Can we better predict readmission for dehydration following creation of a diverting loop ileostomy: development and validation of a prediction model and web-based risk calculator.
Aged
Area Under Curve
Databases, Factual
Dehydration
/ epidemiology
Diagnosis, Computer-Assisted
/ methods
Female
Humans
Ileostomy
/ adverse effects
Incidence
Internet
Male
Middle Aged
Patient Readmission
/ statistics & numerical data
Postoperative Complications
/ epidemiology
Quality Improvement
Retrospective Studies
Risk Factors
Acute renal failure
Dehydration
Ileostomy
Morbidity
Readmission
Journal
Surgical endoscopy
ISSN: 1432-2218
Titre abrégé: Surg Endosc
Pays: Germany
ID NLM: 8806653
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
23
04
2019
accepted:
15
08
2019
pubmed:
28
8
2019
medline:
24
6
2021
entrez:
28
8
2019
Statut:
ppublish
Résumé
Dehydration is the most common morbidity following creation of a diverting loop ileostomy (DLI). We aimed to develop and validate a prediction model and web-based risk calculator for readmission for dehydration following DLI creation. After institutional review board approval, we retrospectively reviewed the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) database between 2012 and 2017. Adult patients (> 18 years) who underwent DLI with a resection for colorectal cancer, inflammatory bowel disease, or diverticulitis were identified. Patient demographics, operative and postoperative data were collected. The final prediction model, developed in 60% of the cohort (training set) and which modeled the 30-day cumulative incidence of readmission for dehydration, was selected using highest area under the receiver operating curve (AUC) criterion. Model calibration was assessed with the Hosmer-Lemeshow goodness-of-fit test. The model was then assessed in validation and test sets, using 20% of the cohort for each. Of 25,638 patients in the ACS-NSQIP database who met inclusion criteria, 15,222 patients were randomly selected for the training set. The incidence of readmission for dehydration in this cohort was 2.1%. The final model with the highest AUC retained 12 candidate variables: age, sex, smoking status, diabetes, hypertension, American Society of Anesthesiologists score, type of admission, underlying diagnosis, procedure performed, operative time, index admission length of stay, and major morbidity. The model demonstrated good discrimination (AUC 0.76, 95% CI 0.74-0.79) and the Hosmer-Lemeshow goodness-of-fit test confirmed good calibration (p = 0.50). Five-thousand and seventy-three patients were available for the validation and test sets, respectively, and the model remained strong in both the validation and test sets (AUCs of 0.73 and 0.73, respectively). The prediction model was then converted into a web-based risk calculator. A prediction model and web-based risk calculator for readmission for dehydration after DLI creation was developed and validated, demonstrating good predictive capabilities.
Sections du résumé
BACKGROUND
Dehydration is the most common morbidity following creation of a diverting loop ileostomy (DLI). We aimed to develop and validate a prediction model and web-based risk calculator for readmission for dehydration following DLI creation.
METHODS
After institutional review board approval, we retrospectively reviewed the American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) database between 2012 and 2017. Adult patients (> 18 years) who underwent DLI with a resection for colorectal cancer, inflammatory bowel disease, or diverticulitis were identified. Patient demographics, operative and postoperative data were collected. The final prediction model, developed in 60% of the cohort (training set) and which modeled the 30-day cumulative incidence of readmission for dehydration, was selected using highest area under the receiver operating curve (AUC) criterion. Model calibration was assessed with the Hosmer-Lemeshow goodness-of-fit test. The model was then assessed in validation and test sets, using 20% of the cohort for each.
RESULTS
Of 25,638 patients in the ACS-NSQIP database who met inclusion criteria, 15,222 patients were randomly selected for the training set. The incidence of readmission for dehydration in this cohort was 2.1%. The final model with the highest AUC retained 12 candidate variables: age, sex, smoking status, diabetes, hypertension, American Society of Anesthesiologists score, type of admission, underlying diagnosis, procedure performed, operative time, index admission length of stay, and major morbidity. The model demonstrated good discrimination (AUC 0.76, 95% CI 0.74-0.79) and the Hosmer-Lemeshow goodness-of-fit test confirmed good calibration (p = 0.50). Five-thousand and seventy-three patients were available for the validation and test sets, respectively, and the model remained strong in both the validation and test sets (AUCs of 0.73 and 0.73, respectively). The prediction model was then converted into a web-based risk calculator.
CONCLUSIONS
A prediction model and web-based risk calculator for readmission for dehydration after DLI creation was developed and validated, demonstrating good predictive capabilities.
Identifiants
pubmed: 31451920
doi: 10.1007/s00464-019-07069-2
pii: 10.1007/s00464-019-07069-2
doi:
Types de publication
Journal Article
Multicenter Study
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
3118-3125Références
Garlipp B, Ptok H, Schmidt U, Meyer F, Gastinger I, Lippert H (2010) Neoadjuvant chemoradiotherapy for rectal carcinoma: effects on anastomotic leak rate and postoperative bladder dysfunction after non-emergency sphincter-preserving anterior rectal resection. Results of the quality assurance in rectal cancer surgery multicenter observational trial. Langenbecks Arch Surg 395:1031–1038
doi: 10.1007/s00423-010-0708-0
Luglio G, Pendlimari R, Holubar SD, Cima RR, Nelson H (2011) Loop ileostomy reversal after colon and rectal surgery: a single institutional 5-year experience in 944 patients. Arch Surg 146:1191–1196
doi: 10.1001/archsurg.2011.234
Chadi SA, Fingerhut A, Berho M, DeMeester SR, Fleshman JW, Hyman NH, Margolin DA, Martz JE, McLemore EC, Molena D, Newman MI, Rafferty JF, Safar B, Senagore AJ, Zmora O, Wexner SD (2016) Emerging trends in the etiology, prevention, and treatment of gastrointestinal anastomotic leakage. J Gastrointest Surg 20:2035–2051
doi: 10.1007/s11605-016-3255-3
Huser N, Michalski CW, Erkan M, Schuster T, Rosenberg R, Kleeff J, Friess H (2008) Systematic review and meta-analysis of the role of defunctioning stoma in low rectal cancer surgery. Ann Surg 248:52–60
doi: 10.1097/SLA.0b013e318176bf65
Li W, Stocchi L, Cherla D, Liu G, Agostinelli A, Delaney CP, Steele S, Gorgun E (2017) Factors associated with hospital readmission following diverting ileostomy creation. Tech Coloproctol 21:641–648
doi: 10.1007/s10151-017-1667-z
Bakx R, Busch OR, Bemelman WA, Veldink GJ, Slors JF, van Lanschot JJ (2004) Morbidity of temporary loop ileostomies. Dig Surg 21:277–281
doi: 10.1159/000080201
Messaris E, Sehgal R, Deiling S, Koltun W, Stewart D, McKenna K, Poritz LS (2012) Dehydration is the most common indication for readmission after diverting ileostomy creation. Dis Colon Rectum 55:175–180
doi: 10.1097/DCR.0b013e31823d0ec5
Fish DR, Mancuso CR, Garcia-Aguilar JE, Lee SW, Nash GM, Sonoda T, Charlson ME, Temple LK (2017) Readmission after ileostomy creation: retrospective review of a common and significant event. Ann Surg 265:379–387
doi: 10.1097/SLA.0000000000001683
Phatak UR, Kao LS, You YN, Rodriguez-Bigas MA, Skibber JM, Feig BW, Nguyen S, Cantor SB, Change GJ (2014) Impact of ileostomy-related complications on the multidisciplinary treatment of rectal cancer. Ann Surg Oncol 21:507–512
doi: 10.1245/s10434-013-3287-9
Li L, Lau KS, Ramanathan V, Orcutt ST, Sansgiry S, Albo D, Berger DH, Anaya DA (2017) Ileostomy creation in colorectal cancer surgery: risk of acute kidney injury and chronic kidney disease. J Surg Res 210:204–212
doi: 10.1016/j.jss.2016.11.039
Paquette I, Solan P, Rafferty JF, Ferguson MA, Davis BR (2013) Readmission for dehydration or renal failure after ileostomy creation. Dis Colon Rectum 56:974–979
doi: 10.1097/DCR.0b013e31828d02ba
Cheung WY, Neville BA, Earle C (2009) Etiology of delays in the initiation of adjuvant chemotherapy and their impact on outcomes for stage II and III rectal cancer. Dis Colon Rectum 52:1054–1064
doi: 10.1007/DCR.0b013e3181a51173
Collins GS, Reitsma JB, Altman DG, Moons KG (2015) Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. J Clin Epidemiol 68:134–143
doi: 10.1016/j.jclinepi.2014.11.010
Shiloach M, Frencher SK Jr, Steeger JE, Rowell KS, Bartzokis K, Tomeh MG, Richards KE, Ko CY, Hall BL (2010) Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg 210:6–16
doi: 10.1016/j.jamcollsurg.2009.09.031
Justiniano CF, Temple LK, Swanger AA, Xu Z, Speranza JR, Cellini C, Salloum RM, Fleming FJ (2018) Readmissions with dehydration after ileostomy creation: rethinking risk factors. Dis Colon Rectum 61:1297–1305
doi: 10.1097/DCR.0000000000001137
Gessler B, Haglind E, Angenete E (2014) A temporary loop ileostomy affects renal function. Int J Colorectal Dis 29:1131–1135
doi: 10.1007/s00384-014-1949-0
Hastie T, Tibshirani R, Friedman J (2009) The elements of statistical learning. Model assessment and selection. Springer, New York
doi: 10.1007/978-0-387-84858-7
Gonella F, Valenti A, Massucco P, Russolillo N, Mineccia M, Fontana AP, Cucco D, Ferrero A (2019) A novel patient-centered protocol to reduce hospital readmissions for dehydration after ileostomy. Surgery 1:8. https://doi.org/10.1007/s13304-019-00643-2
doi: 10.1007/s13304-019-00643-2
Nagle D, Pare T, Keenan E, Marcet K, Tizio S, Poylin V (2012) Ileostomy pathway virtually eliminates readmission for dehydration in new ostomates. Dis Colon Rectum 55:1266–1272
doi: 10.1097/DCR.0b013e31827080c1
Grahn SW, Lowry AC, Osborne MC, Melton GB, Gaertner WB, Vogler SA, Madoff RD, Kwaan MR (2019) System-wide implementation for transitions after ileostomy surgery: can intensive monitoring of protocol compliance decrease readmissions? A randomized trial. Dis Colon Rectum 63:363–370
doi: 10.1097/DCR.0000000000001286
Chen SY, Stem M, Cerullo M, Canner JK, Gearhart SL, Safar B, Fang SH, Efron JE (2018) Predicting the risk of readmission from dehydration after ileostomy formation: the dehydration readmission after ileostomy prediction score. Dis Colon Rectum 61:1410–1417
pubmed: 30303886
pmcid: 6219896
Collins GS, de Groot JA, Dutton S, Omar O, Shanyinde M, Tajar A, Voysey M, Wharton R, Yu LM, Moons KG, Altman DG (2014) External validation of multvariable prediction models: a systematic review of methodological conduct and reporting. BMC Med Res Methodol 14:40
doi: 10.1186/1471-2288-14-40