A multi-centre cohort study evaluating the role of inflammatory markers in patient's presenting with acute ureteric colic (MIMIC).
Int J Surg Protoc
; 6: 1-4, 2017.
Article
en En
| MEDLINE
| ID: mdl-31851729
ABSTRACT
BACKGROUND:
Spontaneous Stone Passage (SSP) rates in acute ureteric colic range from 47 to 75%. There is conflicting evidence on the role of raised inflammatory markers in acute ureteric colic. The use of an easily applicable biomarker that could predict SSP or need for intervention would improve the management of obstructing ureteric stones. Thus, there is a need to determine in an appropriately powered study, in patients who are initially managed conservatively, which factors at the time of acute admission can predict subsequent patient outcome such as SSP and the need for intervention. Particularly, establishing whether levels of white cell count (WBC) at presentation are associated with likelihood of SSP or intervention may guide clinicians on the management of these patients' stones.DESIGN:
Multi-center cohort study disseminated via the UK British Urology Researchers in Surgical Training (BURST) and Australian Young Urology Researchers Organisation (YURO). PRIMARY RESEARCH QUESTION What is the association between WBC and SSP in patients discharged from emergency department after initial conservative management? PATIENT POPULATION Patients who have presented with acute renal colic with CT KUB evidence of a solitary ureteric stone. A minimum sample size of 720 patients across 15 centres will be needed.HYPOTHESIS:
A raised WBC is associated with decreased odds of spontaneous stone passage. PRIMARYOUTCOME:
The occurrence of SSP within six months of presentation with acute ureteric colic (YES/NO). SSP was defined as absence of need for intervention to assist stone passage. STATISTICAL ANALYSIS PLAN A multivariable logistic regression model will be constructed, where the outcome of interest is SSP using data from patients who do not undergo intervention at presentation. A random effect will be used to account for clustering of patients within hospitals/institutions. The model will include adjustments for gender, age as control variables.
Texto completo:
1
Base de datos:
MEDLINE
Tipo de estudio:
Clinical_trials
/
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Int J Surg Protoc
Año:
2017
Tipo del documento:
Article