5 research outputs found
Stopping the revolving door: An exploratory analysis of health care super-utilization in gynecologic oncology
The objective of this study was to determine the prevalence of and risk factors for health care super-utilization among gynecologic oncology patients at a single academic hospital. A retrospective cohort study of gynecologic oncology patients with an index unplanned encounter between January and December 2018 was performed. Super-utilizers were defined as patients with 3 or more unplanned hospital encounters during a 12-month period starting at the time of the index unplanned encounter. We identified 553 patients with gynecologic cancer. Of those, 37(7%) met inclusion criteria for super-utilizers accounting for 193/310(62%) of unplanned visits. The median number of unplanned visits was 4 (range 3–24). The most common cancers were uterine (N = 15 (41%)) and ovarian (N = 11 (30%)). Nineteen (51%) super-utilizers had advanced stage disease. Phases of oncologic care at index unplanned encounter included primary diagnosis (N = 24 (65%)), recurrence (N = 10 (27%)), and surveillance (N = 2 (5%)). Twelve super-utilizers (32%) had new diagnoses of cancer without prior therapy, 19(51%) had prior chemotherapy, 17(46%) had prior surgery, and 10(27%) had prior radiation therapy at the time of initial encounter. Fifteen super-utilizers (41%) were in the last year of life. The most common reasons for unplanned encounters were pain (66%) and gastrointestinal symptoms (61%). Multivariable analysis adjusting for key variables demonstrated that Medicaid insurance, ASA classification, and disease status are risk factors for health care super-utilization. The majority of health care utilization occurred during the first year of diagnosis. This exploratory analysis suggests an opportunity to decrease health care utilization, particularly during upfront treatment
The prevalence of hyperglycemia and its association with perioperative outcomes in gynecologic surgery: a retrospective cohort study
Abstract Background Preoperative hyperglycemia has been associated with perioperative morbidity in general surgery patients. Additionally, preoperative hyperglycemia may indicate underlying impaired glucose metabolism. Thus, identification of preoperative hyperglycemia may provide an opportunity to mitigate both short-term surgical and long-term health risk. We aimed to study this phenomenon specifically in the gynecologic surgery population. Specifically, we aimed to evaluate the association between preoperative hyperglycemia and perioperative complications in gynecologic surgery patients and to characterize adherence to diabetes screening guidelines. Methods This retrospective cohort study included 913 women undergoing major gynecologic surgery on an enhanced recovery pathway from January 2018 to July 2019. The main exposure was day of surgery glucose ≥ 140 g/dL. Multivariate regression identified risk factors for hyperglycemia and composite and wound-specific complications. Results Sixty-seven (7.3%) patients were hyperglycemic. Diabetes (aOR 24.0, 95% CI 12.3–46.9, P < .001) and malignancy (aOR 2.3, 95% CI 1.2–4.5, P = .01) were associated with hyperglycemia. Hyperglycemia was not associated with increased odds of composite perioperative (aOR 1.3, 95% CI 0.7–2.4, P = 0.49) or wound-specific complications (aOR 1.1, 95% CI 0.7–1.5, P = 0.76). Of nondiabetic patients, 391/779 (50%) met the USPSTF criteria for diabetes screening; 117 (30%) had documented screening in the preceding 3 years. Of the 274 unscreened patients, 94 (34%) had day of surgery glucose levels suggestive of impaired glucose metabolism (glucose ≥ 100 g/dL). Conclusion In our study cohort, the prevalence of hyperglycemia was low and was not associated with higher risk of composite or wound-specific complications. However, adherence to diabetes screening guidelines was poor. Future studies should aim to develop a preoperative blood glucose testing strategy that balances the low utility of universal glucose screening with the benefit of diagnosing impaired glucose metabolism in at-risk individuals
Systematic review of international studies evaluating MDRD and CKD-EPI estimated glomerular filtration rate (eGFR) equations in Black adults.
Use of race adjustment in estimating glomerular filtration rate (eGFR) has been challenged given concerns that it may negatively impact the clinical care of Black patients, as it results in Black patients being systematically assigned higher eGFR values than non-Black patients. We conducted a systematic review to assess how well eGFR, with and without race adjustment, estimates measured GFR (mGFR) in Black adults globally. A search across multiple databases for articles published from 1999 to May 2021 that compared eGFR to mGFR and reported outcomes by Black race was performed. We included studies that assessed eGFR using the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPICr) creatinine equations. Risk of study bias and applicability were assessed with the QUality Assessment of Diagnostic Accuracy Studies-2. Of 13,167 citations identified, 12 met the data synthesis criteria (unique patient cohorts in which eGFR was compared to mGFR with and without race adjustment). The studies included patients with and without kidney disease from Africa (n = 6), the United States (n = 3), Europe (n = 2), and Brazil (n = 1). Of 11 CKD-EPI equation studies, all assessed bias, 8 assessed accuracy, 6 assessed precision, and 5 assessed correlation/concordance. Of 7 MDRD equation studies, all assessed bias, 6 assessed accuracy, 5 assessed precision, and 3 assessed correlation/concordance. The majority of studies found that removal of race adjustment improved bias, accuracy, and precision of eGFR equations for Black adults. Risk of study bias was often unclear, but applicability concerns were low. Our systematic review supports the need for future studies to be conducted in diverse populations to assess the possibility of alternative approaches for estimating GFR. This study additionally provides systematic-level evidence for the American Society of Nephrology-National Kidney Foundation Task Force efforts to pursue other options for GFR estimation
Beyond the poverty of national security: toward a critical human security perspective in educational policy
Early stage litter decomposition across biomes
Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies, adding major uncertainty to syntheses, comparisons and meta-analyses across different experiments and sites. In the TeaComposition initiative, the potential litter decomposition is investigated by using standardized substrates (Rooibos and Green tea) for comparison of litter mass loss at 336 sites (ranging from −9 to +26 °C MAT and from 60 to 3113 mm MAP) across different ecosystems. In this study we tested the effect of climate (temperature and moisture), litter type and land-use on early stage decomposition (3 months) across nine biomes. We show that litter quality was the predominant controlling factor in early stage litter decomposition, which explained about 65% of the variability in litter decomposition at a global scale. The effect of climate, on the other hand, was not litter specific and explained <0.5% of the variation for Green tea and 5% for Rooibos tea, and was of significance only under unfavorable decomposition conditions (i.e. xeric versus mesic environments). When the data were aggregated at the biome scale, climate played a significant role on decomposition of both litter types (explaining 64% of the variation for Green tea and 72% for Rooibos tea). No significant effect of land-use on early stage litter decomposition was noted within the temperate biome. Our results indicate that multiple drivers are affecting early stage litter mass loss with litter quality being dominant. In order to be able to quantify the relative importance of the different drivers over time, long-term studies combined with experimental trials are needed.This work was performed within the TeaComposition initiative, carried out by 190 institutions worldwide. We thank Gabrielle Drozdowski for her help with the packaging and shipping of tea, Zora Wessely and Johannes Spiegel for the creative implementation of the acknowledgement card, Josip Dusper for creative implementation of the graphical abstract, Christine Brendle for the GIS editing, and Marianne Debue for her help with the data cleaning. Further acknowledgements go to Adriana Principe, Melanie Köbel, Pedro Pinho, Thomas Parker, Steve Unger, Jon Gewirtzman and Margot McKleeven for the implementation of the study at their respective sites. We are very grateful to UNILEVER for sponsoring the Lipton tea bags and to the COST action ClimMani for scientific discussions, adoption and support to the idea of TeaComposition as a common metric. The initiative was supported by the following grants: ILTER Initiative Grant, ClimMani Short-Term Scientific Missions Grant (COST action ES1308; COST-STSM-ES1308-36004; COST-STM-ES1308-39006; ES1308-231015-068365), INTERACT (EU H2020 Grant No. 730938), and Austrian Environment Agency (UBA). Franz Zehetner acknowledges the support granted by the Prometeo Project of Ecuador's Secretariat of Higher Education, Science, Technology and Innovation (SENESCYT) as well as Charles Darwin Foundation for the Galapagos Islands (2190). Ana I. Sousa, Ana I. Lillebø and Marta Lopes thanks for the financial support to CESAM (UID/AMB/50017), to FCT/MEC through national funds (PIDDAC), and the co-funding by the FEDER, within the PT2020 Partnership Agreement and Compete 2020. The research was also funded by the Portuguese Foundation for Science and Technology, FCT, through SFRH/BPD/107823/2015 (A.I. Sousa), co-funded by POPH/FSE. Thomas Mozdzer thanks US National Science Foundation NSF DEB-1557009. Helena C. Serrano thanks Fundação para a Ciência e Tecnologia (UID/BIA/00329/2013). Milan Barna acknowledges Scientific Grant Agency VEGA (2/0101/18). Anzar A Khuroo acknowledges financial support under HIMADRI project from SAC-ISRO, India