Predictive factors for prolonged hospital stay after retropubic radical prostatectomy in a high-volume teaching center

Abstract

Objective: To evaluate the length hospital stay and predictors of prolonged hospitalization after RRP performed in a high-surgical volume teaching institution, and analyze the rate of unplanned visits to the office, emergency care, hospital readmissions and perioperative complications rates. Materials and Methods: Retrospective analysis of prospectively collected data in a standardized database for patients with localized prostate cancer undergoing RRP in our institution between January/2010 - January/2012. A logistic regression model including preoperative variables was initially built in order to determine the factors that predict prolonged hospital stay before the surgical procedure; subsequently, a second model including both pre and intraoperative variables was analyzed. Results: 1011 patients underwent RRP at our institution were evaluated. The median hospital stay was 2 days, and 217 (21.5%) patients had prolonged hospitalization. Predictors of prolonged hospital stay among the preoperative variables were ICC (OR. 1.40 p=0.003), age (OR 1.050 p<0.001), ASA score of 3 (OR. 3.260 p<0.001), prostate volume on USG-TR (OR, 1.005 p=0.038) and African-American race (OR 2.235 p=0.004); among intra and postoperative factors, operative time (OR 1.007 p=0.022) and the presence of any complications (OR 2.013 p=0.009) or major complications (OR 2.357 p=0.01) were also correlated independently with prolonged hospital stay. The complication rate was 14.5%. Conclusions: The independent predictors of prolonged hospitalization among preoperative variables were CCI, age, ASA score of 3, prostate volume on USG-TR and African-American race; amongst intra and postoperative factors, operative time, presence of any complications and major complications were correlated independently with prolonged hospital stay.

The Frequency of, and Factors Associated with Prolonged Hospitalization: A Multicentre Study in Victoria, Australia

“…Our study identified several independent baseline associations with prolonged hospitalization. Other studies have similarly revealed that increasing age [ 12 , 17 , 18 , 20 , 22 , 24 , 25 , 28 , 29 , 30 , 33 , 34 , 36 , 38 , 39 , 40 , 50 ], female gender [ 22 , 24 , 26 , 30 , 36 , 39 , 50 ], not being in a relationship, [ 52 ] being a current smoker [ 39 ], level of co-morbidity [ 11 , 12 , 14 , 15 , 16 , 18 , 22 , 26 , 40 , 42 , 44 ], weekend admissions [ 42 ], and the number of prior admissions [ 25 , 32 , 44 ] were associated with prolonged hospitalization.…”

“…Most previous studies of prolonged hospitalization have focused on specific sub-groups of patients such as orthopaedic procedures [ 21 , 24 , 26 , 29 , 30 , 31 , 39 ], cardiovascular disease [ 13 , 15 , 17 , 36 , 37 , 38 ], solid organ transplantation [ 33 , 50 ], or oncological conditions [ 11 , 14 , 18 , 20 , 27 , 28 , 34 , 35 ] ( Supplementary Table S7 ). A limited number of studies have examined the epidemiology of prolonged hospitalization in internal medicine patients [ 23 , 45 , 51 ] but only one of these was multi-centre in nature [ 51 ].…”

“…Several studies have identified factors associated with protracted hospitalization, but many of these have focused on targeted patient populations [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ] or involved data collected at a single centre [ 13 , 18 , 19 , 23 , 24 , 28 , 29 , 31 , 37 , 39 , 40 , 41 , 42 , 43 , 44 , 45 ] Understanding the factors that contribute to prolonged hospitalization in a broader patient cohort may guide the development of interventions that target at risk patients, improve overall care, and reduce resource utilisation.…”

Patient characteristics predicting prolonged length of hospital stay following robotic-assisted radical prostatectomy

“… 18 In a NSQIP study on 864 patients undergoing radical nephrectomy, Lorentz et al 12 found that age, hematocrit level, heart failure, functional dependence, and open procedures were associated with longer recovery. As for patients undergoing prostatectomy, Coelho et al 16 showed that age, American Society of Anesthesiology score >3, large prostate, African American race, and prolonged operative times were the main predictors of pLOS. In addition, Charlson comorbidity index >2 was also associated with LOS > 1 day in patients undergoing RARP.…”

“…The category LOS = 2 days was created to account for delays due to logistics or conditions requiring medical observation, and the cutoff for pLOS was set at LOS > 2 based on previous studies and clinical experience. 16 , 17 Thus, we hypothesize that the predictors associated with pLOS are different than either LOS ⩽ 1 day or LOS = 2 days. All patients were categorized into one of the three groups, and only patients with missing LOS were excluded.…”