miércoles, 10 de mayo de 2017

Derivation of decision rules to predict clinically important outcomes in acute flank pain patients. - PubMed - NCBI

Derivation of decision rules to predict clinically important outcomes in acute flank pain patients. - PubMed - NCBI



 2017 Apr;35(4):554-563. doi: 10.1016/j.ajem.2016.12.009. Epub 2016 Dec 11.

Derivation of decision rules to predict clinically important outcomes in acute flank pain patients.

Abstract

OBJECTIVE:

Routine CT for patients with acute flank pain has not been shown to improve patient outcomes, and it may unnecessarily expose patients to radiation and increased costs. As preliminary steps toward the development of a guideline for selective CT, we sought to determine the prevalence of clinically important outcomes in patients with acute flank pain and derive preliminary decision rules.

METHODS:

We analyzed data from a randomized trial of CT vs. ultrasonography for patients with acute flank pain from 15 EDs between October 2011 and February 2013. Clinically important outcomes were defined as inpatient admission for ureteral stones and alternative diagnoses. Clinically important stones were defined as stones requiring urologic intervention. We sought to derive highly sensitive decision rules for both outcomes.

RESULTS:

Of 2759 participants, 236 (8.6%) had a clinically important outcome and 143 (5.2%) had a clinically important stone. A CDR including anemia (hemoglobin <13.2g/dl), WBC count >11000/μl, age>42years, and the absence of CVAT had a sensitivity of 97.9% (95% CI 94.8-99.2%) and specificity of 18.7% (95% 17.2-20.2%) for clinically important outcome. A CDR including hydronephrosis, prior history of stone, and WBC count <8300/μl had a sensitivity of 98.6% (95% CI 94.5-99.7%) and specificity of 26.0% (95% 24.2-27.7%) for clinically important stone.

CONCLUSIONS:

We determined the prevalence of clinically important outcomes in patients with acute flank pain, and derived preliminary high sensitivity CDRs that predict them. Validation of CDRs with similar test characteristics would require prospective enrollment of 2100 patients.

PMID:
 
28082160
 
DOI:
 
10.1016/j.ajem.2016.12.009

[Indexed for MEDLINE]

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