First-order Autoregressive Covariance Structure Research Articles

Predictors of cervical tumour size for outpatients with cervical cancer at the University of Gondar referral hospital: a retrospective study design

BackgroundCervical cancer is one of the most serious threats to women's lives. Modelling the change in tumour size over time for outpatients with cervical cancer was the study's main goal.MethodsA hospital conducted a retrospective cohort study with outpatients who had cervical cancer. The information about the tumour size was taken from the patient's chart and all patient data records between May 20, 2017, and May 20, 2021. The data cover 322 cervical cancer outpatients' basic demographic and medical information. When analysing longitudinal data, the linear mixed effect model and the connection between tumour sizes in outpatients were taken into consideration. A linear mixed model, a random intercept model, and a slope model were used to fit the data.ResultA sample of 322 cervical cancer outpatients was examined, and 148 (or 46% of the outpatients) tested positive for HIV. The linear mixed model with a first-order autoregressive covariance structure revealed that a change in time of one month led to a 0.009 cm2 reduction in tumour size. For every kilogramme more in weight, the tumour size change in cervical cancer patients decreased considerably by 0.0098 cm2. The tumour size change in the cervical cancer patient who was HIV-positive was 0.4360 cm squared greater than that in the HIV-negative outpatients.ConclusionAs a consequence, there was a significant association between the longitudinal change in tumour size and the predictor variables visit time, therapy, patient weight, cancer stage, HIV, oral contraceptive use, history of abortion, and smoking status.

Early postoperative physical activity and function: a descriptive case series study of 53 patients after lumbar spine surgery

BackgroundThe purpose of this prospective case series study was to compare changes in early postoperative physical activity and physical function between 6 weeks and 3 and 6 months after lumbar spine surgery.MethodsFifty-three patients (mean [95% confidence interval; CI] age = 59.2 [56.2, 62.3] years, 64% female) who underwent spine surgery for a degenerative lumbar condition were assessed at 6 weeks and 3- and 6-months after surgery. The outcomes were objectively-measured physical activity (accelerometry) and patient-reported and objective physical function. Physical activity was assessed using mean steps/day and time spent in moderate to vigorous physical activity (MVPA) over a week. Physical function measures included Oswestry Disability Index (ODI), 12-item Short Form Health Survey (SF-12), Timed Up and Go (TUG), and 10-Meter Walk (10 MW). We compared changes over time in physical activity and function using generalized estimating equations with robust estimator and first-order autoregressive covariance structure. Proportion of patients who engaged in meaningful physical activity (e.g., walked at least 4400 and 6000 steps/day or engaged in at least 150 min/week in MVPA) and achieved clinically meaningful changes in physical function were compared at 3 and 6 months.ResultsAfter surgery, 72% of patients initiated physical therapy (mean [95%CI] sessions =8.5 [6.6, 10.4]) between 6 weeks and 3 months. Compared to 6 weeks post-surgery, no change in steps/day or time in MVPA/week was observed at 3 or 6 months. From 21 to 23% and 9 to 11% of participants walked at least 4400 and 6000 steps/day at 3 and 6 months, respectively, while none of the participants spent at least 150 min/week in MVPA at these same time points. Significant improvements were observed on ODI, SF-12, TUG and 10 MW (p < 0.05), with over 43 to 68% and 62 to 87% achieving clinically meaningful improvements on these measures at 3 and 6 months, respectively.ConclusionLimited improvement was observed in objectively-measured physical activity from 6 weeks to 6 months after spine surgery, despite moderate to large function gains. Early postoperative physical therapy interventions targeting physical activity may be needed.

Personal PM2.5Exposure and Resting Heart Rate in the Study of Pollution and COPD Exacerbation (SPACE) Cohort

BackgroundDaily changes in fine particulate matter (PM2.5) exposure have been linked to intermediate cardiovascular outcomes such as reduced heart rate (HR) variability and elevated HR. While less is known about PM exposure and resting HR, higher resting HR can indicate cardiovascular pathophysiology that may predict poor cardiovascular outcomes.MethodsWe recruited 27 former smokers with a clinical diagnosis of COPD and GOLD Stage II or greater airflow obstruction on spirometry residing in the Boston area. Participants were followed for up to 4 months (1 month per season), during which they wore Fitbit Charge 2 activity monitors and a personal air quality monitor by Atmospheric Sensors Ltd (ASL). We applied linear mixed effects models to examine associations between same- and previous-day PM2.5 and daily resting HR. We accounted for intra-individual correlations by using participant-specific random effects and nesting participants within observation month. Errors were assumed to follow a first-order autoregressive covariance structure. Models were adjusted for age, sex, race, BMI, COPD severity (FEV1), education, season, temperature, relative humidity, coronary artery disease, congestive heart failure, arrythmia, and nodal blocker use.ResultsA total of 2,120 observation-days were collected from the study participants, who were 44% female with mean (SD) age of 72 (8) years. 75% of the daily PM2.5 fell between 4-11 µg/m3 (mean=10 µg/m3). Daily resting HR was normally distributed with mean 70 bpm (SD=8.7). Same-day PM2.5 is not associated with resting HR when evaluated as a continuous variable, in quartiles, or as a binary variable relative to the EPA Air Quality Index 24-hour threshold of 12 µg/m3 (for “good” air quality). Previous-day PM2.5 was not associated with resting HR. Across all models, lower education level and arrythmia were associated with higher resting HR.ConclusionSame and previous-day personal PM2.5 exposure was not associated with daily resting HR in this population with moderate to severe COPD.

Hot weather increases competition between dairy cows at the drinker

Heat-stressed dairy cows on pasture will compete for resources that aid cooling, but it is not known how heat stress affects the competition for water by indoor-housed cows. The aim of this observational study was to evaluate how heat stress affects the behavior of indoor-housed cows at the drinker at both group and cow levels. For 3 wk after calving, cows were housed in a dynamic group of 20 animals in a pen with 12 electronic feed bins, 2 electronic water bins, and 24 freestalls. A total of 69 lactating Holstein dairy cows were enrolled over the 59-d study. The electronic water bins recorded time spent at the drinker, frequency of visits, water intake, and competitive events for 24 h/d. Competitive events were quantified using the number of replacements (recorded when there was a ≤29-s interval between 2 cows sequentially visiting the same drinker). The number of replacements a cow was involved in was used to determine her level of competitive success at the drinker (low, medium, high). The temperature-humidity index (THI) was recorded by the local weather station, and moving averages for daily maximum THI over a 3-d period were calculated. For the analysis of time spent at the drinker, frequency of visits, and water intake, the measures from all cows were averaged to create 1 observation per day, and the number of replacements at the drinker was summed. A linear regression was performed to determine the relationship between THI and group-level drinking behavior. At the cow level, a repeated measures mixed model, with fixed effects of level of competitive success, milk yield, and 3-d maximum THI and a first-order autoregressive covariance structure, was used to determine how increasing THI affects the drinking behavior of individual cows based on their level of competitive success. Feed intake was included as a fixed effect in the water intake model. We found that, with increasing THI, cows drank more water, spent more time at the drinker, made more visits to the drinker, and engaged in more competitive events at the drinker. In exploratory analysis, we found that cows with low competitive success at the drinker shifted their drinking behavior to avoid the drinker at the hottest and most competitive time of day. These results indicate that behavior can be used to indicate when cows feel hot. These measures may be of practical value in deciding when to provide cooling, especially for farms where attendance at the drinker can be monitored electronically.

Abstract P062: Individual Level Fine Particulate Air Pollution is Associated with Acute Impairment of Cardiac Autonomic Modulation in Adolescents

Introduction: Fine particulate (PM 2.5 ) air pollution has been associated with impaired cardiac autonomic modulation (CAM) in adults. The association between PM 2.5 exposure and CAM in adolescents is rarely investigated. Hypothesis: We assessed the hypothesis that PM 2.5 air pollution is related to acute impairment of CAM in adolescents. Methods: We used data from 421 adolescents in the Penn State Child Cohort follow-up examination. We obtained 24-hour ECG data using a 12-lead Holter ECG from each participant. After removing artifacts and arrhythmic beats, we performed heart rate variability (HRV) analysis on normal RR intervals to compute 30-min based high frequency (HF) and low frequency (LF) powers, standard deviation of RRs (SDNN), and the square root of mean of the sum of the squared differences of the adjacent RRs (RMSSD). Individual level 24-hour PM 2.5 concentration was obtained by a personal PM 2.5 monitor. We then calculated, on a 30-min basis, the corresponding time-specific exposure to PM 2.5 . Distributed lag models under a framework of linear mixed-effects model, with a first-order autoregressive covariance structure, were used to assess the segment-specific and cumulative effect of 30-min based PM 2.5 and HRV indices. Results: As shown in the table, both individual lag and cumulative effects of PM 2.5 on HRV, based on the lag 0-6 model, were significant after controlling for major covariates. For instance, for a 10 μg/m 3 increase in cumulative PM 2.5 , HF and SDNN decreased by 0.023 (SE=0.006) ms 2 and 0.61 (SE=0.16) ms, respectively. A 10 μg/m 3 increase in PM 2.5 was also significantly associated with elevated heart rate (0.25 (SE=0.09) beat/min). Individual lag effects of PM 2.5 were most consistently associated within 1.5 hours. Conclusion: Individual level exposure to PM 2.5 in adolescents is associated with impaired CAM, towards an elevated sympathetic and decreased parasympathetic outflow. The time to the apparent cumulative effect is about 3 hours, with the most consistent individual lag effects within 1.5 hours.

Increasing Rates of Pulmonary Embolism: A Retrospective Analysis of Pediatric Tertiary Care Hospitals

▪Background: Pulmonary embolism (PE) as a form of venous thromboembolism (VTE) is rare in children, but causes high morbidity and mortality when it occurs. Recent evidence has shown that the incidence of VTE in pediatric tertiary care hospitals has increased over the past 10 years, but the authors did not specifically evaluate PE [Raffini L, et al. Pediatrics 2009]. Utilizing the Pediatric Health Information System (PHIS) database, we sought to evaluate the incidence, treatment and outcome of PE in children over the last decade.Methods: This retrospective study reviewed pediatric patients within the PHIS database diagnosed with PE from 2001 to 2013. Demographics, including type of payer, initial treatment, length of stay, mortality, recurrence and associated chronic illness were included in the analysis. Inclusion criteria were discharge diagnosis codes for PE (415.11, 415.12, 415.19) and age less than 18 years. Demographic characteristics between those admitted with VTE alone vs. those with PE were compared using chi-square or Wilcoxon-rank sum analysis as appropriate. Rates of PE by year were calculated by dividing the number of PE admissions by the total number of hospital admissions and VTE admissions. Age groups were analyzed separately. Trends in medication use were analyzed using generalized estimating equations (GEE), assuming a first-order autoregressive covariance structure across years within the same hospital.Results: Over the period of the study, patients discharged with a diagnosis of PE (n=4,161) made up 15.5% of all pediatric discharges with VTE (n=26,909). The overall rate of PE increased by 184% from 2001 to 2013 (p=<0.001). Compared to all other age groups, adolescents (age 13-18 yrs) were the most likely to present with PE (55%, p<0.001). [Table] Additionally the rate of PE in this age group increased from 10.3 to 24.8 per 10,000 hospital discharges, a 140% increase (p<0.001), and from 17.9 to 36.5 per 100 VTE discharges, a 104% increase (p<0.001). [Figure 1] Individuals with PE were less likely to have a complex chronic condition (CCC) than those with VTE alone [CCC 58% PE vs. 65% VTE, p<0.001]. Those with PE had a higher mortality than those with VTE alone [8.5% vs. 6%, p<0.001]. Black and Hispanic patients were more likely to experience a recurrent PE than Caucasians (11.6% and 9% vs. 7.5% p<0.001). Over the period of the study, unfractionated heparin use decreased (p<0.001) and low molecular weight heparin (LMWH) use increased (p=0.001). [Figures 2 and 3]Conclusions: The rate of PE in children is increasing, particularly in the adolescent age group. The population of children with PE is different than that with VTE alone. From the PHIS data, it appears that they are more likely to be adolescents and less likely to have a complex chronic condition. Black and Hispanic patients appear to be at greater risk of recurrent PE. Treatment of PE has evolved over the past decade with greater use of LMWH compared to unfractionated heparin. Further research is required to determine what factors are contributing to the rapid increase in PE in the adolescent population and which influence the risk of recurrence in certain ethnic populations.Table1All VTE Discharges (%) (N=26,910)Discharges w/o PE (%) (N=22,748)Discharges w/ PE (%) (N=4,162)p-valueAge<0.001a. <28 d3,756 (14)3,523 (15.5)233 (5.6)b. 29 d to <1 y3,912 (15)3,563 (15.7)349 (8.4)c. 1 to <6 y5,262 (20)4,736 (20.8)526 (12.6)d. 6 to <13 y5,163 (19)4,409 (19.4)754 (18.1)e. 13-18 y8,817 (33)6,517 (28.6)2,300 (55.3)Gender0.006a. Male14,544 (54)12,375 (54.4)2,169 (52.1)p<0.001 [Display omitted] p<0.001 [Display omitted] p=0.001 [Display omitted] DisclosuresOff Label Use: Treatment of PE with anticoagulants including tPA and novel anticoagulants..

Analysis of the fluorescence of body fluids on different surfaces and times.

The use of screening techniques, such as an alternative light source (ALS), is important for finding biological evidence at a crime scene. The objective of this study was to evaluate whether biological fluid (blood, semen, saliva, and urine) deposited on different surfaces changes as a function of the age of the sample. Stains were illuminated with a Megamaxx™ ALS System and photographed with a Canon EOS Utility™ camera. Adobe Photoshop™ was utilized to prepare photographs for analysis, and then ImageJ™ was used to record the brightness values of pixels in the images. Data were submitted to analysis of variance using a generalized linear mixed model with two fixed effects (surface and fluid). Time was treated as a random effect (through repeated measures) with a first-order autoregressive covariance structure. Means of significant effects were compared by the Tukey test. The fluorescence of the analyzed biological material varied depending on the age of the sample. Fluorescence was lower when the samples were moist. Fluorescence remained constant when the sample was dry, up to the maximum period analyzed (60 days), independent of the substrate on which the fluid was deposited, showing the novelty of this study. Therefore, the forensic expert can detect biological fluids at the crime scene using an ALS even several days after a crime has occurred.

Rumen temperature change monitored with remote rumen temperature boluses after challenges with bovine viral diarrhea virus and Mannheimia haemolytica12

Remote rumen temperature monitoring is a potential method for early disease detection in beef cattle. This experiment was conducted to determine if remotely monitored rumen temperature boluses could detect a temperature change in steers exposed to bovine viral diarrhea virus (BVDV) and challenged with a common bovine respiratory disease pathogen, Mannheimia haemolytica (MH). Twenty-four Angus crossbred steers (BW = 313 ± 31 kg) were allotted to 1 of 4 treatments: 1) no challenge (control); 2) challenge by a 72-h exposure to 2 steers persistently infected with BVDV; 3) bacterial challenge with MH; and 4) viral challenge by a 72-h exposure to 2 steers persistently infected with BVDV followed by bacterial challenge with MH (BVDV + MH). Remotely monitored rumen temperature boluses programmed to transmit temperature every minute were placed in the rumen before the time of exposure to steers persistently infected with BVDV. Rectal temperatures were taken before MH challenge (0) and at 2, 4, 6, 12, 18, 24, 36, 48, 72, and 96 h after MH challenge. Rumen temperatures were recorded 3 d before (-72 h; period of BVDV exposure) through 14 d after (336 h) MH challenge. Rumen temperatures were analyzed as a randomized complete block design with a 2 × 2 factorial arrangement of treatments and a first-order autoregressive covariance structure for repeated measures. A treatment × day interaction was observed for average daily rumen temperature (P < 0.01). A treatment difference (P < 0.01) was observed on d 0, when MH-challenged steers had greater rumen temperatures than steers not challenged with MH. There was no BVDV × day interaction (P > 0.01). Rumen temperatures averaged every 2 h resulted in a BVDV × hour interaction (P < 0.01) and an MH × hour interaction (P < 0.01). The BVDV × hour differences occurred at h -18 to -14, 40 to 46, 110, 122, and 144 to 146 (P < 0.01). The MH × hour difference occurred at h 4 to 24 (P < 0.01). Maximum rumen temperature was increased (P < 0.01) for BVDV (0.8 °C), MH (1.2 °C), and BVDV + MH (1.3 °C) compared with the control. On average, rumen temperatures measured by the boluses at the same time points as the rectal temperatures were 0.13 °C less than rectal temperatures, and the 2 body temperatures were highly correlated (r = 0.89). Rumen temperature boluses appear to have potential as a tool for detecting temperature changes associated with adverse health events such as exposure to bovine respiratory disease and BVDV.

Modeling bone mineral density (BMD) evolution in postmenopausal patients treated by letrozole (L), tamoxifen (T), and sequences of T and L (SAKK 21/07)

545 Background: Osteoporosis and fractures are long term complications of aromatase inhibitor use in the adjuvant therapy of breast cancer. Early detection of patients (pts) at risk of treatment-induced osteoporosis may allow preventive therapy and selection of the most appropriate endocrine therapy. We developed a statistical model describing the evolution of BMD in pts treated with T, L and sequences of T and L. Methods: Available dual-energy x-ray absorptiometry exams (DXA) of pts treated in trial BIG 1–98 were retrospectively collected from Swiss centers. Treatment arms: A) T for 5 years; B) L for 5 years; C) 2 years of T followed by 3 years of L; and D) 2 years of L followed by 3 years of T. Pts without DXA were used as a control for detecting selection bias. A repeated measures model using the first-order autoregressive covariance structure to allow for different times between DXA was used to model BMD (g/cm2) since trial randomisation. Prospectively defined covariates were considered as fixed effects in a multivariable model using an intention to treat analysis. Covariates at trial randomization were: age, height, weight, race, known osteoporosis, tobacco use, prior bone fracture, prior hormone replacement therapy (HRT), bisphosphonate use and previous neo-/adjuvant chemotherapy (ChT). Results: A total of 247 out of 546 pts had between 1 and 5 DXA; a total of 576 DXA were collected. Arm A contained 67 pts, B 63 pts, C 55 pts and D 62 pts. Median follow-up was 5.8 years. Factors correlated with BMD in the multivariate analysis were weight (0.003/kg, p &lt; 0.0001), height (0.003/cm, p = 0.0083), osteoporosis (-0.130, p &lt; 0.0001), tobacco (current / previously vs. never: -0.057, p = 0.0011 / -0.042, p = 0.0798), previous HRT (0.030, p = 0.0244), ChT (0.032, p = 0.0174), time since endocrine therapy start (-0.009/year, p = 0.0164) and treatment arm (B / C / D vs. A: -0.068, p = 0.0002 / -0.091, p &lt; 0.0001 / -0.064, p = 0.003). Conclusions: Our statistical model describes the BMD evolution for pts treated with L and/or T. All treatment regimens affect BMD. Contrary to expectation, the switch schedule T followed by L does not seem to result in better bone protection compared to L monotherapy. [Table: see text]

Optimal time‐points in clinical trials with linearly divergent treatment effects

In repeated measures studies, equidistant time-points do not always yield efficient treatment effect estimators. In the present paper, the optimal allocation of time-points is calculated for a small number of repeated measures, different covariance structures and linearly divergent treatment effects. The gain in efficiency of the treatment effect estimator by using optimally allocated time-points instead of equidistant time-points or by adding optimally spaced measures (at the expense of patients) is then computed. The assumed covariance structure is crucial for the results. For a compound symmetric covariance structure, a large gain in efficiency is obtained by adding repeated measures at the end of the study. For a first-order auto-regressive covariance structure, highly efficient treatment effect estimators are obtained with only two repeated measures, i.e. at the start and at the end of the study. For a first-order auto-regressive covariance structure including measurement error, the gain in efficiency by adding optimally spaced measures depends on the covariance parameter values. The gain in efficiency is similar with or without a random intercept. For a fixed study budget, the commonly used design with more than two equally spaced measures was never optimal for the linear cost function and covariance structures that were used. If the covariance structure is unknown, the optimal design based on a first-order auto-regressive covariance structure with measurement error is preferable in terms of robustness against misspecification of the covariance structure. The numerical results are illustrated by two examples.

Genetic Evaluation of Dairy Cattle with Test-Day Models with Autoregressive Covariance Structures and with a 305-d Model

This study compared genetic evaluations from 3 test-day (TD) models with different assumptions about the environmental covariance structure for TD records and genetic evaluations from 305-d lactation records for dairy cows. Estimates of genetic values of 12,071 first-lactation Holstein cows were obtained with the 3 TD models using 106,472 TD records. The compound symmetry (CS) model was a simple test-day repeatability animal model with compound symmetry covariance structure for TD environmental effects. The ARs and ARe models also used TD records but with a first-order autoregressive covariance structure among short-term environmental effects or residuals, respectively. Estimates of genetic values with the TD models were also compared with those from a model using 305-d lactation records. Animals were genetically evaluated for milk, fat, and protein yields, and somatic cell score (SCS). The largest average estimates of accuracy of predicted breeding values were obtained with the ARs model and the smallest were with the 305-d model. The 305-d model resulted in smaller estimates of correlations between average predicted breeding values of the parents and lactation records of their daughters for milk and protein yields and SCS than did the CS and ARe models. Predicted breeding values with the 3 TD models were highly correlated (0.98 to 1.00). Predicted breeding values with 305-d lactation records were moderately correlated with those with TD models (0.71 to 0.87 for sires and 0.80 to 0.87 for cows). More genetic improvement can be achieved by using TD models to select for animals for higher milk, fat, and protein yields, and lower SCS than by using models with 305-d lactation records.

Reproductive performance in Ohio dairy herds in the 1990s

The objective of this study was to evaluate trends in reproductive performance in Ohio dairy herds during the 1990s. Stringent criteria for herd inclusion were applied to DHI records to ensure high quality and reliability of the data. The final data set contained 44,425 monthly herd summary records from 1772 herds from years 1992, 1994, 1996 and 1998. Outcomes of interest were calving interval length, calving-to-conception interval, days to first breeding, services per conception and first service conception rate. PROC MIXED in SAS ® (version 8.1) was used and the monthly records were treated as repeated measures nested within years and herds. First-order autoregressive covariance structure was used to model the covariance between the repeated measures within herds. The data were analyzed for the entire herd as well as for the first lactation cows separately. During the 1990s reproductive performance declined in Ohio dairy herds. Herd average calving interval lengthened from 13.6 to 14.1 months and calving-to-conception interval increased from 136 to 150 days between 1992 and 1998, respectively. Days to first service and number of services increased while first service conception rate declined on a herd level. The reproductive performance of first lactation cows, however, remained constant during this same period. Overall herd reproductive performance was associated with herd size and fat-corrected rolling herd average milk production (FCM). As milk yield increased, first service conception rate decreased and services per conception increased. Larger herds had lower first service conception rate and needed more services per conception, but they started breeding their cows earlier resulting in a slightly shorter calving interval and calving-to-conception interval compared to smaller herds.