Browsing by Author "Parikh, Chirag R."

Now showing 1 - 7 of 7
  • Thumbnail Image
    Item
    AKI Treated with Renal Replacement Therapy in Critically Ill Patients with COVID-19
    (Wolters Kluwer, 2021) Gupta, Shruti; Coca, Steven G.; Chan, Lili; Melamed, Michal L.; Brenner, Samantha K.; Hayek, Salim S.; Sutherland, Anne; Puri, Sonika; Srivastava, Anand; Leonberg-Yoo, Amanda; Shehata, Alexandre M.; Flythe, Jennifer E.; Rashidi, Arash; Schenck, Edward J.; Goyal, Nitender; Hedayati, S. Susan; Dy, Rajany; Bansal, Anip; Athavale, Ambarish; Nguyen, H. Bryant; Vijayan, Anitha; Charytan, David M.; Schulze, Carl E.; Joo, Min J.; Friedman, Allon N.; Zhang, Jingjing; Sosa, Marie Anne; Judd, Eric; Velez, Juan Carlos Q.; Mallappallil, Mary; Redfern, Roberta E.; Bansal, Amar D.; Neyra, Javier A.; Liu, Kathleen D.; Renaghan, Amanda D.; Christov, Marta; Molnar, Miklos Z.; Sharma, Shreyak; Kamal, Omer; Boateng, Jeffery Owusu; Short, Samuel A.P.; Admon, Andrew J.; Sise, Meghan E.; Wang, Wei; Parikh, Chirag R.; Leaf, David E.; STOP-COVID Investigators; Medicine, School of Medicine
    Background: AKI is a common sequela of coronavirus disease 2019 (COVID-19). However, few studies have focused on AKI treated with RRT (AKI-RRT). Methods: We conducted a multicenter cohort study of 3099 critically ill adults with COVID-19 admitted to intensive care units (ICUs) at 67 hospitals across the United States. We used multivariable logistic regression to identify patient-and hospital-level risk factors for AKI-RRT and to examine risk factors for 28-day mortality among such patients. Results: A total of 637 of 3099 patients (20.6%) developed AKI-RRT within 14 days of ICU admission, 350 of whom (54.9%) died within 28 days of ICU admission. Patient-level risk factors for AKI-RRT included CKD, men, non-White race, hypertension, diabetes mellitus, higher body mass index, higher d-dimer, and greater severity of hypoxemia on ICU admission. Predictors of 28-day mortality in patients with AKI-RRT were older age, severe oliguria, and admission to a hospital with fewer ICU beds or one with greater regional density of COVID-19. At the end of a median follow-up of 17 days (range, 1-123 days), 403 of the 637 patients (63.3%) with AKI-RRT had died, 216 (33.9%) were discharged, and 18 (2.8%) remained hospitalized. Of the 216 patients discharged, 73 (33.8%) remained RRT dependent at discharge, and 39 (18.1%) remained RRT dependent 60 days after ICU admission. Conclusions: AKI-RRT is common among critically ill patients with COVID-19 and is associated with a hospital mortality rate of >60%. Among those who survive to discharge, one in three still depends on RRT at discharge, and one in six remains RRT dependent 60 days after ICU admission.
  • Thumbnail Image
    Item
    An atlas of healthy and injured cell states and niches in the human kidney
    (Springer Nature, 2023) Lake, Blue B.; Menon, Rajasree; Winfree, Seth; Hu, Qiwen; Ferreira, Ricardo Melo; Kalhor, Kian; Barwinska, Daria; Otto, Edgar A.; Ferkowicz, Michael; Diep, Dinh; Plongthongkum, Nongluk; Knoten, Amanda; Urata, Sarah; Mariani, Laura H.; Naik, Abhijit S.; Eddy, Sean; Zhang, Bo; Wu, Yan; Salamon, Diane; Williams, James C.; Wang, Xin; Balderrama, Karol S.; Hoover, Paul J.; Murray, Evan; Marshall, Jamie L.; Noel, Teia; Vijayan, Anitha; Hartman, Austin; Chen, Fei; Waikar, Sushrut S.; Rosas, Sylvia E.; Wilson, Francis P.; Palevsky, Paul M.; Kiryluk, Krzysztof; Sedor, John R.; Toto, Robert D.; Parikh, Chirag R.; Kim, Eric H.; Satija, Rahul; Greka, Anna; Macosko, Evan Z.; Kharchenko, Peter V.; Gaut, Joseph P.; Hodgin, Jeffrey B.; KPMP Consortium; Eadon, Michael T.; Dagher, Pierre C.; El-Achkar, Tarek M.; Zhang, Kun; Kretzler, Matthias; Jain, Sanjay; Medicine, School of Medicine
    Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.
  • Thumbnail Image
    Item
    Association Between Early Treatment With Tocilizumab and Mortality Among Critically Ill Patients With COVID-19
    (American Medical Association, 2020-10-20) Gupta, Shruti; Wang, Wei; Hayek, Salim S.; Chan, Lili; Mathews, Kusum S.; Melamed, Michal L.; Brenner, Samantha K.; Leonberg-Yoo, Amanda; Schenck, Edward J.; Radbel, Jared; Reiser, Jochen; Bansal, Anip; Srivastava, Anand; Zhou, Yan; Finkel, Diana; Green, Adam; Mallappallil, Mary; Faugno, Anthony J.; Zhang, Jingjing; Velez, Juan Carlos Q.; Shaefi, Shahzad; Parikh, Chirag R.; Charytan, David M.; Athavale, Ambarish M.; Friedman, Allon N.; Redfern, Roberta E.; Short, Samuel A. P.; Correa, Simon; Pokharel, Kapil K.; Admon, Andrew J.; Donnelly, John P.; Gershengorn, Hayley B.; Douin, David J.; Semler, Matthew W.; Hernán, Miguel A.; Leaf, David E.; STOP-COVID Investigators; Medicine, School of Medicine
    Importance: Therapies that improve survival in critically ill patients with coronavirus disease 2019 (COVID-19) are needed. Tocilizumab, a monoclonal antibody against the interleukin 6 receptor, may counteract the inflammatory cytokine release syndrome in patients with severe COVID-19 illness. Objective: To test whether tocilizumab decreases mortality in this population. Design, Setting, and Participants: The data for this study were derived from a multicenter cohort study of 4485 adults with COVID-19 admitted to participating intensive care units (ICUs) at 68 hospitals across the US from March 4 to May 10, 2020. Critically ill adults with COVID-19 were categorized according to whether they received or did not receive tocilizumab in the first 2 days of admission to the ICU. Data were collected retrospectively until June 12, 2020. A Cox regression model with inverse probability weighting was used to adjust for confounding. Exposures: Treatment with tocilizumab in the first 2 days of ICU admission. Main Outcomes and Measures: Time to death, compared via hazard ratios (HRs), and 30-day mortality, compared via risk differences. Results: Among the 3924 patients included in the analysis (2464 male [62.8%]; median age, 62 [interquartile range {IQR}, 52-71] years), 433 (11.0%) received tocilizumab in the first 2 days of ICU admission. Patients treated with tocilizumab were younger (median age, 58 [IQR, 48-65] vs 63 [IQR, 52-72] years) and had a higher prevalence of hypoxemia on ICU admission (205 of 433 [47.3%] vs 1322 of 3491 [37.9%] with mechanical ventilation and a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen of <200 mm Hg) than patients not treated with tocilizumab. After applying inverse probability weighting, baseline and severity-of-illness characteristics were well balanced between groups. A total of 1544 patients (39.3%) died, including 125 (28.9%) treated with tocilizumab and 1419 (40.6%) not treated with tocilizumab. In the primary analysis, during a median follow-up of 27 (IQR, 14-37) days, patients treated with tocilizumab had a lower risk of death compared with those not treated with tocilizumab (HR, 0.71; 95% CI, 0.56-0.92). The estimated 30-day mortality was 27.5% (95% CI, 21.2%-33.8%) in the tocilizumab-treated patients and 37.1% (95% CI, 35.5%-38.7%) in the non-tocilizumab–treated patients (risk difference, 9.6%; 95% CI, 3.1%-16.0%). Conclusions and Relevance: Among critically ill patients with COVID-19 in this cohort study, the risk of in-hospital mortality in this study was lower in patients treated with tocilizumab in the first 2 days of ICU admission compared with patients whose treatment did not include early use of tocilizumab. However, the findings may be susceptible to unmeasured confounding, and further research from randomized clinical trials is needed.
  • Thumbnail Image
    Item
    Development and external validation of a diagnostic model for biopsy-proven acute interstitial nephritis using electronic health record data
    (Oxford University Press, 2022) Moledina, Dennis G.; Eadon, Michael T.; Calderon, Frida; Yamamoto, Yu; Shaw, Melissa; Perazella, Mark A.; Simonov, Michael; Luciano, Randy; Schwantes-An, Tae-Hwi; Moeckel, Gilbert; Kashgarian, Michael; Kuperman, Michael; Obeid, Wassim; Cantley, Lloyd G.; Parikh, Chirag R.; Wilson, F. Perry; Medicine, School of Medicine
    Background: Patients with acute interstitial nephritis (AIN) can present without typical clinical features, leading to a delay in diagnosis and treatment. We therefore developed and validated a diagnostic model to identify patients at risk of AIN using variables from the electronic health record. Methods: In patients who underwent a kidney biopsy at Yale University between 2013 and 2018, we tested the association of >150 variables with AIN, including demographics, comorbidities, vital signs and laboratory tests (training set 70%). We used least absolute shrinkage and selection operator methodology to select prebiopsy features associated with AIN. We performed area under the receiver operating characteristics curve (AUC) analysis with internal (held-out test set 30%) and external validation (Biopsy Biobank Cohort of Indiana). We tested the change in model performance after the addition of urine biomarkers in the Yale AIN study. Results: We included 393 patients (AIN 22%) in the training set, 158 patients (AIN 27%) in the test set, 1118 patients (AIN 11%) in the validation set and 265 patients (AIN 11%) in the Yale AIN study. Variables in the selected model included serum creatinine {adjusted odds ratio [aOR] 2.31 [95% confidence interval (CI) 1.42-3.76]}, blood urea nitrogen:creatinine ratio [aOR 0.40 (95% CI 0.20-0.78)] and urine dipstick specific gravity [aOR 0.95 (95% CI 0.91-0.99)] and protein [aOR 0.39 (95% CI 0.23-0.68)]. This model showed an AUC of 0.73 (95% CI 0.64-0.81) in the test set, which was similar to the AUC in the external validation cohort [0.74 (95% CI 0.69-0.79)]. The AUC improved to 0.84 (95% CI 0.76-0.91) upon the addition of urine interleukin-9 and tumor necrosis factor-α. Conclusions: We developed and validated a statistical model that showed a modest AUC for AIN diagnosis, which improved upon the addition of urine biomarkers. Future studies could evaluate this model and biomarkers to identify unrecognized cases of AIN.
  • Thumbnail Image
    Item
    Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US
    (American Medical Association, 2020-07-15) Gupta, Shruti; Hayek, Salim S.; Wang, Wei; Chan, Lili; Mathews, Kusum S.; Melamed, Michal L.; Brenner, Samantha K.; Leonberg-Yoo, Amanda; Schenck, Edward J.; Radbel, Jared; Reiser, Jochen; Bansal, Anip; Srivastava, Anand; Zhou, Yan; Sutherland, Anne; Green, Adam; Shehata, Alexandre M.; Goyal, Nitender; Vijayan, Anitha; Velez, Juan Carlos Q.; Shaefi, Shahzad; Parikh, Chirag R.; Arunthamakun, Justin; Athavale, Ambarish M.; Friedman, Allon N.; Short, Samuel A. P.; Kibbelaar, Zoe A.; Omar, Samah Abu; Admon, Andrew J.; Donnelly, John P.; Gershengorn, Hayley B.; Hernán, Miguel A.; Semler, Matthew W.; Leaf, David E.; Medicine, School of Medicine
    Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, Setting, and Participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main Outcomes and Measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2 vs 0: OR, 2.61; 95% CI, 1.30–5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46–4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and Relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.
  • Thumbnail Image
    Item
    Factors Associated With Death in Critically Ill Patients With Coronavirus Disease 2019 in the US
    (American Medical Association, 2020-11) Gupta, Shruti; Hayek, Salim S.; Wang, Wei; Chan, Lili; Mathews, Kusum S.; Melamed, Michal L.; Brenner, Samantha K.; Leonberg-Yoo, Amanda; Schenck, Edward J.; Radbel, Jared; Reiser, Jochen; Bansal, Anip; Srivastava, Anand; Zhou, Yan; Sutherland, Anne; Green, Adam; Shehata, Alexandre M.; Goyal, Nitender; Vijayan, Anitha; Velez, Juan Carlos Q.; Shaefi, Shahzad; Parikh, Chirag R.; Arunthamakun, Justin; Athavale, Ambarish M.; Friedman, Allon N.; Short, Samuel A.P.; Kibbelaar, Zoe A.; Omar, Samah Abu; Admon, Andrew J.; Donnelly, John P.; Gershengorn, Hayley B.; Hernán, Miguel A.; Semler, Matthew W.; Leaf, David E.; Medicine, School of Medicine
    Importance: The US is currently an epicenter of the coronavirus disease 2019 (COVID-19) pandemic, yet few national data are available on patient characteristics, treatment, and outcomes of critical illness from COVID-19. Objectives: To assess factors associated with death and to examine interhospital variation in treatment and outcomes for patients with COVID-19. Design, setting, and participants: This multicenter cohort study assessed 2215 adults with laboratory-confirmed COVID-19 who were admitted to intensive care units (ICUs) at 65 hospitals across the US from March 4 to April 4, 2020. Exposures: Patient-level data, including demographics, comorbidities, and organ dysfunction, and hospital characteristics, including number of ICU beds. Main outcomes and measures: The primary outcome was 28-day in-hospital mortality. Multilevel logistic regression was used to evaluate factors associated with death and to examine interhospital variation in treatment and outcomes. Results: A total of 2215 patients (mean [SD] age, 60.5 [14.5] years; 1436 [64.8%] male; 1738 [78.5%] with at least 1 chronic comorbidity) were included in the study. At 28 days after ICU admission, 784 patients (35.4%) had died, 824 (37.2%) were discharged, and 607 (27.4%) remained hospitalized. At the end of study follow-up (median, 16 days; interquartile range, 8-28 days), 875 patients (39.5%) had died, 1203 (54.3%) were discharged, and 137 (6.2%) remained hospitalized. Factors independently associated with death included older age (≥80 vs <40 years of age: odds ratio [OR], 11.15; 95% CI, 6.19-20.06), male sex (OR, 1.50; 95% CI, 1.19-1.90), higher body mass index (≥40 vs <25: OR, 1.51; 95% CI, 1.01-2.25), coronary artery disease (OR, 1.47; 95% CI, 1.07-2.02), active cancer (OR, 2.15; 95% CI, 1.35-3.43), and the presence of hypoxemia (Pao2:Fio2<100 vs ≥300 mm Hg: OR, 2.94; 95% CI, 2.11-4.08), liver dysfunction (liver Sequential Organ Failure Assessment score of 2-4 vs 0: OR, 2.61; 95% CI, 1.30-5.25), and kidney dysfunction (renal Sequential Organ Failure Assessment score of 4 vs 0: OR, 2.43; 95% CI, 1.46-4.05) at ICU admission. Patients admitted to hospitals with fewer ICU beds had a higher risk of death (<50 vs ≥100 ICU beds: OR, 3.28; 95% CI, 2.16-4.99). Hospitals varied considerably in the risk-adjusted proportion of patients who died (range, 6.6%-80.8%) and in the percentage of patients who received hydroxychloroquine, tocilizumab, and other treatments and supportive therapies. Conclusions and relevance: This study identified demographic, clinical, and hospital-level risk factors that may be associated with death in critically ill patients with COVID-19 and can facilitate the identification of medications and supportive therapies to improve outcomes.
  • Thumbnail Image
    Item
    Uromodulin to Osteopontin Ratio in Deceased Donor Urine Is Associated With Kidney Graft Outcomes
    (Wolters Kluwer, 2021) Mansour, Sherry G.; Liu, Caroline; Jia, Yaqi; Reese, Peter P.; Hall, Isaac E.; El-Achkar, Tarek M.; LaFavers, Kaice A.; Obeid, Wassim; Rosenberg, Avi Z.; Daneshpajouhnejad, Parnaz; Doshi, Mona D.; Akalin, Enver; Bromberg, Jonathan S.; Harhay, Meera N.; Mohan, Sumit; Muthukumar, Thangamani; Schröppel, Bernd; Singh, Pooja; El-Khoury, Joe M.; Weng, Francis L.; Thiessen-Philbrook, Heather R.; Parikh, Chirag R.; Medicine, School of Medicine
    Background: Deceased-donor kidneys experience extensive injury, activating adaptive and maladaptive pathways therefore impacting graft function. We evaluated urinary donor uromodulin (UMOD) and osteopontin (OPN) in recipient graft outcomes. Methods: Primary outcomes: all-cause graft failure (GF) and death-censored GF (dcGF). Secondary outcomes: delayed graft function (DGF) and 6-month estimated glomerular filtration rate (eGFR). We randomly divided our cohort of deceased donors and recipients into training and test datasets. We internally validated associations between donor urine UMOD and OPN at time of procurement, with our primary outcomes. The direction of association between biomarkers and GF contrasted. Subsequently, we evaluated UMOD:OPN ratio with all outcomes. To understand these mechanisms, we examined the effect of UMOD on expression of major histocompatibility complex II in mouse macrophages. Results: Doubling of UMOD increased dcGF risk (adjusted hazard ratio [aHR], 1.1; 95% confidence interval [CI], 1.02-1.2), whereas OPN decreased dcGF risk (aHR, 0.94; 95% CI, 0.88-1). UMOD:OPN ratio ≤3 strengthened the association, with reduced dcGF risk (aHR, 0.57; 0.41-0.80) with similar associations for GF, and in the test dataset. A ratio ≤3 was also associated with lower DGF (aOR, 0.73; 95% CI, 0.60-0.89) and higher 6-month eGFR (adjusted β coefficient, 3.19; 95% CI, 1.28-5.11). UMOD increased major histocompatibility complex II expression elucidating a possible mechanism behind UMOD's association with GF. Conclusions: UMOD:OPN ratio ≤3 was protective, with lower risk of DGF, higher 6-month eGFR, and improved graft survival. This ratio may supplement existing strategies for evaluating kidney quality and allocation decisions regarding deceased-donor kidney transplantation.