Caustic Ingestion: A Risk-Based Algorithm
Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches...
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| Published in | The American journal of gastroenterology Vol. 117; no. 10; pp. 1593 - 1604 |
|---|---|
| Main Authors | , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Wolters Kluwer
01.10.2022
Wolters Kluwer Health Medical Research, Lippincott Williams & Wilkins |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0002-9270 1572-0241 1572-0241 |
| DOI | 10.14309/ajg.0000000000001953 |
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| Abstract | Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy.
All patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series.
The sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3-16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9-388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2-55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4-23.5) and computed tomography (16.3%; 95% CI: 13.0-19.5) would be lower than that for the other 2 algorithms.
A risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements. |
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| AbstractList | INTRODUCTION:Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy.METHODS:All patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series.RESULTS:The sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3–16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9–388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2–55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4–23.5) and computed tomography (16.3%; 95% CI: 13.0–19.5) would be lower than that for the other 2 algorithms.DISCUSSION:A risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements. abstract-type="graphical"> Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy.INTRODUCTIONCaustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy.All patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series.METHODSAll patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series.The sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3-16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9-388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2-55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4-23.5) and computed tomography (16.3%; 95% CI: 13.0-19.5) would be lower than that for the other 2 algorithms.RESULTSThe sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3-16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9-388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2-55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4-23.5) and computed tomography (16.3%; 95% CI: 13.0-19.5) would be lower than that for the other 2 algorithms.A risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements.DISCUSSIONA risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements. Caustic ingestion management could be improved with a diagnostic approach based on risk factors. This study aimed to develop an algorithm derived from predictive factors of a poor clinical course, to evaluate its diagnostic accuracy and resource consumption, and to compare it with 2 other approaches, a radiological one based on computed tomography and a classical one based on symptoms and endoscopy. All patients older than 15 years presenting with caustic ingestion in our tertiary care hospital between 1995 and 2021 were prospectively included. Adverse outcome was defined as intensive care unit admission, emergency surgery, or death. Ingestion characteristics, symptoms, and laboratory and endoscopic findings were analyzed to determine the most relevant risk factors. Diagnostic accuracy and the number of examinations required were estimated and compared with the other 2 algorithms applied to our series. The sample included 532 cases of caustic ingestion, 13.2% (95% confidence interval [CI]: 10.3-16.0) of which had adverse outcomes. Volume and type of caustic substance; presence of symptoms and pharyngolaryngeal involvement; and neutrophilia, acidosis, and endoscopic injury were combined to develop an algorithm that would provide the highest diagnostic odds ratio (167.2; 95% CI: 71.9-388.7). Following this approach, half of the patients (50.6%; 95% CI: 46.2-55.1) would not require any examination and, overall, the need for endoscopy (20.0%; 95% CI: 16.4-23.5) and computed tomography (16.3%; 95% CI: 13.0-19.5) would be lower than that for the other 2 algorithms. A risk-based algorithm could improve caustic ingestion management by maintaining high diagnostic accuracy while reducing diagnostic test requirements. |
| Author | Tosca, Joan Herreros, Belén Mas, Pilar Sánchiz, Vicente Poyatos, Paloma Pascual, Isabel Sanahuja, Ana Villagrasa, Rosana Mínguez, Miguel Peña, Andrés Sánchez, Ana Lluch, Paloma |
| AuthorAffiliation | Department of Digestive Medicine, Hospital de la Marina Baixa de la Vila Joiosa, Alicante, Spain Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain |
| AuthorAffiliation_xml | – name: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – name: Department of Digestive Medicine, Hospital de la Marina Baixa de la Vila Joiosa, Alicante, Spain |
| Author_xml | – sequence: 1 givenname: Joan surname: Tosca fullname: Tosca, Joan organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 2 givenname: Ana surname: Sánchez fullname: Sánchez, Ana organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 3 givenname: Ana surname: Sanahuja fullname: Sanahuja, Ana organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 4 givenname: Rosana surname: Villagrasa fullname: Villagrasa, Rosana organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 5 givenname: Paloma surname: Poyatos fullname: Poyatos, Paloma organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 6 givenname: Pilar surname: Mas fullname: Mas, Pilar organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 7 givenname: Isabel surname: Pascual fullname: Pascual, Isabel organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 8 givenname: Paloma surname: Lluch fullname: Lluch, Paloma organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 9 givenname: Belén surname: Herreros fullname: Herreros, Belén organization: Department of Digestive Medicine, Hospital de la Marina Baixa de la Vila Joiosa, Alicante, Spain – sequence: 10 givenname: Andrés surname: Peña fullname: Peña, Andrés organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 11 givenname: Vicente surname: Sánchiz fullname: Sánchiz, Vicente organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain – sequence: 12 givenname: Miguel surname: Mínguez fullname: Mínguez, Miguel organization: Department of Digestive Medicine, Hospital Clínic Universitari de València, Universitat de València, Valencia, Spain |
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| SubjectTerms | Ability tests Accuracy Algorithms Burns, Chemical - diagnosis Caustics - toxicity Eating Emergency medical care Endoscopy Gastroenterology Hemodynamics Humans Medical prognosis Missing data Multivariate analysis Normal distribution Observational studies Patients Regression analysis Retrospective Studies Sample size Variables |
| Title | Caustic Ingestion: A Risk-Based Algorithm |
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