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Record W3000020807 · doi:10.1097/dcr.0000000000001542

Readmission for Treatment Failure After Nonoperative Management of Acute Diverticulitis: A Nationwide Readmissions Database Analysis

2020· article· en· W3000020807 on OpenAlexaff
Safiya Al-Masrouri, Richard Garfinkle, Faisal Al-Rashid, Kaiqiong Zhao, Nancy Morin, Gabriela Ghitulescu, Carol‐Ann Vasilevsky, Marylise Boutros

Bibliographic record

VenueDiseases of the Colon & Rectum · 2020
Typearticle
Languageen
FieldMedicine
TopicDiverticular Disease and Complications
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsMedicineDiverticulitisIncidence (geometry)Retrospective cohort studyEmergency medicineSurgery

Abstract

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BACKGROUND: The true incidence of, and risk factors for, readmission for treatment failure after nonoperative management of acute diverticulitis remain poorly understood. OBJECTIVE: The purpose of this study was to describe the incidence and risk factors for readmission for treatment failure after nonoperative management of acute diverticulitis using a large national database. DESIGN: This was a retrospective cohort study. SETTINGS: A representative sample of admissions and discharges from hospitals in the United States captured in the National Readmissions Database were included. PATIENTS: Adult patients (age ≥18 y) admitted with a primary diagnostic of colonic diverticulitis between 2010 and 2015 and who were managed nonoperatively and discharged from hospital alive were included. INTERVENTIONS: Study intervention included nonoperative management, consisting of medical therapy with or without percutaneous drainage. MAIN OUTCOME MEASURES: Readmission for treatment failure (defined as a nonelective readmission for diverticulitis within 90 d of discharge), complicated treatment failure (defined as a treatment failure with complicated diverticulitis), and time-to-treatment failure were measured. RESULTS: In total, 201,384 patients were included. The overall incidence of readmission for treatment failure was 6.6%. Treatment failure was significantly higher among patients with an index episode of acute complicated diverticulitis compared with acute uncomplicated diverticulitis (12.5% vs 5.7%; p < 0.001). The median time-to-readmission for treatment failure was 21.0 days (range, 20.4-21.6 d), and 85% of all readmissions occurred within 60 days of discharge. On multiple logistic regression, factors independently associated with readmission for treatment failure were an index admission of complicated diverticulitis (OR = 2.06 (95% CI, 1.97-2.16)), disposition on discharge (against medical advice: OR = 1.92 (95% CI, 1.66-2.20); home health care arrangements: OR = 1.24 (95% CI, 1.16-1.33)), and immunosuppression (OR = 1.42 (95% CI, 1.28-1.57)), among others. Risk factors for a complicated treatment failure were also described, after an index episode of complicated and uncomplicated diverticulitis. LIMITATIONS: The study was limited by residual confounding from missing covariates and its observational study design. CONCLUSIONS: The incidence of readmission for treatment failure after an episode of diverticulitis managed nonoperatively is 6.6%, and an index episode of complicated diverticulitis is the strongest risk factor for treatment failure. See Video Abstract at http://links.lww.com/DCR/B92. REINGRESO POR FRACASO DEL TRATAMIENTO DESPUÉS DEL TRATAMIENTO NO QUIRÚRGICO DE LA DIVERTICULITIS AGUDA: UN ANÁLISIS DE LA BASE DE DATOS DE REINGRESOS A NIVEL NACIONAL: La verdadera incidencia y los factores de riesgo para el reingreso por fracaso del tratamiento después de manejo no quirúrgico de la diverticulitis aguda siguen siendo mal definidos.Definir la incidencia y los factores de riesgo de reingreso por fracaso del tratamiento no quirúrgico de la diverticulitis aguda utilizando una base de datos nacional.Estudio de cohorte retrospectivo.Una muestra representativa de ingresos y egresos de hospitales en los Estados Unidos capturados en la base de datos nacional de reingresos hospitalarios.Pacientes adultos (≥18 años) ingresados con un diagnóstico primario de diverticulitis colónica entre 2010-2015, y que fueron tratados de forma no operativa y dados de alta del hospital vivos.Manejo no quirúrgico, que consiste en terapia médica con o sin drenaje percutáneo.Reingreso por fracaso del tratamiento (definido como un reingreso no electivo por diverticulitis dentro de los 90 días despues de ser dados de alta), fracaso del tratamiento complicado (definido como un fracaso del tratamiento con diverticulitis complicada) y el tiempo hasta el tratamiento en casos fracasaados.201.384 pacientes incluidos en total. La incidencia global de reingreso por fracaso del tratamiento fue del 6,6%. El fracaso del tratamiento fue significativamente mayor entre los pacientes con un episodio índice de diverticulitis aguda complicada en comparación con la diverticulitis aguda no complicada (12.5% vs. 5.7%, p <0.001). La mediana del tiempo hasta el reingreso por fracaso del tratamiento fue de 21.0 (20.4 - 21.6) días, y el 85% de todos los reingresos ocurrieron dentro de los 60 días posteriores a ser dados de alta. En la regresión logística múltiple, los factores asociados independientemente con el reingreso por fracaso del tratamiento fueron un índice de admisión de diverticulitis complicada (OR 2.06, IC 95% 1.97-2.16), disposición (de alta en contra del consejo médico: OR 1.92, IC 95% 1.66-2.2; atención médica domiciliaria: OR 1.24, IC 95% 1.16-1.33) e inmunosupresión (OR 1.42, IC 95% 1.28-1.57), entre otros. Los factores de riesgo para un fracaso del tratamiento complicado también se describieron, respectivamente, después de un episodio índice de diverticulitis complicada y no complicada.Covariables faltantes y diseño de estudio observacional.La incidencia de reingreso por fracaso del tratamiento después de un episodio de diverticulitis manejado de forma no operativa es del 6,6%, y un episodio índice de diverticulitis complicada es el factor de riesgo más fuerte para el fracaso del tratamiento. Consulte Video Resumen en http://links.lww.com/DCR/B92. (Traducción-Dr. Adrian E. Ortega).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.227
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.291
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations9
Published2020
Admission routes1
Has abstractyes

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