Do functional status and Medicare claims data improve the predictive accuracy of an electronic health record mortality index? Findings from a national Veterans Affairs cohort

BackgroundElectronic health record (EHR) prediction models may be easier to use in busy clinical settings since EHR data can be auto-populated into models. This study assessed whether adding functional status and/or Medicare claims data (which are often not available in EHRs) improves the accuracy of a previously developed Veterans Affairs (VA) EHR-based mortality index.MethodsThis was a retrospective cohort study of veterans aged 75 years and older enrolled in VA primary care clinics followed from January 2014 to April 2020 (n = 62,014). We randomly split participants into development (n = 49,612) and validation (n = 12,402) cohorts. The primary outcome was all-cause mortality. We performed logistic regression with backward stepwise selection to develop a 100-predictor base model using 854 EHR candidate variables, including demographics, laboratory values, medications, healthcare utilization, diagnosis codes, and vitals. We incorporated functional measures in a base + function model by adding activities of daily living (range 0-5) and instrumental activities of daily living (range 0-7) scores. Medicare data, including healthcare utilization (e.g., emergency department visits, hospitalizations) and diagnosis codes, were incorporated in a base + Medicare model. A base + function + Medicare model included all data elements. We assessed model performance with the c-statistic, reclassification metrics, fraction of new information provided, and calibration plots.ResultsIn the overall cohort, mean age was 82.6 years and 98.6% were male. At the end of follow-up, 30,263 participants (48.8%) had died. The base model c-statistic was 0.809 (95% CI 0.805-0.812) in the development cohort and 0.804 (95% CI 0.796-0.812) in the validation cohort. Validation cohort c-statistics for the base + function, base + Medicare, and base + function + Medicare models were 0.809 (95% CI 0.801-0.816), 0.811 (95% CI 0.803-0.818), and 0.814 (95% CI 0.807-0.822), respectively. Adding functional status and Medicare data resulted in similarly small improvements among other model performance measures. All models showed excellent calibration.ConclusionsIncorporation of functional status and Medicare data into a VA EHR-based mortality index led to small but likely clinically insignificant improvements in model performance

Cell biology of Candida albicans-host interactions

Acknowledgements The authors are supported by the Wellcome Trust via a Senior Investigator Award to NG, an ISST award and a Wellcome Trust Strategic Award in Medical Mycology and Fungal Immunology. The authors are also part of the MRC Centre for Medical Mycology at Aberdeen.Peer reviewedPublisher PD

Endoscopic Ultrasound-Guided Celiac Plexus Neurolysis in Pancreatic Cancer: A Prospective Pilot Study of Safety Using 10 mL versus 20 mL Alcohol

Background. The dose of alcohol used in EUS-CPN is not standardized. The objective was to compare the safety of 20 mL alcohol versus 10 mL alcohol during EUS-CPN for patients with pancreatic cancer-related pain. Methods. 20 patients were selected to receive 10 mL or 20 mL of alcohol during EUS-CPN. Followup was done at baseline, 24 hours, and weekly. Health-related quality of life (HRQoL) was assessed at baseline, week 2, week 4, and every 4 weeks thereafter until pain returned. Results. There were no major complications in both groups. Minor self-limited adverse effects were seen in 6 (30%) subjects and included lightheadedness in 1 (5%), transient diarrhea in 2 (10%), and transient nausea and vomiting in 3. Pain relief was similar in both groups: 80% in the 10 mL group and 100% in the 20 mL group (P = 0.21). The mean (± SD) duration of pain relief in the 10 mL and 20 mL groups was 7.9 ± 10.8 and 8.4 ± 9.2 weeks, respectively. 30% of patients in each group had complete pain relief. Conclusions. EUS-CPN using 20 mL of alcohol is safe. Similar clinical outcomes were seen in both groups. Further investigations to confirm these findings are warranted

Addressing Systemic Factors Related to Racial and Ethnic Disparities among Older Adults in Long-Term Care Facilities

Disparities in older adults’ care and experiences in long-term care facilities (LTCFs) such as nursing homes and assisted living/residential care communities reflect disparities in the broader society. Various policies and institutional practices related to economic opportunity, education, housing, health care, and retirement financing have created and maintain inequitable social structures in the United States. This chapter describes racial and ethnic disparities among older adults in LTCFs in the United States and the systemic factors associated with those disparities. It presents a conceptual framework for understanding the role of structural racism in the racial and ethnic inequities experienced by LTCF residents. In the framework, structural racism directly contributes to racial and ethnic inequities among LTCF residents through LTCF-related policies and practices. Structural racism also indirectly causes disparities among LTCF residents through health and economic disparities. The chapter describes current efforts that address the effects of structural racism within LTCFs and concludes with practice and policy recommendations to redress racial and ethnic disparities among LTCF residents

Journey with Ting-Peng Liang in Pacific Asia Information Systems Field

Our respectful old friend Professor Ting-Peng Liang (in short, TP) whom we loved suddenly passed away on May 20, 2021. But we cannot forget his smile and passion, and his inerasable footprints in PACIS, PAJAIS, and AIS Community. He was the founder of PACIS, founding editor-in-chief of PAJAIS, and past president of AIS to list just a few. He was the pioneer who received the first AIS Fellow and the first LEO Award from Asia Pacific. That is why the leaders of the information systems field organized the first ever special tribute session in PACIS 2021 in memory of TP (https://aisel.aisnet.org/pacis2021/253/

Risk Alleles for Systemic Lupus Erythematosus in a Large Case-Control Collection and Associations with Clinical Subphenotypes

Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. Recent studies have greatly expanded the number of established SLE risk alleles, but the distribution of multiple risk alleles in cases versus controls and their relationship to subphenotypes have not been studied. We studied 22 SLE susceptibility polymorphisms with previous genome-wide evidence of association (p<5×10−8) in 1919 SLE cases from 9 independent Caucasian SLE case series and 4813 independent controls. The mean number of risk alleles in cases was 15.1 (SD 3.1) while the mean in controls was 13.1 (SD 2.8), with trend p = 4×10−128. We defined a genetic risk score (GRS) for SLE as the number of risk alleles with each weighted by the SLE risk odds ratio (OR). The OR for high-low GRS tertiles, adjusted for intra-European ancestry, sex, and parent study, was 4.4 (95% CI 3.8–5.1). We studied associations of individual SNPs and the GRS with clinical manifestations for the cases: age at diagnosis, the 11 American College of Rheumatology classification criteria, and double-stranded DNA antibody (anti-dsDNA) production. Six subphenotypes were significantly associated with the GRS, most notably anti-dsDNA (ORhigh-low = 2.36, p = 9e−9), the immunologic criterion (ORhigh-low = 2.23, p = 3e−7), and age at diagnosis (ORhigh-low = 1.45, p = 0.0060). Finally, we developed a subphenotype-specific GRS (sub-GRS) for each phenotype with more power to detect cumulative genetic associations. The sub-GRS was more strongly associated than any single SNP effect for 5 subphenotypes (the above plus hematologic disorder and oral ulcers), while single loci are more significantly associated with renal disease (HLA-DRB1, OR = 1.37, 95% CI 1.14–1.64) and arthritis (ITGAM, OR = 0.72, 95% CI 0.59–0.88). We did not observe significant associations for other subphenotypes, for individual loci or the sub-GRS. Thus our analysis categorizes SLE subphenotypes into three groups: those having cumulative, single, and no known genetic association with respect to the currently established SLE risk loci

Epidemiology and survival of the five stages of chronic kidney disease in a systolic heart failure population

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/102653/1/ejhfhfq077.pd

Expert consensus and recommendations on safety criteria for active mobilization of mechanically ventilated critically ill adults

Introduction: The aim of this study was to develop consensus recommendations on safety parameters for mobilizing adult, mechanically ventilated, intensive care unit (ICU) patients. Methods: A systematic literature review was followed by a meeting of 23 multidisciplinary ICU experts to seek consensus regarding the safe mobilization of mechanically ventilated patients. Results: Safety considerations were summarized in four categories: respiratory, cardiovascular, neurological and other. Consensus was achieved on all criteria for safe mobilization, with the exception being levels of vasoactive agents. Intubation via an endotracheal tube was not a contraindication to early mobilization and a fraction of inspired oxygen less than 0.6 with a percutaneous oxygen saturation more than 90% and a respiratory rate less than 30 breaths/minute were considered safe criteria for in- and out-of-bed mobilization if there were no other contraindications. At an international meeting, 94 multidisciplinary ICU clinicians concurred with the proposed recommendations. Conclusion: Consensus recommendations regarding safety criteria for mobilization of adult, mechanically ventilated patients in the ICU have the potential to guide ICU rehabilitation whilst minimizing the risk of adverse events