scholarly journals Predicting and Preventing Postoperative Outcomes

2019 ◽  
Vol 32 (03) ◽  
pp. 149-156 ◽  
Author(s):  
Sung Lee ◽  
Andrew Russ
Keyword(s):  
Postoperative Complications ◽  
Colorectal Surgery ◽  
Modifiable Risk Factors ◽  
Risk Calculator ◽  
Improvement Program ◽  
Mortality And Morbidity ◽  
Know How ◽  
Operative Severity Score ◽  
American College Of Surgeons

AbstractComplications after colorectal surgery are common. Given the frequency of postoperative complications and their implications on quality of life, it is important to know how to predict and prevent the complications that we encounter. This article aims to provide ways to predict and prevent postoperative complications in colorectal surgery. Here, we review the predictive models, American College of Surgeons National Surgery Quality Improvement Program risk calculator and Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity on their practicality and usefulness. Additionally, this review summarizes nonmodifiable and modifiable risk factors in colorectal surgery, which are important for surgeons to understand to minimize and attempt to avoid postoperative complications as well as providing ways to optimize patients preoperatively. Thus, this review will provide information to surgeons to predict and prevent postoperative complications, how to optimize patients preoperatively and ultimately to help reduce their occurrence.

Estimation of risk in cancer patients undergoing palliative procedures by the American College of Surgeons risk calculator.

2014 ◽  
Vol 32 (31_suppl) ◽  
pp. 93-93
Author(s):  
Rodrigo Andres Rodriguez ◽  
Molly McClain ◽  
Bridget N. Fahy ◽  
Katherine Teresa Morris
Keyword(s):  
Postoperative Complications ◽  
Cancer Patients ◽  
Surgical Oncology ◽  
Patient Specific ◽  
Cancer Type ◽  
Complication Rates ◽  
Risk Calculator ◽  
Improvement Program ◽  
Specific Level ◽  
American College Of Surgeons

93 Background: Surgical palliation is defined as the use of a procedure in patients with incurable disease to relieve symptoms. The American College of Surgeons Risk Calculator (ACSRC) was created based on data from the National Surgical Quality Improvement Program to predict the risk of surgical complications on a patient specific level. Whether the ACSRC can accurately predict the risk of postoperative complications following palliative procedures in cancer patients is unknown. The purpose of this study was to determine if the ACSRC accurately predicted postoperative complication rates in this setting. Methods: Our surgical oncology database of patients treated from 2011 to 2013 was queried. Thirty-two patients who underwent palliative procedures were identified. Data extracted included: demographics, comorbidities, site and stage of cancer, type of procedure and post-operative complication rate and type. Risk assessment was performed for each patient using the ACSRC. Actual frequency of complications and length of stay (LOS) were compared to ACSRC predicted rate of complications and LOS. Results: See Table. Conclusions: The ACSRC is a powerful tool for aid in surgical decision-making; however, in the case of palliative procedures, it overestimated the risk of postoperative complications and underestimated the LOS. Overestimation of postoperative complications could result in fewer patients being offered potentially beneficial palliative procedures. [Table: see text]

Congenital Diaphragmatic Hernia: Demographics and 30-day Outcomes in Adults

2020 ◽  
pp. 000313482096006
Author(s):  
Joseph G. Brungardt ◽  
Quinn A. Nix ◽  
Kurt P. Schropp
Keyword(s):  
Postoperative Complications ◽  
Congenital Diaphragmatic Hernia ◽  
Diaphragmatic Hernia ◽  
Pediatric Population ◽  
Case Series ◽  
National Database ◽  
Improvement Program ◽  
American College Of Surgeons ◽  
Postoperative Diagnosis ◽  
Acs Nsqip Database

Background Congenital diaphragmatic hernia (CDH) is a pathology most often affecting the pediatric population, although adults can also be affected. Few studies exist of adults undergoing repair of this defect. Using a national database, we sought to determine demographics and outcomes of this population. Methods An analysis of the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database (2015-2018) was performed, capturing patients with postoperative diagnosis of CDH, distinct from ventral hernia. Two groups were created based upon surgical approach of open or minimally invasive (MIS) repair. Baseline demographics and outcomes were compared. Results 110 patients undergoing surgical correction of CDH were captured in the database. We found rates of return to the operating room (4.55%), postoperative respiratory failure (5.45%), and reintubation (3.64%) with no difference between groups. There was no mortality and no difference between groups in length of operation, discharge to home, or postoperative complications. Patients undergoing open repair had a longer length of stay than patients in the MIS group (6.47 ± 10.76 days vs. 3.68 ± 3.74 days, P = .0471). Mesh was used in MIS more often than the open group (47.30% vs. 5.56%, P < .0001). Discussion This study describes rates of postoperative complications in patients undergoing repair of CDH, and suggests outcomes those are equivalent between patients receiving open or MIS approaches. Further case series or retrospective studies are needed to further describe this population of patients.

scholarly journals Impact of the Choice of Risk Model for Identifying Low-risk Patients Using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines

2018 ◽  
Vol 129 (5) ◽  
pp. 889-900 ◽  
Author(s):  
Laurent G. Glance ◽  
Eric Faden ◽  
Richard P. Dutton ◽  
Stewart J. Lustik ◽  
Yue Li ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Cardiac Arrest ◽  
Quality Improvement ◽  
Cardiac Index ◽  
Correlation Coefficient ◽  
Intraclass Correlation ◽  
Risk Calculator ◽  
Improvement Program ◽  
Surgical Quality ◽  
American College Of Surgeons

Abstract Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New Background The 2014 American College of Cardiology Perioperative Guideline recommends risk stratifying patients scheduled to undergo noncardiac surgery using either: (1) the Revised Cardiac Index; (2) the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator; or (3) the Myocardial Infarction or Cardiac Arrest calculator. The aim of this study is to determine how often these three risk-prediction tools agree on the classification of patients as low risk (less than 1%) of major adverse cardiac event. Methods This is a retrospective observational study using a sample of 10,000 patient records. The risk of cardiac complications was calculated for the Revised Cardiac Index and the Myocardial Infarction or Cardiac Arrest models using published coefficients, and for the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator using the publicly available website. The authors used the intraclass correlation coefficient and kappa analysis to quantify the degree of agreement between these three risk-prediction tools. Results There is good agreement between the American College of Surgeons National Surgical Quality Improvement Program and Myocardial Infarction or Cardiac Arrest estimates of major adverse cardiac events (intraclass correlation coefficient = 0.68, 95% CI: 0.66 to 0.70), while only poor agreement between (1) American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator and the Revised Cardiac Index (intraclass correlation coefficient = 0.37; 95% CI: 0.34 to 0.40), and (2) Myocardial Infarction or Cardiac Arrest and Revised Cardiac Index (intraclass correlation coefficient = 0.26; 95% CI: 0.23 to 0.30). The three prediction models disagreed 29% of the time on which patients were low risk. Conclusions There is wide variability in the predicted risk of cardiac complications using different risk-prediction tools. Including more than one prediction tool in clinical guidelines could lead to differences in decision-making for some patients depending on which risk calculator is used.

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