scholarly journals Risk Stratification for Organ/Space Surgical Site Infection in Advanced Digestive System Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Chen Sun ◽  
Hui Gao ◽  
Yuelun Zhang ◽  
Lijian Pei ◽  
Yuguang Huang
Keyword(s):  
Risk Factors ◽  
Clinical Trial ◽  
Logistic Regression ◽  
Risk Stratification ◽  
Surgical Site Infection ◽  
Digestive System ◽  
Logistic Regression Model ◽  
Site Infection ◽  
Multivariable Logistic Regression Model ◽  
Digestive System Cancer

BackgroundOrgan/space surgical site infection (organ/space SSI) is a serious postoperative complication, closely related to a poor prognosis. Few studies have attempted to stratify the risk of organ/space SSI for patients with advanced digestive system cancer. This study aimed to identify a simple risk stratification for these patients based on perioperative factors.MethodsThe study was based on two randomized controlled trials (RCT) (NCT02715076, ChiCTR-IPR-17011099), including 839 patients undergoing elective radical resection of advanced digestive system cancer. The primary outcome was organ/space SSI within 30 days after surgery. Multivariable logistic regression model was used to identify risk factors. The risk of organ/space SSI stratified over those risk factors was compared using chi-square tests and the relative risk (RR) was estimated.ResultsAmong the 839 patients, 51 developed organ/space SSI (6.1%) within 30 days after surgery. According to the multivariable logistic regression model, 3 procedure types, including gastrectomy (OR=8.22, 95% CI: 2.71-24.87, P<0.001), colorectal resection (OR=8.65, 95% CI: 3.13-23.85, P<0.001) and pancreatoduodenectomy (OR=7.72, 95% CI: 2.95-20.21, P<0.001), as well as anaesthesia time > 4 h (OR=2.38, 95% CI: 1.08-5.27, P=0.032) and prolonged ICU stay (OR=4.10, 95% CI: 1.67-10.10, P=0.002), were risk factors for postoperative organ/space SSI. The number of risk factors was significantly associated with an increased risk of organ/space SSI (P<0.001), which was 2.8% in patients with 0-1 risk factor (RR=0.20, 95% CI: 0.11-0.35), 13.0% in patients with 2 risk factors (RR=3.64, 95% CI: 2.14-6.20) and 35.7% in patients with 3 risk factors (RR=6.41, 95% CI: 3.01-13.65).ConclusionThis study is a preliminary exploratory and provides a simple risk stratification to identify the risk of postoperative organ/space SSI for patients with advanced digestive system cancer. Further research is needed to validate and generalize the results in a wider population.Clinical Trial RegistrationClinicalTrials.gov, identifier NCT02715076; Chinese Clinical Trial Registry [https://www.chictr.org.cn/enindex.aspx], identifier ChiCTR-IPR-17011099.

scholarly journals Risk Stratification for Organ/Space Surgical Site Infection in Digestive System Cancer: A Prospective Cohort Study

2021 ◽  
Author(s):  
Chen Sun ◽  
Hui Gao ◽  
Yuelun Zhang ◽  
Lijian Pei ◽  
Yuguang Huang
Keyword(s):  
Risk Factors ◽  
Cohort Study ◽  
Risk Stratification ◽  
Surgical Site Infection ◽  
Prospective Cohort Study ◽  
Prospective Cohort ◽  
Digestive System ◽  
Site Infection ◽  
Digestive System Cancer ◽  
Risk Stratification Score

Abstract Background: Organ/space surgical site infection (organ/space SSI) is one of the serious postoperative complications, closely related to a poor prognosis. Few studies have attempted to design risk scoring systems for patients with digestive system cancer. This study aimed to develop a simple and practical risk stratification score for these patients to identify a priori risk of organ/space SSI.Methods: This prospective cohort study was based on two prospective studies (NCT02756910, ChiCTR-IPR-17011099), including patients undergoing elective radical resection of digestive system cancer. Logistic regression analysis was used to identify the determinant variables. The incidence of organ/space SSI stratified over perioperative factors was compared and compounded in a risk score.Results: Among the 839 patients, 51 developed organ/space SSI (6.1%) within 30 days after surgery. Patients undergoing gastrectomy (OR=8.466, 95% CI: 2.728-26.270, P<0.001), colorectal resection (OR=11.180, 95% CI: 3.921-31.881, P<0.001) and pancreatoduodenectomy (OR=9.054, 95% CI: 3.329-24.624, P<0.001) with an anaesthesia time > 4 h (OR=2.335, 95% CI: 1.035-5.271, P=0.041) and prolonged intensive care unit (ICU) stays > 24 h (OR=4.243, 95% CI: 1.715-10.498, P=0.002) had a significantly higher risk of organ/space SSI. These risk factors (procedure type, anaesthesia time, prolonged ICU stays) were also associated with an increase in organ/space SSI rates based on a compounded score (P<0.001). Comparisons with the overall population revealed that patients with 0 or 1 risk factor (n=602) had an organ/space SSI rate of 2.8% (RR=0.197, 95% CI: 0.112-0.345), those with 2 risk factors (n=223) had an organ/space SSI rate of 13.0% (RR=3.641; 95% CI: 2.138-6.202), and those with 3 risk factors (n=14) had an organ/space SSI rate of 35.7% (RR=6.405, 95% CI: 3.005-13.653).Conclusion: The risk stratification score in this study provides a simple and practical tool to stratify patients with digestive system cancer so that the relative risk of developing postoperative organ/space SSIs can be predicted.Trial Registration: This study was based on one randomized controlled trial (NCT02756910) registered at ClinicalTrials.gov on April 29, 2016 and one prospective cohort study (ChiCTR-IPR-17011099) registered at the Chinese Clinical Trial Registry on April 9, 2017.

Surgical Site Infection in a Tertiary Neonatal Surgery Centre

2018 ◽  
Vol 29 (03) ◽  
pp. 260-265 ◽  
Author(s):  
Adiam Woldemicael ◽  
Sarah Bradley ◽  
Caroline Pardy ◽  
Justin Richards ◽  
Paolo Trerotoli ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Model ◽  
Surgical Site Infection ◽  
Hospital Stay ◽  
Logistic Regression Model ◽  
Length Of Hospital Stay ◽  
Neonatal Surgery ◽  
Site Infection ◽  
Increased Risk

Introduction Surgical site infection (SSI) is a key performance indicator to assess the quality of surgical care. Incidence and risk factors for SSI in neonatal surgery are lacking in the literature. Aim To define the incidence of SSI and possible risk factors in a tertiary neonatal surgery centre. Materials and Methods This is a prospective cohort study of all the neonates who underwent abdominal and thoracic surgery between March 2012 and October 2016. The variables analyzed were gender, gestational age, birth weight, age at surgery, preoperative stay in neonatal intensive care unit, type of surgery, length of stay, and microorganisms isolated from the wounds. Statistical analysis was done with chi-square, Student's t- or Mann–Whitney U-tests. A logistic regression model was used to evaluate determinants of risk for SSI; variables were analyzed both with univariate and multivariate models. For the length of hospital stay, a logistic regression model was performed with independent variables. Results A total of 244 neonates underwent 319 surgical procedures. The overall incidence of SSIs was 43/319 (13.5%). The only statistical differences between neonates with and without SSI were preoperative stay (<4 days vs. ≥4 days, p < 0.01) and length of hospital stay (<30 days vs. ≥30 days, p < 0.01). A pre-operative stay longer than 4 days was associated with almost three times increased risk of SSI (odds ratio [OR] 2.96, 95% confidence interval [CI] 1.05–8.34, p = 0.0407). Gastrointestinal procedures were associated with more than ten times the risk of SSI compared with other procedures (OR 10.17, 95% CI 3.82–27.10, p < 0.0001). Gastroschisis closure and necrotizing enterocolitis (NEC) laparotomies had the highest incidence SSI (54% and 62%, respectively). The risk of longer length of hospital stay after SSI was more than three times higher (OR = 3.36, 95%CI 1.63–6.94, p = 0.001). Conclusion This is the first article benchmarking the incidence of SSI in neonatal surgery in the United Kingdom. A preoperative stay ≥4 days and gastrointestinal procedures were independent risk factors for SSI. More research is needed to develop strategies to reduce SSI in selected neonatal procedures.

Independent Predictors of In-Hospital Mortality in Elderly and Non-elderly Adult Patients Undergoing Emergency Admission for Hemorrhoids

2022 ◽  
pp. 000313482110604
Author(s):  
Lior Levy ◽  
Abbas Smiley ◽  
Rifat Latifi
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Elderly Patients ◽  
Diagnostic Procedure ◽  
Logistic Regression Model ◽  
Emergency Admission ◽  
Adult Patients ◽  
Elderly Adult ◽  
Multivariable Logistic Regression Model ◽  
Invasive Diagnostic Procedure

Background The study explored determinants of mortality of admitted emergently patients with the primary diagnosis of hemorrhoids, during the years 2005-2014. Methods Demographics, clinical data, and outcomes were obtained from the National Inpatient Sample, 2005-2014, in elderly (65+ years) and non-elderly adult patients (18-64 years) with hemorrhoids who underwent emergency admission. Multivariable logistic regression model with backward elimination was used to identify predictors of mortality. Results 25 808 adult and 26 978 elderly patients were included. Female patients consisted of 42.5% and 59.3% in adult and elderly, respectively. 42 (.2%) adults died, of which 50% were female and 125 (.5%) elderly patients died, of which 60% were female. Mean (SD) age of the adult patients was 47.8 (11) years and in elderly patients was 78.7 (8) years. 82.2% and 85.7% had internal hemorrhoids in adult and elderly patients, respectively. 9326 (36.1%) adult and 7282 (27%) elderly patients underwent an operation. In the final multivariable logistic regression model for adult patients with operation, delayed operation and invasive diagnostic procedures increased the odds of mortality, whereas in elderly patients, delayed operation and frailty index were the risk factors of mortality. In both adults and elderly with no operation, increased hospital length of stay (HLOS) significantly increased the odds of mortality, and undergoing an invasive diagnostic procedure significantly decreased the odds of mortality. Conclusion In all operated patients, increased time to operation and undergoing an invasive diagnostic procedure were the risk factors for mortality. On the other hand, in non-operated emergency hemorrhoids patients, increased age and increased HLOS were the risk factors for mortality while undergoing an invasive diagnostic procedure decreased the odds of mortality.

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.

scholarly journals Developing a Risk Stratification Model for Surgical Site Infection after Abdominal Hysterectomy

2009 ◽  
Vol 30 (11) ◽  
pp. 1077-1083 ◽  
Author(s):  
Margaret A. Olsen ◽  
James Higham-Kessler ◽  
Deborah S. Yokoe ◽  
Anne M. Butler ◽  
Johanna Vostok ◽  
...  
Keyword(s):  
Risk Factors ◽  
Health Insurance ◽  
Blood Transfusion ◽  
Risk Stratification ◽  
Surgical Site Infection ◽  
Private Health Insurance ◽  
Abdominal Hysterectomy ◽  
Site Infection ◽  
Independent Risk Factors ◽  
Duration Of Operation

Objective.The incidence of surgical site infection (SSI) after hysterectomy ranges widely from 2% to 21%. A specific risk stratification index could help to predict more accurately the risk of incisional SSI following abdominal hysterectomy and would help determine the reasons for the wide range of reported SSI rates in individual studies. To increase our understanding of the risk factors needed to build a specific risk stratification index, we performed a retrospective multihospital analysis of risk factors for SSI after abdominal hysterectomy.Methods.Retrospective case-control study of 545 abdominal and 275 vaginal hysterectomies from July 1, 2003, to June 30, 2005, at 4 institutions. SSIs were defined by using Centers for Disease Control and Prevention/National Nosocomial Infections Surveillance criteria. Independent risk factors for abdominal hysterectomy were identified by using logistic regression.Results.There were 13 deep incisional, 53 superficial incisional, and 18 organ-space SSIs after abdominal hysterectomy and 14 organ-space SSIs after vaginal hysterectomy. Because risk factors for organ-space SSI were different according to univariate analysis, we focused further analyses on incisional SSI after abdominal hysterectomy. The maximum serum glucose level within 5 days after operation was highest in patients with deep incisional SSI, lower in patients with superficial incisional SSI, and lowest in uninfected patients (median, 189, 156, and 141 mg/dL, respectively; P = .005). Independent risk factors for incisional SSI included blood transfusion (odds ratio [OR], 2.4) and morbid obesity (body mass index [BMI], >35; OR, 5.7). Duration of operation greater than the 75th percentile (OR, 1.7), obesity (BMI, 30–35; OR, 3.0), and lack of private health insurance (OR, 1.7) were marginally associated with increased odds of SSI.Conclusions.Incisional SSI after abdominal hysterectomy was associated with increased BMI and blood transfusion. Longer duration of operation and lack of private health insurance were marginally associated with SSI.

scholarly journals Surgical Site Infection After Emergency Abdominal Surgery in China: A Multicenter Prospective Study

2020 ◽  
Author(s):  
Ze Li ◽  
Hui Li ◽  
Pin Lv ◽  
Xingang Peng ◽  
Changliang Wu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Length Of Stay ◽  
Abdominal Surgery ◽  
Surgical Site Infection ◽  
Secondary Outcome ◽  
Microbial Culture ◽  
Site Infection ◽  
High Blood Glucose ◽  
Emergency Abdominal Surgery

Abstract Background There is still a lack of relevant studies on surgical site infection (SSI) after emergency abdominal surgery (EAS) in China. This study aims to understand the status of SSI after EAS in China and discuss its risk factors. Materials and Methods All adult patients who underwent EAS in 47 hospitals in China from May 1 to 31, 2018, and from May 1 to June 7, 2019, were enrolled in this study. The basic information, perioperative data, and microbial culture results of infected incision were prospectively collected.The primary outcome measure was the incidence of SSI after EAS, and the secondary outcome variables were postoperative length of stay, ICU admission rate, ICU length of stay, 30-day postoperative mortality, and treatment costs. Univariate and multivariate logistic regression were used to analyze the risk factors.Results A total of 953 patients (age 48.8 ± 17.9 years, male 51.9%) with EAS were included in this study: 71 patients (7.5%) developed SSI after surgery.The main pathogen of SSI was Escherichia coli (culture positive rate 29.6%). Patients with SSI had significantly longer overall hospital (p < 0.001) and ICU stays (p < 0.001), significantly higher ICU admissions (p < 0.001), and medical costs (p < 0.001) than patients without SSI.Multivariate logistic regression analysis showed that male (P = 0.010), high blood glucose level (P < 0.001), colorectal surgery (P < 0.001), intestinal obstruction (P = 0.045) and surgical duration (P = 0.007) were risk factors for SSI, whereas laparoscopic surgery (P < 0.001 = 0.022) was a protective factor. Conclusion This study found a high incidence of SSI after EAS in China. The occurrence of SSI prolongs the patient's hospital stay and increases the medical burden. The study also revealed predictors of SSI after EAS and provides a basis for the development of norms for the prevention of surgical site infection after emergency abdominal surgery.

scholarly journals 994. Risk for Viral Rebound in the Era of U=U; A CNICS Analysis

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S525-S526
Author(s):  
Blake Hansen ◽  
Tao Liu ◽  
Lauri Bazerman ◽  
Mari-Lynn Drainoni ◽  
Fizza S Gillani ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Viral Suppression ◽  
Viral Rebound ◽  
Research Support ◽  
Multivariable Logistic Regression Model ◽  
Multivariable Logistic Regression

Abstract Background The “Undetectable equals Untransmittable (U=U)” HIV prevention campaign is a cornerstone of HIV prevention. However, there are few recommendations to guide patients and providers in U=U implementation and limited data on risk factors for viral rebound among persons eligible for U=U. Methods We conducted a retrospective multi-center study using data from the CNICS HIV research network to identify risk factors for viral rebound among persons with established viral suppression [two viral loads (VL) and all VLs of &lt; 200 copies/ul within a one-year period (U=U eligible)]. Demographics, patient-reported outcomes, and longitudinal clinical data from 21,359 persons with HIV were analyzed. To include missing data in the analysis, they were treated as a separate category. The primary outcome of viral rebound was defined as any VL &gt; 200 copies/ul within two years after U=U eligibility. A univariable logistic regression model was conducted to identify predictors of viral rebound. Significant variables (p&lt; 0.05) were included in a multivariable logistic regression model. Predictive values of individual variables were captured by adjusted odds ratios (aORs). Results From 2011-2019, 12,150 patients met criteria for U=U eligibility and had two years of follow up data. The median age was 46 (IQR: 38-53); 68% male; 51% were white, 39% black. 1544 (13%) experienced viral rebound during follow-up. Forest plot summaries of univariable and multivariable logistic regression models are in Figures 1&2. In multivariable analysis, Black race (aOR=1.56, p&lt; 0.001); MSM-IDU risk (aOR=1.38, p=0.006); lower QoL score (aOR=1.49, p=0.005); poorer ART adherence (aOR=1.84, p&lt; 0.001); duration of lifetime ART [aOR=1.47 (10+yrs), = 1.37 (5-10 yrs); and = 1.28 (2-5 yrs), p&lt; 0.001]; use of InSTIs after eligibility (aOR=1.60, p&lt; 0.001); current smoker (aOR=1.49, p&lt; 0.001), current amphetamine (aOR=1.83, p&lt; 0.001) or cocaine use (aOR=1.46, p=0.012), were associated with viral rebound. In both analyses, older age was protective against viral rebound. Figure 1. Summary of Univariate Logistic Regression Model Figure 2. Summary of Multivariable Logistic Regression Model Conclusion We identified multiple risk factors for viral rebound among PWH with viral suppression. Further research is needed to identify synergistic risk factors that increase probability of viral rebound to inform optimal implementation of U=U. Disclosures Edward Cachay, MD, MAS, Gilead (Consultant, Grant/Research Support)Merck Sciences (Grant/Research Support) Heidi Crane, MD, MPH, ViiV (Grant/Research Support) Benigno Rodriguez, MD, Gilead (Speaker’s Bureau)ViiV (Speaker’s Bureau)

scholarly journals Prospective multicenter study on the incidence of surgical site infection after emergency abdominal surgery in China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ze Li ◽  
Hui Li ◽  
Pin Lv ◽  
Xingang Peng ◽  
Changliang Wu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Length Of Stay ◽  
Abdominal Surgery ◽  
Surgical Site Infection ◽  
Secondary Outcome ◽  
Site Infection ◽  
Multivariate Logistic Regression ◽  
High Blood Glucose ◽  
Emergency Abdominal Surgery

AbstractThere is still a lack of relevant studies on surgical site infection (SSI) after emergency abdominal surgery (EAS) in China. This study aims to understand the incidence of SSI after EAS in China and discuss its risk factors. All adult patients who underwent EAS in 47 hospitals in China from May 1 to 31, 2018, and from May 1 to June 7, 2019, were enrolled in this study. The basic information, perioperative data, and microbial culture results of infected incision were prospectively collected. The primary outcome measure was the incidence of SSI after EAS, and the secondary outcome variables were postoperative length of stay, ICU admission rate, ICU length of stay, 30-day postoperative mortality, and hospitalization cost. Univariate and multivariate logistic regression were used to analyze the risk factors. The results were expressed as the odds ratio and 95% confidence interval. A total of 953 patients [age 48.8 (SD: 17.9), male 51.9%] with EAS were included in this study: 71 patients (7.5%) developed SSI after surgery. The main pathogen of SSI was Escherichia coli (culture positive rate 29.6%). Patients with SSI had significantly longer overall hospital (p < 0.001) and ICU stays (p < 0.001), significantly higher ICU admissions (p < 0.001), and medical costs (p < 0.001) than patients without SSI. Multivariate logistic regression analysis showed that male (P = 0.010), high blood glucose level (P < 0.001), colorectal surgery (P < 0.001), intestinal obstruction (P = 0.045) and surgical duration (P = 0.007) were risk factors for SSI, whereas laparoscopic surgery (P < 0.001) was a protective factor. This study found a high incidence of SSI after EAS in China. The occurrence of SSI prolongs the patient's hospital stay and increases the medical burden. The study also revealed predictors of SSI after EAS and provides a basis for the development of norms for the prevention of surgical site infection after emergency abdominal surgery.

scholarly journals Heart Rate n-Variability (HRnV) Measures for Prediction of Mortality in Sepsis Patients Presenting at the Emergency Department

2021 ◽  
Author(s):  
Nan Liu ◽  
Marcel Lucas Chee ◽  
Mabel Zhi Qi Foo ◽  
Jeremy Zhenwen Pong ◽  
Dagang Guo ◽  
...  
Keyword(s):  
Heart Rate ◽  
Logistic Regression ◽  
Risk Stratification ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Primary Outcome ◽  
Univariable Analysis ◽  
Sepsis Mortality ◽  
Multivariable Logistic Regression Model ◽  
Multivariable Logistic Regression

AbstractBackgroundSepsis is a potentially life threatening condition that requires prompt recognition and treatment for optimal outcomes. There is little consensus on an objective way to assess for sepsis severity and risk for mortality. In recent years, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality, and its use as a prognostic variable and for risk stratification has been promising. In this paper, we present using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and compare against current mortality prediction scores.MethodsThis study was a retrospective cohort study on a convenience sample of patients presenting to the emergency department (ED) of Singapore General Hospital between September 2014 to April 2017. Patients were included in the study if they were above 21 years old, were suspected to have sepsis by their attending physician, triaged as emergency or urgent cases, and if they met two or more of the Systemic Inflammatory Response Syndrome (SIRS) criteria. Demographic and clinical variables were obtained from the electronic medical records, and HRV and novel HRnV parameters were calculated from five minute ECG tracings. Univariable analysis was conducted on variables obtained, with the primary outcome being 30-day in-hospital mortality (IHM). Variables selected through univariable analysis and stepwise selection were included in a multivariable logistic regression model, the results of which were presented using receiver operating curve (ROC) analysis.ResultsOf 342 patients included for final analysis, 66 (19%) met with the primary outcome. On univariable analysis, 85 out of 142 analysed HRV and HRnV parameters showed statistical difference between groups. The final multivariable logistic regression model comprised of 21 variables including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve (AUC) of the model was 0.86 (95% confidence interval 0.81-0.90), outperforming several established clinical scores.ConclusionThe use of novel HRnV measures can provide adequate power to predictive models in the risk stratification of patients presenting to the ED with sepsis. When included in a multivariable logistic regression model, the HRnV-based model outperformed traditional risk stratification scoring systems. The HRnV measures may have potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality.

Finding a Method for Optimizing Risk Adjustment When Comparing Surgical-Site Infection Rates

2004 ◽  
Vol 25 (4) ◽  
pp. 313-318 ◽  
Author(s):  
Christian Brandt ◽  
Sonja Hansen ◽  
Dorit Sohr ◽  
Franz Daschner ◽  
Henning Rüden ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Surgical Site Infection ◽  
Regression Models ◽  
Predictive Power ◽  
Risk Index ◽  
Significant Risk ◽  
Site Infection ◽  
Logistic Regression Models ◽  
System Risk

AbstractObjective:To investigate whether stratification of the risk of developing a surgical-site infection (SSI) is improved when a logistic regression model is used to weight the risk factors for each procedure category individually instead of the modified NNIS System risk index.Design and Setting:The German Nosocomial Infection Surveillance System, based on NNIS System methodology, has 273 acute care surgical departments participating voluntarily. Data on 9 procedure categories were included (214,271 operations).Methods:For each of the procedure categories, the significant risk factors from the available data (NNIS System risk index variables of ASA score, wound class, duration of operation, and endoscope use, as well as gender and age) were identified by multiple logistic regression analyses with stepwise variable selection. The area under the receiver operating characteristic (ROC) curve resulting from these analyses was used to evaluate the predictive power of logistic regression models.Results:For most procedures, at least two of the three variables contributing to the NNIS System risk index were shown to be independent risk factors (appendectomy, knee arthroscopy, cholecystectomy, colon surgery, herniorrhaphy, hip prosthesis, knee prosthesis, and vascular surgery). The predictive power of logistic regression models (including age and gender, when appropriate) was low (between 0.55 and 0.71) and for most procedures only slightly better than that of the NNIS System risk index.Conclusion:Without the inclusion of additional procedure-specific variables, logistic regression models do not improve the comparison of SSI rates from various hospitals.

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