What have we learned in minimally invasive colorectal surgery from NSQIP and NIS large databases? A systematic review

Evaluating frailty using the modified frailty index for colonic diverticular disease surgery: analysis of the national inpatient sample 2015-2019

BACKGROUND

Frailty has been associated with increased postoperative mortality and morbidity; however, the use of the modified frailty index (mFI-11) to assess patients undergoing surgery for diverticular disease has not been widely assessed. This paper aims to examine frailty, evaluated by mFI-11, to assess postoperative morbidity and mortality among patients undergoing operative intervention for colonic diverticular disease.

METHODS

We used data from the Healthcare Cost and Utilization Project National Inpatient Sample (October 1, 2015-December 31, 2019). ICD-10-CM codes were utilized to identify a cohort of adult patients with a primary admission diagnosis of diverticulitis. mFI-11 items were adapted to correspond with ICD-10-CM codes. Patients were stratified into robust (mFI < 0.27) and frail (mFI ≥ 0.27) groups. Primary outcomes were in-hospital postoperative morbidity and mortality. Secondary outcomes included system-specific postoperative complications, length of stay (LOS), total admission cost, and discharge disposition. Multivariable regression models were fit.

RESULTS

Of the 26,826 patients, there were 24,194 patients with mFI-11 < 0.27 (i.e., robust) and 2,632 patients with mFI-11 ≥ 0.27 (i.e., frail). Adjusted analysis showed significant increases in postoperative mortality (aOR 2.16, 95% CI 1.38-3.38, p = 0.001) and overall postoperative morbidity (aOR 1.84, 95% CI 1.65-2.06, p < 0.001). LOS was higher in the frail group (MD 1.78 days, 95% CI 1.46-2.11, p < 0.001) as well as total cost (MD $25,495.19, 95% CI $19,851.63-$31,138.75, p < 0.001).

CONCLUSION

In the elective setting, a high mFI-11 (i.e., presence of the variables comprising the index) could alert clinicians to the possibility of implementing preoperative optimization strategies. In the emergent setting, a high mFI-11 may help guide prognostication for these vulnerable patients.

Frailty as a predictor of postoperative outcomes in neurosurgery: a systematic review

INTRODUCTION

Baseline frailty status has been utilized to predict a wide range of outcomes and guide preoperative decision making in neurosurgery. This systematic review aims to analyze existing literature on the utilization of frailty as a predictor of neurosurgical outcomes.

EVIDENCE ACQUISITION

We conducted a systematic review following PRISMA guidelines. Studies that utilized baseline frailty status to predict outcomes after a neurosurgical intervention were included in this systematic review. Studies that utilized sarcopenia as the sole measure of frailty were excluded. PubMed, EMBASE, and Cochrane library was searched from inception to March 1st, 2023, to identify relevant articles.

EVIDENCE SYNTHESIS

Overall, 244 studies met the inclusion criteria. The 11-factor modified frailty index (mFI-11) was the most utilized frailty measure (N.=91, 37.2%) followed by the five-factor modified Frailty Index (mFI-5) (N.=80, 32.7%). Spine surgery was the most common subspecialty (N.=131, 53.7%), followed by intracranial tumor resection (N.=57, 23.3%), and post-operative complications were the most reported outcome (N.=130, 53.2%) in neurosurgical frailty studies. The USA and the Bowers author group published the greatest number of articles within the study period (N.=176, 72.1% and N.=37, 15.2%, respectively).

CONCLUSIONS

Frailty literature has grown exponentially over the years and has been incorporated into neurosurgical decision making. Although a wide range of frailty indices exist, their utility may vary according to their ability to be incorporated in the outpatient clinical setting.

National Databases for Assessment of Quality

With the rise in the availability of large health care datasets, database research has become an important tool for colorectal surgeon to assess health care quality and implement practice changes. In this chapter, we will discuss the benefits and drawbacks of database research for quality improvement, review common markers of quality for colorectal surgery, provide an overview of frequently used datasets (including Veterans Affairs Surgical Quality Improvement Program, National Surgical Quality Improvement Project, National Cancer Database, National Inpatient Sample, Medicare Data, and Surveillance, Epidemiology, and End Results), and look ahead to the future of database research for the improvement of quality.

Predictors and Consequences of Unplanned Conversion to Open During Robotic Colectomy: An ACS-NSQIP Database Analysis

Robotic-assisted surgery has become a desired modality for performing colectomy; however, unplanned conversion to an open procedure may be associated with worse outcomes. The purpose of this study is to examine predictors and consequences of unplanned conversion to open in a large, high fidelity data set. A retrospective analysis of 11 061 robotic colectomies was conducted using the American College of Surgeons - National Surgical Quality Improvement Program (ACS-NSQIP) 2012-2017 database. Predictors of conversion and the effect of conversion on outcomes were analyzed by multivariate logistic regression resulting in risk-adjusted odds ratios of conversion and morbidity/mortality. Overall, 10 372 (93.8%) patients underwent successful robotic colectomy, and 689 (6.2%) had an unplanned conversion. Predictors of conversion included age ≥ 65 years, male gender, obesity, functional status not independent, American Society of Anesthesia (ASA) classification IV-V, non-oncologic indication, emergency case, smoking, recent weight loss, bleeding disorder, and preoperative organ space infection. Conversion is an independent risk factor for mortality, overall morbidity, cardiac morbidity, pulmonary morbidity, renal morbidity, venous thromboembolism morbidity, wound morbidity, sepsis, bleeding, readmission, return to the operating room, and extended length of stay (LOS). Unplanned conversion to open during robotic colectomy is an independent predictor of morbidity and mortality.

Postoperative Hospital Outcomes of Elective Surgery for Nonmalignant Colorectal Polyps: Does the Burden Justify the Indication?

INTRODUCTION

Despite the increasing availability of advanced endoscopic resections and its favorable safety profile, surgery for nonmalignant colorectal polyps has continually increased. We sought to evaluate readmission rates and outcomes of elective surgery for nonmalignant colorectal polyps on a national level in the United States.

METHODS

The Nationwide Readmissions Database (2010-2014 [International Classification of Diseases, Ninth Revision] and 2016-2018 [International Classification of Diseases, 10th Revision]) was used to identify all adult subjects (age ≥18 years) who underwent elective surgical resection of nonmalignant colorectal polyps. Multivariable analyses were performed for predictors of postoperative morbidity and 30-day readmission.

RESULTS

Elective surgery for nonmalignant colorectal polyps was performed in 108,468 subjects from 2010 to 2014 and in 54,956 subjects from 2016 to 2018, most of whom were laparoscopic. Postoperative morbidity and 30-day readmission rates were 20.5% and 8.5% from 2010 to 2014, and 13.0% and 7.6% from 2016 to 2018, respectively. Index admission mortality rates were 0.3-0.4%; mortality rates were higher in those with postoperative morbidity. Multivariable analyses revealed that male sex, ≥3 comorbidities, insurance status, and open surgery predicted an increased risk of both postoperative morbidity and 30-day readmission. In addition, postoperative morbidity (2010-2014 [odds ratio 1.58; 95% confidence interval 1.44-1.74] and 2016-2018 [odds ratio 1.55; 95% confidence interval 1.37-1.75]) predicted early readmission.

DISCUSSION

In this investigation of national practices, elective surgery for nonmalignant colorectal polyps remains common. There is considerable risk of adverse postoperative outcomes, which highlights the importance of increasing awareness of the range of endoscopic resections and referring subjects to expert endoscopy centers.

Anatomical framework for pre-operative planning of laparoscopic left-sided colorectal surgery: Potential relevance of the distance between the inferior mesenteric artery and inferior mesenteric vein

BACKGROUND

The medial-to-lateral approach is favored by most colorectal surgeons for laparoscopic retroperitoneal dissection and mobilisation of the left colon. The peritoneal access window, i.e. the distance between the inferior mesenteric vein (IMV) and inferior mesenteric artery (IMA) must be large enough to perform the procedure safely and successfully. However, studies investigating the IMA-IMV distance and factors affecting this variable, are scarce. Therefore, we examined the IMA-IMV and D3-IMA distances to determine an anatomical framework on planning and adapting surgical therapy.

BASIC PROCEDURES

The IMA-IMV and D3-IMA distances were retrospectively measured in 230 patients (127 Male/103 Female, Median Age=54.5) who had undergone pre-operative CT-scanning before laparoscopic left-sided colorectal surgery. Two observers rated the images and interrater reliability was calculated. Subgroup, simple and multiple linear regression analyses were performed in order to detect potential interaction between morphometric variables and IMA-IMV distance.

MAIN FINDINGS

We demonstrated a significant correlation between the inferior margin of the duodenum and the origin of IMA. Determination of the IMA-IMV distance was simple and reproducible. Approximately 45% of patients undergoing laparoscopic colorectal procedures had a narrow distance (≤50mm). There was a sexual dimorphism in IMA-IMV distance, being consistently large in males. There were no other pre-operative factors which predicted whether the peritoneal dissection window for a medial-to-lateral approach was sufficient.

CONCLUSIONS

Our results provide new data for a better understanding of metric variations in abdominal vascular structures and complement previous observations. In view of our results, we recommend pre-operative measurement of the IMA-IMV before colorectal surgery where the medial-to-lateral approach is planned. Given that a narrow distance may predict a difficult dissection, this factor should be taken into account to determine the optimal surgical approach in each patient.

Evaluating the ACS-NSQIP Risk Calculator in Primary GI Neuroendocrine Tumor: Results from the United States Neuroendocrine Tumor Study Group

The ACS established an online risk calculator to help surgeons make patient-specific estimates of postoperative morbidity and mortality. Our objective was to assess the accuracy of the ACS-NSQIP calculator for estimating risk after curative intent resection for primary GI neuroendocrine tumors (GI-NETs). Adult patients with GI-NET who underwent complete resection from 2000 to 2017 were identified using a multi-institutional database, including data from eight academic medical centers. The ability of the NSQIP calculator to accurately predict a particular outcome was assessed using receiver operating characteristic curves and the area under the curve (AUC). Seven hundred three patients were identified who met inclusion criteria. The most commonly performed procedures were resection of the small intestine with anastomosis (N = 193, 26%) and partial colectomy with anastomosis (N = 136, 18%). The majority of patients were younger than 65 years (N = 482, 37%) and ASA Class III (N = 337, 48%). The most common comorbidities were diabetes (N = 128, 18%) and hypertension (N = 395, 56%). Complications among these patients based on ACS NSQIP definitions included any complication (N = 132, 19%), serious complication (N = 118, 17%), pneumonia (N = 7, 1.0%), cardiac complication (N = 1, 0.01%), SSI (N = 80, 11.4%), UTI (N = 17, 2.4%), venous thromboembolism (N = 18, 2.5%), renal failure (N = 16, 2.3%), return to the operating room (N = 27, 3.8%), discharge to nursing/rehabilitation (N = 22, 3.1%), and 30-day mortality (N = 9, 1.3%). The calculator provided reasonable estimates of risk for pneumonia (AUC = 0.721), cardiac complication (AUC = 0.773), UTI (AUC = 0.716), and discharge to nursing/ rehabilitation (AUC = 0.779) and performed poorly (AUC < 0.7) for all other complications Fig. 1). The ACS-NSQIP risk calculator estimates a similar proportion of risk to actual events in patients with GI-NET but has low specificity for identifying the correct patients for many types of complications. The risk calculator may require modification for some patient populations.

Do Diagnostic and Procedure Codes Within Population-Based, Administrative Datasets Accurately Identify Patients with Rectal Cancer?

BACKGROUND

Procedural and diagnostic codes may inaccurately identify specific patient populations within administrative datasets.

PURPOSE

Measure the accuracy of previously used coding algorithms using administrative data to identify patients with rectal cancer resections (RCR).

METHODS

Using a previously published coding algorithm, we re-created a RCR cohort within administrative databases, limiting the search to a single institution. The accuracy of this cohort was determined against a gold standard reference population. A systematic review of the literature was then performed to identify studies that use similar coding methods to identify RCR cohorts and whether or not they comment on accuracy.

RESULTS

Over the course of the study period, there were 664,075 hospitalizations at our institution. Previously used coding algorithms identified 1131 RCRs (administrative data incidence 1.70 per 1000 hospitalizations). The gold standard reference population was 821 RCR over the same period (1.24 per 1000 hospitalizations). Administrative data methods yielded a RCR cohort of moderate accuracy (sensitivity 89.5%, specificity 99.9%) and poor positive predictive value (64.9%). Literature search identified 18 studies that utilized similar coding methods to derive a RCR cohort. Only 1/18 (5.6%) reported on the accuracy of their study cohort.

CONCLUSIONS

The use of diagnostic and procedure codes to identify RCR within administrative datasets may be subject to misclassification bias because of low PPV. This underscores the importance of reporting on the accuracy of RCR cohorts derived within population-based datasets.