Dataset Information

Derivation and internal validation of an equation for albumin-adjusted calcium.

ABSTRACT:

Background

Previously published equations to adjust calcium for albumin concentration may vary depending on factors such as the type of reagents used. Albumin-adjusted calcium equations derived from laboratories using the bromocresol purple (BCP) albumin binding reagent have not been described.

Methods

The linear regression equation for the binding of calcium and BCP-albumin was derived in a cohort of 4613 outpatients, and the albumin-adjusted calcium equation was internally validated in a separate cohort of 1538 subjects. The performance of this equation was compared with a previously published equation (adjusted [Ca](mmol/L) = total [Ca](mmol/L) + 0.02 (40 - [albumin] (g/L)) in 343 subjects with albumin < 33 g/L (below reference range).

Results

The local adjustment equation was expressed by the relationship; adjusted [Ca](mmol/L) = total [Ca](mmol/L) + 0.012 (39.9 - [albumin](g/L)). The equation showed evidence of good internal validity (shrinkage value of adjusted r2 = -0.0059). Classification of calcium status differed between the two equations in 47 of 343 subjects with low serum albumin (weighted kappa = 0.46; moderate agreement).

Conclusion

A locally derived and internally validated albumin-adjusted calcium equation differed from previously published equations and resulted in important differences in classification of calcium status in hypoalbuminemia patients. Individual laboratories should determine their own linear regression equation for calcium on albumin rather than relying on published formulas.

SUBMITTER: James MT

PROVIDER: S-EPMC2607282 | biostudies-literature | 2008 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Derivation and internal validation of an equation for albumin-adjusted calcium.

James Matthew T MT Zhang Jianguo J Lyon Andrew W AW Hemmelgarn Brenda R BR

BMC clinical pathology 20081127

<h4>Background</h4>Previously published equations to adjust calcium for albumin concentration may vary depending on factors such as the type of reagents used. Albumin-adjusted calcium equations derived from laboratories using the bromocresol purple (BCP) albumin binding reagent have not been described.<h4>Methods</h4>The linear regression equation for the binding of calcium and BCP-albumin was derived in a cohort of 4613 outpatients, and the albumin-adjusted calcium equation was internally valid ...[more]

PMID: 19038049

Similar Datasets

Project description:ImportanceProtein binding of valproate varies among ICU patients, altering the biologically active free valproate concentration (VPAC). Free VPAC is measured at few laboratories and is often discordant with total VPAC. Existing equations to predict free VPAC are either not validated or are inaccurate in ICU patients.ObjectivesWe designed this study to derive and validate a novel equation to predict free VPAC using data from ICU patients and to compare its performance to published equations.DesignRetrospective cohort study.SettingTwo academic medical centers.ParticipantsPatients older than 18 years old with concomitant free and total VPACs measured in the ICU were included in the derivation cohort if admitted from 2014 to 2018, and the validation cohort if admitted from 2019 to 2022.Main outcomes and measuresMultivariable linear regression was used to derive an equation to predict free VPAC. Modified Bland-Altman plots and the rate of therapeutic concordance between the measured and predicted free VPAC were compared.ResultsDemographics, median free and total VPACs, and valproate free fractions were similar among 115 patients in the derivation cohort and 147 patients in the validation cohort. The Bland-Altman plots showed the new equation performed better (bias, 0.3 [95% limits of agreement, -13.6 to 14.2]) than the Nasreddine (-9.2 [-26.5 to 8.2]), Kodama (-9.7 [-30.0 to 10.7]), Conde Giner (-7.9 [-24.9 to 9.1]), and Parent (-9.9 [-30.7 to 11.0]) equations, and similar to Doré (-2.0 [-16.0 to 11.9]). The Doré and new equations had the highest therapeutic concordance rate (73%).Conclusions and relevanceFor patients at risk of altered protein binding such as ICU patients, existing equations to predict free VPAC are discordant with measured free VPAC. A new equation had low bias but was imprecise. External validation should be performed to improve its precision and generalizability. Until then, monitoring free valproate is recommended during critical illness.

Project description:OBJECTIVES:Albumin-adjusted total calcium is often used as a surrogate marker for free calcium to evaluate hypocalcaemia or hypercalcaemia. Many adjustment formulas based on simple linear regression models have been published, and continue to be used in spite of questionable diagnostic accuracy. In the hope of finding a more pure albumin effect on total calcium, we used multiple linear regression models to adjust for other relevant variables. The regression coefficients of albumin were used to construct local adjustment formulas, and we tested whether the diagnostic accuracy was improved compared with previously published formulas and unadjusted calcium. DESIGN:A retrospective hospital laboratory data study. DATA SOURCES:The local hospital laboratory data system. SETTING:Norway, 2006-2015. PARTICIPANTS:6549 patients above 2 years of age, where free calcium standardised at pH 7.40, total calcium, creatinine, albumin and phosphate had been analysed in a single blood draw, including hospitalised patients and patients from outpatient clinics and general practice. MAIN OUTCOME MEASURES:Diagnostic accuracy by Harrell's c and receiver operating characteristic curve analysis, using free calcium standardised at pH 7.40 as a gold standard, in subgroups with estimated glomerular filtration rate (eGFR) ?60?or <60?mL/min/1.73?m2. RESULTS:In the subgroup with eGFR <60?mL/min/1.73?m2, the Harrell's c of unadjusted total calcium (0.801) was significantly larger than those of the local formulas (0.790, p=0.002) and the best formula taken from literature (0.791, p=0.004). In the subgroup with eGFR ?60?mL/min/1.73?m2, no significant differences were found between these three formulas. CONCLUSIONS:Our study shows that the diagnostic accuracy of unadjusted total calcium is superior to several commonly used adjustment formulas, and we suggest that the use of such formulas should be abandoned in clinical practice. If the clinician does not trust total calcium to reflect the calcium status of the patient, free calcium should be measured.

Project description:OBJECTIVES:To develop a clinical prediction score for predicting mortality in children following return of spontaneous circulation after in-hospital cardiac arrest. DESIGN:Observational study using prospectively collected data. SETTING:This was an analysis using data from the Get With The Guidelines-Resuscitation registry between January 2000 and December 2015. PATIENTS:Pediatric patients (< 18 yr old) who achieved return of spontaneous circulation. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The primary outcome was in-hospital mortality. Patients were divided into a derivation (3/4) and validation (1/4) cohort. A prediction score was developed using a multivariable logistic regression model with backward selection. Patient and event characteristics for the derivation cohort (n = 3,893) and validation cohort (n = 1,297) were similar. Seventeen variables associated with the outcome remained in the final reduced model after backward elimination. Predictors of in-hospital mortality included age, illness category, pre-event characteristics, arrest location, day of the week, nonshockable pulseless rhythm, duration of chest compressions, and interventions in place at time of arrest. The C-statistic for the final score was 0.77 (95% CI, 0.75-0.78) in the derivation cohort and 0.77 (95% CI, 0.74-0.79) in the validation cohort. The expected versus observed mortality plot indicated good calibration in both the derivation and validation cohorts. The score showed a stepwise increase in mortality with an observed mortality of less than 15% for scores 0-9 and greater than 80% for scores greater than or equal to 25. The model also performed well for neurologic outcome and in sensitivity analyses for events within the past 5 years and for patients with or without a pulse at the onset of chest compressions. CONCLUSIONS:We developed and internally validated a prediction score for initial survivors of pediatric in-hospital cardiac arrest. This prediction score may be useful for prognostication following cardiac arrest, stratifying patients for research, and guiding quality improvement initiatives.

Project description:BackgroundRheumatoid arthritis (RA) patients have increased risk for cardiovascular disease (CVD). Accurate CVD risk prediction could improve care for RA patients. Our goal is to develop and validate a biomarker-based model for predicting CVD risk in RA patients.MethodsMedicare claims data were linked to multi-biomarker disease activity (MBDA) test results to create an RA patient cohort with age ??40?years that was split 2:1 for training and internal validation. Clinical and RA-related variables, MBDA score, and its 12 biomarkers were evaluated as predictors of a composite CVD outcome: myocardial infarction (MI), stroke, or fatal CVD within 3?years. Model building used Cox proportional hazard regression with backward elimination. The final MBDA-based CVD risk score was internally validated and compared to four clinical CVD risk prediction models.Results30,751 RA patients (904 CVD events) were analyzed. Covariates in the final MBDA-based CVD risk score were age, diabetes, hypertension, tobacco use, history of CVD (excluding MI/stroke), MBDA score, leptin, MMP-3 and TNF-R1. In internal validation, the MBDA-based CVD risk score was a strong predictor of 3-year risk for a CVD event, with hazard ratio (95% CI) of 2.89 (2.46-3.41). The predicted 3-year CVD risk was low for 9.4% of patients, borderline for 10.2%, intermediate for 52.2%, and high for 28.2%. Model fit was good, with mean predicted versus observed 3-year CVD risks of 4.5% versus 4.4%. The MBDA-based CVD risk score significantly improved risk discrimination by the likelihood ratio test, compared to four clinical models. The risk score also improved prediction, reclassifying 42% of patients versus the simplest clinical model (age + sex), with a net reclassification index (NRI) (95% CI) of 0.19 (0.10-0.27); and 28% of patients versus the most comprehensive clinical model (age + sex + diabetes + hypertension + tobacco use + history of CVD + CRP), with an NRI of 0.07 (0.001-0.13). C-index was 0.715 versus 0.661 to 0.696 for the four clinical models.ConclusionA prognostic score has been developed to predict 3-year CVD risk for RA patients by using clinical data, three serum biomarkers and the MBDA score. In internal validation, it had good accuracy and outperformed clinical models with and without CRP. The MBDA-based CVD risk prediction score may improve RA patient care by offering a risk stratification tool that incorporates the effect of RA inflammation.

Dataset Information

Derivation and internal validation of an equation for albumin-adjusted calcium.

Background

Methods

Results

Conclusion

Publications

Derivation and internal validation of an equation for albumin-adjusted calcium.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets