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7 citation(s) found for "Russell, Steven".

Early Stages of Automated Insulin Delivery
Zisser, Howard , Hovorka, Roman , Basu, Ananda , Battelino, Tadej , Boughton, Charlotte K. , Breton, Marc D. , Buckingham, Bruce A. , Brown, Sue A. , Cherñavvsky, Daniel R. , Dassau, Eyal , Ekhlaspour, Laya , Forlenza, Gregory P. , Haidar, Ahmad , Klonoff, David C. , Kovatchev, Boris , Kowalski, Aaron J. , Kudva, Yogish C., Maahs, David M. , Phillip, Moshe , Russell, Steven J. , Steil, Garry M. , Weinzimer, Stuart A. , Doyle, Francis J , Ekhlaspour, Laya , Fabris, Chiara , Forlenza, Gregory P , Klonoff, David C , Kovatchev, Boris , Levy, Carol J , Maahs, David M , Phillip, Moshe , Renard, Eric , Russell, Steven J , Shah, Viral N , Wadwa, R Paul , Battelino, Tadej , Hovorka, Roman , Buckingham, Bruce , DeBoer, Mark Daniel , Doyle, Francis J. , Levy, Carol J. , Kudva, Yogish C. , Shah, Viral N.

Diabetes Technology & Therapeutics | July 1, 2025 | Volume: 27 | Issue: 3_suppl | Pages: No page available

10.1089/dia.2025.18802.hz | PMID 40590745 Get It

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.
Early Stages of Automated Insulin Delivery
Zisser, Howard , Hovorka, Roman , Basu, Ananda , Battelino, Tadej , Boughton, Charlotte K. , Breton, Marc D. , Buckingham, Bruce A. , Brown, Sue A. , Cherñavvsky, Daniel R. , Dassau, Eyal , Ekhlaspour, Laya , Forlenza, Gregory P. , Haidar, Ahmad , Klonoff, David C. , Kovatchev, Boris , Kowalski, Aaron J. , Kudva, Yogish C. , Maahs, David M. , Phillip, Moshe , Russell, Steven J. , Steil, Garry M. , Weinzimer, Stuart A. , Doyle, Francis J , Ekhlaspour, Laya , Fabris, Chiara , Forlenza, Gregory P , Klonoff, David C , Kovatchev, Boris , Levy, Carol J , Maahs, David M , Phillip, Moshe , Renard, Eric , Russell, Steven J , Shah, Viral N , Wadwa, R Paul , Battelino, Tadej , Hovorka, Roman , Buckingham, Bruce , DeBoer, Mark Daniel , Doyle, Francis J. , Levy, Carol J. , Shah, Viral N.

Journal of Diabetes Science and Technology | July 1, 2025 | Volume: 19 | Issue: 4 | Pages: 908-923

10.1177/19322968251335685 | PMID 40590463 Get It

The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.
A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings
Klonoff, David C. , Wang, Jing , Rodbard, David , Kohn, Michael A. , Li, Chengdong , Liepmann, Dorian , Kerr, David , Ahn, David , Peters, Anne L. , Umpierrez, Guillermo E. , Xu, Nicole Y. , Nguyen, Kevin T. , Simonson, Gregg D. , Agus, Michael S. D. , Armaiz-Peña, Gustavo , Basu, Ananda , Battelino, Tadej , Yeshiwas, Sewagegn , Bequette, B. Wayne , Blevins, Thomas , Breton, Marc D. , Castle, Jessica R. , Close, Kelly L. , Drincic, Angela, Dungan, Kathleen , Ejskjær, Niels , Espinoza, Juan , Fleming, G. Alexander , Forlenza, Gregory P. , Freckmann, Guido , Galindo, Rodolfo J. , Gómez, Ana María , Gutow, Hanna A. , Hovorka, Roman , Ji, Linong , Joubert, Michaël , Koliwad, Suneil K. , Lal, Rayhan , Lansang, M. Cecilia , Lee, Wei-An , Leelarathna, Lalantha , Lind, Marcus , Mahoney, Katherine , Mankovsky, Boris , Masharani, Umesh , Mathioudakis, Nestoras , Mayorov, Alexander Yur'evich , Messler, Jordan , Mohan, Viswanathan , Nichols, James H. , O’Neal, David N. , Pasquel, Francisco J. , Philis‐Tsimikas, Athena , Phillip, Moshe , Rayman, Gerry , Russell, Steven J. , Spanakis, Elias K. , Waki, Kayo , Wallia, Amisha , Weinberg, Melissa E. , Wolpert, Howard , Zilbermint, Mihail , Kovatchev, Boris , Seley, Jane Jeffrie , Xu, Nicole Y , Nguyen, Kevin T , Simonson, Gregg , Agus, Michael S D , Al-Sofiani, Mohammed E , Armaiz-Pena, Gustavo , Bailey, Timothy S , Basu, Ananda , Battelino, Tadej , Bekele, Sewagegn Yeshiwas , Benhamou, Pierre-Yves , Bequette, B Wayne , Blevins, Thomas , Breton, Marc D , Castle, Jessica R , Chase, James Geoffrey , Chen, Kong , Choudhary, Pratik , Clements, Mark A , Close, Kelly L , Cook, Curtiss B , Doyle, Francis J , Drincic, Angela , Dungan, Kathleen M , Edelman, Steven V , Ejskjaer, Niels , Espinoza, Juan , Fleming, G Alexander , Forlenza, Gregory P , Freckmann, Guido , Galindo, Rodolfo J , Gomez, Ana Maria , Gutow, Hanna A , Heinemann, Lutz , Hirsch, Irl B , Hoang, Thanh D , Hovorka, Roman , Jendle, Johan H , Ji, Linong , Joshi, Shashank R , Joubert, Michael , Koliwad, Suneil K , Lal, Rayhan A , Lansang, M Cecilia , Lee, Wei-An Andy , Leelarathna, Lalantha , Leiter, Lawrence A , Lind, Marcus , Litchman, Michelle L , Mader, Julia K , Mahoney, Katherine M , Mankovsky, Boris , Masharani, Umesh , Mathioudakis, Nestoras N , Mayorov, Alexander , Messler, Jordan , Miller, Joshua D , Mohan, Viswanathan , Nichols, James H , Nørgaard, Kirsten , O'Neal, David N , Pasquel, Francisco J , Philis-Tsimikas, Athena , Pieber, Thomas , Phillip, Moshe , Polonsky, William H , Pop-Busui, Rodica , Rayman, Gerry , Rhee, Eun-Jung , Russell, Steven J , Shah, Viral N , Sherr, Jennifer L , Sode, Koji , Spanakis, Elias K , Wake, Deborah J , Waki, Kayo , Wallia, Amisha , Weinberg, Melissa E , Wolpert, Howard , Wright, Eugene E , Zilbermint, Mihail , Kovatchev, Boris , Kohn, Michael , Umpierrez, Guillermo E. , Peters, Anne L , Ahn, David T , Liepmann, Dorian , Bailey, Timothy S. , Chen, Kong Y. , Choudhary, Pratik , Cook, Curtiss B. , Danne, Thomas , Doyle, Francis J. , Heinemann, Lutz , Hirsch, Irl B. , Leiter, Lawrence A. , Mader, Julia K. , Pop‐Busui, Rodica , Shah, Viral N. , Sode, Koji , Wright, Eugene E.

Journal of Diabetes Science and Technology | March 29, 2022 | Volume: 17 | Issue: 5 | Pages: 1226-1242

10.1177/19322968221085273 | PMID 35348391 Get It

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low–glucose and low-glucose hypoglycemia; very high–glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.
Lenalidomide Has Activity in a Phase II Trial in Patients with Primary Systemic Amyloidosis.
Lacy, Martha Q. , Zeldenrust, Steven R., Geyer, Susan M. , Lust, John A., Hayman, Suzanne R. , Kumar, Shaji , Allred, Jacob B., Kabat, Brian, Greipp, Philip R., Dispenzieri, Angela , Rajkumar, S. Vincent , Witzig, Thomas E. , Russell, Steven R., Ghobrial, Irene M. , Gertz, Morie A.

Blood | April 19, 2020 | Volume: 106 | Issue: 11 | Pages: 252-252

10.1182/blood.v106.11.252.252 Get It

Abstract Background: Primary systemic amyloidosis (AL) is an incurable plasma cell disorder. For selected patients high dose chemotherapy with peripheral blood stem cell support is effective, but even in those patients, only 50% derive organ responses. Other patients are too sick to undergo that therapy. Thalidomide has limited utility in this disease, largely because of its toxicity profile in patients with AL. Lenalidomide, Celgene’s lead clinical compound in a new group of drugs called IMiDs®, is highly active in patients with multiple myeloma, especially in conjunction with dexamethasone. We sought to determine the toxicity and efficacy of lenalidomide in patients with AL. Methods: Patients with symptomatic AL who had a measurable plasma cell disorder (defined as serum M-spike ≥ g/dL urine M-spike >200 mg/24 hours; or involved immunoglobulin free light chain (FLC) ≥10 mg/dL and an abnormal FLC ratio) and adequate organ reserve defined as a creatinine ≤3 mg/dL, absolute neutrophil count ≥1000, platelet count ≥75000, and a hemoglobin ≥8 g/dL were eligible. Patients were started on lenalidomide 25 mg/day for 21 days followed by a 7 day rest (1 cycle). Dose modifications were made based on toxicity. If there was evidence of progression before 3 months or no evidence of hematologic response after 3 cycles, dexamethasone 40 mg p.o. days 1–4 and 15–18 was added. Results: Twenty-three patients were enrolled between 10/28/04 and 4/7/05; 14 were previously treated. Patient characteristics are shown in Table. Organ involvement was as follows: cardiac (61%); renal (70%), hepatic (22%); nerve (13%). Nine patients withdrew from study before completing 3 months of therapy. The reasons were: cancel (1); death (4); adverse events (2); and progression (2). At the time of our preliminary analysis in July 2005, an additional 3 patients have withdrawn from study: death (1) and patient refusal (2). Of the 5 patients who died, 4 had severe cardiac involvement and at least 3 organs involved by amyloid. The median follow-up for the eleven patients remaining on study is 6.2 months. Of the 12 patients who have crossed the 3 month treatment landmark, there are 7 hematologic partial responses (4 confirmed and 3 unconfirmed), two renal responses and one liver response. Of these same 12 patients, all but one has had dexamethasone added to their treatment program. The most common grade 3–4 adverse advents at least possibly attributable to lenalidomide were neutropenia (43%), thrombocytopenia (26%), rash (17%), dyspnea (9%), fatigue (9%), and edema (4%). Expansion of the trial is planned to accrue an additional 10 evaluable patients. Conclusions: Early results suggest that lenalidomide ± dexamethasone has activity in patients with primary systemic amyloidosis. Supported in part by the Caliguiri Fund for Amyloidosis Research, Robert A. Kyle Hematologic Malignancies Program, and Celgene. Patient Characteristics Median Range Age 64 44–88 Major Organs 2 0–3 Involved FLC, mg/dl 23 4.1–278 Serum alb, g/dl 2.8 1.2–3.7 Urine protein, g/24 hrs 3.7 0.02–14.3 Creatinine, mg/dl 1.3 0.7–2.6 Alkaline phos IU/l (nml <115) 99 57–1729 NY Heart Class 1 1–3 Troponin T, mcg/l 0.03 0.01–0.55 NT-proBNP, ng/l 1419 109–42844 LV Septum, mm 13 9–24 LV EF, % 63 22–72