{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/97685"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/97685","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Predictive model to estimate ionized calcium from routine serum biochemical profiles in dogs","abstract":"Ionized calcium is the gold standard to assess calcium status in dogs, but measurement is not readily available in private veterinary practices. The objectives of this study were to (1) predict ionized calcium concentration from serum biochemical values and (2) compare the diagnostic performance of predicted ionized calcium (piCa) to those of total calcium (tCa) and two corrected tCa formulae; and (3) study the relationship between biochemical values and variation of measured ionized calcium (miCa). This was a cross-sectional study. Records from 1,200 dogs who were patients at the University of Illinois Veterinary Teaching Hospital were randomly selected from a population of 1,719 dogs with mical and biochemical profile performed within 24 hours for the creation of a multivariate adaptive regression splines (MARS) model, with the final model being determined by backward elimination. Accuract and diagnostic performance of piCal and its prediction interval (PI) were tested on 519 dogs via Bland-Altman analysis, Pearson’s R, and receiver operator characteristic (ROC) curves. The final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Predicted ionized calcium was better correlated to miCa than tCa and corrected tCa, and its overall diagnostic accuracy was significantly higher to diagnose hypocalcemia and improved for hypercalcemia. The average difference between the piCal and miCal was 0.002 +/- 0.080 mmol/L. The PI included miCal 94% of the time. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) than tCa, and more specific (98.4%) than corrected tCa formulae. Positive predictive values of piCa were high for both hypercalcemia (90%) and hypocalcemia (70.8%). Predicted ionized calcium can be obtained from readily available biochemical and patient variables, and seems more useful than tCa and corrected tCa to approach calcium disorders in dogs when miCa is not available. A webpage has been designed for piCa calculation (http://vetmed.illinois.edu/study/mars-model/VetMed.php).","abstract_html":"Ionized calcium is the gold standard to assess calcium status in dogs, but measurement is not readily available in private veterinary practices. The objectives of this study were to (1) predict ionized calcium concentration from serum biochemical values and (2) compare the diagnostic performance of predicted ionized calcium (piCa) to those of total calcium (tCa) and two corrected tCa formulae; and (3) study the relationship between biochemical values and variation of measured ionized calcium (miCa). This was a cross-sectional study. Records from 1,200 dogs who were patients at the University of Illinois Veterinary Teaching Hospital were randomly selected from a population of 1,719 dogs with mical and biochemical profile performed within 24 hours for the creation of a multivariate adaptive regression splines (MARS) model, with the final model being determined by backward elimination. Accuract and diagnostic performance of piCal and its prediction interval (PI) were tested on 519 dogs via Bland-Altman analysis, Pearson’s R, and receiver operator characteristic (ROC) curves. The final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Predicted ionized calcium was better correlated to miCa than tCa and corrected tCa, and its overall diagnostic accuracy was significantly higher to diagnose hypocalcemia and improved for hypercalcemia. The average difference between the piCal and miCal was 0.002 +/- 0.080 mmol/L. The PI included miCal 94% of the time. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) than tCa, and more specific (98.4%) than corrected tCa formulae. Positive predictive values of piCa were high for both hypercalcemia (90%) and hypocalcemia (70.8%). Predicted ionized calcium can be obtained from readily available biochemical and patient variables, and seems more useful than tCa and corrected tCa to approach calcium disorders in dogs when miCa is not available. A webpage has been designed for piCa calculation (http://vetmed.illinois.edu/study/mars-model/VetMed.php).","abstract_has_math":false,"creators":["Danner, Julie Ann"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"VMS-Veterinary Clinical Medcne","degree_department":null,"school":null,"contributors":["Ridgway, Marcella D.","Rubin, Stanley I.","Solter, Philip"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-08-10T20:32:50Z","date_published":"2017-08-10T20:32:50Z","updated_at":"2026-07-22T22:24:34Z","subjects":["Calcium","Hypercalcemia","Ionized","Veterinary"],"languages":["en"],"rights":["Copyright 2017 Julie Danner"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/97685","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ridgway, Marcella D.","Rubin, Stanley I.","Solter, Philip"]},{"key":"dc:creator","label":"Author","values":["Danner, Julie Ann"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2017-08-10T20:32:50Z","2019-08-11T09:15:09Z","2017-04-12","2017-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["VMS-Veterinary Clinical Medcne"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Calcium","Hypercalcemia","Ionized","Veterinary"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2017 Julie Danner"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/97685"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ionized calcium is the gold standard to assess calcium status in dogs, but measurement is not readily available in private veterinary practices. The objectives of this study were to (1) predict ionized calcium concentration from serum biochemical values and (2) compare the diagnostic performance of predicted ionized calcium (piCa) to those of total calcium (tCa) and two corrected tCa formulae; and (3) study the relationship between biochemical values and variation of measured ionized calcium (miCa). This was a cross-sectional study. Records from 1,200 dogs who were patients at the University of Illinois Veterinary Teaching Hospital were randomly selected from a population of 1,719 dogs with mical and biochemical profile performed within 24 hours for the creation of a multivariate adaptive regression splines (MARS) model, with the final model being determined by backward elimination. Accuract and diagnostic performance of piCal and its prediction interval (PI) were tested on 519 dogs via Bland-Altman analysis, Pearson’s R, and receiver operator characteristic (ROC) curves. The final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Predicted ionized calcium was better correlated to miCa than tCa and corrected tCa, and its overall diagnostic accuracy was significantly higher to diagnose hypocalcemia and improved for hypercalcemia. The average difference between the piCal and miCal was 0.002 +/- 0.080 mmol/L. The PI included miCal 94% of the time. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) than tCa, and more specific (98.4%) than corrected tCa formulae. Positive predictive values of piCa were high for both hypercalcemia (90%) and hypocalcemia (70.8%). Predicted ionized calcium can be obtained from readily available biochemical and patient variables, and seems more useful than tCa and corrected tCa to approach calcium disorders in dogs when miCa is not available. A webpage has been designed for piCa calculation (http://vetmed.illinois.edu/study/mars-model/VetMed.php).","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-05-01","The student, Julie Danner, accepted the attached license on 2017-04-10 at 17:13.","The student, Julie Danner, submitted this Thesis for approval on 2017-04-10 at 17:20.","This Thesis was approved for publication on 2017-04-12 at 10:10.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10693 on 2017-08-10 at 15:05:22","Made available in DSpace on 2017-08-10T20:32:50Z (GMT). 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The objectives of this study were to (1) predict ionized calcium concentration from serum biochemical values and (2) compare the diagnostic performance of predicted ionized calcium (piCa) to those of total calcium (tCa) and two corrected tCa formulae; and (3) study the relationship between biochemical values and variation of measured ionized calcium (miCa). This was a cross-sectional study. Records from 1,200 dogs who were patients at the University of Illinois Veterinary Teaching Hospital were randomly selected from a population of 1,719 dogs with mical and biochemical profile performed within 24 hours for the creation of a multivariate adaptive regression splines (MARS) model, with the final model being determined by backward elimination. Accuract and diagnostic performance of piCal and its prediction interval (PI) were tested on 519 dogs via Bland-Altman analysis, Pearson’s R, and receiver operator characteristic (ROC) curves. The final model included creatinine, albumin, tCa, phosphorus, sodium, potassium, chloride, alkaline phosphatase, triglycerides, and age, with tCa, albumin, and chloride having the highest impact on miCa variation. Predicted ionized calcium was better correlated to miCa than tCa and corrected tCa, and its overall diagnostic accuracy was significantly higher to diagnose hypocalcemia and improved for hypercalcemia. The average difference between the piCal and miCal was 0.002 +/- 0.080 mmol/L. The PI included miCal 94% of the time. For hypercalcemia, piCa was as sensitive (64%) but more specific (99.6%) than tCa and corrected tCa. For hypocalcemia, piCa was more sensitive (21.8%) than tCa, and more specific (98.4%) than corrected tCa formulae. Positive predictive values of piCa were high for both hypercalcemia (90%) and hypocalcemia (70.8%). Predicted ionized calcium can be obtained from readily available biochemical and patient variables, and seems more useful than tCa and corrected tCa to approach calcium disorders in dogs when miCa is not available. A webpage has been designed for piCa calculation (http://vetmed.illinois.edu/study/mars-model/VetMed.php).","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-05-01","The student, Julie Danner, accepted the attached license on 2017-04-10 at 17:13.","The student, Julie Danner, submitted this Thesis for approval on 2017-04-10 at 17:20.","This Thesis was approved for publication on 2017-04-12 at 10:10.","DSpace SAF Submission Ingestion Package generated from Vireo submission #10693 on 2017-08-10 at 15:05:22","Made available in DSpace on 2017-08-10T20:32:50Z (GMT). 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