The Perceptions of Second-Year, First-Generation Minority Students Regarding the Influence of AVID Mentoring on Students’ Retention

Despite the increase in diversity, institutions continue to struggle to provide, retain, and graduate students of color to the same degree as their counterparts (Banks & Dohy, 2019). The purpose of this narrative qualitative research study was to examine the perceptions of second-year, first- generation minority college students regarding the influence of the Advancement Via Individual Determination (AVID) program on their persistence and academic achievement. The study was framed by Swail’s (2004) geometric model of student persistence and achievement, aimed to identify the cognitive, social, and institutional factors contributing to student retention. The following questions guided the study: (1) What are the perceptions of first-generation minority college students regarding the cognitive factors associated with AVID mentoring programs?; (2) What are the perceptions of first-generation minority college students regarding the social factors associated with AVID mentoring programs?; and (3) What are the perceptions of first-generation minority college students regarding the institutional factors associated with AVID mentoring programs? The researcher conducted interviews to reveal the perceptions of six students who participated in AVID programs in high school. The major themes that emerged were the importance of AVID and teacher support, academic rigor and learning, social support, expectations and goal commitment, and challenges transitioning to the postsecondary institution. The study demonstrated that these factors significantly contribute to student persistence and retention. The results provide educational leaders with evidence to support adjustments to their practices and initiatives essential to student retention

Issues With Variability in Electronic Health Record Data About Race and Ethnicity: Descriptive Analysis of the National COVID Cohort Collaborative Data Enclave

Background:The adverse impact of COVID-19 on marginalized and under-resourced communities of color has highlighted the need for accurate, comprehensive race and ethnicity data. However, a significant technical challenge related to integrating race and ethnicity data in large, consolidated databases is the lack of consistency in how data about race and ethnicity are collected and structured by health care organizations. Objective:This study aims to evaluate and describe variations in how health care systems collect and report information about the race and ethnicity of their patients and to assess how well these data are integrated when aggregated into a large clinical database. Methods:At the time of our analysis, the National COVID Cohort Collaborative (N3C) Data Enclave contained records from 6.5 million patients contributed by 56 health care institutions. We quantified the variability in the harmonized race and ethnicity data in the N3C Data Enclave by analyzing the conformance to health care standards for such data. We conducted a descriptive analysis by comparing the harmonized data available for research purposes in the database to the original source data contributed by health care institutions. To make the comparison, we tabulated the original source codes, enumerating how many patients had been reported with each encoded value and how many distinct ways each category was reported. The nonconforming data were also cross tabulated by 3 factors: patient ethnicity, the number of data partners using each code, and which data models utilized those particular encodings. For the nonconforming data, we used an inductive approach to sort the source encodings into categories. For example, values such as “Declined” were grouped with “Refused,” and “Multiple Race” was grouped with “Two or more races” and “Multiracial.” Results:“No matching concept” was the second largest harmonized concept used by the N3C to describe the race of patients in their database. In addition, 20.7% of the race data did not conform to the standard; the largest category was data that were missing. Hispanic or Latino patients were overrepresented in the nonconforming racial data, and data from American Indian or Alaska Native patients were obscured. Although only a small proportion of the source data had not been mapped to the correct concepts (0.6%), Black or African American and Hispanic/Latino patients were overrepresented in this category. Conclusions:Differences in how race and ethnicity data are conceptualized and encoded by health care institutions can affect the quality of the data in aggregated clinical databases. The impact of data quality issues in the N3C Data Enclave was not equal across all races and ethnicities, which has the potential to introduce bias in analyses and conclusions drawn from these data. Transparency about how data have been transformed can help users make accurate analyses and inferences and eventually better guide clinical care and public policy

Issues with variability in electronic health record data about race and ethnicity: Descriptive analysis of the National COVID Cohort Collaborative Data Enclave

BACKGROUND: The adverse impact of COVID-19 on marginalized and under-resourced communities of color has highlighted the need for accurate, comprehensive race and ethnicity data. However, a significant technical challenge related to integrating race and ethnicity data in large, consolidated databases is the lack of consistency in how data about race and ethnicity are collected and structured by health care organizations. OBJECTIVE: This study aims to evaluate and describe variations in how health care systems collect and report information about the race and ethnicity of their patients and to assess how well these data are integrated when aggregated into a large clinical database. METHODS: At the time of our analysis, the National COVID Cohort Collaborative (N3C) Data Enclave contained records from 6.5 million patients contributed by 56 health care institutions. We quantified the variability in the harmonized race and ethnicity data in the N3C Data Enclave by analyzing the conformance to health care standards for such data. We conducted a descriptive analysis by comparing the harmonized data available for research purposes in the database to the original source data contributed by health care institutions. To make the comparison, we tabulated the original source codes, enumerating how many patients had been reported with each encoded value and how many distinct ways each category was reported. The nonconforming data were also cross tabulated by 3 factors: patient ethnicity, the number of data partners using each code, and which data models utilized those particular encodings. For the nonconforming data, we used an inductive approach to sort the source encodings into categories. For example, values such as Declined were grouped with Refused, and Multiple Race was grouped with Two or more races and Multiracial. RESULTS: No matching concept was the second largest harmonized concept used by the N3C to describe the race of patients in their database. In addition, 20.7% of the race data did not conform to the standard; the largest category was data that were missing. Hispanic or Latino patients were overrepresented in the nonconforming racial data, and data from American Indian or Alaska Native patients were obscured. Although only a small proportion of the source data had not been mapped to the correct concepts (0.6%), Black or African American and Hispanic/Latino patients were overrepresented in this category. CONCLUSIONS: Differences in how race and ethnicity data are conceptualized and encoded by health care institutions can affect the quality of the data in aggregated clinical databases. The impact of data quality issues in the N3C Data Enclave was not equal across all races and ethnicities, which has the potential to introduce bias in analyses and conclusions drawn from these data. Transparency about how data have been transformed can help users make accurate analyses and inferences and eventually better guide clinical care and public policy

Patterns of Renal Dysfunction and Profile of Kidney Biopsies in Hematopoietic Stem Cell Transplant Recipients

Introduction: Post hematopoietic stem cell transplant (HSCT), kidney can be subjected to injury by various causes. Of these, graft versus host disease (GvHD) affecting the kidney is an under-recognized entity with no clear guidelines on its diagnosis, clinicopathological manifestations, and outcomes. Material and Methods: Out of 2,930 patients who underwent HSCT at our center between 2005 and 2020, kidney biopsy was performed in 19 allogenic and 5 autologous recipients. Results: The mean age of the cohort at transplant was 33.2 ± 7 years, and 15 (62%) were males. Median time to kidney biopsy from HSCT was 14 (IQR, 9–30) months. Aplastic anemia was the most common underlying hematological disease (54.2%). All 19 allogenic recipients were classified based on clinicopathological manifestations into either thrombotic microangiopathy (TMA, 12/19 [63%]) or nephrotic syndrome (NS, 7/19 [37%]) pattern. Glomerular tuft “mesangiolysis” was the dominant pattern of injury noted in 9/12 cases of TMA pattern. There was a predominance of acute microangiopathic changes restricted primarily to the glomerular compartment. Of the 7 patients with NS pattern, membranous nephropathy was seen in 4 (57%) and minimal change disease in 3 (43%) patients. Thirty-nine percent (7/18) stained positive for C4d which was predominantly glomerular. Allogenic recipients who did not receive immunosuppression (IS) for renal disease had a lower eGFR at biopsy, a longer latency between withdrawal of GvHD prophylaxis and biopsy, and were significantly at a higher risk of kidney failure (IS: 2/11, 18.1% vs. no IS: 2/6, 33.3%, p = 0.04). “Associated extra-renal GvHD” occurred in 11/19 (57.9%) allogenic recipients. Patients with “associated extra-renal GvHD” had significantly more deaths (6/11, 60% vs. 0, p = 0.02) but comparable renal outcomes. Conclusion: Renal GvHD can present with or without “associated extra-renal GvHD” after a prolonged period of withdrawal of GvHD prophylaxis, requiring careful diagnostic vigilance and consideration of IS

Thigh-length compression stockings and DVT after stroke

Controversy exists as to whether neoadjuvant chemotherapy improves survival in patients with invasive bladder cancer, despite randomised controlled trials of more than 3000 patients. We undertook a systematic review and meta-analysis to assess the effect of such treatment on survival in patients with this disease