[METATARSUS ADDUCTUS - A COMMON DEFORMITY - WHAT TO DO AND WHEN?]

INTRODUCTION: The most common foot deformity in newborns is the forefoot adduction deformity (FAD), where the hindfoot foot is in a normal position. The diagnosis for this problem is mainly based on a physical examination. The use of imaging methods has been described, but no advantage was shown with their utilization in determining the diagnosis and guiding treatment. Several classification systems have been proposed to characterize the degree of severity. The classifications are based on the degree of deviation and the flexibility of the foot. Early diagnosis and early treatment, if necessary, are extremely important to improve the chances of treatment success. Treatment depends on the severity of the deformity. For mild deformities the treatment is conservative - follow-up or stretching of the foot. The usual treatment for severe deformities is serial casting. Several orthoses have recently been proposed to address the problem and these demonstrated similar results, higher comfort and satisfaction, lower cost and a similar side effect profile. Surgical treatments to correct the deformity are reserved for cases where conservative treatment failed and for older children. This review aims to summarize the current knowledge on the subject, describe the ways to diagnose and classify the deformity, and present the variety of ways to treat the problem including the use of innovative braces. In addition, we will offer a protocol for the treatment of the deformity that is accepted in our institution. The protocol will assist primary care physicians to both diagnose and treat appropriate deformities, and know when a specialist referral is necessary.

Review of Current Concepts in Metatarsus Adductus.

Metatarsus adductus (MA), the most common congenital foot deformity, involves adduction of the forefoot at the tarsometatarsal joint, with normal hindfoot alignment. Early diagnosis is important because treatment is more successful if initiated before age 9 months. Treatment of MA depends on deformity severity, in which mild to moderate deformity can be treated conservatively. Current standard of care for severe or rigid deformity involves referral by primary care physicians to specialists for management by casting and splinting. Recently, several orthoses have demonstrated equal effectiveness to casting and may allow for primary care physicians to treat MA without the need for referral. In this review article, we provide an overview of MA and discuss diagnosis and treatment. We also discuss novel devices and suggest how they may affect the future management of severe and rigid MA. [Pediatr Ann. 2024;53(4):e152-e156.].

Intraoperative Anaphylaxis to Gelatin during Alveolar Bone Grafting for Cleft Palate.

Intraoperative anaphylaxis can be life threatening. Anaphylaxis to gelatin-based topical hemostatic agents is an underrecognized hypersensitivity. To date, only 21 cases of intraoperative anaphylaxis have been reported for gelatin-based hemostatic agents. In this article, we report the case of a 10-year-old male patient who sustained anaphylaxis after the use of Gelfoam during harvest of a bone graft. Rapid diagnosis and treatment of intraoperative anaphylaxis is imperative to prevent adverse outcomes. Referral to an allergist for identification of the allergen and appropriate notation in the medical record are paramount to avoid future anaphylactic events. Surgeons should avoid gelatin-based hemostatic agents, such as Gelfoam, in patients with reported intolerance of gelatin-based foods and medicines.

Repair of an Occipital Meningocele and Scalp Soft-tissue Reconstruction in a Newborn Patient.

The differential diagnosis of large congenital scalp defects includes aplasia cutis and encephalocele, among others. Treatment includes conservative management with dressings or operative management with dermal substitutes, skin grafting, local flaps, and free flaps. This case report discusses the technical considerations and reconstructive strategies for repair of a meningocele in a newborn with a large 5.5-cm scalp defect. The key strategies include preemptive cerebrospinal fluid (CSF) diversion with external ventricular drain to reduce the risk of CSF leak and mitigate wound-healing complications; careful identification and avoidance of key anatomic structures, such as the superior sagittal sinus, as anatomy may be significantly distorted due to the presence of a meningocele and after CSF diversion; and careful, thoughtful design of the local scalp flaps to maximize blood supply and to avoid tension on the final reconstruction.

Wildfires and climate justice: future wildfire events predicted to disproportionally impact socioeconomically vulnerable communities in North Carolina.

Wildfire events are becoming increasingly common across many areas of the United States, including North Carolina (NC). Wildfires can cause immediate damage to properties, and wildfire smoke conditions can harm the overall health of exposed communities. It is critical to identify communities at increased risk of wildfire events, particularly in areas with that have sociodemographic disparities and low socioeconomic status (SES) that may exacerbate incurred impacts of wildfire events. This study set out to: (1) characterize the distribution of wildfire risk across NC; (2) implement integrative cluster analyses to identify regions that contain communities with increased vulnerability to the impacts of wildfire events due to sociodemographic characteristics; (3) provide summary-level statistics of populations with highest wildfire risk, highlighting SES and housing cost factors; and (4) disseminate wildfire risk information via our online web application, ENVIROSCAN. Wildfire hazard potential (WHP) indices were organized at the census tract-level, and distributions were analyzed for spatial autocorrelation via global and local Moran's tests. Sociodemographic characteristics were analyzed via k-means analysis to identify clusters with distinct SES patterns to characterize regions of similar sociodemographic/socioeconomic disparities. These SES groupings were overlayed with housing and wildfire risk profiles to establish patterns of risk across NC. Resulting geospatial analyses identified areas largely in Southeastern NC with high risk of wildfires that were significantly correlated with neighboring regions with high WHP, highlighting adjacent regions of high risk for future wildfire events. Cluster-based analysis of SES factors resulted in three groups of regions categorized through distinct SES profiling; two of these clusters (Clusters 2 and 3) contained indicators of high SES vulnerability. Cluster 2 contained a higher percentage of younger (<5 years), non-white, Hispanic and/or Latino residents; while Cluster 3 had the highest mean WHP and was characterized by a higher percentage of non-white residents, poverty, and less than a high school education. Counties of particular SES and WHP-combined vulnerability include those with majority non-white residents, tribal communities, and below poverty level households largely located in Southeastern NC. WHP values per census tract were dispersed to the public via the ENVIROSCAN application, alongside other environmentally-relevant data.

What a Ratchet! A Gripping Case Report of an Entrapped Finger with an Unyielding Wrench.

Finger entrapment with rings or ring-like objects is an uncommon possible hand emergency. In cases in which noncutting removal is ineffective, ring cutters or dental drills with carbide or diamond burs have been successfully used. However, objects composed of hard metallic alloys, such as lug nuts or wrenches, are often resistant to such equipment. In these instances, larger diameter metal cutting burrs or rasps may be more advantageous. Due to their increased size and cutting power, these tools are better suited to handle the toughness of hard metals. In this case report, we present the effective and efficient removal of a stainless steel wrench from an entrapped digit using a helicoidal rasp. Availability of this instrument within orthopedic departments may prevent the delays often described in the treatment of finger entrapment when traditional cutting equipment fails.

The Effect of COVID-19 on Mood Disorders in Urban and Suburban Detroit.

Introduction: The COVID-19 pandemic has increased the global experience of anxiety and depression owing to social isolation and government-mandated quarantine for transmission reduction. To date, literature surrounding the mental health effects of COVID-19 for the U.S. population is limited. Methods: This is a retrospective study from a large metropolitan Detroit health system. Patient encounters between December 23, 2018 and June 22, 2021, with March 23, 2020 being the start of Michigan state-wide lockdown, were used to define pre- and post-COVID-19 encounters, respectively. The data were divided into Detroit and non-Detroit on the basis of patient ZIP code. All patients aged ≥13 years with a visit with a family medicine provider were included. Outcome variables included Patient Health Questionnaires-2 and -9 and General Anxiety Disorder-7 scores; diagnoses of depression, anxiety, adjustment, and grief disorders; antidepressant prescriptions; and behavioral health referrals. Logistic regression was used to determine the incidence of composite mood disorder, depression, and anxiety. Results: A total of 20,970 individuals were included in this study: 10,613 in the Detroit subgroup and 10,357 in the non-Detroit subgroup. A total of 88.2% of the Detroit population were Black, and 70% were female. Logistic regression shows that the incidence of composite mood disorder decreased with increasing age (OR=0.787, 0.608, 0.422, and 0.392; p<0.001). Male sex is a protective factor (OR=0.646, p<0.001). Federal insurance is the only factor presenting a statistically significant increased risk (OR=1.395, p<0.001). There was no statistical difference between residing in urban and suburban areas in the incidence of composite mood disorder (OR=0.996, p=0.953). Conclusions: This research demonstrates that residing in an urban setting did not increase the risk of developing a mental health disorder during the COVID-19 period.

The application of natural language processing for the extraction of mechanistic information in toxicology.

To study the ways in which compounds can induce adverse effects, toxicologists have been constructing Adverse Outcome Pathways (AOPs). An AOP can be considered as a pragmatic tool to capture and visualize mechanisms underlying different types of toxicity inflicted by any kind of stressor, and describes the interactions between key entities that lead to the adverse outcome on multiple biological levels of organization. The construction or optimization of an AOP is a labor intensive process, which currently depends on the manual search, collection, reviewing and synthesis of available scientific literature. This process could however be largely facilitated using Natural Language Processing (NLP) to extract information contained in scientific literature in a systematic, objective, and rapid manner that would lead to greater accuracy and reproducibility. This would support researchers to invest their expertise in the substantive assessment of the AOPs by replacing the time spent on evidence gathering by a critical review of the data extracted by NLP. As case examples, we selected two frequent adversities observed in the liver: namely, cholestasis and steatosis denoting accumulation of bile and lipid, respectively. We used deep learning language models to recognize entities of interest in text and establish causal relationships between them. We demonstrate how an NLP pipeline combining Named Entity Recognition and a simple rules-based relationship extraction model helps screen compounds related to liver adversities in the literature, but also extract mechanistic information for how such adversities develop, from the molecular to the organismal level. Finally, we provide some perspectives opened by the recent progress in Large Language Models and how these could be used in the future. We propose this work brings two main contributions: 1) a proof-of-concept that NLP can support the extraction of information from text for modern toxicology and 2) a template open-source model for recognition of toxicological entities and extraction of their relationships. All resources are openly accessible via GitHub (https://github.com/ontox-project/en-tox).