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Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem

A newborn girl had, from two weeks on, small bruises on varying body locations, but not on her chest. Her Armenian grandmother easily bruised, too. Her mother was diagnosed with hypermobility-type Ehlers-Danlos-Syndrome (hEDS), an autosomal dominant connective tissue disorder, with a 50% inheritance...

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Autores principales: van Gemert, Martin J. C., Zwinderman, Aeilko H., van Koppen, Peter J., Neumann, H. A. Martino, Vlaming, Marianne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217160/
https://www.ncbi.nlm.nih.gov/pubmed/37238391
http://dx.doi.org/10.3390/children10050843
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author van Gemert, Martin J. C.
Zwinderman, Aeilko H.
van Koppen, Peter J.
Neumann, H. A. Martino
Vlaming, Marianne
author_facet van Gemert, Martin J. C.
Zwinderman, Aeilko H.
van Koppen, Peter J.
Neumann, H. A. Martino
Vlaming, Marianne
author_sort van Gemert, Martin J. C.
collection PubMed
description A newborn girl had, from two weeks on, small bruises on varying body locations, but not on her chest. Her Armenian grandmother easily bruised, too. Her mother was diagnosed with hypermobility-type Ehlers-Danlos-Syndrome (hEDS), an autosomal dominant connective tissue disorder, with a 50% inheritance probability. Referral to a University Medical Center located “Dutch Expertise Center for Child Abuse” resulted (prior to consultation) in physical abuse suspicion. Protocol-based skeletal X-rays showed three healed, asymptomatic rib fractures. A protocol-based Bayesian likelihood ratio guesstimation gave 10–100, erroneously used to suggest a 10–100 times likelier non-accidental-than-accidental cause. Foster care placement followed, even in a secret home, where she also bruised, suggesting hEDS inheritance. Correct non-accidental/accidental Bayes’ probability of symptoms is (likelihood ratio) × (physical abuse incidence). From the literature, we derived an infant abuse incidence between about ≈0.0009 and ≈0.0026 and a likelihood ratio of <5 for bruises. For rib fractures, we used a zero likelihood ratio, arguing their cause was birth trauma from the extra delivery pressure on the chest, combined with fragile bones as the daughter of an hEDS-mother. We thus derived a negligible abuse/accidental probability between <5 × 0.0009 <0.005 and <5 × 0.0026 <0.013. The small abuse incidence implies that correctly using Bayes’ theorem will also miss true infant physical abuse cases. Curiously, because likelihood ratios assess how more often symptoms develop if abuse did occur versus non-abuse, Bayes’ theorem then implies a 100% infant abuse incidence (unwittingly) used by LECK. In conclusion, probabilities should never replace differential diagnostic procedures, the accepted medical method of care. Well-known from literature, supported by the present case, is that (child abuse pediatrics) physicians, child protection workers, and judges were unlikely to understand Bayesian statistics. Its use without statistics consultation should therefore not have occurred. Thus, Bayesian statistics, and certainly (misused) likelihood ratios, should never be applied in cases of physical child abuse suspicion. Finally, parental innocence follows from clarifying what could have caused the girl’s bruises (inherited hEDS), and rib fractures (birth trauma from fragile bones).
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spelling pubmed-102171602023-05-27 Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem van Gemert, Martin J. C. Zwinderman, Aeilko H. van Koppen, Peter J. Neumann, H. A. Martino Vlaming, Marianne Children (Basel) Case Report A newborn girl had, from two weeks on, small bruises on varying body locations, but not on her chest. Her Armenian grandmother easily bruised, too. Her mother was diagnosed with hypermobility-type Ehlers-Danlos-Syndrome (hEDS), an autosomal dominant connective tissue disorder, with a 50% inheritance probability. Referral to a University Medical Center located “Dutch Expertise Center for Child Abuse” resulted (prior to consultation) in physical abuse suspicion. Protocol-based skeletal X-rays showed three healed, asymptomatic rib fractures. A protocol-based Bayesian likelihood ratio guesstimation gave 10–100, erroneously used to suggest a 10–100 times likelier non-accidental-than-accidental cause. Foster care placement followed, even in a secret home, where she also bruised, suggesting hEDS inheritance. Correct non-accidental/accidental Bayes’ probability of symptoms is (likelihood ratio) × (physical abuse incidence). From the literature, we derived an infant abuse incidence between about ≈0.0009 and ≈0.0026 and a likelihood ratio of <5 for bruises. For rib fractures, we used a zero likelihood ratio, arguing their cause was birth trauma from the extra delivery pressure on the chest, combined with fragile bones as the daughter of an hEDS-mother. We thus derived a negligible abuse/accidental probability between <5 × 0.0009 <0.005 and <5 × 0.0026 <0.013. The small abuse incidence implies that correctly using Bayes’ theorem will also miss true infant physical abuse cases. Curiously, because likelihood ratios assess how more often symptoms develop if abuse did occur versus non-abuse, Bayes’ theorem then implies a 100% infant abuse incidence (unwittingly) used by LECK. In conclusion, probabilities should never replace differential diagnostic procedures, the accepted medical method of care. Well-known from literature, supported by the present case, is that (child abuse pediatrics) physicians, child protection workers, and judges were unlikely to understand Bayesian statistics. Its use without statistics consultation should therefore not have occurred. Thus, Bayesian statistics, and certainly (misused) likelihood ratios, should never be applied in cases of physical child abuse suspicion. Finally, parental innocence follows from clarifying what could have caused the girl’s bruises (inherited hEDS), and rib fractures (birth trauma from fragile bones). MDPI 2023-05-06 /pmc/articles/PMC10217160/ /pubmed/37238391 http://dx.doi.org/10.3390/children10050843 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Case Report
van Gemert, Martin J. C.
Zwinderman, Aeilko H.
van Koppen, Peter J.
Neumann, H. A. Martino
Vlaming, Marianne
Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title_full Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title_fullStr Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title_full_unstemmed Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title_short Child Abuse, Misdiagnosed by an Expertise Center—Part II—Misuse of Bayes’ Theorem
title_sort child abuse, misdiagnosed by an expertise center—part ii—misuse of bayes’ theorem
topic Case Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217160/
https://www.ncbi.nlm.nih.gov/pubmed/37238391
http://dx.doi.org/10.3390/children10050843
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