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External Validation of the STONE Score, a Clinical Prediction Rule for Ureteral Stone: An Observational Multi-institutional Study.

ABSTRACT: The STONE score is a clinical decision rule that classifies patients with suspected nephrolithiasis into low-, moderate-, and high-score groups, with corresponding probabilities of ureteral stone. We evaluate the STONE score in a multi-institutional cohort compared with physician gestalt and hypothesize that it has a sufficiently high specificity to allow clinicians to defer computed tomography (CT) scan in patients with suspected nephrolithiasis.We assessed the STONE score with data from a randomized trial for participants with suspected nephrolithiasis who enrolled at 9 emergency departments between October 2011 and February 2013. In accordance with STONE predictors, we categorized participants into low-, moderate-, or high-score groups. We determined the performance of the STONE score and physician gestalt for ureteral stone.Eight hundred forty-five participants were included for analysis; 331 (39%) had a ureteral stone. The global performance of the STONE score was superior to physician gestalt (area under the receiver operating characteristic curve=0.78 [95% confidence interval {CI} 0.74 to 0.81] versus 0.68 [95% CI 0.64 to 0.71]). The prevalence of ureteral stone on CT scan ranged from 14% (95% CI 9% to 19%) to 73% (95% CI 67% to 78%) in the low-, moderate-, and high-score groups. The sensitivity and specificity of a high score were 53% (95% CI 48% to 59%) and 87% (95% CI 84% to 90%), respectively.The STONE score can successfully aggregate patients into low-, medium-, and high-risk groups and predicts ureteral stone with a higher specificity than physician gestalt. However, in its present form, the STONE score lacks sufficient accuracy to allow clinicians to defer CT scan for suspected ureteral stone.

SUBMITTER: Wang RC

PROVIDER: S-EPMC4808407 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature

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External Validation of the STONE Score, a Clinical Prediction Rule for Ureteral Stone: An Observational Multi-institutional Study.

Wang Ralph C RC Rodriguez Robert M RM Moghadassi Michelle M Noble Vicki V Bailitz John J Mallin Mike M Corbo Jill J Kang Tarina L TL Chu Phillip P Shiboski Steve S Smith-Bindman Rebecca R

Annals of emergency medicine 20151003 4

<h4>Study objective</h4>The STONE score is a clinical decision rule that classifies patients with suspected nephrolithiasis into low-, moderate-, and high-score groups, with corresponding probabilities of ureteral stone. We evaluate the STONE score in a multi-institutional cohort compared with physician gestalt and hypothesize that it has a sufficiently high specificity to allow clinicians to defer computed tomography (CT) scan in patients with suspected nephrolithiasis.<h4>Methods</h4>We assess ...[more]

PMID: 26440490

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Project description:ObjectiveTo derive and validate an objective clinical prediction rule for the presence of uncomplicated ureteral stones in patients eligible for computed tomography (CT). We hypothesized that patients with a high probability of ureteral stones would have a low probability of acutely important alternative findings.DesignRetrospective observational derivation cohort; prospective observational validation cohort.SettingUrban tertiary care emergency department and suburban freestanding community emergency department.ParticipantsAdults undergoing non-contrast CT for suspected uncomplicated kidney stone. The derivation cohort comprised a random selection of patients undergoing CT between April 2005 and November 2010 (1040 patients); the validation cohort included consecutive prospectively enrolled patients from May 2011 to January 2013 (491 patients).Main outcome measuresIn the derivation phase a priori factors potentially related to symptomatic ureteral stone were derived from the medical record blinded to the dictated CT report, which was separately categorized by diagnosis. Multivariate logistic regression was used to determine the top five factors associated with ureteral stone and these were assigned integer points to create a scoring system that was stratified into low, moderate, and high probability of ureteral stone. In the prospective phase this score was observationally derived blinded to CT results and compared with the prevalence of ureteral stone and important alternative causes of symptoms.ResultsThe derivation sample included 1040 records, with five factors found to be most predictive of ureteral stone: male sex, short duration of pain, non-black race, presence of nausea or vomiting, and microscopic hematuria, yielding a score of 0-13 (the STONE score). Prospective validation was performed on 491 participants. In the derivation and validation cohorts ureteral stone was present in, respectively, 8.3% and 9.2% of the low probability (score 0-5) group, 51.6% and 51.3% of the moderate probability (score 6-9) group, and 89.6% and 88.6% of the high probability (score 10-13) group. In the high score group, acutely important alternative findings were present in 0.3% of the derivation cohort and 1.6% of the validation cohort.ConclusionsThe STONE score reliably predicts the presence of uncomplicated ureteral stone and lower likelihood of acutely important alternative findings. Incorporation in future investigations may help to limit exposure to radiation and over-utilization of imaging.Trial registrationwww.clinicaltrials.gov NCT01352676.

Project description:BackgroundMany dementia prediction models have been developed, but only few have been externally validated, which hinders clinical uptake and may pose a risk if models are applied to actual patients regardless. Externally validating an existing prediction model is a difficult task, where we mostly rely on the completeness of model reporting in a published article. In this study, we aim to externally validate existing dementia prediction models. To that end, we define model reporting criteria, review published studies, and externally validate three well reported models using routinely collected health data from administrative claims and electronic health records.MethodsWe identified dementia prediction models that were developed between 2011 and 2020 and assessed if they could be externally validated given a set of model criteria. In addition, we externally validated three of these models (Walters' Dementia Risk Score, Mehta's RxDx-Dementia Risk Index, and Nori's ADRD dementia prediction model) on a network of six observational health databases from the United States, United Kingdom, Germany and the Netherlands, including the original development databases of the models.ResultsWe reviewed 59 dementia prediction models. All models reported the prediction method, development database, and target and outcome definitions. Less frequently reported by these 59 prediction models were predictor definitions (52 models) including the time window in which a predictor is assessed (21 models), predictor coefficients (20 models), and the time-at-risk (42 models). The validation of the model by Walters (development c-statistic: 0.84) showed moderate transportability (0.67-0.76 c-statistic). The Mehta model (development c-statistic: 0.81) transported well to some of the external databases (0.69-0.79 c-statistic). The Nori model (development AUROC: 0.69) transported well (0.62-0.68 AUROC) but performed modestly overall. Recalibration showed improvements for the Walters and Nori models, while recalibration could not be assessed for the Mehta model due to unreported baseline hazard.ConclusionWe observed that reporting is mostly insufficient to fully externally validate published dementia prediction models, and therefore, it is uncertain how well these models would work in other clinical settings. We emphasize the importance of following established guidelines for reporting clinical prediction models. We recommend that reporting should be more explicit and have external validation in mind if the model is meant to be applied in different settings.

Project description:BackgroundRespiratory viruses are important etiologies of community-acquired pneumonia. However, current knowledge on the prognosis of respiratory virus-related pneumonia (RV-p) is limited. Thus, here we aimed to establish a clinical predictive model for mortality of patients with RV-p.MethodsA total of 1431 laboratory-confirmed patients with RV-p, including 1169 and 262 patients from respective derivation and validation cohorts from five teaching hospitals in China were assessed between January 2010 and December 2019. A prediction rule was established on the basis of risk factors for 30-day mortality of patients with RV-p from the derivation cohort using a multivariate logistic regression model.ResultsThe 30-day mortality of patients with RV-p was 16.8% (241/1431). The RV-p score was composed of nine predictors (including respective points of mortality risk): (a) age ⩾65 years (1 point); (b) chronic obstructive pulmonary disease (1 point); (c) mental confusion (1 point); (d) blood urea nitrogen (1 point); (e) cardiovascular disease (2 points); (f) smoking history (2 points); (g) arterial pressure of oxygen/fraction of inspiration oxygen (PaO2/FiO2) < 250 mmHg (2 points); (h) lymphocyte counts <0.8 × 109/L (2 points); (i) arterial PH < 7.35 (3 points). A total of six points was used as the cut-off value for mortality risk stratification. Our model showed a sensitivity of 0.831 and a specificity of 0.783. The area under the receiver operating characteristic curve was more prominent for RV-p scoring [0.867, 95% confidence interval (CI)0.846-0.886] when compared with both pneumonia severity index risk (0.595, 95% CI 0.566-0.624, p < 0.001) and CURB-65 scoring (0.739, 95% CI 0.713-0.765, p < 0.001).ConclusionRV-p scoring was able to provide a good predictive accuracy for 30-day mortality, which accounted for a more effective stratification of patients with RV-p into relevant risk categories and, consequently, help physicians to make more rational clinical decisions.The reviews of this paper are available via the supplemental material section.

Dataset Information

External Validation of the STONE Score, a Clinical Prediction Rule for Ureteral Stone: An Observational Multi-institutional Study.

Publications

External Validation of the STONE Score, a Clinical Prediction Rule for Ureteral Stone: An Observational Multi-institutional Study.

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