Diagnostic utility of clinicodemographic, biochemical and metabolite variables to identify viable pregnancies in a symptomatic cohort during early gestation.

A significant number of pregnancies are lost in the first trimester and 1-2% are ectopic pregnancies (EPs). Early pregnancy loss in general can cause significant morbidity with bleeding or infection, while EPs are the leading cause of maternal mortality in the first trimester. Symptoms of pregnancy loss and EP are very similar (including pain and bleeding); however, these symptoms are also common in live normally sited pregnancies (LNSP). To date, no biomarkers have been identified to differentiate LNSP from pregnancies that will not progress beyond early gestation (non-viable or EPs), defined together as combined adverse outcomes (CAO). In this study, we present a novel machine learning pipeline to create prediction models that identify a composite biomarker to differentiate LNSP from CAO in symptomatic women. This prospective cohort study included 370 participants. A single blood sample was prospectively collected from participants on first emergency presentation prior to final clinical diagnosis of pregnancy outcome: LNSP, miscarriage, pregnancy of unknown location (PUL) or tubal EP (tEP). Miscarriage, PUL and tEP were grouped together into a CAO group. Human chorionic gonadotrophin ß (ß-hCG) and progesterone concentrations were measured in plasma. Serum samples were subjected to untargeted metabolomic profiling. The cohort was randomly split into train and validation data sets, with the train data set subjected to variable selection. Nine metabolite signals were identified as key discriminators of LNSP versus CAO. Random forest models were constructed using stable metabolite signals alone, or in combination with plasma hormone concentrations and demographic data. When comparing LNSP with CAO, a model with stable metabolite signals only demonstrated a modest predictive accuracy (0.68), which was comparable to a model of ß-hCG and progesterone (0.71). The best model for LNSP prediction comprised stable metabolite signals and hormone concentrations (accuracy = 0.79). In conclusion, serum metabolite levels and biochemical markers from a single blood sample possess modest predictive utility in differentiating LNSP from CAO pregnancies upon first presentation, which is improved by variable selection and combination using machine learning. A diagnostic test to confirm LNSP and thus exclude pregnancies affecting maternal morbidity and potentially life-threatening outcomes would be invaluable in emergency situations.

The natural history of recovery from psychological trauma: An observational model.

Following observation of patients who have experienced psychological trauma, a model of recovery is described with implications for the efficiency and effectiveness of treatment.

Using a decline in serum hCG between days 0-4 to predict ectopic pregnancy treatment success after single-dose methotrexate: a retrospective cohort study.

BACKGROUND: The current measure of treatment efficacy of single-dose methotrexate for ectopic pregnancy, is a fall in serum hCG of ≥15% between days 4-7 of treatment, which has a positive predictive value of 93% for treatment success. Two small studies have proposed a fall in serum hCG between days 0-4 after treatment confers similar, earlier prognostic information, with positive predictive values of 100% and 88% for treatment success. We sought to validate this in a large, independent cohort because of the potentially significant clinical implications. METHODS: We conducted a retrospective study of women (n=206) treated with single-dose methotrexate for ectopic pregnancy (pre-treatment serum hCG levels ≤3000 IU/L) at Scottish hospitals between 2006-2011. Women were divided into two cohorts based on whether their serum hCG levels rose or fell between days 0-4 after methotrexate. Treatment outcomes of women in each cohort were compared, and the test performance characteristics calculated. This methodology was repeated for the current measure (≥15% fall in serum hCG between days 4-7 of treatment) and an alternate early measure (<20% fall in serum hCG between days 0-4 of treatment), and all three measures were compared for their ability to predict medical treatment success. RESULTS: In our cohort, the positive predictive value of the current clinical measure was 89% (95% CI 84-94%) (121/136). A falling serum hCG between days 0-4 predicted treatment success in 85% (95% CI 79-92%) of cases (94/110) and a <20% fall in serum hCG between days 0-4 predicted treatment success in 94% (95% CI 88-100%) of cases (59/63). There was no significant difference in the ability of these tests to predict medical treatment success. CONCLUSIONS: We have verified that a decline in serum hCG between days 0-4 after methotrexate treatment for ectopic pregnancies, with pre-treatment serum hCG levels ≤3000 IU/L, provides an early indication of likelihood of treatment success, and performs just as well as the existing measure, which only provides prognostic information on day 7.

Predictors of poor perinatal outcome following maternal perception of reduced fetal movements--a prospective cohort study.

BACKGROUND: Maternal perception of reduced fetal movement (RFM) is associated with increased risk of stillbirth and fetal growth restriction (FGR). RFM is thought to represent fetal compensation to conserve energy due to insufficient oxygen and nutrient transfer resulting from placental insufficiency. OBJECTIVE: To identify predictors of poor perinatal outcome after maternal perception of reduced fetal movements (RFM). DESIGN: Prospective cohort study. METHODS: 305 women presenting with RFM after 28 weeks of gestation were recruited. Demographic factors and clinical history were recorded and ultrasound performed to assess fetal biometry, liquor volume and umbilical artery Doppler. A maternal serum sample was obtained for measurement of placentally-derived or modified proteins including: alpha fetoprotein (AFP), human chorionic gonadotrophin (hCG), human placental lactogen (hPL), ischaemia-modified albumin (IMA), pregnancy associated plasma protein A (PAPP-A) and progesterone. Factors related to poor perinatal outcome were determined by logistic regression. RESULTS: 22.1% of pregnancies ended in a poor perinatal outcome after RFM. The most common complication was small-for-gestational age infants. Pregnancy outcome after maternal perception of RFM was related to amount of fetal activity while being monitored, abnormal fetal heart rate trace, diastolic blood pressure, estimated fetal weight, liquor volume, serum hCG and hPL. Following multiple logistic regression abnormal fetal heart rate trace (Odds ratio 7.08, 95% Confidence Interval 1.31-38.18), (OR) diastolic blood pressure (OR 1.04 (95% CI 1.01-1.09), estimated fetal weight centile (OR 0.95, 95% CI 0.94-0.97) and log maternal serum hPL (OR 0.13, 95% CI 0.02-0.99) were independently related to pregnancy outcome. hPL was related to placental mass. CONCLUSION: Poor perinatal outcome after maternal perception of RFM is closely related to factors which are connected to placental dysfunction. Novel tests of placental function and associated fetal response may provide improved means to detect fetuses at greatest risk of poor perinatal outcome after RFM.

Maternal perception of reduced fetal movements is associated with altered placental structure and function.

BACKGROUND: Maternal perception of reduced fetal movement (RFM) is associated with increased risk of stillbirth and fetal growth restriction (FGR). DFM is thought to represent fetal compensation to conserve energy due to insufficient oxygen and nutrient transfer resulting from placental insufficiency. To date there have been no studies of placental structure in cases of DFM. OBJECTIVE: To determine whether maternal perception of reduced fetal movements (RFM) is associated with abnormalities in placental structure and function. DESIGN: Placentas were collected from women with RFM after 28 weeks gestation if delivery occurred within 1 week. Women with normal movements served as a control group. Placentas were weighed and photographs taken. Microscopic structure was evaluated by immunohistochemical staining and image analysis. System A amino acid transporter activity was measured as a marker of placental function. Placentas from all pregnancies with RFM (irrespective of outcome) had greater area with signs of infarction (3.5% vs. 0.6%; p<0.01), a higher density of syncytial knots (p<0.001) and greater proliferation index (p<0.01). Villous vascularity (p<0.001), trophoblast area (p<0.01) and system A activity (p<0.01) were decreased in placentas from RFM compared to controls irrespective of outcome of pregnancy. CONCLUSIONS: This study provides evidence of abnormal placental morphology and function in women with RFM and supports the proposition of a causal association between placental insufficiency and RFM. This suggests that women presenting with RFM require further investigation to identify those with placental insufficiency.