BackgroundLittle is known about the quality of life of parents and families of preterm infants after discharge from the neonatal intensive care unit (NICU). Our aims were (1) to describe the impact of preterm birth on parents and families and (2) and to identify potentially modifiable determinants of parent and family impact.MethodsWe surveyed 196 parents of preterm infants <24 months corrected age in 3 specialty clinics (82% response rate). Primary outcomes were: (1) the Impact on Family Scale total score; and (2) the Infant Toddler Quality of Life parent emotion and (3) time limitations scores. Potentially modifiable factors were use of community-based services, financial burdens, and health-related social problems. We estimated associations of potentially modifiable factors with outcomes, adjusting for socio-demographic and infant characteristics using linear regression.ResultsMedian (inter-quartile range) infant gestational age was 28 (26–31) weeks. Higher Impact on Family scores (indicating worse effects on family functioning) were associated with taking ≥3 unpaid hours/week off from work, increased debt, financial worry, unsafe home environment and social isolation. Lower parent emotion scores (indicating greater impact on the parent) were also associated with social isolation and unpaid time off from work. Lower parent time limitations scores were associated with social isolation, unpaid time off from work, financial worry, and an unsafe home environment. In contrast, higher parent time limitations scores (indicating less impact) were associated with enrollment in early intervention and Medicaid.ConclusionsInterventions to reduce social isolation, lessen financial burden, improve home safety, and increase enrollment in early intervention and Medicaid all have the potential to lessen the impact of preterm birth on parents and families.Electronic supplementary materialThe online version of this article (doi:10.1186/s12955-017-0602-3) contains supplementary material, which is available to authorized users.
Endocrine mucin-producing sweat gland carcinoma (EMPSGC) is a rare, low-grade adnexal neoplasm with predilection for the periorbital skin of older women. Histologically and immunophenotypically, EMPSGC is analogous to another neoplasm with neuroendocrine differentiation, solid papillary carcinoma of the breast. Both lesions are spatially associated with neuroendocrine mucinous adenocarcinomas of the skin and breast, respectively. EMPSGC is ostensibly a precursor of neuroendocrine-type mucinous sweat gland adenocarcinoma (MSC), a lesion of uncertain prognosis. Non-neuroendocrine MSC has been deemed locally aggressive with metastatic potential, and previous works speculated that EMPSGC-associated (neuroendocrine-type) MSC had similar recurrence and metastatic potential with implications for patient follow-up. Only 96 cases of EMPSGC have been reported (12 cases in the largest case series). Herein, we present 63 cases diagnosed as “EMPSGC” in comparison with aggregated results from known published EMPSGC cases. We aim to clarify the clinicopathologic features and prognostic significance of the neuroendocrine differentiation of EMPSGC and its associated adenocarcinoma and to determine the nosological relevance of EMPSGC association in the spectrum of MSC histopathogenesis. Results established an overall female predominance (66.7%) and average presenting age of 64 years. EMPSGC lesions were associated with adjacent MSC in 33.3% of cases. The recurrence rate for neuroendocrine-type MSC was ~21%, less than the reported 30% for non-neuroendocrine MSC. There were no cases of metastasis. EMPSGC and neuroendocrine-type MSC are distinct entities with more indolent behavior than previously reported, supporting a favorable prognosis for patients.
Optical coherence tomography angiography documented significant enlargement of deep foveal avascular zone as well as reduction in superficial and deep CVD in affected eyes. These findings correlated with the presence of subretinal fluid and increasing tumor size, suggesting that tumor-related factors contribute to parafoveal microvascular ischemia.
Emailed questionnaires after NICU discharge were feasible to implement and acceptable to families. Repeated post-discharge assessments may help identify infants at heightened health and developmental risk.
Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks make their predictions remains a significant challenge, but explainability tools help provide insights into what models have learned when corresponding histologic features are poorly defined. Here, we present a method for improving explainability of DNN models using synthetic histology generated by a conditional generative adversarial network (cGAN). We show that cGANs generate high-quality synthetic histology images that can be leveraged for explaining DNN models trained to classify molecularly-subtyped tumors, exposing histologic features associated with molecular state. Fine-tuning synthetic histology through class and layer blending illustrates nuanced morphologic differences between tumor subtypes. Finally, we demonstrate the use of synthetic histology for augmenting pathologist-in-training education, showing that these intuitive visualizations can reinforce and improve understanding of histologic manifestations of tumor biology.
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