Modelo predictivo de hipocalcemia iónica grave mediante la estimación de calcio total, albúmina y fósforo.
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| Title: | Modelo predictivo de hipocalcemia iónica grave mediante la estimación de calcio total, albúmina y fósforo. |
|---|---|
| Alternate Title: | Predictive model of severe ionized hypocalcemia based on total calcium, albumin, and phosphorus estimation. |
| Authors: | Yee Barrios, Adriana Guadalupe1 maggiani@gmail.com, Zambrano León, Andrea Guadalupe2, Uriarte Zamora, Brandon Javier2, Saldaña Rocha, Edgar2, Alejandro Gómez, José2, Maggiani Aguilera, Pablo3 |
| Source: | Medicina Interna de México. dic2025, Vol. 41 Issue 12, p725-731. 7p. |
| Subjects: | HYPOCALCEMIA, PREDICTION models, PHOSPHORUS, CALCIUM, ALBUMINS, LOGISTIC regression analysis, CLINICAL decision making |
| Abstract (English): | OBJECTIVE: To develop and validate a predictive model for severe hypocalcemia (ionized calcium < 1.0 mmol/L) using conventional biochemical parameters without the need for blood gas analysis. MATERIALS AND METHODS: A retrospective observational study was conducted in 713 hospitalized patients at the General Hospital of Mazatlán (April 2024-June 2025). Inclusion criteria: patients with simultaneous measurements of total calcium, serum albumin, phosphorus, and ionized calcium upon admission. Exclusion criteria: Patients on renal replacement therapy, or those using calcium/vitamin D supplements or citrate. A logistic regression model was constructed using three predictor variables. Model performance was evaluated using ROC curves, AUC, and predictive values. RESULTS: Severe hypocalcemia was identified in 7.1% of patients. The final model was: logit(p) = 2.5303 - 1.4256 × [total calcium] + 1.3753 × [albumin] + 0.3275 × [phosphorus], with an AUC of 0.862. At a probability cutoff < 0.3, specificity was 0.98 and negative predictive value was 0.96. A significant negative correlation was found between model predictions and ionized calcium levels (r = -0.52; p < 0.001). CONCLUSIONS: This model reliably predicts severe hypocalcemia using readily available parameters, making it a practical tool in settings without access to ionized calcium measurement, and supports timely clinical decision-making. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | OBJETIVO: Desarrollar y validar un modelo predictivo de hipocalcemia grave (calcio ionizado menor de 1.0 mmol/L) utilizando parámetros bioquímicos convencionales sin necesidad de gasometría. MATERIALES Y MÉTODOS: Estudio observacional, retrospectivo, efectuado en pacientes del Hospital General de Mazatlán atendidos entre los meses de abril de 2024 y junio de 2025. Criterios de inclusión: pacientes con mediciones simultáneas de calcio total, albúmina, fósforo y calcio ionizado al ingreso. Criterios de exclusión: pacientes en terapia renal sustitutiva, con consumo reciente de suplementos de calcio y vitamina D o citrato. Se construyó un modelo de regresión logística con tres variables predictoras. El desempeño se evaluó mediante curva ROC, área bajo la curva y valores predictivos. RESULTADOS: Se estudiaron 713 pacientes. La hipocalcemia grave se identificó en el 7.1% (n = 50). El modelo resultante fue: logit(p) = 2.5303 - 1.4256 × [calcio total] + 1.3753 × [albúmina] + 0.3275 × [fósforo], con un área bajo la curva de 0.862. A un punto de corte de probabilidad menor de 0.3; especificidad de 0.98 y el valor predictivo negativo de 0.96. Se observó correlación negativa entre la predicción del modelo y el calcio ionizado (r = -0.52; p < 0.001). CONCLUSIONES: El modelo analizado permite predecir, con buena precisión, la hipocalcemia grave mediante parámetros accesibles. Es útil en escenarios sin gasometría y facilita la toma de decisiones clínicas oportunas. [ABSTRACT FROM AUTHOR] |
| Copyright of Medicina Interna de México is the property of Colegio de Medicina Interna de Mexico and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | MedicLatina |
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| Header | DbId: lth DbLabel: MedicLatina An: 190425232 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Modelo predictivo de hipocalcemia iónica grave mediante la estimación de calcio total, albúmina y fósforo. – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Predictive model of severe ionized hypocalcemia based on total calcium, albumin, and phosphorus estimation. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yee+Barrios%2C+Adriana+Guadalupe%22">Yee Barrios, Adriana Guadalupe</searchLink><relatesTo>1</relatesTo><i> maggiani@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Zambrano+León%2C+Andrea+Guadalupe%22">Zambrano León, Andrea Guadalupe</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Uriarte+Zamora%2C+Brandon+Javier%22">Uriarte Zamora, Brandon Javier</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Saldaña+Rocha%2C+Edgar%22">Saldaña Rocha, Edgar</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Alejandro+Gómez%2C+José%22">Alejandro Gómez, José</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Maggiani+Aguilera%2C+Pablo%22">Maggiani Aguilera, Pablo</searchLink><relatesTo>3</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Medicina+Interna+de+México%22">Medicina Interna de México</searchLink>. dic2025, Vol. 41 Issue 12, p725-731. 7p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22HYPOCALCEMIA%22">HYPOCALCEMIA</searchLink><br /><searchLink fieldCode="DE" term="%22PREDICTION+models%22">PREDICTION models</searchLink><br /><searchLink fieldCode="DE" term="%22PHOSPHORUS%22">PHOSPHORUS</searchLink><br /><searchLink fieldCode="DE" term="%22CALCIUM%22">CALCIUM</searchLink><br /><searchLink fieldCode="DE" term="%22ALBUMINS%22">ALBUMINS</searchLink><br /><searchLink fieldCode="DE" term="%22LOGISTIC+regression+analysis%22">LOGISTIC regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22CLINICAL+decision+making%22">CLINICAL decision making</searchLink> – Name: Abstract Label: Abstract (English) Group: Ab Data: OBJECTIVE: To develop and validate a predictive model for severe hypocalcemia (ionized calcium < 1.0 mmol/L) using conventional biochemical parameters without the need for blood gas analysis. MATERIALS AND METHODS: A retrospective observational study was conducted in 713 hospitalized patients at the General Hospital of Mazatlán (April 2024-June 2025). Inclusion criteria: patients with simultaneous measurements of total calcium, serum albumin, phosphorus, and ionized calcium upon admission. Exclusion criteria: Patients on renal replacement therapy, or those using calcium/vitamin D supplements or citrate. A logistic regression model was constructed using three predictor variables. Model performance was evaluated using ROC curves, AUC, and predictive values. RESULTS: Severe hypocalcemia was identified in 7.1% of patients. The final model was: logit(p) = 2.5303 - 1.4256 × [total calcium] + 1.3753 × [albumin] + 0.3275 × [phosphorus], with an AUC of 0.862. At a probability cutoff < 0.3, specificity was 0.98 and negative predictive value was 0.96. A significant negative correlation was found between model predictions and ionized calcium levels (r = -0.52; p < 0.001). CONCLUSIONS: This model reliably predicts severe hypocalcemia using readily available parameters, making it a practical tool in settings without access to ionized calcium measurement, and supports timely clinical decision-making. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Spanish) Group: Ab Data: OBJETIVO: Desarrollar y validar un modelo predictivo de hipocalcemia grave (calcio ionizado menor de 1.0 mmol/L) utilizando parámetros bioquímicos convencionales sin necesidad de gasometría. MATERIALES Y MÉTODOS: Estudio observacional, retrospectivo, efectuado en pacientes del Hospital General de Mazatlán atendidos entre los meses de abril de 2024 y junio de 2025. Criterios de inclusión: pacientes con mediciones simultáneas de calcio total, albúmina, fósforo y calcio ionizado al ingreso. Criterios de exclusión: pacientes en terapia renal sustitutiva, con consumo reciente de suplementos de calcio y vitamina D o citrato. Se construyó un modelo de regresión logística con tres variables predictoras. El desempeño se evaluó mediante curva ROC, área bajo la curva y valores predictivos. RESULTADOS: Se estudiaron 713 pacientes. La hipocalcemia grave se identificó en el 7.1% (n = 50). El modelo resultante fue: logit(p) = 2.5303 - 1.4256 × [calcio total] + 1.3753 × [albúmina] + 0.3275 × [fósforo], con un área bajo la curva de 0.862. A un punto de corte de probabilidad menor de 0.3; especificidad de 0.98 y el valor predictivo negativo de 0.96. Se observó correlación negativa entre la predicción del modelo y el calcio ionizado (r = -0.52; p < 0.001). CONCLUSIONES: El modelo analizado permite predecir, con buena precisión, la hipocalcemia grave mediante parámetros accesibles. Es útil en escenarios sin gasometría y facilita la toma de decisiones clínicas oportunas. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Medicina Interna de México is the property of Colegio de Medicina Interna de Mexico and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24245/mim.v41i12.10826 Languages: – Code: spa Text: Spanish PhysicalDescription: Pagination: PageCount: 7 StartPage: 725 Subjects: – SubjectFull: HYPOCALCEMIA Type: general – SubjectFull: PREDICTION models Type: general – SubjectFull: PHOSPHORUS Type: general – SubjectFull: CALCIUM Type: general – SubjectFull: ALBUMINS Type: general – SubjectFull: LOGISTIC regression analysis Type: general – SubjectFull: CLINICAL decision making Type: general Titles: – TitleFull: Modelo predictivo de hipocalcemia iónica grave mediante la estimación de calcio total, albúmina y fósforo. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yee Barrios, Adriana Guadalupe – PersonEntity: Name: NameFull: Zambrano León, Andrea Guadalupe – PersonEntity: Name: NameFull: Uriarte Zamora, Brandon Javier – PersonEntity: Name: NameFull: Saldaña Rocha, Edgar – PersonEntity: Name: NameFull: Alejandro Gómez, José – PersonEntity: Name: NameFull: Maggiani Aguilera, Pablo IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: dic2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 01864866 Numbering: – Type: volume Value: 41 – Type: issue Value: 12 Titles: – TitleFull: Medicina Interna de México Type: main |
| ResultId | 1 |
