Using Frailty to Predict Who Will Fail Early Discharge After Laparoscopic Colorectal Surgery With an Established Recovery Pathway

Keller, Deborah S.; Bankwitz, Blake; Nobel, Tamar; Delaney, Conor P.

doi:10.1097/01.dcr.0000442661.76345.f5

Cited by 76 publications

(59 citation statements)

References 31 publications

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“…(17, 21-23, 31, 32) Increasing mFI has been associated with increased morbidity and mortality for procedures in general surgery,(17, 31) vascular surgery,(21) and colorectal surgery. (33)…”

Section: Discussionmentioning

confidence: 99%

Measurement and validation of frailty as a predictor of outcomes in women undergoing major gynaecological surgery

George

Burke

Hou

et al. 2015

BJOG

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Objective Frailty is the loss of physical or mental reserve that impairs function, often in the absence of a defined comorbidity. Our aim was to determine whether a modified frailty index (mFI) correlates with morbidity and mortality in patients undergoing hysterectomy. Design Retrospective cohort study. Setting Hospitals across the USA participating in the National Surgical Quality Improvement Program (NSQIP). Sample Patients who underwent hysterectomy from 2008 to 2012. Methods An mFI was calculated using 11 variables in NSQIP. The associations between mFI and morbidity and mortality were assessed. Model fit statistics (c‐statistics) were utilised to evaluate the ability of mFI to distinguish outcomes. Main outcome measure Wound infection, severe complications and mortality. Results A total of 66 105 patients were identified. Wound complications increased from 2.4% in patients with an mFI of zero to 4.8% in those with mFI ≥ 0.5 (P < 0.0001). Similarly, severe complications increased from 0.98% to 7.3% (P < 0.0001), overall complications rose from 3.7% to 14.5% (P < 0.0001) and mortality increased from 0.06% to 3.2% (P < 0.0001) for patients with a frailty index of zero compared with those with an index of ≥0.5. Versus chance, the goodness‐of‐fit c‐statistics suggested that mFI increases the ability to detect wound complications by 11.4%, severe complications by 22.0% and overall complications by 11.0%. Conclusions The mFI is easily reproducible from routinely collected clinical data and predictive of outcomes in patients undergoing hysterectomy. Frailty may be useful in the preoperative risk assessment of women undergoing gynaecological surgery. Tweetable abstract Frailty may be useful in the preoperative risk assessment of women undergoing gynaecological surgery.

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“…(17, 21-23, 31, 32) Increasing mFI has been associated with increased morbidity and mortality for procedures in general surgery,(17, 31) vascular surgery,(21) and colorectal surgery. (33)…”

Section: Discussionmentioning

confidence: 99%

Measurement and validation of frailty as a predictor of outcomes in women undergoing major gynaecological surgery

George

Burke

Hou

et al. 2015

BJOG

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“…In this study, we use the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), a high-fidelity database of perioperative information, to develop and evaluate two geriatric-specific surgical risk scores. The first is a model that closely approximates the modified frailty index (mFI), 15–17 and therefore includes fields that must be manually entered by NSQIP participant institutions (e.g., transfer status, functional level). Though these are simple parameters and do not require a geriatrics consult, they still require input from a trained individual, are subject to input error, and cost $10,000–29,000 per institution.…”

Section: Introductionmentioning

confidence: 99%

Can Routine Preoperative Data Predict Adverse Outcomes in the Elderly? Development and Validation of a Simple Risk Model Incorporating a Chart-Derived Frailty Score

Amrock

Neuman

Lin

et al. 2014

Journal of the American College of Surgeons

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Background Frailty has emerged as an important predictor of operative risk among elderly surgical patients. However, the complexity of prospective frailty scores has limited their widespread use. Our goal was to develop two frailty-based surgical risk models employing only routine preoperative data. Our hypothesis was these models could easily integrate into an electronic medical record (EMR) to predict 30-day morbidity and mortality. Study Design ACS-NSQIP participant use files from 2005–2010 were reviewed, and patients ≥65 years old who underwent elective lower gastrointestinal surgery were identified. Two multivariate logistic regression models were constructed and internally cross-validated. The first included simple functional data, a comorbidity index based on the Charlson Comorbidity Index, demographics, BMI, and laboratory data (albumin <3.4g/dL, hematocrit<35%, creatinine>2mg/dL). The second model contained only parameters that can directly auto-populate from an EMR: demographics, laboratory data, BMI, and ASA score. To further assess diagnostic accuracy, receiver operating characteristic (ROC) curves were constructed. Results 76,106 patients met criteria for inclusion. 30-day mortality was seen in 2,853 patients or 3.7% of the study population. 18,436 patients (24.2%) experienced major complication. The c-statistic of the first expanded model was 0.813 for mortality and 0.629 for morbidity. The second simplified model had a c-statistic of 0.795 for mortality and 0.621 for morbidity. Both models were well calibrated per the Hosmer-Lemeshow test. Conclusions Our work demonstrates that routine preoperative data can approximate frailty and predict geriatric-specific surgical risk. The models’ predicative power was comparable to that of established prospective frailty scores. Our calculator could be used as a low cost simple screen for high-risk individuals who may require further evaluation or specialized services.

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“…The "significantly higher" than estimated risk changes the predicted incidence of complications by 2-to 3-fold, and places all risk factors in the red category. Use of a frailty index 34,35 might be an alternative method to more objectively grade the risk of the patient, and increase risk by more graded amounts. With respect to colorectal procedures, the risk calculator also fails to capture individual preoperative risks that have a substantial impact on patient outcomes, such as radiation, chemotherapy, biologic therapy, or immunosuppression.…”

Section: Discussionmentioning

confidence: 99%

Use of the American College of Surgeons NSQIP Surgical Risk Calculator for Laparoscopic Colectomy: How Good Is It and How Can We Improve It?

Cologne

Keller

Liwanag

et al. 2015

Journal of the American College of Surgeons

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Using Frailty to Predict Who Will Fail Early Discharge After Laparoscopic Colorectal Surgery With an Established Recovery Pathway

Cited by 76 publications

References 31 publications

Measurement and validation of frailty as a predictor of outcomes in women undergoing major gynaecological surgery

Measurement and validation of frailty as a predictor of outcomes in women undergoing major gynaecological surgery

Can Routine Preoperative Data Predict Adverse Outcomes in the Elderly? Development and Validation of a Simple Risk Model Incorporating a Chart-Derived Frailty Score

Use of the American College of Surgeons NSQIP Surgical Risk Calculator for Laparoscopic Colectomy: How Good Is It and How Can We Improve It?

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