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1.  Severe Cutaneous Reactions requiring Hospitalization in Allopurinol Initiators: a Population-based Cohort Study 
Arthritis care & research  2013;65(4):578-584.
Background
Rare but potentially life-threatening cutaneous adverse reactions have been associated with allopurinol, but population-based data on incidence and mortality of such reactions is scarce.
Methods
We conducted a propensity score-matched cohort study to evaluate incidence rate (IR) and in-hospital mortality of hospitalization for severe cutaneous adverse reactions (SCARs) in allopurinol initiators compared to non-allopurinol users, using data from five large Medicaid programs. The primary outcome was identified by the principal discharge diagnosis code 695.1. Cox proportional hazards model evaluated the relative risk of SCARs associated with use of allopurinol and determined the relative risk of SCARs associated with allopurinol dose.
Results
During a follow-up period of 65,625 person-years for allopurinol initiators, 45 were hospitalized with SCARs. The crude IR was 0.69 (95% CI 0.50–0.92) per 1,000 person-years. All 45 cases occurred within 365 days and 41 (91.1%) within 180 days after initiating treatment with allopurinol. Twelve (26.7%) patients died during the hospitalization. The crude IR in non-allopurinol users was 0.04 (95% CI 0.02–0.08) per 1,000 person-years. The risk of SCARs was increased in allopurinol initiators vs. non-users (HR 9.67, 95% CI 4.55–20.57). Among allopurinol initiators, the HR for the high- (>300mg/day) vs. low-dose allopurinol was 1.30 (95% CI 0.31–5.36) after adjusting for age, comorbidities and recent diuretic use.
Conclusions
Among allopurinol initiators, SCARs were found to be rare but often fatal and occurred mostly in the first 180 days of treatment. The risk of SCARs was ten times as high in allopurinol initiators compared to allopurinol non-users.
doi:10.1002/acr.21817
PMCID: PMC3502684  PMID: 22899369
2.  Bayesian Inference for the Causal Effect of Mediation 
Biometrics  2012;68(4):1028-1036.
Summary
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects through a mediator in the setting of a continuous mediator and a binary response. Several conditional independence assumptions are introduced (with corresponding sensitivity parameters) to make these effects identifiable from the observed data. We suggest strategies for eliciting sensitivity parameters and conduct simulations to assess violations to the assumptions. This approach is used to assess mediation in a recent weight management clinical trial.
doi:10.1111/j.1541-0420.2012.01781.x
PMCID: PMC3927554  PMID: 23005030
3.  The Art versus Science of Predicting Prognosis: Can a Prognostic Index Predict Short-Term Mortality Better than Experienced Nurses Do? 
Journal of Palliative Medicine  2012;15(6):703-708.
Abstract
Objective
To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can.
Method
An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment.
Results
A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%).
Conclusions
Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality.
doi:10.1089/jpm.2011.0531
PMCID: PMC3409445  PMID: 22583382
4.  Primary Caregiver Characteristics and Transitions in Community-Based Care 
Objectives.
To identify informal primary caregiver characteristics associated with care transitions of community-dwelling older persons with impairments in daily living activities.
Method.
Data for this study were pooled to observe transitions from Wave 1–Wave 2 and Wave 2–Wave 3 of the Second Longitudinal Survey on Aging (LSOA II). The sample includes respondents with at least one impairment in daily living activities and with an informal caregiver at baseline of each transition period (n = 2,990). Primary caregiver transitions to another informal caregiver, to formal care, to a nursing home, or to no care were modeled using multinomial logistic regression.
Results.
More than half (54%) of the surviving respondents experienced a care transition for a period of 2 years. Multivariate results indicate that husband and son primary caregivers are more likely to transfer care than wives and daughters, although children caring for same-gender parents were less likely to transfer out of the primary caregiver role than children caring for parents of the opposite sex. Respondents with primary caregivers who are “other” relatives or nonrelatives, who are not coresident with the care receiver, or who are assisted by secondary helpers were at elevated risk for care transitions over the 2-year study period.
Discussion.
The results of this study suggest that older persons’ care transitions result from complex informal network dynamics, with primary caregiver gender and relationship to the care receiver playing key roles.
doi:10.1093/geronb/gbs032
PMCID: PMC3325088  PMID: 22492069
Caregiving; Community-based care; Disability
5.  The Effectiveness of CBT in 3–7 Year Old Anxious Children: Preliminary Data 
Introduction:
While CBT has been found to be an effective treatment for anxious older children, it has not been empirically validated in children younger than 8 years. In this study we report on an open pilot trial to establish whether a modified form of CBT can benefit young children.
Methods:
Participants were 37 anxious children aged 37–89 months attending a university anxiety specialty clinic. Symptom severity and functioning were assessed before and after treatment by independent evaluators. Feasibility and acceptability of the intervention were high. Parents attended part of each treatment session and were considered part of the treatment team.
Results:
Patients exhibited significant improvement from pre – to post-treatment assessments after an average of 8.3 treatment sessions, using the Strengths and Difficulties Questionnaire (SDQ) and the Global Assessment of Functioning Scale (GAF) ratings.
Conclusions:
A modified form of CBT with active parent involvement may be a useful tool in treating anxiety disorders in preschool and early school aged children.
PMCID: PMC2868557  PMID: 20467547
anxiety; preschool; CBT; anxiété; âge préscolaire; TCC
6.  Risk Factors for Umbilical Venous Catheter-Associated Thrombosis in Very Low Birth Weight Infants 
Pediatric blood & cancer  2009;52(1):75-79.
Background
Thrombosis in neonates is a rare but serious occurrence, usually associated with central catheterization. The objective of this study was to investigate the risk factors associated with catheter related thrombosis in very low birth weight (VLBW) infants.
Procedure
The present retrospective study was performed using data from a randomized trial of duration of umbilical venous catheters (UVC) placement among infants <1250 g birth weight. Twenty-two cases of UVC-associated thrombosis were identified in this sample. The remaining study sample (n=188) served as the comparison group. Data on thrombosis, platelets, gestational age, birth weight, hematocrit, serum sodium, maternal preeclampsia, blood group, infant of diabetic mother and demographic factors were collected using database and record review.
Results
Among the total subjects (n=210), 112 (53%) were males and 126 (60%) were Caucasians, with mean gestational age of 27.7 ± 2.1 weeks (standard deviation) and mean birth weight of 923 ± 195 grams. Bivariate analysis revealed significant association of thrombosis with hematocrit >55% in the first week (odds ratio [OR] 5.4; 95% confidence interval [CI] 2.0-14.6; p=0.0003), being small for gestational age (OR, 2.9; 95% CI, 1.2-7.4; p=0.02) and maternal preeclampsia (OR, 3.97; 95% CI, 1.6-9.84; p=0.0017). In multivariate logistic regression analysis, only hematocrit >55% was independently associated with thrombus (OR, 3.7; 95% CI 1.1-11.8; p=0.03).
Conclusions
This study demonstrates a significant, independent association between elevated hematocrit and development of UVC-associated thrombosis. Careful monitoring for catheter-associated thrombosis may be indicated in VLBW infants who have hematocrit >55% in the first week of life.
doi:10.1002/pbc.21714
PMCID: PMC2585148  PMID: 18680150
neonate; thrombosis; risk factors; umbilical venous catheters
7.  A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times 
Biometrics  2007;64(2):538-545.
Summary
In this article we consider the problem of fitting pattern mixture models to longitudinal data when there are many unique dropout times. We propose a marginally specified latent class pattern mixture model. The marginal mean is assumed to follow a generalized linear model, whereas the mean conditional on the latent class and random effects is specified separately. Because the dimension of the parameter vector of interest (the marginal regression coefficients) does not depend on the assumed number of latent classes, we propose to treat the number of latent classes as a random variable. We specify a prior distribution for the number of classes, and calculate (approximate) posterior model probabilities. In order to avoid the complications with implementing a fully Bayesian model, we propose a simple approximation to these posterior probabilities. The ideas are illustrated using data from a longitudinal study of depression in HIV-infected women.
doi:10.1111/j.1541-0420.2007.00884.x
PMCID: PMC2791415  PMID: 17900312
Bayesian model averaging; Incomplete data; Latent variable; Marginal model; Random effects
8.  The Quality of the Quality Indicator of Pain Derived from the Minimum Data Set 
Health Services Research  2005;40(4):1197-1216.
Objective
To examine facility variation in data quality of the level of pain documented in the minimum data set (MDS) as a function of level of hospice enrollment in nursing homes (NHs).
Data Source
Clinical assessments on 3,469 nonhospice residents from 178 NHs were merged with On-line Survey Certification and Reporting data of 2000, Medicare Claims data of 2000 and the MDS of 2000–2002.
Study Design
Using the same assessment protocol, NH staff and study nurses independently assessed 3,469 nonhospice residents. Study nurses' assessments being gold standard, we quantified and compared quality of NH staff's pain rating across NHs with high, medium, or low hospice use. Multilevel models were built to assess the effect of NH hospice use levels on the occurrence of false positive (FP) and false negative (FN) errors in NH-rated “severe pain.”
Principal Findings
Of 178 NHs, 25 had medium and 41 high hospice use. NHs with higher hospice use had lower sensitivities. In multilevel analysis, we found a significant facility-level variation in the probability of FP and FN errors in facility-rated “severe pain.” Resident characteristics only explained 4 and 0 percent of the facility variation in FP and FN, respectively; characteristics and locations (state) of NHs further explained 53 and 52 percent of the variance. After controlling for resident and NH characteristics, staff in NHs with medium or high hospice use were less likely to have FP or FN errors in their MDS documentation of pain than were staff in NHs with low or no hospice use.
Conclusions
The examination of data quality of pooled MDS data from multiple NHs is insufficient. Multilevel analysis is needed to elucidate sources of heterogeneity in the quality of MDS data across NHs. Facility characteristics, e.g., hospice use or NH location, are systematically associated with overrated/underrated pain and may bias pain quality indicator (QI) comparisons. To ensure the integrity of QI comparison in the NH setting, the government may need to institute regular audits of MDS data quality.
doi:10.1111/j.1475-6773.2005.00400.x
PMCID: PMC1361186  PMID: 16033500
Multilevel analysis; nursing home; minimum data set; pain; hospice; quality indicator; reliability
9.  Inter-rater reliability of nursing home quality indicators in the U.S 
Background
In the US, Quality Indicators (QI's) profiling and comparing the performance of hospitals, health plans, nursing homes and physicians are routinely published for consumer review. We report the results of the largest study of inter-rater reliability done on nursing home assessments which generate the data used to derive publicly reported nursing home quality indicators.
Methods
We sampled nursing homes in 6 states, selecting up to 30 residents per facility who were observed and assessed by research nurses on 100 clinical assessment elements contained in the Minimum Data Set (MDS) and compared these with the most recent assessment in the record done by facility nurses. Kappa statistics were generated for all data items and derived for 22 QI's over the entire sample and for each facility. Finally, facilities with many QI's with poor Kappa levels were compared to those with many QI's with excellent Kappa levels on selected characteristics.
Results
A total of 462 facilities in 6 states were approached and 219 agreed to participate, yielding a response rate of 47.4%. A total of 5758 residents were included in the inter-rater reliability analyses, around 27.5 per facility. Patients resembled the traditional nursing home resident, only 43.9% were continent of urine and only 25.2% were rated as likely to be discharged within the next 30 days.
Results of resident level comparative analyses reveal high inter-rater reliability levels (most items >.75). Using the research nurses as the "gold standard", we compared composite quality indicators based on their ratings with those based on facility nurses. All but two QI's have adequate Kappa levels and 4 QI's have average Kappa values in excess of .80. We found that 16% of participating facilities performed poorly (Kappa <.4) on more than 6 of the 22 QI's while 18% of facilities performed well (Kappa >.75) on 12 or more QI's. No facility characteristics were related to reliability of the data on which Qis are based.
Conclusion
While a few QI's being used for public reporting have limited reliability as measured in US nursing homes today, the vast majority of QI's are measured reliably across the majority of nursing facilities. Although information about the average facility is reliable, how the public can identify those facilities whose data can be trusted and whose cannot remains a challenge.
doi:10.1186/1472-6963-3-20
PMCID: PMC280691  PMID: 14596684

Results 1-9 (9)