in terms of discrimination and calibration.

scholarly journals Tocilizumab for patients with COVID-19 pneumonia. The single-arm TOCIVID-19 prospective trial

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Francesco Perrone ◽  
◽  
Maria Carmela Piccirillo ◽  
Paolo Antonio Ascierto ◽  
Carlo Salvarani ◽  
...  
Keyword(s):  
Logistic Regression ◽  
A Priori ◽  
Prospective Trial ◽  
Respiratory Support ◽  
Validation Dataset ◽  
Multivariable Logistic Regression Analysis ◽  
Phase 2 ◽  
Multivariable Logistic Regression Model ◽  
Intention To Treat ◽  
Multivariable Logistic Regression

Abstract Background Tocilizumab blocks pro-inflammatory activity of interleukin-6 (IL-6), involved in pathogenesis of pneumonia the most frequent cause of death in COVID-19 patients. Methods A multicenter, single-arm, hypothesis-driven trial was planned, according to a phase 2 design, to study the effect of tocilizumab on lethality rates at 14 and 30 days (co-primary endpoints, a priori expected rates being 20 and 35%, respectively). A further prospective cohort of patients, consecutively enrolled after the first cohort was accomplished, was used as a secondary validation dataset. The two cohorts were evaluated jointly in an exploratory multivariable logistic regression model to assess prognostic variables on survival. Results In the primary intention-to-treat (ITT) phase 2 population, 180/301 (59.8%) subjects received tocilizumab, and 67 deaths were observed overall. Lethality rates were equal to 18.4% (97.5% CI: 13.6–24.0, P = 0.52) and 22.4% (97.5% CI: 17.2–28.3, P < 0.001) at 14 and 30 days, respectively. Lethality rates were lower in the validation dataset, that included 920 patients. No signal of specific drug toxicity was reported. In the exploratory multivariable logistic regression analysis, older age and lower PaO2/FiO2 ratio negatively affected survival, while the concurrent use of steroids was associated with greater survival. A statistically significant interaction was found between tocilizumab and respiratory support, suggesting that tocilizumab might be more effective in patients not requiring mechanical respiratory support at baseline. Conclusions Tocilizumab reduced lethality rate at 30 days compared with null hypothesis, without significant toxicity. Possibly, this effect could be limited to patients not requiring mechanical respiratory support at baseline. Registration EudraCT (2020-001110-38); clinicaltrials.gov (NCT04317092).

scholarly journals Evaluating the Validity of Risk Scoring in Predicting Pacemaker Rates following Transcatheter Aortic Valve Replacement

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
Alexander M. Spring ◽  
Michael A. Catalano ◽  
Vikram Prasad ◽  
Bruce Rutkin ◽  
Elana Koss ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Aortic Valve Replacement ◽  
Valve Replacement ◽  
Risk Score ◽  
Transcatheter Aortic Valve Replacement ◽  
Characteristic Curve ◽  
Multivariable Analysis ◽  
Postoperative Management ◽  
Transcatheter Aortic Valve ◽  
The Individual

Introduction. Requirement of permanent pacemaker (PPM) implantation is a known and common postoperative consequence of transcatheter aortic valve replacement (TAVR). The Emory risk score has been recently developed to help risk stratify the need for PPM insertion in patients undergoing TAVR with SAPIEN 3 valves. Our aim was to assess the validity of this risk score in our patient population, as well as its applicability to patients receiving self-expanding valves. Methods. We conducted a retrospective review of 479 TAVR patients without preoperative pacemakers from November 2016 through December 2018. Preoperative risk factors included in the Emory risk score were collected for each patient: preoperative QRS, preoperative right bundle branch block (RBBB), preoperative syncope, and degree of valve oversizing. Multivariable analysis of the individual variables within the scoring system to identify predictors of PPM placement was performed. The predictive discrimination of the risk score for the risk of PPM placement after TAVR was assessed with the area under the receiver operating characteristic curve (AUC). Results. Our results demonstrated that, of the 479 patients analyzed, 236 (49.3%) received balloon-expandable valves and 243 (50.7%) received self-expanding valves. Pacemaker rates were higher in patients receiving self-expanding valves than those receiving balloon-expandable valves (25.1% versus 16.1%, p = 0.018 ). The Emory risk score showed a moderate correlation with pacemaker requirement in patients receiving each valve type, with AUC for balloon-expandable and self-expanding valves of 0.657 and 0.645, respectively. Of the four risk score components, preoperative RBBB was the only predictor of pacemaker requirement with an AUC of 0.615 for both balloon-expandable and self-expanding valves. Conclusion. In our cohort, the Emory risk score had modest predictive utility for PPM insertion after balloon-expandable and self-expanding TAVR. The risk score did not offer better discriminatory utility than that of preoperative RBBB alone. Understanding the determinants of PPM insertion after TAVR can better guide patient education and postoperative management.

scholarly journals 1244. Evaluation of Intraoperative Topical Vancomycin and the Incidence of Acute Kidney Injury

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S448-S448
Author(s):  
Alison L Blackman ◽  
Sabeen Ali ◽  
Xin Gao ◽  
Rosina Mesumbe ◽  
Carly Cheng ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Kidney Injury ◽  
Logistic Regression ◽  
Serum Creatinine ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Kidney Injury ◽  
Topical Formulation ◽  
Multivariable Logistic Regression Model ◽  
Multivariable Logistic Regression

Abstract Background The use of intraoperative topical vancomycin (VAN) is a strategy aimed to prevent surgical site infections (SSI). Although there is evidence to support its efficacy in SSI prevention following orthopedic spine surgeries, data describing its safety, specifically acute kidney injury (AKI) risk, is limited. The purpose of this study was to determine the AKI incidence associated with intraoperative topical VAN. Methods This is a retrospective cohort study reviewing patient encounters where intraoperative topical VAN was administered from February 2018 to July 2018. All adult patients ( ≥18 years) that received topical VAN in the form of powder, beads, rods, paste, cement spacers, or unspecified topical routes were included. Patient encounters were excluded for AKI or renal replacement therapy (RRT) at baseline, ≤ 2 serum creatinine values drawn after surgery, and/or if irrigation was the only topical formulation given. The primary outcome was the percentage of patients who developed AKI after intraoperative topical VAN administration. AKI was defined as an increase in serum creatinine (SCr) ≥50% from baseline, an increase in SCr >0.5 from baseline, or0 if RRT was initiated after topical VAN was given. Secondary outcomes included analysis of AKI risk factors and SSI incidence. AKI risk factors were analyzed using a multivariable logistic regression model. Results A total of 589 patient encounters met study criteria. VAN powder was the most common formulation (40.9%), followed by unspecified topical routes (30.7%) and beads (9.9%%). Nonspinal orthopedic surgeries were the most common procedure performed 46.7%. The incidence of AKI was 8.7%. In a multivariable logistic regression model, AKI was associated with concomitant systemic VAN (OR 3.39, [3.39–6.22]) and total topical VAN dose. Each doubling of the topical dose was associated with increased odds of developing AKI (OR = 1.42, [1.08–1.86]). The incidence of SSI was 5.3%. Conclusion AKI rates associated with intraoperative topical VAN are comparable to that of systemic VAN. Total topical vancomycin dose and concomitant systemic VAN was associated with an increased AKI risk. Additional analysis is warranted to compare these patients to a similar population that did not receive topical VAN. Disclosures All authors: No reported disclosures.

Surgical Thoracoabdominal Aortic Aneurysm Repair in a Non-High-Volume Institution

2020 ◽  
Author(s):  
Takashi Kunihara ◽  
Claudia Vukic ◽  
Fumihiro Sata ◽  
Hans-Jaochim Schäfers
Keyword(s):  
Spinal Cord ◽  
Logistic Regression ◽  
Aortic Aneurysm ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Thoracoabdominal Aortic Aneurysm ◽  
Left Ventricular ◽  
Multivariable Logistic Regression Model ◽  
Multivariable Logistic Regression ◽  
Cord Injury

Abstract Background Surgical thoracoabdominal aortic aneurysm (TAAA) repair remains challenging. Apart from mortality, spinal cord injury (SCI) is a dreaded complication. We analyzed our experience to identify predictors for SCI in a nonhigh-volume institution. Patients and Methods All patients who underwent TAAA repair between February 1996 and November 2016 (n = 182) were enrolled. Most were male (n = 121; 66.4%), median age was 68 years (range: 21–84). Elective operations were performed in 153 instances (84.1%). Our approach to minimize SCI includes distal aortic perfusion, mild hypothermia, identification of the Adamkiewicz artery, and sequential aortic clamping. Cerebrospinal fluid drainage was introduced in 2001 and liberal use of selective visceral perfusion in 2006. Results Early mortality was 12.1%; it was 8.5% after elective procedures. Reduced left ventricular function, nonelective setting, older age, and longer bypass time were identified as independent predictors for mortality in multivariable logistic regression model. Permanent SCI was observed in nine patients (4.9%), of whom seven (3.8%) developed paraplegia. In a multivariable logistic regression model for paraplegia, peripheral arterial disease (PAD), Crawford type II repair, smaller body surface area, and era before 2001 were identified as independent predictors, whereas only PAD was significant for SCI. The incidence of paraplegia was 13.8% in extensive repair out of the first 91 cases, whereas it was improved up to 2.7% thereafter. Conclusion Using an integrated approach, acceptable outcome of TAAA repair can be achieved, even in a nonhigh-volume center. PAD and extensive involvement of the aorta are strong independent predictors for spinal cord deficit after TAAA repair.

Beyond TILs: Predictors of pathologic complete response (pCR) in triple-negative breast cancer (TNBC) patients with moderate tumor-infiltrating lymphocytes (TIL) receiving neoadjuvant therapy.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 572-572
Author(s):  
Nour Abuhadra ◽  
Kenneth R. Hess ◽  
Jennifer Keating Litton ◽  
Gaiane M Rauch ◽  
Alastair Mark Thompson ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Neoadjuvant Therapy ◽  
Logistic Regression Model ◽  
Stage I ◽  
Multivariable Logistic Regression Model ◽  
Ki 67 ◽  
Early Stage Disease ◽  
Cut Points ◽  
Multivariable Logistic Regression

572 Background: Increased TIL in TNBC is associated with higher rates of pCR. High TIL is also associated with improved disease free survival and overall survival. The aim of this study is to identify data cut-points of pre-treatment low, moderate and high TIL count based on pCR and to identify clinical and pathological predictors of pCR in patients with moderate TIL. Methods: We evaluated the relationship between pCR and TIL in 180 patients with stage I-III TNBC enrolled in the ARTEMIS trial (NCT02276443). Recursive portioning was used to identify cut-points. Clinical and pathological variables such as age at diagnosis, stage, race, histology as well as Ki-67, vimentin, and androgen receptor (AR) by immunohistochemistry, were evaluated in pts with moderate TIL. A multivariable logistic regression model identified variables independently, significantly associated with pCR. Results: Four TIL groups were identified with pCR rates of 23%, 31%, 48% and 78% respectively (p < 0.0001) (Table A). In the two combined moderate TIL groups, 90 (97%) pts were evaluable for the multivariate model. Stage I-II disease, high Ki-67 and low AR were associated with increased probability of pCR (Table B). The multivariable logistic regression model area under the ROC curve was 0.78 (95% CI=0.68-0.88; p<0.0001). A model of computed risk score [ Stage I-II (score 2)+Ki-67≥ 50% (score 1)+AR<10% (score 1)] predicted a probability of 67% for pCR when all three variables were favorable (Table). Conclusions: Four TIL groups were identified. In pts with moderate TIL levels, early stage disease, high Ki-67 and low AR were associated with increased probability of pCR with neoadjuvant therapy. [Table: see text]

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