Optimum predetection diversity receiving system Patent

Development of optimum pre-detection diversity combining receiving system adapted for use with amplitude modulation, phase modulation, and frequency modulation system

Improved estimators for dispersion models with dispersion covariates

In this paper we discuss improved estimators for the regression and the dispersion parameters in an extended class of dispersion models (J{\o}rgensen, 1996). This class extends the regular dispersion models by letting the dispersion parameter vary throughout the observations, and contains the dispersion models as particular case. General formulae for the second-order bias are obtained explicitly in dispersion models with dispersion covariates, which generalize previous results by Botter and Cordeiro (1998), Cordeiro and McCullagh (1991), Cordeiro and Vasconcellos (1999), and Paula (1992). The practical use of the formulae is that we can derive closed-form expressions for the second-order biases of the maximum likelihood estimators of the regression and dispersion parameters when the information matrix has a closed-form. Various expressions for the second-order biases are given for special models. The formulae have advantages for numerical purposes because they require only a supplementary weighted linear regression. We also compare these bias-corrected estimators with two different estimators which are also bias-free to the second-order that are based on bootstrap methods. These estimators are compared by simulation

The Accuracy of Recalled versus Measured Pre-Pregnancy Weight for the Calculation of Pre-Pregnancy Body Mass Index

Background: In 2009, the Institute of Medicine (IOM) published gestational weight gain (GWG) guidelines with the goal of optimizing maternal and fetal outcomes. GWG recommendations are specific to pre-pregnancy body mass index (BMI): 28-40 lbs for underweight (UW; BMI2), 25-35 lbs for normal weight (NW; 18.5≤BMI/m2), 15-25 lbs for overweight (OW; 25 ≤BMI/m2), and 11-20 lbs for obese (OB; BMI≥30 kg/m2) women. With upwards of 50% of pregnancies in the U.S. unplanned, measured pre-pregnancy weight is often unavailable in clinical and research settings. Evaluating the accuracy of recalled pre-pregnancy weight early in prenatal care is important in order to establish accuracy of pre-pregnancy BMI calculations in order to counsel about GWG accurately. Objective: To examine differences in recalled versus measured pre-pregnancy weight and to examine factors associated with accuracy of recalled weights. Methods: Medical record review of 1,998 randomly selected pregnancies. Eligible women received prenatal care in faculty and resident clinics at UMass Memorial Health Care (UMMHC), delivered between January 2007 and December 2012, and had available both: (1) a measured weight within one year of conception and (2) a pre-pregnancy weight self-reported at first prenatal visit. Data were obtained from the UMMHC paper or electronic prenatal record and the Allscripts EMR. We calculated the difference in weights as recalled pre-pregnancy weight minus most recent measured weight within one year of conception. Subjects were excluded if they received care at a non-faculty or non-resident practice, charts not available after three separate retrieval attempts, both weights of interest not available, or if measured weight occurred at a prenatal visit for a prior pregnancy. For women with more than one pregnancy during the study time frame, one was randomly selected for inclusion in the analytic data set. Results: Of the 1,998 pregnancy charts reviewed, 400 records met eligibility criteria and were included in this analysis. Women were mean age 29.7 (SD: 6.2) years, 69.3% multigravida, 64.4% non-Hispanic white, 65.2% married, and 62.4% had a college or greater education. Based on recalled weight, 3.3% of women were underweight, 46.6% were normal weight, 25.9% overweight, and 24.2% obese. 63% received care in the faculty obstetric clinic. Recorded recalled weights were mean 2.4 (SD: 11.1) pounds lower than measured pre-pregnancy weight. This difference did not differ by age, location of care, pre-pregnancy BMI, marital status, race/ethnicity, primary language, gravity, education, or time between measured weight and conception, in unadjusted and adjusted models. For 88.7% of women, calculating pre-pregnancy BMI based on weight measured up to a year prior to conception or based on recalled pre-pregnancy weight reported at the first prenatal visit resulted in the same classification of pre-pregnancy BMI. Conclusion: Prenatal care providers may calculate pre-pregnancy BMIs using recalled pre-pregnancy weights early in prenatal care and use such calculated BMIs to accurately provide GWG recommendations regardless of demographic variables, gravity, or location of care

Demographic Characteristics Associated with the Presence of Recalled and Measured Prepregnancy Weights

Background: Gestational weight gain within prepregnancy BMI-specific Institute of Medicine (IOM) recommended ranges are associated with good outcomes for both mother and baby. Availability of measured prepregnancy weight, recalled prepregnancy weight or measured weight at first prenatal visit if the former two weights are not available, influences the accuracy of provider recommendations for gestational weight gain. Objective: The purpose of this study is to examine demographic characteristics associated with the presence of recalled prepregnancy weight and measured prepregnancy weight in the prenatal care medical record. Methods: Medical record review of 1,998 randomly selected pregnancies, of which 1,911 met inclusion criteria of delivery between January 2007 and December 2012 and receipt of prenatal care in faculty and resident clinic sites at UMass Memorial Health Care (UMMHC). Subjects\u27 paper prenatal chart and electronic record (AllScripts and QS prenatal EMR) were fully abstracted if available and contained both: (1) a recorded measured weight within one year of conception, and (2) a self-reported prepregnancy weight obtained at first prenatal visit. Additionally, exclusion criteria included those pregnancies with only prenatal weights recorded one year prior to conception for index pregnancy. For women with multiple pregnancies during the study time period, one pregnancy was randomly selected for inclusion in study analyses. Demographic data was abstracted for all available charts regardless of presence or absence of weights of interest. Demographic characteristics considered were age (15-29, 20-24, 25-29, 30-34, 35+ years), prepregnancy BMI calculated based on recalled height and weight (underweight: BMI2, normal weight: 18.5≤ BMI/m2, overweight: 25≤BMI/m2, and obese: 30 kg/m2≤BMI), race/ethnicity (non-Hispanic white vs. other race/ethnicity), marital status (not married vs. married), primary language (non-English vs. English), gravidity (1, 2, 3+), education (high school diploma or less, some college, 4 year college or more) and prenatal care site (faculty vs. resident obstetric clinic). Logistic regressions were performed to calculate crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs) and adjusted analyses controlled for demographics. Results: Of the 1911 pregnancies meeting initial inclusion criteria, 1711 (89.5%) had charts available for abstraction; fifty-three subjects had multiple pregnancies of which only one was included in analyses resulting in an analytic sample of 1656 pregnancies. Of these, 511 (30.9%) were missing a recalled prepregnancy weight at first prenatal visit, 711 (42.9%) had the recalled prepregnancy weight but did not have a measured weight; and only 434 (26.2%) had both weights of interest. Overweight women had decreased odds of having a recalled weight compared to women of normal weight (aOR 0.75; 95% CI 0.56-1.00). Additionally, women with ≥4 years of college compared to those with ≤ high school diploma (aOR 0.54; 95% CI 0.40-0.73), and those receiving care in the faculty compared to the resident clinics (aOR 0.48; 95% CI 0.35-0.65) had decreased odds of having a recalled weight available in the chart. Among women with available recalled prepregnancy weight (n=1101), 390 (35.4%) also had a documented measured weight within one year of conception and 711 (64.6%) did not. Women who were not married (aOR 0.54; 95% 0.39-0.76) had decreased odds of having a measured weight, whereas those receiving care in the faculty compared to resident clinics had greater odds (aOR 1.79; 95% CI 1.26-2.53) of having a measured weight within one year of conception available in their charts. Conclusions: Our results suggest that approximately 25% of women have both recalled weight at first prenatal visit and at least one weight measured within one year of conception in their medical records. Prepregnancy BMI, education, and prenatal care site were associated with presence or absence of recalled weight. Similarly, amongst those with recalled weight, martial status and prenatal care in faculty practice where associated with decreased and increased odds respectively of having a measured weight within one year of conception. We can use this information to help practitioners target women for which greater efforts are needed to provide accurate IOM-recommended BMI-specific gestational weight gain guidelines. This may be utilized to discern patterns of health care access in this patient population