A predictive model of macrosomic birth based upon real-world clinical data from pregnant women.

BACKGROUND: Fetal macrosomia is associated with an increased risk of several maternal and newborn complications. Antenatal predication of fetal macrosomia remains challenging. We aimed to develop a nomogram model for the prediction of macrosomia using real-world clinical data to improve the sensitivity and specificity of macrosomia prediction. METHODS: In the present study, we performed a retrospective, observational study based on 13,403 medical records of pregnant women who delivered singleton infants at a tertiary hospital in Shanghai from 1 January 2018 through 31 December 2019. We split the original dataset into a training set (n = 9382) and a validation set (n = 4021) at a 7:3 ratio to generate and validate our model. The candidate variables, including maternal characteristics, laboratory tests, and sonographic parameters were compared between the two groups. A univariate and multivariate logistic regression was carried out to explore the independent risk factors for macrosomia in pregnant women. Thus, the regression model was adopted to establish a nomogram to predict the risk of macrosomia. Nomogram performance was determined by discrimination and calibration metrics. All the statistical analysis was analyzed using R software. RESULTS: We compared the differences between the macrosomic and non-macrosomic groups within the training set and found 16 independent risk factors for macrosomia (P < 0.05), including biparietal diameter (BPD), head circumference (HC), femur length (FL), amniotic fluid index (AFI) at the last prenatal examination, pre-pregnancy body mass index (BMI), and triglycerides (TG). Values for the areas under the curve (AUC) for the nomogram model were 0.917 (95% CI, 0.908-0.927) and 0.910 (95% CI, 0.894-0.927) in the training set and validation set, respectively. The internal and external validation of the nomogram demonstrated favorable calibration as well as discriminatory capability of the model. CONCLUSIONS: Our model has precise discrimination and calibration capabilities, which can help clinical healthcare staff accurately predict macrosomia in pregnant women.

Complete remission of two patients with recurrent and wide spread extramammary Paget disease obtained from 5-aminolevulinic acid-based photodynamic therapy and imiquimod combination treatment.

BACKGROUND: Extramammary Paget disease (EMPD) is an uncommon malignant neoplasm affecting apocrine gland-bearing skin which usually occurs in the anogenital area of patients older than 50 years. However, as EMPD in old men develops in penoscrotal area and sometimes asymptomatic, in situ or dermal invasion is usually widely spread before a confirmed diagnosis was made. Skin graft is needed after surgery. Both photodynamic therapy (PDT) and topical use of imiquimod reported effective for EMPD. METHODS: Two patients with recurrent and wide spread at penoscrotal and groin area were diagnosed EMPD by biopsy and histopathological and immunohistochemical examination. We use 6 cycles of 20% 5-aminolevulinic acid (ALA) photodynamic therapy guided by 5-ALA induced porphyrin fluorescence. After PDT, patients were treated by topical use of imiquimod to prevent the recurrence. RESULTS: After 6 cycles of PDT and imiquimod treatments, the patients' examination showed total remission. At the end of the 6 and 12 months, biopsy and pathology examination remain no signal of recurrence. No clinical recurrence after 24 and 36 months' follow up. CONCLUSION: The combination treatment with 20% PDT and imiquimod acquired complete remission in treatment for recurrent and wide spread extramammary Paget disease in two patients.