Lifetime rates and types of subsequent child protection system contact following a first report of neglect: An age-stratified analysis

An estimated 1 in 3 U.S. children will be the subject of a child protective services (CPS) investigation during their lifetime, typically for allegations of neglect. Whether and how an initial report of neglect is addressed may place children on divergent trajectories for safety and stability throughout childhood. The purpose of this study is to track subsequent CPS contact among children born in California in 2000 who were first investigated by CPS for neglect allegations alone (no co-occurring abuse) and not permanently separated from their families of origin (i.e., not removed or reunified if removed). We estimated the rates of subsequent CPS referrals, substantiated maltreatment, placement in foster care, and allegations of physical and sexual abuse by age 18. We assessed how rates of subsequent contact varied by initial CPS response and age at first investigation. Supplemental analyses disaggregated data by race and ethnicity. Results indicate that 64% of children initially investigated for neglect alone were re-referred to CPS by age 18 and 16% experienced a subsequent removal; however, these estimates varied greatly by age. Four out of five (79% to 83%) of children initially investigated as infants had one or more subsequent CPS referrals during childhood. Children were not only re-referred for allegations of neglect; more than half of children re-referred were reported for allegations of physical or sexual abuse, indicating that abuse risk was either missed during the initial CPS investigation or escalated afterward. The failure to address maltreatment risks when children first present to the system is a complex problem with no easy solution. Our findings document that a majority of children initially referred for neglect experience future CPS involvement, often for allegations of physical or sexual abuse

Expansion of Fc receptor-bearing T lymphocytes in patients with immunoglobulin G and immunoglobulin A myeloma.

Lymphocytes obtained from the blood of normal individuals and six patients with newly diagnosed multiple myeloma were separated into T and non-T cell populations by rosette-formation with sheep erythrocytes, and were then assayed for the presence of surface membrane Fc receptors. When compared with normal individuals, four patients with IgG myeloma had a three- to fourfold increase in T cells with IgG receptors (T gamma cells) and two patients with IgA myeloma had a two- to threefold increase in T cells with IgA receptors (T alpha cells). Patients with IgG or IgA myeloma had normal numbers of non-T lymphocytes with surface receptors for IgG and IgA, respectively. The finding that human myeloma is accompanied by elevated numbers of T cells with Fc receptors for the heavy chain class of the myeloma protein: (1) may account for the apparent "monoclonal" lymphocyte population in patients with myeloma; (b) extends to humans similar observations made in mice with secretory plasmacytomas; and (c) is of interest because T cells with Fc receptors are immunoregulatory lymphocytes

Predicting Nodal Metastases in Squamous Cell Carcinoma of the Oral Tongue Using Artificial Intelligence

OBJECTIVE: The presence of occult nodal metastases in patients with squamous cell carcinoma (SCC) of the oral tongue has implications for treatment. Upwards of 30% of patients will have occult nodal metastases, yet a significant number of patients undergo unnecessary neck dissection to confirm nodal status. This study sought to predict the presence of nodal metastases in patients with SCC of the oral tongue using a convolutional neural network (CNN) that analyzed visual histopathology from the primary tumor alone. METHODS: Cases of SCC of the oral tongue were identified from the records of a single institution. Only patients with complete pathology data were included in the study. The primary tumors were randomized into 2 groups for training and testing, which was performed at 2 different levels of supervision. Board-certified pathologists annotated each slide. HALO-AI convolutional neural network and image software was used to perform training and testing. Receiver operator characteristic (ROC) curves and the Youden J statistic were used for primary analysis. RESULTS: Eighty-nine cases of SCC of the oral tongue were included in the study. The best performing algorithm had a high level of supervision and a sensitivity of 65% and specificity of 86% when identifying nodal metastases. The area under the curve (AUC) of the ROC curve for this algorithm was 0.729. CONCLUSION: A CNN can produce an algorithm that is able to predict nodal metastases in patients with squamous cell carcinoma of the oral tongue by analyzing the visual histopathology of the primary tumor alone