Influence of Preoperative and Postoperative Factors on Prolonged Length of Stay and Readmission After Minimally Invasive Radical Prostatectomy

Abstract

Background:

The mean length of stay (LOS) after minimally invasive radical prostatectomy (MI-RP) is <2 days. Our main objective was to utilize the National Surgical Quality Improvement Program (NSQIP) database to evaluate preoperative factors that may contribute to prolonged hospital stay and readmission.

Materials and Methods:

Utilizing the NSQIP database, records for surgery with the Current Procedural Terminology code 55866 (prostatectomy) between 2007 and 2017 were evaluated. Chi-square and t-tests were used to assess the effects of preoperative factors on prolonged LOS and rates of hospital readmission within 30 days. Odds ratios (ORs), p-values, and confidence intervals were determined using multivariable logistic regression.

Results:

A total of 40,764 patients underwent MI-RP between 2007 and 2017. Of these, 11.7% reported an LOS of >2 days, whereas 3.9% of patients were readmitted to the hospital within 30 days. Preoperative congestive heart failure within 30 days of surgery was shown to be strongly associated with both prolonged LOS (OR = 6.16) and readmission (OR = 3.28). Bleeding requiring transfusion was demonstrated to be the most significant postoperative factor for prolonged LOS (OR = 23.9), whereas unplanned intubation was shown to be the most significant postoperative factor for readmission (OR = 57.1). Body mass index (BMI) >30 was associated with both prolonged LOS and increase in readmission.

Conclusions:

Upon NSQIP database analysis, cardiopulmonary factors and BMI were demonstrated to have negative impacts on postoperative quality indicators. Patients with comorbidities should be counseled preoperatively concerning their individual risk factors. Mitigation of these factors is important in ensuring optimal outcomes.

Introduction

Prostate cancer is among the most prevalent malignancies in the United States, with one-in-nine men being diagnosed with prostate cancer during their lifetime.¹ It is also a leading cause of cancer-related death with 2.4% of men dying from prostate cancer-related conditions.^1,2

Minimally invasive radical prostatectomy (MI-RP) has gained popularity in recent years, being associated with superior perioperative outcomes compared with open retropubic radical prostatectomy.^3
–5 In addition, MI-RP demonstrates lower transfusion rates, less blood loss, and shorter postoperative length of stay (LOS), compared with open approach.⁶

The National Surgical Quality Improvement Program (NSQIP) database is a national database maintained by the American College of Surgeons. Arising initially from the Veterans Affairs in the 1980s, it has been widely utilized by institutions since the early 2000s.⁷ More than 350 institutions, primarily within the United States, actively contribute datapoints for 135 variables collected from the preoperative through 30-day postoperative periods.⁷ NSQIP database utilization for retrospective analyses is advantageous because it provides abundant reliable risk-adjusted data. This permits high-quality statistical analyses among groups with large sample sizes and similar risk profiles.⁷

LOS and readmission rate are important performance indicators widely utilized by hospitals and health systems. The mean LOS after MI-RP is 1.17 days, with a mean readmission rate of 2.7%.^8,9 Older age (>70 years), lower socioeconomic status, and increased body mass index (BMI) have been previously implicated as major risk factors for postoperative complications and readmissions.^10
–12 We sought to determine pre- and postoperative variables that may contribute to a prolonged LOS and increased likelihood of readmission in patients undergoing MI-RP utilizing the NSQIP database.

Materials and Methods

This protocol was evaluated by the Wake Forest School of Medicine and determined to be exempt.

Records containing the Current Procedural Terminology (CPT) code for minimally invasive prostatectomy (55866) were downloaded, and a manual review of cases from the NSQIP database for minimally invasive prostatectomies between 2007 and 2017 was performed.¹³ Data on readmission within 30 days of procedure were only available after 2012; therefore, its analysis was limited to the years 2012 to 2017. Patient demographics and preoperative characteristics associated with prolonged LOS (>2 days) and 30-day readmission were examined.

For the purposes of the analysis, ethnicity was coded as Hispanic or non-Hispanic, whereas race was independently coded as white, African American (AA), Asian, or unknown/other. Other preoperative characteristics examined included history of diabetes, smoking status, history of severe chronic obstructive pulmonary disease (COPD) and symptomatic dyspnea, recent preoperative congestive heart failure (CHF), hypertension, steroid use, bleeding disorders, recent open wound/wound infection, recent weight loss (>10% for the preceding 6 months), transfusion within the past 72 hours, renal failure/dialysis, systemic sepsis, overall functional status, and American Society of Anesthesiologists (ASA) classification score. Postoperative factors examined included return to operating room, and the occurrence of any of the following complications: wound disruption, deep surgical site infection (DSSI) and superficial surgical site infection (SSSI), urinary tract infection (UTI), sepsis, pneumonia, deep vein thrombosis (DVT) and/or pulmonary embolism (PE), unplanned intubation, acute renal failure (ARF) and/or progressive renal failure, cerebrovascular accidents (CVA), myocardial infarction (MI), bleeding requiring transfusion, and/or cardiac arrest. Patients without complete data for LOS, readmission, or any covariates were excluded.

Descriptive statistics included means and standard deviations of continuous factors or frequencies and percentages of categorical factors. Univariate comparisons were conducted with Student's t-test for continuous variables with Satterthwaite's adjustment for unequal variances, and chi-square or Fisher's exact test for categorical data. Logistic regression models were also utilized to assess pre- and postoperative risk factors for prolonged LOS and 30-day readmission. All analyses were performed using SAS software, versions 9.4 (BASE) and 15.4 (STAT), SAS Institute (Cary, NC).

Results

A total of 49,411 patients were identified on the NSQIP database as having undergone MI-RP between 2007 and 2017. After restricting the data set to procedures performed in 2012 or later and removing patients with missing outcomes or covariates, 40,764 remained available for analysis. Of that group, 11.7% of patients (4789/40,764) reported an LOS of >2 days. Furthermore, 3.9% of patients (1610) were readmitted within 30 days postprocedure.

Demographics

The mean age of this cohort was 62.6 years, with the majority being Caucasian (75%) and AA (12.4%). The mean BMI was 29.1, with 38% of patients having a BMI ≥30.

Length of stay

Univariate analysis

Univariate analysis of pre- and postoperative factors for prolonged LOS (>2 days) was performed (Supplementary Tables S1 and S2). CHF showed the strongest preoperative association (odds ratio [OR] = 8.73) for prolonged LOS, whereas bleeding requiring transfusion showed the strongest postoperative association (OR = 32.21).

Multivariate analysis

A multivariate analysis of preoperative factors for prolonged LOS was performed (Table 1). When normalized to Caucasian patients, AA and Asian patients exhibited stronger associations for prolonged LOS, with ORs of 1.65 and 1.25, respectively. Asian race gained significance (p ≤ 0.001) from the model found in Supplementary Table S1. CHF within 30 days preoperatively maintained the strongest association with LOS >2 days (OR = 5.93) (Table 1).

Table 1.

Multivariate Analysis for Preoperative Factors in Patients with Length of Stay >2 Days

Factor	OR	95% CI	p
Hypertension requiring medication	0.91	0.85–0.98	0.017
BMI ≥30 kg/m²	1.14	1.07–1.22	<0.0001
Dyspnea	1.2	1.00–1.45	0.0478
Hispanic ethnicity	1.21	1.05–1.40	0.0082
DM with oral agents or insulin	1.23	1.13–1.34	<0.0001
Age of patient	1.25	1.21–1.29	<0.0001
Asian	1.25	1.04–1.49	<0.0001
Steroid use for chronic condition	1.32	1.05–1.65	0.0166
Current smoker within 1 year	1.34	1.22–1.46	<0.0001
ASA class: severe	1.37	1.28–1.46	<0.0001
Other race	1.4	1.27–1.55	<0.0001
History of severe COPD	1.44	1.19–1.74	0.0002
African American race	1.65	1.51–1.80	<0.0001
Bleeding disorders	1.69	1.34–2.14	<0.0001
Renal failure or dialysis	1.99	1.31–3.01	0.0012
Partially/totally dependent functional status	2.51	1.47–4.27	0.0007
>10% loss body weight in past 6 months	2.97	1.68–5.27	0.0002
CHF within 30 days	5.93	3.14–11.2	<0.0001

ASA = American Society of Anesthesiologists; BMI = body mass index; CHF = congestive heart failure; CI = confidence interval; COPD = chronic obstructive pulmonary disease; DM = diabetes mellitus; OR = odds ratio.

Further multivariate analysis for postoperative factors for prolonged LOS was performed. Cardiac arrest and DSSI lost significance in the multivariate model. The following postoperative variables maintained significance with p ≤ 0.0001: sepsis, wound disruption, UTI, pneumonia, ARF, return to operating room, DVT/thrombophlebitis, and bleeding requiring transfusions. SSSI (p = 0.0053), progressive renal insufficiency (p = 0.0328), PE (p = 0.0328), MI (p = 0.001), and CVA/stroke (p = 0.0002) maintained significance also. Bleeding requiring transfusions showed the strongest association with prolonged LOS (OR = 27.004) (Table 2).

Table 2.

Multivariate Analysis for Postoperative Factors in Patients with Length of Stay >2 Days

Factor	OR	95% CI	p
PE	1.476	1.032–2.111	0.0328
Cardiac arrest requiring CPR	1.482	0.610–3.603	NS
UTI	1.526	1.247–1.867	<0.0001
DSSI	1.643	0.545–4.955	NS
SSSI	1.793	1.190–2.703	0.0053
DVT/thrombophlebitis	2.09	1.565–4.391	<0.0001
MI	2.557	1.461–4.477	0.001
Wound disruption	3.179	1.757–5.751	0.0001
Sepsis	3.228	2.373–4.391	<0.0001
Return to operating room	3.712	2.963–4.651	<0.0001
CVA/stroke with neurologic deficit	4.408	2.033–9.557	0.0002
Acute renal failure	5.935	2.593–13.586	<0.0001
Pneumonia	6.214	3.894–9.915	<0.0001
Progressive renal insufficiency	6.63	4.383–10.028	0.0328
Bleeding requiring transfusion	27.004	21.984–33.170	<0.0001

CPR = cardiopulmonary resuscitation; CVA = cerebrovascular accident; DSSI = deep surgical site infection; DVT = deep vein thrombosis; MI = myocardial infarction; NS = not significant; PE = pulmonary embolism; SSSI = superficial surgical site infection; UTI = urinary tract infection.

A multivariable logistic regression model for LOS was created, utilizing pre- and postoperative factors as predictors (Table 3). Preoperatively, CHF within 30 days of procedure continued demonstrating the strongest association for prolonged LOS (OR = 5.93). Postoperatively, bleeding requiring transfusion showed the strongest association (OR = 27.004) for prolonged LOS.

Table 3.

Results of Multivariable Logistic Regression Model for Patients with Length of Stay >2 Days Including Pre- and Postoperative Factors as Predictors; N = 4789 (11.7%)

Factor	OR	95% CI	p	Factor	OR	95% CI	p
Preoperative factors	Postoperative factors
Hypertension requiring medication	0.91	0.85–0.98	0.017	DSSI	1.34	0.44–4.08	NS
Dyspnea	1.11	1.00–1.45	0.0478	Cardiac arrest requiring CPR	1.42	0.58–3.49	NS
BMI ≥30 kg/m²	1.16	1.07–1.22	<0.0001	UTI	1.47	1.20–1.80	0.0003
Asian race	1.19	1.04–1.49	<0.0001	PE	1.6	1.12–2.29	0.0101
DM with oral agents or insulin	1.19	1.13–1.34	<0.0001	Unplanned intubation	1.63	0.92–2.92	NS
Hispanic ethnicity	1.2	1.05–1.40	0.0082	SSSI	1.73	1.12–2.65	0.0128
Current smoker within 1 year	1.33	1.22–1.46	<0.0001	DVT/thrombophlebitis	2.08	1.55–2.80	<0.0001
ASA class 3 or 4	1.35	1.28–1.46	<0.0001	MI	2.21	1.25–3.90	0.0061
Other race	1.44	1.27–1.55	<0.0001	Sepsis	2.94	2.14–4.03	<0.0001
History of severe COPD	1.45	1.19–1.74	0.0002	Wound disruption	2.97	1.61–5.46	0.0005
Bleeding disorders	1.45	1.34–2.14	<0.0001	Return to operating room	3.61	2.87–4.54	<0.0001
African American race	1.61	1.51–1.80	<0.0001	CVA/stroke with neurologic deficit	4.02	1.86–8.69	0.0004
Renal failure or dialysis	1.7	1.31–3.01	0.0012	Acute renal failure	4.24	1.78–10.1	0.0002
>10% loss body weight in past 6 months	2.52	1.68–5.27	0.0002	Pneumonia	5.26	3.25–8.50	<0.0001
Functional status	2.61	1.47–4.27	0.0007	Progressive renal insufficiency	5.32	3.48–8.13	<0.0001
CHF within 30 days	6.16	3.14–11.2	<0.0001	Bleeding requiring transfusion	23.9	19.4–29.5	<0.0001

Readmission

Univariate analysis

Univariate analysis of the influence of pre- and postoperative factors on hospital readmission was performed (Supplementary Tables S3 and S4). Among preoperative factors, renal failure was the most strongly associated, statistically significant factor (OR = 2.44) for readmission. Postoperatively, PE (OR = 81.56) demonstrated the strongest association with readmission.

Multivariate analysis

Upon multivariate analysis of preoperative factors for readmission, Asian race (p = 0.0163) and other race (p = 0.0163) gained significance. Hypertension requiring medication, diabetes mellitus treated with oral agents/insulin, and history of severe COPD lost significance between univariate and multivariate analysis. When normalized to Caucasians, Asian race showed a weaker association with readmission (OR = 0.79), whereas AA race showed an increased association with readmission (OR = 1.23). Renal failure or dialysis remained the most strongly associated factor for readmission (OR = 2) (Supplementary Table S5).

A multivariate analysis was utilized to evaluate postoperative factors for readmission. In this analysis, return to the operating room gained significance (p ≤ 0.001), whereas bleeding requiring transfusion and ARF lost significance between the univariate and multivariate analyses. Unplanned intubation showed a weaker association with readmission (OR = 0.462), whereas PE continued to show the strongest association with readmission (OR = 56.59) (Supplementary Table S6) (Fig. 1).

FIG. 1.

(A) Pre- and postoperative variables for LOS >2 days. (B) Pre- and postoperative variables for readmission <30 days. Blue indicates preoperative factors, Red indicates postoperative factors. ASA = American Society of Anesthesiologists; BMI = body mass index; BW = body weight; CHF = congestive heart failure; COPD = chronic obstructive pulmonary disease; CPR = cardiopulmonary resuscitation; CVA = cerebrovascular accident; DM = diabetes mellitus; DVT = deep vein thrombosis; HTN = hypertension; LOS = length of stay; MI = myocardial infarction; ND = neurologic deficits; PE = pulmonary embolism; PRI = progressive renal insufficiency; SSSI = superficial surgical site infection; TFN = transfusion; UTI = urinary tract infection. Color images are available online.

A multivariable logistic regression model for the influence of preoperative factors on readmission was created, utilizing pre- and postoperative variables, morbidity, and mortality as predictors (Table 4). No preoperative factors maintained significance between the multivariate analysis found in Supplementary Table S5 and this model.

Table 4.

Results of Multivariable Logistic Regression Model Readmission Within 30 Days of Surgery Including Pre- and Postoperative Factors as Predictors; N = 1610 (3.9%)

Factor	OR	95% CI	p	Factor	OR	95% CI	p
Preoperative factors	Postoperative factors
Dyspnea	0.82	0.66–1.01	NS	Pneumonia	0.47	0.23–0.97	0.0408
Renal failure or dialysis	0.84	0.52–1.37	NS	Sepsis	1.11	1.04–1.19	0.0021
History of severe COPD	0.86	0.69–1.06	NS	Myocardial infarction	1.22	0.88–1.70	NS
Hypertension requiring medication	0.91	0.85–0.98	NS	Progressive renal insufficiency	1.29	0.52–3.19	NS
Steroid use for chronic condition	0.94	0.73–1.20	NS	Return to operating room	1.84	0.93–3.64	NS
ASA class 3 or 4	0.98	0.90–1.06	NS	CVA/stroke with neurologic deficit	3.1	1.11–8.69	0.0316
BMI ≥30 kg/m²	1.01	0.94–1.09	NS	DSSI	3.29	1.82–5.96	<0.0001
Bleeding disorders	1.03	0.79–1.33	NS	Bleeding requiring transfusion	8.01	5.75–11.2	<0.0001
Diabetes mellitus with oral agents or insulin	1.06	0.96–1.17	NS	Wound disruption	8.12	2.54–26.0	0.0004
Age of patient	1.12	1.08–1.16	NS	Cardiac arrest requiring CPR	8.34	4.45–15.6	<0.0001
Current smoker within 1 year	1.12	1.01–1.23	NS	Acute renal failure	9.35	7.62–11.5	<0.0001
Hispanic ethnicity	1.22	1.05–1.42	NS	UTI	9.83	3.89–24.9	<0.0001
Asian race	1.24	1.03–1.51	NS	Pulmonary embolism	11.6	7.25–18.5	<0.0001
Other race	1.44	1.30–1.60	NS	SSSI	21.2	16.7–26.8	<0.0001
African American race	1.6	1.45–1.75	NS	DVT/thrombophlebitis	29.6	20.8–42.2	<0.0001
>10% loss body weight in past 6 months	1.62	0.80–3.27	NS	Unplanned intubation	57.1	40.1–81.2	<0.0001
Functional status	1.67	0.94–2.98	NS
CHF within 30 days	3.28	1.64–6.56	NS

Using this same model, the influence of postoperative factors on readmission was evaluated (Table 4). ARF (p ≤ 0.0001) and bleeding requiring transfusion (p ≤ 0.0001) gained significance, whereas returning to the operating room, progressive renal insufficiency, and MI lost significance from the analysis shown in Supplementary Table S6.

Discussion

We demonstrated that patients with preoperative histories of obesity, bleeding disorders, smoking, decreased functional status, and pulmonary/cardiac/renal disease are at significantly increased risk of prolonged LOS, after MI-RP. Many of these same factors also independently increase the likelihood of readmission (Supplementary Tables S3–S6). Furthermore, the combination of multiple comorbidities may compound readmission and/or LOS risk. Patients should be appropriately counseled about the heightened surgical risks, including prolonged hospitalization and readmission. Specifically, patients with decreased functional status, in the setting of preoperative weight loss and CHF may want to consider other treatment options. Cardiac dysfunction demonstrated the strongest preoperative predictor for both prolonged LOS (OR = 6.16) and readmission (OR = 3.28). Postoperatively, transfusion-dependent anemia (OR = 23.9) and respiratory collapse (OR = 57.1) had the strongest association with prolonged LOS and readmission, respectively.

Patients with decreased functional status, in the setting of preoperative cardiac and renal disease, would be the least optimal for surgery because of increased combined risk for LOS and readmission, but early aggressive perioperative risk factor management can be key to improving MI-RP outcomes. We showed that CHF, bleeding requiring transfusion, DVT/PE, and UTI have the highest impact on prolonged LOS and readmission. Preoperative optimization of patients with impaired cardiac function is important. Patients should undergo a thorough history and physical, along with an electrocardiogram, echocardiogram, and electrolyte panels to evaluate cardiac function for electrolyte imbalances, preoperatively.^14,15 Surgeons should work closely with anesthesia to ensure optimal perioperative cardiopulmonary and electrolyte status in CHF patients. Intraoperative fluid overload is also a concern in CHF patients, but these risks may be mitigated with serum lactate, urine output, central venous pressure, and vital sign monitoring.¹⁴ In addition, increased intra-abdominal pressure from pneumoperitoneum during minimally invasive surgery negatively impacts patient cardiovascular and respiratory outcomes.¹⁶ A lower pneumoperitoneum pressure of 6 mm Hg during MI-RP may provide adequate observation and have minimal cardiovascular and respiratory impact.

Several recent retrospective series have examined prolonged hospitalization after MI-RP. In a 2016 single institution review of 274 consecutive patients, a Charlson comorbidity index ≥2 was found to be the only preoperative predictor for prolonged LOS (OR = 3.3, p = 0.04). Readmission rates were similar between patients with LOS above and below 2 days.¹⁷ No statistically significant association was identified between individual cardiovascular or pulmonary risk factors and prolonged LOS.¹⁷ Our study demonstrated multiple, independent cardiopulmonary risk factors, such as CHF and transfusion-dependent anemia, significantly increased the likelihood of prolonged LOS. In another 2018 study of 1011 cases, the authors reported prolonged LOS in 21.5% (217/1011) of patients.¹⁸ Age, AA race, ASA Score >3, and TRUS prostate volume were implicated as independent preoperative predictors of LOS.¹⁸ Our NSQIP database evaluation reports a lower rate of prolonged LOS (11.7% vs 21.5%). ASA score was not a significant risk factor for prolonged LOS. NSQIP database is a more robust database and may be closer to the true value given the large sample size.

Predictors for readmission after robot-assisted radical prostatectomy were investigated in a 2017 NSQIP review.¹⁹ Rates of readmission were reported at 3.2% (332/9975), with 30.6% (3057/9975) of patients having an LOS ≥2 days. Causes for readmission were further delineated, with intestinal obstruction being the most common cause for readmission (11.7%), followed by thromboembolism and bleeding events at 10.2% and 6.0%, respectively.¹⁹ Patient BMI and severe ASA classification had a statistically significant influence on readmission, in both the 2017 NSQIP analysis and this report. We report similar rates of readmission at 3.9% vs 3.2% and a lower rate of prolonged LOS at 11.7% vs 30.6%. This discrepancy may be partly caused by slight differences in definition of prolonged LOS. In our study, prolonged LOS was defined as >2 days, whereas the 2017 NSQIP analysis considered a prolonged LOS to be ≥2 days. Our definition of prolonged LOS being >2 days is predicated on a 2007 single-institution multisurgeon analysis in which 97.5% (613/629) of patients were discharged with a mean LOS of 1.17 days postoperatively.⁸ Furthermore, we sought to have a more nuanced analysis of patients that truly had an LOS >2 days. Unlike in our current report, the 2017 NSQIP analysis did not evaluate for influencing factors for prolonged LOS, as prolonged LOS was only analyzed as a contributing variable to readmission.

In this study based on NSQIP database, the rate of readmission was 3.9%, within the previously reported rates between 2.7% and 4.7%. The rate of prolonged LOS in this study was 11.7%. AA patients (OR = 1.61; p < 0.0001) showed increased risk for prolonged LOS, comparing with their Caucasian and Asian counterparts (OR = 1.19; p < 0.0001). AA men also had increased rates of readmission, although this was not statistically significant. These results should be interpreted cautiously and may represent a complex interplay between multiple socioeconomic and disease factors. Historically, research has consistently reported less satisfactory outcomes for AA men undergoing surgical management for their prostate cancer disease.²⁰ A recent multicohort study, however, suggested that black men had similar prostate cancer-specific mortality compared with white men, with outcome discrepancies showing the most significant divergence in other-cause mortality (OCM).²¹ Socioeconomic disparities have been shown to be the primary driver of inferior OCM outcomes in black men, not AA lineage itself.^18,21

It is well documented that high BMI is a strong risk factor for multiple postoperative cardiovascular, thromboembolic, wound, and renal complications, and is an independent predictor for both prolonged LOS and readmission rates.^12,22 Furthermore, surgeries performed in patients with elevated BMI may be more technically challenging and require slight technique modification.²³ Preoperative BMI reduction may help to moderate these associated risks factors. Weight goals may be achieved with regular aerobic exercise in conjunction with a healthy, sustainable diet plan.¹² Furthermore, it has been demonstrated that even a short preoperative regimen of exercise, stress reduction, and proper nutrition may improve postoperative outcomes in at-risk patients.²⁴ DVT/PE prophylaxis in obese and nonobese patients alike, including smoking cessation, early ambulation, and risk-adjusted utilization of sequential compression devices and pharmacologic prophylaxis depending on the patient's own risk factors.^25,26

The role of UTI prevention is unclear in the current literature. Current American Urological Association recommendations support a single preoperative dose of either cefazolin or trimethoprim-sulfamethoxazole.²⁷ There are no guidelines on antibiotic administration after removal of urinary catheter, in men without any known risk factors for UTI. In men with predisposing factors for UTI, antibiotic prophylaxis with a short course of trimethoprim-sulfamethoxazole or a fluoroquinolone is recommended.²⁸

Limitations should be noted, primarily stemming from characteristics inherent to the NSQIP database. First, the CPT code 55866 indicates both laparoscopic and robot-assisted laparoscopic prostatectomies, although many of the cases performed in the United States would have been performed robotically. The code also makes no distinction between different techniques approaches (e.g., trans- and extraperitoneal Retzius-sparing approaches). Second, the 55688 CPT code does not include lymph node dissection, which, depends on the disease stage and the extent of the dissection, can be a substantial component of MI-RP.²⁹ Third, no information pertaining to prostate cancer staging, disease characteristics, patient medication, nor comorbidity severity are collected by NSQIP. Likewise, the database contains no precise detail concerning patient socioeconomic factors. Fourth, NSQIP only provides postoperative data for 30 days after surgery, making evaluation of long-term complications impossible.¹³ Fifth, NSQIP is a data sampling, not a case review. Thereby only providing data from a portion of all operations performed, and not from all eligible patients in a population. Sixth, NSQIP sampling is done on an 8-day cycle, during which 40 cases meeting inclusion/exclusion criteria are randomly sampled.³⁰ Finally, specific causes for readmission are not collected by NSQIP.

Conclusion

Using a large national database to provide insights into potentially modifiable risk factors, patients with suboptimal cardiopulmonary status and/or elevated BMI were demonstrated to be at higher risk of poorer outcomes. These factors may not necessarily preclude these patients from their operation, perioperative optimization of these risk factors would be prudent, although other management options may be explored (watchful waiting or radiation), in patients deemed unfit for surgery because of poor cardiovascular parameters. Future investigation should be directed toward preoperative pathway development in at-risk patients to optimize postoperative outcomes.

Footnotes

Author Disclosure Statement

The authors have no conflicts of interest or competing interests to disclose.

Funding Information

Internal Institutional Funding.

Supplementary Material

Supplementary Table S1

Supplementary Table S2

Supplementary Table S3

Supplementary Table S4

Supplementary Table S5

Supplementary Table S6

Abbreviations Used

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