Simulation of the Impact of Programs for Prevention and Screening of Pediatric Abusive Head Trauma.

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Journal of Neurotrauma Simulation of the impact of programs for prevention and screening of Pediatric Abusive Head Trauma (doi: 10.1089/neu.2015.4014) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof.

1 Simulation of the impact of programs for prevention and screening of Pediatric Abusive Head Trauma Marion Bailhachea, b, MD, MSc, Antoine Bénardb, c, d, MD, PhD, Louis-Rachid Salmib, c, MD, PhD Author Affiliations: a CHU de Bordeaux, Pole de pediatrie, F-33000 Bordeaux, France, b Univ. Bordeaux, ISPED, Centre INSERM U897-Epidemiologie-Biostatistique, F-33000 Bordeaux, France c CHU de Bordeaux, Pole de sante publique, Service d’information medicale, F-33000 Bordeaux, France d Unité de Soutien Méthodologique à la Recherche Clinique et Épidémiologique, CIC 14-01 module EC, Bordeaux, France Running title: Programs targeted at Abusive Head Trauma Corresponding Author Marion Bailhache, MD, MSc, Hôpital des Enfants – Urgences Pédiatriques, Place Amélie Raba Léon 33 076 Bordeaux Cedex, France, [email protected], tel + 33 5 56 79 59 12, fax + 33 5 56 79 48 66 Contact information for other authors: Antoine Bénard, MD, PhD, Unité de Soutien Méthodologique à la Recherche Clinique et Epidémiologique du CHU de Bordeaux, Université de Bordeaux, 146 Léo Saignat CS361292 – case 75, 33 076 Bordeaux cedex, [email protected], tel + 33 5 57 57 11 81 Louis-Rachid Salmi, MD, PhD, Université de Bordeaux, ISPED, 146 Rue Léo Saignat, 33 076 Bordeaux Cedex, France, [email protected], tel + 33 5 57 57 14 37 Word count: 3092

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2 ABSTRACT Primary prevention programs of Pediatric Abusive Head Trauma exist and early screening are proposed, but negative effects of mislabeling parents as abusers, an important issue, are not well documented. The aim of our study was to simulate the possible impact of programs for the primary prevention and screening of Pediatric Abusive Head Trauma. We developed Markov models that simulate the life histories of Pediatric Abusive Head Trauma without intervention, with primary prevention only, with screening program and with both programs, in a hypothetical cohort of 800 000 newborns in a high-income country. Screening program would be addressed to all families until children have two years old, during repeated consultations. Potential side effects for parents being mislabeled as abusers were supposed to increase probability of Pediatric Abusive Head Trauma and decrease participation in screening. Time horizon was two years with cycles of 15 days. Outcomes were number of deaths and abused children avoided. Uncertainty was specified with probability distributions. After two years, the median number of death avoided through primary prevention would vary from 6 (95% confidence interval [CI] 2–11) to 28 (95% CI 6–51) for 100 000 newborns. Screening could prevent up to 6 (95% CI 0–29) or cause up to 66 (95% CI 0–361) deaths for 100 000 children born alive. The impact of both programs was uncertain. Our model confirmed the potential benefits of primary prevention and documented the uncertainty associated with screening of Pediatric Abusive Head Trauma. Key words Child abuse; Pediatric Abusive Head Trauma; craniocerebral trauma; primary prevention; mass screening

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3

Introduction Pediatric Abusive Head Trauma (PAHT) results in significant morbidity in infants and toddlers and is one of the main cause of child abuse mortality.1–3 In the U.S. National Child Death Review Case Reporting System, PAHT accounted for 60% of physical-abuse deaths, and 30% of all child-abuse deaths from 2005 to 2009.4 Several programs to prevent abusive PAHT, in particular the shaken baby syndrome, have been developed.5–8 Danger of violent infant shaking was explained to parents of newborns before the infant’s discharge from the hospital and alternative responses to persistent infant crying were suggested.5,9 Dias et al5 and Altman et al9 showed a decrease of PAHT incidence during the months following program introduction. A favorable cost-utility ratio of a prevention program based on Dias et al’s program was estimated from a five-year cohort of infants with PAHT admitted to a hospital in Auckland, New Zealand.10 However sensitivity analyses did not test uncertainties on incidence, mortality and program coverage. The estimation of incidence is challenging because of inconsistencies in the definition of PAHT, and variation in how definitions are applied.11 The American Academy of Pediatrics proposed in 2012 definition of Abusive Head Trauma.11 Several studies suggest that children could be victims of repeated episodes of PAHT before been detected,12 or that physicians missed cases of PAHT.13 For these reasons, several authors advocated systematic screening of PAHT, for example among infants presenting to the Emergency Department.14,15 The understanding of how PAHT occurs has also improved. The role of infant crying has been recognized as the most common stimulus for PAHT.16,17 Crying, especially when parents do not understand its meaning, can provoke negative, destructive, survival-endangering responses resulting in PAHT. PAHT could result from a

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4 failure of normal iterative interactions between infants and their parents.17 Theoretically, this abnormal interaction could be the target of screening, before any head trauma. The impact of possible prevention or screening programs is difficult to estimate, in particular because of the lack of knowledge about the beginning of PAHT, difficulties to measure all cases of PAHT. Large and expensive cohorts would be necessary in view of PAHT incidence. Negative effects of mislabeling parents as abusers are yet not well documented, but several authors have raised the issue of the potential impact of such stigmatization.18 Consequently, a clinical study considering early screening of PAHT before children have serious consequences or when children have only abnormal interaction with their parents is not ethically acceptable. To overcome this difficulty, computer modeling has many advantages. Impact of strategies as a systematic early screening could be studied, while in reality such strategies could cause ethical problems. Cost of computer stimulation is very low and no expensive and time consuming studies are necessary. Alternative strategies can be easily compared and; even if better knowledge about PAHT remains to be acquired, the contributions of each parameter or research hypothesis to uncertainty about potential impact of programs can be estimated.19 We developed a Markov modeling of the evolution of PAHT, for four alternative strategies: no intervention, primary prevention program, screening program, and both primary prevention and screening programs. Our objective was to evaluate the possible impact, on a cohort of newborns, of primary prevention and screening programs targeted at PAHT.

Methods Decision Model

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5 Our Markov model compared the evolution of PAHT with: no intervention, primary prevention alone, screening alone, and both primary prevention and screening. The simulated population was a cohort of 800 000 newborns, corresponding approximately to the annual number of newborns in France.20 The model of natural evolution had five possible and mutually exclusive states (Figure 1): 1. Normal interaction: Children are healthy with normal interaction between them and their parents. 2. Subclinical: Children have no clinical symptoms, but parents have negative interactions with their children. 3. Reversible clinical: Children have reversible clinical temporary consequences of PAHT, consecutive to a first shaking or another mechanism of inflicted trauma, such as cerebral contusion, which can be responsible of faintness with spontaneous recovery. 4. Irreversible clinical: Children have irreversible consequences of PAHT without spontaneous recovery, consecutive repetitive shaking or when first shaking was extremely violent, such as motor deficit with paralysis and spasticity, epilepsy. 5. Death: At each state child could die from PAHT or other causes. Because the existence of a subclinical state is not formally defined, we considered two evolutions of PAHT: a model with a subclinical state and a model without subclinical state. Each Markov cycle was fifteen-day long.

Interventions A primary prevention program aims to prevent PAHT before it ever occurs, that is before the possible subclinical state, when parent and child have negative interactions,

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6 or if no subclinical state exists, before a reversible clinical state. The modeled primary prevention program would be offered to all parents with their consent. The proposed intervention would be based on current PAHT education interventions, such as the Dias or Altman program or in the first stage of the PURPLE program.5,8,9 These programs were delivered during the postpartum hospital stay, immediately following delivery. For example, the PURPLE program used an educational package that includes a 10-min DVD and an eleven-page booklet to explain to the parents that infant crying is normal, what are the appropriate responses to inconsolable crying, and the danger of shaking a baby. No side effects were considered.21 Screening aims at identifying PAHT when children have not symptoms or signs and are apparently in good health, which corresponds to the potential subclinical state and the reversible clinical state when the child has spontaneous recovered a normal state. A screening program would include all actions to identify early children who are victims of PAHT, and improve their health by avoiding severe consequences. It would include the initial screening test, confirmation diagnostic strategy, and an intervention. Several authors explored screening tests such as serum biomarkers22 but no formal screening program currently exists. A hypothetical screening program was defined to be directed to all parents and children until the latter are two-years-old and had no irreversible consequences; it would be provided by family physicians or pediatricians during repeated follow-up consultations, monthly during the first six months of the child, and at nine, 12, 16, 20 and 24 months. If detection were positive, education intervention would be proposed to stop PAHT evolution. Because the potential harm associated with mislabeling parents as child abusers has been emphasized,18 we modeled side effects for parents wrongly detected as abusers. Indeed some parents could be identified as parents who have negative interactions with their children (subclinical state, reversible clinical state) while they have in fact normal interaction with

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7 their children (normal interaction state). These parents would be false positive. The effects of this stigmatization might lead to an increase of parent’s stress and of their anxiety.18 We also assumed that these parents could experience losing confidence in themselves, poor selfesteem, depression or paranoia, and social isolation. As these effects have been identified as risk factors of child abuse,23,24 this stigmatization may place children at greater risk to become abused than before the screening. Thus we assumed that potential side effects of screening could be to increase the probability of PAHT and to decrease future participation in the screening program.

Model parameters and assumptions Whenever possible, transition probabilities were extracted from the literature (Table 1). Transition probability between normal and clinical states of PAHT varied over time. It was more important when the child had less than one year of age.25,26 When considering a subclinical state, we chose two extreme scenarios, most in favor and most in disfavor of screening. The scenario most in favor of screening assumes that all parent/child pairs are in subclinical state after the first Markov cycle, and remain in this state until children have clinical symptoms. In this scenario, no parents could be false positive. Indeed after screening intervention, some parents are in normal interaction state but in the following cycle all these parents return to subclinical state. The impact of simultaneous primary prevention and screening programs could not be estimated in this case. The scenario is most in disfavor of screening when transition probability to remain in subclinical state is nil. Parents and children are in subclinical state during only the fifteen days before clinical manifestations of PAHT. For the two above-mentioned extreme situations and the model without subclinical state, we have modeled three scenarios based on maximum, minimum and median estimations of the incidence of PAHT in high-income countries, varying according to definitions used and

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8 populations.3,25–27 Shanahan et al and Parrish et al used the definition recommended by the Centers for Disease Control and Prevention in 2012.11,25,27 Fujiwara et al used the International Classification of Diseases-10 codes.26 Because Shanahan et al estimated incidence only for children younger than one-year old, we used the incidence estimation of Keenan et al for children aged one- and two-years old.3,27 Keenan et al focused only on serious or fatal PAHT3. The case-fatality of PAHT was estimated around 20%,3,28,29 sometimes less (6.7%) as in a study in the U.S.A.30 Thus we had this parameter vary from 0 to 0.3. When neither data nor estimations were available, we assumed variation between extreme possible values. These values were zero, and the sum of transition probabilities from one state was one. We assumed a probability of participation for primary prevention program between 0.6 to 15,9,31 and effectiveness between 0.4 to 0.8.5,9

Outcomes Outcomes were measured after two years. Numbers of children in each state for 100 000 children born, the number of avoided or added deaths and the difference of number of children in clinical states were reported.

Data analysis We used Microsoft Office 2013’s Excel (Microsoft, Redmond, WA) to run the model. Children moved from state to state during 49 cycles. For each scenario considering or not a subclinical state, we conducted probabilistic sensitivity analyses with three scenarios for transition probability between normal state and clinical states of PAHT. Beta distributions were used for transition probability between normal state and clinical states of PAHT and, when lack of knowledge did not allow estimating distributions, uniform distributions between extreme values. For the beta distributions, alpha and beta estimations were obtained by the method of moments. Random numbers bounded by these distributions assumptions were

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9 generated to calculate outputs for each cycle. We used 1000 simulations, where the analysis modeled uncertainty for all parameters simultaneously.

Results Potential impact of primary prevention Primary prevention programs would reduce mortality and morbidity (Table 2). Depending on the level of incidence, the application of primary prevention alone would avoid 6 (95% confidence interval [CI] 2–11) to 28 (95%CI 6–51) deaths per 100 000 children. The number of irreversible consequences of PAHT avoided would vary from 0 (95%CI 0–5) to 1 (95%CI 0–26) for 100 000 children. The number of children who would remain in a normal or subclinical state as a consequence of prevention would vary from 7 (95% CI 4–11) to 32 (95% CI 18–54) per 100 000 children.

Potential impact of screening The impact of screening was uncertain (Table 2). If being wrongly identified as abuser would decrease participation in screening programs and increase the probability to become abusers, screening could cause more cases of PAHT. Screening could prevent, after two years of evolution, up to 6 (95%CI 0–29) deaths for 100 000 children, or cause up to 66 (95%CI 0– 361) deaths for 100 000 children. The number of children with irreversible consequences could be reduced down to 0 (95%CI 0–11) per 100 000 children or increased up to 5 (95%CI 0–152) per 100 000 children (Table 2).

Potential impact of associating primary prevention and screening Simultaneous application of primary prevention and screening would not reduce mortality and morbidity with certainty (Table 2). In scenarios without any subclinical state, application of

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10 both primary prevention and screening could cause from 19 (95%CI -5–77) to 91 (95%CI 21– 355) deaths for 100 000 children. When considering a subclinical state lasting only 15 days, from 16 (95%CI -6–76) to 85 (95%CI -21–375) deaths for 100 000 children could be caused. With a subclinical state lasting more than 15 days, screening would be more effective, because more parents would be potentially detected early, and fewer would be wrongly identified as abusers. Primary prevention would decrease the incidence of PAHT and increase the number of parents wrongly identified as abusers. The latter would less participate to subsequent rounds of screening and would be more likely to become abusers.

Discussion We examined the potential impact of primary prevention and screening programs on PAHT in a hypothetical cohort from a high-income country, taking into account major uncertainties. We showed the potential benefit of primary prevention program and the uncertainties concerning screening. We hypothesized that false identification of parents as abusers could either have no impact on evolution of PAHT or increase the probability of becoming abusers. Under the latter hypothesis, screening program could potentially increase the mortality and morbidity. Very few studies considered effects of being wrongly identified as abusers. When parents were victims of separation from their children because of false allegations of child abuse, they described the loss of the sense of being competent parents and modification of their attachment to their child.32 These feelings would lead some parents to relations with disorganized attachment with child. Although the link between child maltreatment and disorganized attachment is unclear, maltreatment could be the cause of disorganized attachment and vice-versa.33,34 Researches on the potential effects of being wrongly identified as abusers are very important to consider screening programs.

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11 We hypothesized in two models that a true subclinical state preceded the clinical state in which parents are acting out and become physically violent with their child. During this potential subclinical state, parents would go through stages of emotions like accumulation of frustration or anger, especially because of child persistent crying.7,17 Because of their incapacity to control and overcome these emotions, some parents could become violent. Parents could learn how to recognize and cope with these emotions though stress different techniques. For instance, the Perinatal Shaken Baby Syndrome Prevention Program uses coping strategies with an “anger thermometer”. Parents are reassured about the experience of anger that crying can cause and they identify strategies for dealing with anger.7 Screening of child-parent interaction difficulties should not result into a negative perception, but as positive parenting support measures, especially because many parents with these difficulties could never become authors of PAHT. We often chose extreme limits for distributions of transition probabilities between stages leading to PAHT used in probabilistic sensitivity analyses. Indeed few studies documented the mid- and long-term outcomes of PAHT.1,2,35,36 In these studies, the definition and qualification of injury varied, as well as initial severity, age at time of injury, follow-up periods, and outcome measures; attrition rates were often high. The use of a consensual definition, better follow-up of all victims, and measures of any possible consequences of PAHT are necessary. We used available information about the incidence, based on the International Classification of Diseases. Several studies have documented the lack of accuracy of external cause coding in hospital records, in particular its low sensitivity.37,38 A recent study estimated however the sensitivity and specificity respectively at 92% and 96%.39 Consequently, the incidence of PAHT might be underestimated in our models, so that the benefits of primary prevention program are underestimated. Similarly we did not take into account the incidence variation

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12 during the first year of life by lack of precise estimations but incidence is higher the younger the children and the benefits of the screening program would be underestimated.16 In our model, we have considered that without intervention, child health could deteriorate gradually but not improve. However, after the occurrence of PAHT, some improvement of child health over time could occur.40 Consequences of the same PAHT would be also more important for younger child because of higher physiologic vulnerability during early infancy.41 The effectiveness of primary prevention was considered constant over time but might decrease over time. The impact of this decrease is likely to be small, because of decrease of the incidence over time. We considered that effectiveness of screening was constant over time. However the effectiveness of screening could vary according to the state of detection and the age of children. Similarly, we chose probability of screening participation constant over the time in each group (parents who were never false positive and parents who were already at least once false positive). But screening participation could change over the time. We have considered a primary prevention program directed to all parents of newborns. A primary prevention program could be also only targeted for families with risk factors of PAHT. However, identification of high-risk families, before the occurrence of PAHT could be responsible for stigmatization of these families and negative effect could be foreseen. Moreover, the predictive value of risk factors should be very strong, and should not imply missing opportunities to prevent occurrence of PAHT in other families. Current scientific knowledge is insufficient to define an adequate high-risk population. Actually, proposed primary prevention program are systematic programs.5,8,9 Similarly, a screening program could be considered in a high-risk population seen in emergency departments; similarly, current knowledge is insufficient to define such population. The

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13 rhythm at which screening tests should be repeated, who would be the program actors, and the type of intervention remain to be defined. We have chosen a decreasing frequency of screening tests because of age specific incidence curves of PAHT.16 Actors who would screen should accept this procedure. Finally, no early intervention is welldefined, but coping strategies to better react to infant crying could be adapted for parents who have negative interaction with their child.7 Following current recommendations that cost-effectiveness analysis should only be carried for programs with a demonstrated effectiveness we have not considered the economic impact of the modeled programs.42 Nevertheless, the cost-effectiveness ratio is important and should be estimated before implementation of prevention or screening programs. Furthermore, the full cost of PAHT to society is not well documented today, precluding any full cost-effectiveness analysis. Medical costs has been studied,43 but indirect costs of PAHT has never, to our knowledge, been considered. PAHT has an impact on educational pathways of affected children and, later, on their social integration and working capacity, in particular when they have severe physical or psychic disability.43 These long-term consequences and their cost have not been sufficiently studied.

Conclusions Our models confirm the relevance of primary prevention of PAHT. Before considering screening, future research should focus on describe the effects of wrongly identifying parents as abusers, develop and evaluate tests to identify earlier children with PAHT.

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14 Acknowledgments We have no acknowledgments Author Disclosure Statement Marion Bailhache has no conflicts of interest relevant to this article to disclose. Antoine Bénard has no conflicts of interest relevant to this article to disclose. Louis-Rachid Salmi has no conflicts of interest relevant to this article to disclose. No competing financial interests exists.

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15 References 1. Barlow, K. M., Thomson, E., Johnson, D. and Minns, R. A. (2005). Late neurologic and cognitive sequelae of inflicted traumatic brain injury in infancy. Pediatrics 116, e174– 185. 2. Makaroff, K. L. and Putnam, F. W. (2003). Outcomes of infants and children with inflicted traumatic brain injury. Dev. Med. Child Neurol. 45, 497–502. 3. Keenan, H. T., Runyan, D. K., Marshall, S. W., Nocera, M. A., Merten, D. F. and Sinal, S. H. (2003). A population-based study of inflicted traumatic brain injury in young children. JAMA 290, 621–626. 4. Palusci, V. J. and Covington, T. M. (2014). Child maltreatment deaths in the U.S. National Child Death Review Case Reporting System. Child Abuse Negl. 38, 25–36. 5. Dias, M. S., Smith, K., DeGuehery, K., Mazur, P., Li, V. and Shaffer, M. L. (2005). Preventing abusive head trauma among infants and young children: a hospital-based, parent education program. Pediatrics 115, e470–477. 6. Keenan, H. T. and Leventhal, J. M. (2010). A case-control study to evaluate Utah’s shaken baby prevention program. Acad. Pediatr. 10, 389–394. 7. Goulet, C., Frappier, J.Y., Fortin, S., Déziel, L., Lampron, A. and Boulanger, M. (2009). Development and evaluation of a shaken baby syndrome prevention program. J. Obstet. Gynecol. Neonatal Nurs. 38, 7–21. 8. Barr, R. G., Barr, M., Fujiwara, T., Conway, J., Catherine, N. and Brant, R. (2009). Do educational materials change knowledge and behaviour about crying and shaken baby syndrome? A randomized controlled trial. Can. Med. Assoc. J. 180, 727–733. 9. Altman, R. L., Canter, J., Patrick, P. A., Daly, N., Butt, N.K. and Brand, D. N. (2011). Parent education by maternity nurses and prevention of abusive head trauma. Pediatrics 128, e1164–1172.

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16 10. Friedman, J., Reed, P., Sharplin, P. and Kelly, P. (2012). Primary prevention of pediatric abusive head trauma: a cost audit and cost-utility analysis. Child Abuse Negl. 36, 760– 770. 11. Parks, S. E., Annest, J. L., Hill, Holly A. and Karch, D. L. (2012). Pediatric Abusive Head trauma recommanded definitions for public health surveillance and research. Atlanta (GA): Centers of Disease Control and Prevention; 2012. 12. Adamsbaum, C., Grabar, S., Mejean, N. and Rey-Salmon, C. (2010). Abusive head trauma: judicial admissions highlight violent and repetitive shaking. Pediatrics 126, 546– 555. 13. Jenny, C., Hymel, K. P., Ritzen, A., Reinert, S. E. and Hay, T. C. (1999). Analysis of missed cases of abusive head trauma. JAMA. 281, 621–626. 14. Campbell, K. A., Berger, R. P., Ettaro, L. and Roberts, M. S. (2007). Cost-effectiveness of head computed tomography in infants with possible inflicted traumatic brain injury. Pediatrics 120, 295–304. 15. Rangel, E. L., Cool, B.S., Bennett, B. L., Shebesta, K., Ying, J. and Falcone, R.A. (2009). Eliminating disparity in evaluation for abuse in infants with head injury: use of a screening guideline. J. Pediatr. Surg. 44, 1229–1234; discussion 1234–1235. 16. Barr, R. G., Trent, R. B. and Cross, J. (2006). Age-related incidence curve of hospitalized Shaken Baby Syndrome cases: convergent evidence for crying as a trigger to shaking. Child Abuse Negl. 30, 7–16. 17. Barr, R. G. (2012). Preventing abusive head trauma resulting from a failure of normal interaction between infants and their caregivers. Proc. Natl. Acad. Sci. U. S. A. 109 Suppl 2, 17294–17301.

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17 18. MacMillan, H. L., MacMillan, J. H. and Offord, D. R. (1993). Periodic health examination, 1993 update: 1. Primary prevention of child maltreatment. The Canadian Task Force on the Periodic Health Examination. Can. Med. Assoc. J. 148, 151–163. 19. Russell, L. B. (2011). Exploring the Unknown and the Unknowable with Simulation Models. Med. Decis. Making 31, 521–523. 20. Bellamy, V. and Beaumel, C. (2013). Bilan Démographique 2012. INSEE première n°1429. 21. Selph, S. S., Bougatsos, C., Blazina, I. and Nelson, H. D. (2013). Behavioral Interventions and Counseling to Prevent Child Abuse and Neglect: A Systematic Review to Update the U.S. Preventive Services Task Force Recommendation. Ann. Intern. Med. 158, 179–190. 22. Berger, R. P., Fromkin, J., Rubin, P., Snyder, J., Richichi, R. and Kochanek, P. (2015). Serum D-dimer concentrations are increased after pediatric traumatic brain injury. J. Pediatr. 166, 383–388. 23. Dubowitz, H., Kim, J., Black, M.M., Weisbart, C., Semiatin, J. and Magder, L. S. (2011). Identifying children at high risk for a child maltreatment report. Child Abuse Negl. 35, 96–104. 24. Kotch, J. B., Browne, D.S., RIngwalt, C. L., Stewart, P.W., Ruina, E., Holt, K. Lowman, B. and Jung, J.W. (1995). Risk of child abuse or neglect in a cohort of low-income children. Child Abuse Negl. 19, 1115–1130. 25. Parrish, J., Baldwin-Johnson, C., Volz, M. and Goldsmith, Y. (2013). Abusive head trauma among children in Alaska: a population-based assessment. Int. J. Circumpolar Health 72. doi: 10.3402/ijch.v72i0.21216, eCollection 2013. 26. Fujiwara, T., Barr, R. G., Brant, R. F., Rajabali, F. and Pike, I. (2012). Using International Classification of Diseases, 10th edition, codes to estimate abusive head trauma in children. Am. J. Prev. Med. 43, 215–220.

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18 27. Shanahan, M. E., Zolotor, A. J., Parrish, J. W., Barr, R. G. and Runyan, D. K. (2013). National, regional, and state abusive head trauma: application of the CDC algorithm. Pediatrics 132, e1546–1553. 28. Kesler, H., Dias, M.S., Shaffer, M., Rottmund, C., Cappos, K. and Thomas, N.J. (2008).. Demographics of abusive head trauma in the Commonwealth of Pennsylvania. J. Neurosurg. Pediatr. 1, 351–356. 29. Shein, S. L., Bell, M.J., Kochanek, P.M., Tyler-Kabara, E.C., Wisniewski, S. R., Feldman, K., Makoroff, K., Scribano, P.V. and Berger, R.P. (2012). Risk factors for mortality in children with abusive head trauma. J. Pediatr. 161, 716–722.e1. 30. Niederkrotenthaler, T., Xu, L., Parks, S. E. and Sugerman, D. E. (2013). Descriptive factors of abusive head trauma in young children--United States, 2000-2009. Child Abuse Negl. 37, 446–455. 31. Stewart, T. C., Polgar, D., Gilliland, J., Tanner, D.A., Girotti, M.J., Parry, N. and Fraser, D.D. (2011). Shaken baby syndrome and a triple-dose strategy for its prevention. J. Trauma 71, 1801–1807. 32. Zeman, L. (2005). Etiology of Loss Among Parents Falsely Accused of Abuse or Neglect. Journal of Loss and Trauma 10, 19–31. 33. Rodriguez, C.M.and Tucker, M.C. (2011). Behind the Cycle of Violence, Beyond Abuse History: A Brief Report on the Association of Parental Attachment to Physical Child Abuse Potential. Violence and Victims 26, 246-256. 34. Wilkins, D. (2012). Disorganised attachment indicates child maltreatment: how is this link useful for child protection social workers? Journal of Social Work Practice 26, 15-30. 35. Stipanicic, A., Nolin, P., Fortin, G. and Gobeil, M.F. (2008). Comparative study of the cognitive sequelae of school-aged victims of Shaken Baby Syndrome. Child Abuse Negl. 32, 415–428.

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19 36. Talvik, I., Männamaa, M., Jüri, P, Põder, H., Hämarik, M., Kool, P., Talvik, T. (2007). Outcome of infants with inflicted traumatic brain injury (shaken baby syndrome) in Estonia. Acta Paediatr. 96, 1164–1168. 37. McKenzie, K., Enraght-Moony, E. L., Walker, S. M., McClure, R. J. and Harrison, J. E. (2009). Accuracy of external cause-of-injury coding in hospital records. Inj. Prev. 15, 60– 64. 38. Hooft, A., Ronda, J., Schaeffer, P., Asnes, A. G. and Leventhal, J. M. (2012). Identification of Physical Abuse Cases in Hospitalized Children: Accuracy of International Classification of Diseases Codes. J. Pediatr. 162, 80-85. 39. Berger, R. P., Parks, S., Fromkin, J., Rubin, P. and Pecora, P. J. (2015). Assessing the accuracy of the International Classification of Diseases codes to identify abusive head trauma: a feasibility study. Inj. Prev. 21, e133-137. 40. Haviland, J. and Russell, R. I. (1997). Outcome after severe non-accidental head injury. Arch. Dis. Child. 77, 504–507. 41. Anderson, V., Spencer-Smith, M. and Wood, A. (2011). Do children really recover better? Neurobehavioural plasticity after early brain insult. Brain J. Neurol. 134, 2197– 2221. 42. Drummond, M. F., Sculpher, M. J., Torrance, G. W., O'Brien, O. J. and Stoddart, G. L. (2005). Methods for the economic evaluation of health care programmes. Oxford: Oxford University Press. Third Edition. 43. Peterson, C., Xu, L., Florence, C., Parks, S. E., Miller, T. R., Barr, R. G., Barr, M. and Steinbeigle, R. (2014). The medical cost of abusive head trauma in the United States. Pediatrics 134, 91–99.

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20 TABLE 1. PARAMETERS FOR ESTIMATING THE IMPACT OF PRIMARY PREVENTION AND SCREENING OF PEDIATRIC ABUSIVE HEAD TRAUMA

TABLE 2. ESTIMATIONS OF THE IMPACT OF PROGRAMS ON MORTALITY AND MORBIDITY BY PEDIATRIC ABUSIVE HEAD TRAUMA (per 100 000 children born alive, 95% confidence interval)

FIG. 1. Markov model of the impact of prevention and screening programs of Pediatric Abusive Head Trauma. Normal interaction state: child healthy with normal interaction with his/her parent(s); subclinical state: asymptomatic child with abnormal interaction; reversible/irreversible clinical state: child with reversible/irreversible consequences. Arrows: transitions between states; thick arrows: transitions increased by programs. P: targeted by prevention; S: targeted by screening; NSS: no when subclinical state is considered.

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21

FIG. 1. Markov model of the impact of prevention and screening programs of Pediatric Abusive Head Trauma. Normal interaction state: child healthy with normal interaction with his/her parent(s); subclinical state: asymptomatic child with abnormal interaction; reversible/irreversible clinical state: child with reversible/irreversible consequences. Arrows: transitions between states; thick arrows: transitions increased by programs. P: targeted by prevention; S: targeted by screening; NSS: no when subclinical state is considered.

Journal of Neurotrauma Simulation of the impact of programs for prevention and screening of Pediatric Abusive Head Trauma (doi: 10.1089/neu.2015.4014) been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ f

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22 TABLE 1. PARAMETERS FOR ESTIMATING THE IMPACT OF PRIMARY PREVENTION AND SCREENING OF PEDIATRIC ABUSIVE HEAD TRAUMA Parameters Inc= transition probability between normal state and clinical states of PAHT

Plausible values

Sources and references

Three scenario with β distribution of annual incidence: < 1-years old (α=180; β=1383041); > 1-years old (α=34.6; β=1440530)

Literature25

< 1-years old (α=1071 ; β=3205592.6); > 1-years old (α=8.8;

Literature3, 26

β=227434.9)

Literature24

< 1-years old (α=37;β=66085); > 1-years old (α=8; β=64573) Inc=1-EXP(LN(1-annual incidence)*(1/24)) p1: transition between normal and subclinical state

p2: transition between subclinical and reversible clinical state when subclinical

p1=(1-pmortaBL) in the scenario most in favor of screening

Assumptions according to scenario in favor or

p1=Inc in the scenario most in disfavor of screening

disfavor of screening

p2=x1*X with x1 uniform distribution from 0 to 1

x1 randomly selected between extreme possible values

state is considered, otherwise transition between normal and reversible state p4: transition between subclinical and irreversible clinical state when subclinical

p4=X-p2

Computed from other parameters

pmorta1AHT=x2*(p2+p4) with x2 uniform distribution from 0 to 0.428:

Literature3, 27-29

state is considered; otherwise transition between normal and irreversible state pmorta1AHT: mortality rate of PAHT in subclinical state

pmorta1AHT/(pmorta1AHT + p2 + p4) = 0 to 0.3 X=p2+p4

X=Inc/(1+x2) when subclinical state has not been considered and in the

According to scenario

scenario most in favor of screening X=(1-pmortaBL)/(1+x2) in the scenario most in disfavor of screening pmorta2AHT: mortality rate of PAHT in reversible state

Uniform distribution from 0 to 0.3

Literature3, 27-29

pmorta3AHT: mortality rate of PAHT in irreversible state

Uniform distribution from 0 to 0.3

Literature3, 27-29

p3: transition between reversible clinical state and irreversible clinical state

Uniform distribution from 0 to (1-pmortaBL-pmorta2AHT)

Randomly selected between extreme possible values


Page 23 of 29

23 adhP1: adherence to primary prevention

Uniform distribution from 0.6 to 1

Literature5 ,9, 30

eP1: effectiveness of primary prevention

Uniform distribution from 0.4 to 0.8

Literature5, 9

spec: specificity of screening strategy


Assumption

sens1: sensitivity of screening strategy for subclinical state


Assumption

sens2: sensitivity of screening strategy for reversible clinical state

Uniform distribution from sens1 to 1

Assumption

ad: adherence to screening when caregivers were never false positive and when

Uniform distribution from 0 to 1


Uniform distribution from 0 to ad

Assumption

eD: effectiveness of screening



eSE: Side effects of being false positive during screening on probability of

Uniform distribution from 1 to (10 or maximum possible as sum of

Assumption

becoming abuser, likened to relative risk

probabilities from normal state is 1)

adP0: adherence to screening when caregivers were never false positive and when



Uniform distribution from 0 to adP0

Assumption

Uniform distribution from adP0 to 1

Assumption

Uniform distribution from 0 to adP1

Assumption

primary prevention is not proposed adFplus: adherence to screening when caregivers were at least once false positive and when primary prevention is not proposed

they have not adhered to primary prevention adP0Fplus: adherence to screening when caregivers were at least once false positive and when they have not adhered to primary prevention adP1: adherence to screening when caregivers were never false positive and when they have adhered to primary prevention adP1Fplus: adherence to screening when caregivers were at least once false positive and when they have adhered to primary prevention PAHT, Pediatric Abusive Head Trauma; pmortaBL, probability to die from other causes than PAHT


Page 24 of 29

24

Journal of Neurotrauma Simulation of the impact of programs for prevention and screening of Pediatric Abusive Head Trauma (doi: 10.1089/neu.2015.4014) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Page 25 of 29

25


Page 26 of 29

26 TABLE 2. ESTIMATIONS OF THE IMPACT OF PROGRAMS ON MORTALITY AND MORBIDITY BY PEDIATRIC ABUSIVE HEAD TRAUMA (per 100 000 children born alive, 95% confidence interval)

Scenario without subclinical state

Scenario with a subclinical state lasting only fifteen days

Outcome after two years

Scenario with the longest subclinical state

Medium

Medium

Low incidence

Medium incidence

High incidence

Low incidence

incidence

High incidence

Low incidence

incidence

High incidence

hypothesis

hypothesis

hypothesis

hypothesis

hypothesis

hypothesis

hypothesis

hypothesis

hypothesis

Deaths of any cause

Without intervention

356 (345–538)

377 (355–381)

403 (355–429)

355 (345–358)

376 (350–380)

404 (356–426)

355 (344–357)

375 (356–379)

401(350–424)

Change with prevention

-7 (-11–-2)

-16 (-26–-6)

-28 (-51–-6)

-6 (-11–-2)

-16 (-26–-4)

-28 (-50–-7)

NE

NE

NE

Change with screening

14 (0–80)

35 (0–189)

66 (0–361)

12 (-1–77)

30 (-2–177)

59 (-3–352)

-1 (-7–0)

-3 (-16–0)

-6 (-29–0)

19 (-5–77)

50 (-14–191)

91 (-21–355)

16 (-6–76)

42 (-14–181)

85 (-21–375)

NE

NE

NE

Without intervention

1 (0–12)

1 (0–23)

3 (1–55)

1 (0–12)

1 (0–28)

2 (1–53)

1 (0–12)

1 (0–21)

2 (1–55)


0 (-6–0)

0 (-11–0)

-1 (-26–0)

0 (-5–0)

0 (-13–0)

-1 (-24–0)

NE

NE

NE


1 (0–30)

2 (0–56)

5 (0–152)

1 (0–23)

2 (0–52)

4 (0–95)

0 (-2–0)

0 (-4–0)

0 (-11–0)

1 (0–31)

2 (0–60)

6 (-1–137)

1 (0–28)

2 (-2–55)

6 (-2–115)

NE

NE

NE

Change with prevention and screening Children with irreversible consequences of PAHT

Change with prevention and screening


Page 27 of 29

27 Children in normal state and potential subclinical state Without intervention

99643

99622

99591

99644

99622

99591

99644

99623

99593


7 (4–11)

17 (11–27)

32 (18–54)

7 (4–11)

17 (11–27)

31 (18–54)

NE

NE

NE


-17 (-85–0)

-43 (-208–0)

-79 (-404–-1)

-15 (-81–1)

-40 (-198–3)

-75 (-379–3)

2 (0–7)

4 (0–17)

7 (0–32)

-24 (-84–6)

-59 (-207–15)

-115 (-397–22)

-21 (-81–7)

-53 (-192–15)

-104 (-415–25)

NE

NE

NE

Change with prevention and screening NE: Not estimable


Page 28 of 29

28

Journal of Neurotrauma Simulation of the impact of programs for prevention and screening of Pediatric Abusive Head Trauma (doi: 10.1089/neu.2015.4014) This article has been peer-reviewed and accepted for publication, but has yet to undergo copyediting and proof correction. The final published version may differ from this proof. Page 29 of 29

29

Process evaluation of a statewide abusive head trauma prevention program.

Update on abusive head trauma.

[Abusive head trauma: report of a case].

Long-term outcome of abusive head trauma.

Abusive head trauma: past, present, and future.

The impact of an educational intervention on knowledge about infant crying and abusive head trauma.

Handle With Care: Preventing Abusive Head Trauma.

Evaluation of Period of PURPLE Crying, an abusive head trauma prevention program.

Abusive head trauma: a review of the evidence base.

Crying as a trigger for abusive head trauma: a key to prevention.

Abusive head trauma: two case reports.

International issues in abusive head trauma.

Effectiveness of a Statewide Abusive Head Trauma Prevention Program in North Carolina.

Head circumference: a key sign in dating abusive head trauma.

Imaging of skeletal injuries associated with abusive head trauma.

The Anesthesiologist's Role in Treating Abusive Head Trauma.

Diagnosing abusive head trauma: the challenges faced by clinicians.

The neonatal nurse's role in preventing abusive head trauma.

Spinal injuries in abusive head trauma: patterns and recommendations.

Differences between abusive head trauma and physical abuse in Japan.

Identifying Characteristics in Abusive Head Trauma: A Single-Institution Experience.

Retroclival collections associated with abusive head trauma in children.

Validation of the Pittsburgh Infant Brain Injury Score for Abusive Head Trauma.

Abusive head trauma: differentiation between impact and non-impact cases based on neuroimaging findings and skeletal surveys.