Critical gaps in the medical knowledge base of eating disorders

Anorexia nervosa: Outpatient treatment and medical management

Anorexia nervosa (AN) is a disabling, costly and potentially deadly illness. Treatment failure and relapse are common after completing treatment, and a substantial proportion of patients develop severe and enduring AN. The time from AN debut to the treatment initiation is normally unreasonably long. Over the past 20 years there has been empirical support for the efficacy of several treatments for AN. Moreover, outpatient treatment with family-based therapy or individual psychotherapy is associated with good outcomes for a substantial proportion of patients. Early intervention improves outcomes and should be a priority for all patients. Outpatient treatment is usually the best format for early intervention, and it has been demonstrated that even patients with severe or extreme AN can be treated as outpatients if they are medically stable. Inpatient care is more disruptive, more costly, and usually has a longer waiting list than does outpatient care. The decision as to whether to proceed with outpatient treatment or to transfer the patient for inpatient therapy may be difficult. The core aim of this opinion review is to provide the knowledge base needed for performing safe outpatient treatment of AN. The scientific essentials for outpatient treatment are described, including how to assess and manage the medical risks of AN and how to decide when transition to inpatient care is indicated. The following aspects are discussed: early intervention, outpatient treatment of AN, including outpatient psychotherapy for severe and extreme AN, how to determine when outpatient treatment is safe, and when transfer to inpatient healthcare is indicated. Emerging treatments, ethical issues and outstanding research questions are also addressed.

Non-alcoholic beriberi, Wernicke encephalopathy and long-term eating disorder: case report and a mini-review

INTRODUCTION

Nowadays, reports of beriberi are rare in developed countries. Wernicke encephalopathy may be present in about 25% of patients with beriberi.

CASE REPORT

We report the case of a woman with history of depression and chronic eating disorder, who complained Wernicke encephalopathy and beriberi. Sural nerve and muscular biopsy were performed, showing severe axonal neuropathy. Thiamine supplementation was started with rapid improvement of the pulmonary and cardiac affections; improvement of peripheral neuropathy was incomplete.

CONCLUSIONS

Thiamine deficiency can be misdiagnosed. Beriberi is an important cause of acute flaccid paralysis; hence, clinicians should consider this diagnosis and prompt start thiamine treatment to avoid permanent neurological sequelae.

Identification and Management of Eating Disorders in Children and Adolescents

Eating disorders are serious, potentially life-threatening illnesses afflicting individuals through the life span, with a particular impact on both the physical and psychological development of children and adolescents. Because care for children and adolescents with eating disorders can be complex and resources for the treatment of eating disorders are often limited, pediatricians may be called on to not only provide medical supervision for their patients with diagnosed eating disorders but also coordinate care and advocate for appropriate services. This clinical report includes a review of common eating disorders diagnosed in children and adolescents, outlines the medical evaluation of patients suspected of having an eating disorder, presents an overview of treatment strategies, and highlights opportunities for advocacy.

Sounds unrealistic: an adolescent girl with anorexia nervosa consumes 19 L of fluid in a few hours: what happens to the physiology?

BACKGROUND

Adolescents with eating disorders (EDs) may present not only with abnormal eating behaviors but also with abnormal drinking behaviors varying widely. These behaviors include water loading to cheat on weight measurements, to feel full and suppress appetite and/or to induce vomiting; as well as restricting fluid intake in addition to food.

METHOD

We present a 16-year-old female adolescent with anorexia nervosa restrictive type and major depressive disorder who was hospitalized due to acute food refusal and developed generalized seizures due to dilutional hyponatremia in consequence of consuming excessive amount of water. Psychiatric diagnoses were made according to 'The Diagnostic and Statistical Manual of Mental Disorders' (5th ed.; DSM-5) criteria.

RESULTS

After starting nutritional rehabilitation with a low calorie meal plan to avoid refeeding syndrome, a weight gain of 2 kg was noted in the second day of hospitalization. At the bedside visit, she was observed in a disoriented manner and consecutively in seconds, lost consciousness with a generalized tonic-clonic seizure lasting 2 min. Her serum sodium level was measured as 116 mEq/L, which was normal at the time of admission. It was later learned that she secretly ingested 19 L of water in a short amount of time. She regained consciousness and no further seizures were observed after intravenous sodium deficit correction and fluid restriction therapy. Her serum sodium level was normalized (137 mEq/L) within 12 h.

CONCLUSION

A thorough clinical assessment of hydration and drinking behaviors as well as eating behaviors is essential for patients with EDs to avoid serious medical complications with high mortality and morbidity during follow-up. It is interesting that this amount of fluid consumption in such a short period of time did not present to the clinic with vomiting, gastric dilatation or bowel irrigation symptoms in a case with acute food refusal and restriction for a year, instead absorbed very quickly causing acute and severe symptomatic hyponatremia with generalized seizures.

Artificial intelligence, osteoporosis and fragility fractures

PURPOSE OF REVIEW

Artificial intelligence tools have found new applications in medical diagnosis. These tools have the potential to capture underlying trends and patterns, otherwise impossible with previous modeling capabilities. Machine learning and deep learning models have found a role in osteoporosis, both to model the risk of fragility fracture, and to help with the identification and segmentation of images.

RECENT FINDINGS

Here we survey the latest research in the artificial intelligence application to the prediction of osteoporosis that has been published between January 2017 and March 2019. Around half of the articles that are covered here predict (by classification or regression) an indicator of osteoporosis, such as bone mass or fragility fractures; the other half of studies use tools for automatic segmentation of the images of patients with or at risk of osteoporosis. The data for these studies include diverse signal sources: acoustics, MRI, CT, and of course, X-rays.

SUMMARY

New methods for automatic image segmentation, and prediction of fracture risk show promising clinical value. Though these recent developments have had a successful initial application to osteoporosis research, their development is still under improvement, such as accounting for positive/negative class bias. We urge care when reporting accuracy metrics, and when comparing such metrics between different studies.