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Last Name

profileLeo Anthony Gutierrez Celi, M.D.

TitleAssistant Professor of Medicine, Part-time
InstitutionBeth Israel Deaconess Medical Center
AddressBeth Israel Deaconess Medical Center
Ksb 23
330 Brookline Ave
Boston MA 02215
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Collapse Biography 
Collapse awards and honors
2010Information Technology Award
2010Featured Designer, Smithsonian National Design Triennial
2010mHeath Alliance Award (for Sana)
2010Wireless Innovation Prize, 3rd Place (for Sana)
2011Finalist, INDEX: Award, Design to Improve Life (for Sana)
2012Mobile Health University Challenge, 1st place (for Sana)
2013MIT Sloan Innovation Showcase (for Sana)

Collapse Overview 
Collapse overview
Improving patient care by bridging the divide between doctors and data scientist

While wonderful new medical discoveries and innovations are in the news every day, doctors struggle daily with using information and techniques available right now while carefully adopting new concepts and treatments. As a practicing doctor, I deal with uncertainties and unanswered clinical questions all the time.

I encounter two key limitations in making the best possible decisions for my patients under any circumstances. First, while there are reams of information in books and online, doctors often lack the time to find and digest it all. Instead, we must work with what we carry in our heads, from personal experience and education. Another constraint, perhaps even more important, is that the information available is usually not focused on the specific individual or situation at hand.

For example, there are general guidelines for the ideal blood pressure a patient with a severe infection should have. However, the truly best target blood pressure levels likely differ from patient to patient, and perhaps even changes for an individual patient over the course of treatment.

The ongoing computerization of health records presents an opportunity to overcome these limitations. Analyzing electronic data from many doctors' experiences with many patients, we can move ever closer to answering the age-old question: what is truly best for each patient? In countries with advanced health care systems, we can find optimal care by improving analysis of the data doctors already collect. In poorer and more rural countries, we must first collect that data before being able to analyze it. In both cases, medical professionals and data scientists need to work together to improve health care for everyone.

Toward individual application of mass data

This type of data-driven approach could be very useful. At the moment, a report from the National Academy of Medicine tells us, most doctors base most of their everyday decisions on guidelines from (sometimes biased) expert opinions or small clinical trials. It would be better if they were from multicenter, large, randomized controlled studies, with tightly controlled conditions ensuring the results are as reliable as possible. However, those are expensive and difficult to perform, and even then often exclude a number of important patient groups on the basis of age, disease and sociological factors.

Part of the problem is that health records are traditionally kept on paper, making them hard to analyze en masse. As a result, most of what medical professionals might have learned from experiences was lost – or at least was inaccessible to another doctor meeting with a similar patient.

A digital system would collect and store as much clinical data as possible from as many patients as possible. It could then use information from the past – such as blood pressure, blood sugar levels, heart rate and other measurements of patients' body functions – to guide future doctors to the best diagnosis and treatment of similar patients.

Industrial giants such as Google, IBM, SAP and Hewlett-Packard have also recognized the potential for this kind of approach, and are now working on how to leverage population data for the precise medical care of individuals.

Collaborating on data and medicine

At the Laboratory of Computational Physiology at the Massachusetts Institute of Technology, we have begun to collect large amounts of detailed patient data in the Medical Information Mart in Intensive Care (MIMIC). It is a database containing information from 60,000 patient admissions to the intensive care units of the Beth Israel Deaconess Medical Center, a Boston teaching hospital affiliated with Harvard Medical School. The data in MIMIC has been meticulously scoured so individual patients cannot be recognized, and is freely shared online with the research community.

But the database itself is not enough. We bring together front-line clinicians (such as nurses, pharmacists and doctors) to identify questions they want to investigate, and data scientists to conduct the appropriate analyses of the MIMIC records. This gives caregivers and patients the best individualized treatment options in the absence of a randomized controlled trial.

Bringing data analysis to the world

At the same time we are working to bring these data-enabled systems to assist with medical decisions to countries with limited health care resources, where research is considered an expensive luxury. Often these countries have few or no medical records – even on paper – to analyze. We can help them collect health data digitally, creating the potential to significantly improve medical care for their populations.

This task is the focus of Sana, a collection of technical, medical and community experts from across the globe that is also based in our group at MIT. Sana has designed a digital health information system specifically for use by health providers and patients in rural and underserved areas.

At its core is an open-source system that uses cellphones – common even in poor and rural nations – to collect, transmit and store all sorts of medical data. It can handle not only basic patient data such as height and weight, but also photos and X-rays, ultrasound videos, and electrical signals from a patient’s brain (EEG) and heart (ECG).

Partnering with universities and health organizations, Sana organizes training sessions (which we call “bootcamps”) and collaborative workshops (called “hackathons”) to connect nurses, doctors and community health workers at the front lines of care with technology experts in or near their communities. In 2015, we held bootcamps and hackathons in Colombia, Uganda, Greece and Mexico. The bootcamps teach students in technical fields like computer science and engineering how to design and develop health apps that can run on cellphones. Immediately following the bootcamp, the medical providers join the group and the hackathon begins.

Originally the brainchild of Silicon Valley, a hackathon brings people from different fields together over a short period of time to attack a specific problem or type of problem. At Sana events, attendees focus on a specific health problem, such as how to screen rural populations for heart disease or monitor children with epilepsy, using cellphones.

Teams build prototype apps to address specific problems the doctors and nurses have encountered. Some projects from the hackathon are continued as research or start-up ventures.

Delivering better health care through technology

In Mexico City at the beginning of 2016, Sana held a bootcamp-hackathon focusing on the health needs of older people. Joining the efforts of the engineering department of the local university, Tec de Monterrey, and geriatricians at a local hospital, it produced several promising prototype applications.

One app would help to provide patients with exercises to control urinary incontinence. An “Uber-like” app would connect families with caretakers – relieving them from relying on word of mouth or worse, the phone book. A third “Tinder-like” app would help elderly people find others with similar interests, reducing their social isolation. The collaborations continue to further develop the prototypes and test a few of them in the hospital and clinics.

At the end of the day, though, the purpose is not the apps. By fostering relationships among engineers, health care providers and even patients, the Sana and MIMIC projects are helping to move medicine into a truly functional and beneficial digital age.

Collapse Mentoring 
Collapse completed student projects
Evaluating a Mobile Health Platform for Patient Triage by Community Health Workers in Nairobi, Kenya
International, 06/12/14 - 07/31/14
Predicting Serum Lactate Levels in Sepsis Patients in Critical Care
Summer, 04/23/12 - 08/17/12

Collapse Bibliographic 
Collapse selected publications
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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  1. Lynch KE, Ghassemi F, Flythe JE, Feng M, Ghassemi M, Celi LA, Brunelli SM. Sodium modelling to reduce intradialytic hypotension during haemodialysis for acute kidney injury in the intensive care unit. Nephrology (Carlton). 2016 Oct; 21(10):870-7. PMID: 26590371; PMCID: PMC4875881 [Available on 10/01/17].
  2. Johnson AE, Pollard TJ, Shen L, Lehman LW, Feng M, Ghassemi M, Moody B, Szolovits P, Celi LA, Mark RG. MIMIC-III, a freely accessible critical care database. Sci Data. 2016 May 24; 3:160035. PMID: 27219127; PMCID: PMC4878278.
  3. Danziger J, Chen K, Cavender S, Lee J, Feng M, Mark RG, Mukamal KJ, Celi LA. Admission Peripheral Edema, Central Venous Pressure, and Survival in Critically Ill Patients. Ann Am Thorac Soc. 2016 May; 13(5):705-11. PMID: 26966784.
    View in: PubMed
  4. Aboab J, Celi LA, Charlton P, Feng M, Ghassemi M, Marshall DC, Mayaud L, Naumann T, McCague N, Paik KE, Pollard TJ, Resche-Rigon M, Salciccioli JD, Stone DJ. A "datathon" model to support cross-disciplinary collaboration. Sci Transl Med. 2016 Apr 06; 8(333):333ps8. PMID: 27053770.
    View in: PubMed
  5. Boone MD, Massa J, Mueller A, Jinadasa SP, Lee J, Kothari R, Scott DJ, Callahan J, Celi LA, Hacker MR. The organizational structure of an intensive care unit influences treatment of hypotension among critically ill patients: A retrospective cohort study. J Crit Care. 2016 Jun; 33:14-8. PMID: 26975737; PMCID: PMC4842333 [Available on 06/01/17].
  6. Danziger J, Chen KP, Lee J, Feng M, Mark RG, Celi LA, Mukamal KJ. Obesity, Acute Kidney Injury, and Mortality in Critical Illness. Crit Care Med. 2016 Feb; 44(2):328-34. PMID: 26496453; PMCID: PMC4715729 [Available on 02/01/17].
  7. Chen KP, Cavender S, Lee J, Feng M, Mark RG, Celi LA, Mukamal KJ, Danziger J. Peripheral Edema, Central Venous Pressure, and Risk of AKI in Critical Illness. Clin J Am Soc Nephrol. 2016 Apr 07; 11(4):602-8. PMID: 26787777; PMCID: PMC4822669 [Available on 04/07/17].
  8. Van Poucke S, Zhang Z, Schmitz M, Vukicevic M, Laenen MV, Celi LA, De Deyne C. Scalable Predictive Analysis in Critically Ill Patients Using a Visual Open Data Analysis Platform. PLoS One. 2016; 11(1):e0145791. PMID: 26731286; PMCID: PMC4701479.
  9. Shrime MG, Ferket BS, Scott DJ, Lee J, Barragan-Bradford D, Pollard T, Arabi YM, Al-Dorzi HM, Baron RM, Hunink MG, Celi LA, Lai PS. Time-Limited Trials of Intensive Care for Critically Ill Patients With Cancer: How Long Is Long Enough? JAMA Oncol. 2016 Jan; 2(1):76-83. PMID: 26469222; PMCID: PMC4713248 [Available on 01/01/17].
  10. Naidus E, Celi LA. Big data in healthcare: are we close to it? Rev Bras Ter Intensiva. 2016 Jan-Mar; 28(1):8-10. PMID: 27096670; PMCID: PMC4828085.
  11. Stupple A, Geocadin RG, Celi LA. Conversation prior to resuscitation: The new CPR. Resuscitation. 2016 Feb; 99:e3. PMID: 26740412; PMCID: PMC4955534.
  12. Hsu DJ, Feng M, Kothari R, Zhou H, Chen KP, Celi LA. The Association Between Indwelling Arterial Catheters and Mortality in Hemodynamically Stable Patients With Respiratory Failure: A Propensity Score Analysis. Chest. 2015 Dec; 148(6):1470-6. PMID: 26270005; PMCID: PMC4665738 [Available on 12/01/16].
  13. Celi LA, Marshall JD, Lai Y, Stone DJ. Disrupting Electronic Health Records Systems: The Next Generation. JMIR Med Inform. 2015 Oct 23; 3(4):e34. PMID: 26500106; PMCID: PMC4704959.
  14. Paonessa JR, Brennan T, Pimentel M, Steinhaus D, Feng M, Celi LA. Hyperdynamic left ventricular ejection fraction in the intensive care unit. Crit Care. 2015 Aug 07; 19:288. PMID: 26250903; PMCID: PMC4528812.
  15. Pereira RD, Salgado CM, Dejam A, Reti SR, Vieira SM, Sousa JM, Celi LA, Finkelstein SN. Fuzzy Modeling to Predict Severely Depressed Left Ventricular Ejection Fraction following Admission to the Intensive Care Unit Using Clinical Physiology. ScientificWorldJournal. 2015; 2015:212703. PMID: 26345130; PMCID: PMC4542022.
  16. Byamba K, Syed-Abdul S, García-Romero M, Huang CW, Nergyi S, Nyamdorj A, Nguyen PA, Iqbal U, Paik K, Celi L, Nikore V, Somai M, Jian WS, Li YC. Mobile teledermatology for a prompter and more efficient dermatological care in rural Mongolia. Br J Dermatol. 2015 Jul; 173(1):265-7. PMID: 25494968.
    View in: PubMed
  17. Minhas MA, Velasquez AG, Kaul A, Salinas PD, Celi LA. Effect of Protocolized Sedation on Clinical Outcomes in Mechanically Ventilated Intensive Care Unit Patients: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Mayo Clin Proc. 2015 May; 90(5):613-23. PMID: 25865475.
    View in: PubMed
  18. Ghassemi M, Celi LA, Stone DJ. State of the art review: the data revolution in critical care. Crit Care. 2015 Mar 16; 19:118. PMID: 25886756; PMCID: PMC4361206.
  19. Chen KP, Lee J, Mark RG, Feng M, Celi LA, Malley BE, Danziger J. Proton pump inhibitor use is not associated with cardiac arrhythmia in critically ill patients. J Clin Pharmacol. 2015 Jul; 55(7):774-9. PMID: 25655574; PMCID: PMC4911225.
  20. de Louw EJ, Sun PO, Lee J, Feng M, Mark RG, Celi LA, Mukamal KJ, Danziger J. Increased incidence of diuretic use in critically ill obese patients. J Crit Care. 2015 Jun; 30(3):619-23. PMID: 25721030; PMCID: PMC4626009.
  21. Wyber R, Vaillancourt S, Perry W, Mannava P, Folaranmi T, Celi LA. Big data in global health: improving health in low- and middle-income countries. Bull World Health Organ. 2015 Mar 01; 93(3):203-8. PMID: 25767300; PMCID: PMC4339829.
  22. Stone DJ, Celi LA, Csete M. Engineering control into medicine. J Crit Care. 2015 Jun; 30(3):652.e1-7. PMID: 25680579; PMCID: PMC4414787.
  23. Salciccioli JD, Marshall DC, Pimentel MA, Santos MD, Pollard T, Celi LA, Shalhoub J. The association between the neutrophil-to-lymphocyte ratio and mortality in critical illness: an observational cohort study. Crit Care. 2015 Jan 19; 19:13. PMID: 25598149; PMCID: PMC4344736.
  24. Moskowitz A, McSparron J, Stone DJ, Celi LA. Preparing a New Generation of Clinicians for the Era of Big Data. Harv Med Stud Rev. 2015 Jan; 2(1):24-27. PMID: 25688383.
    View in: PubMed
  25. Moseley ET, Hsu DJ, Stone DJ, Celi LA. Beyond open big data: addressing unreliable research. J Med Internet Res. 2014 Nov 11; 16(11):e259. PMID: 25405277; PMCID: PMC4260008.
  26. Celi LA, Csete M, Stone D. Optimal data systems: the future of clinical predictions and decision support. Curr Opin Crit Care. 2014 Oct; 20(5):573-80. PMID: 25137399; PMCID: PMC4215932.
  27. Celi LA, Ippolito A, Montgomery RA, Moses C, Stone DJ. Crowdsourcing knowledge discovery and innovations in medicine. J Med Internet Res. 2014 Sep 19; 16(9):e216. PMID: 25239002; PMCID: PMC4180345.
  28. Dejam A, Malley BE, Feng M, Cismondi F, Park S, Samani S, Samani ZA, Pinto DS, Celi LA. The effect of age and clinical circumstances on the outcome of red blood cell transfusion in critically ill patients. Crit Care. 2014 Aug 30; 18(4):487. PMID: 25175389; PMCID: PMC4174663.
  29. Badawi O, Brennan T, Celi LA, Feng M, Ghassemi M, Ippolito A, Johnson A, Mark RG, Mayaud L, Moody G, Moses C, Naumann T, Pimentel M, Pollard TJ, Santos M, Stone DJ, Zimolzak A. Making big data useful for health care: a summary of the inaugural mit critical data conference. JMIR Med Inform. 2014 Aug 22; 2(2):e22. PMID: 25600172; PMCID: PMC4288071.
  30. Ghassemi MM, Richter SE, Eche IM, Chen TW, Danziger J, Celi LA. A data-driven approach to optimized medication dosing: a focus on heparin. Intensive Care Med. 2014 Sep; 40(9):1332-9. PMID: 25091788; PMCID: PMC4157935.
  31. De Waele J, Lipman J, Sakr Y, Marshall JC, Vanhems P, Barrera Groba C, Leone M, Vincent JL. Abdominal infections in the intensive care unit: characteristics, treatment and determinants of outcome. BMC Infect Dis. 2014 Jul 29; 14:420. PMID: 25074742; PMCID: PMC4122779.
  32. Lee J, de Louw E, Niemi M, Nelson R, Mark RG, Celi LA, Mukamal KJ, Danziger J. Association between fluid balance and survival in critically ill patients. J Intern Med. 2015 Apr; 277(4):468-77. PMID: 24931482; PMCID: PMC4265574.
  33. Celi LA, Zimolzak AJ, Stone DJ. Dynamic clinical data mining: search engine-based decision support. JMIR Med Inform. 2014 Jun 23; 2(1):e13. PMID: 25600664; PMCID: PMC4288074.
  34. Boone MD, Celi LA, Ho BG, Pencina M, Curry MP, Lior Y, Talmor D, Novack V. Model for End-Stage Liver Disease score predicts mortality in critically ill cirrhotic patients. J Crit Care. 2014 Oct; 29(5):881.e7-13. PMID: 24974049.
    View in: PubMed
  35. Velasquez A, Ghassemi M, Szolovits P, Park S, Osorio J, Dejam A, Celi L. Long-term outcomes of minor troponin elevations in the intensive care unit. Anaesth Intensive Care. 2014 May; 42(3):356-64. PMID: 24794476.
    View in: PubMed
  36. Moskowitz A, Lee J, Donnino MW, Mark R, Celi LA, Danziger J. The Association Between Admission Magnesium Concentrations and Lactic Acidosis in Critical Illness. J Intensive Care Med. 2016 Mar; 31(3):187-92. PMID: 24733810; PMCID: PMC4909152.
  37. Fuchs L, Novack V, McLennan S, Celi LA, Baumfeld Y, Park S, Howell MD, Talmor DS. Trends in severity of illness on ICU admission and mortality among the elderly. PLoS One. 2014; 9(4):e93234. PMID: 24699251; PMCID: PMC3974713.
  38. Ghassemi M, Marshall J, Singh N, Stone DJ, Celi LA. Leveraging a critical care database: selective serotonin reuptake inhibitor use prior to ICU admission is associated with increased hospital mortality. Chest. 2014 Apr; 145(4):745-52. PMID: 24371841; PMCID: PMC3971969.
  39. Gustot T, Felleiter P, Pickkers P, Sakr Y, Rello J, Velissaris D, Pierrakos C, Taccone FS, Sevcik P, Moreno C, Vincent JL. Impact of infection on the prognosis of critically ill cirrhotic patients: results from a large worldwide study. Liver Int. 2014 Nov; 34(10):1496-503. PMID: 24606193.
    View in: PubMed
  40. Walker X, Lee J, Koval L, Kirkwood A, Taylor J, Gibbs J, Ng S, Steele L, Thompson P, Celi LA. Predicting ICU admissions from attempted suicide presentations at an Emergency Department in Central Queensland. Australas Med J. 2013; 6(11):536-41. PMID: 24348869; PMCID: PMC3858606.
  41. DePasse J, Celi LA. Collaboration, capacity building and co-creation as a new mantra in global health. Int J Qual Health Care. 2016 Sep; 28(4):536-7. PMID: 24225268.
    View in: PubMed
  42. Celi LA, Scott DJ, Lee J, Nelson R, Alper SL, Mukamal KJ, Mark RG, Danziger J. Association of hypermagnesemia and blood pressure in the critically ill. J Hypertens. 2013 Nov; 31(11):2136-41; discussion 2141. PMID: 24029865.
    View in: PubMed
  43. Lee J, Govindan S, Celi LA, Khabbaz KR, Subramaniam B. Customized Prediction of Short Length of Stay Following Elective Cardiac Surgery in Elderly Patients Using a Genetic Algorithm. World J Cardiovasc Surg. 2013 Sep; 3(5):163-170. PMID: 24482754.
    View in: PubMed
  44. Fuchs L, Lee J, Novack V, Baumfeld Y, Scott D, Celi L, Mandelbaum T, Howell M, Talmor D. Severity of acute kidney injury and two-year outcomes in critically ill patients. Chest. 2013 Sep; 144(3):866-75. PMID: 23681257.
    View in: PubMed
  45. Fialho AS, Celi LA, Cismondi F, Vieira SM, Reti SR, Sousa JM, Finkelstein SN. Disease-based modeling to predict fluid response in intensive care units. Methods Inf Med. 2013; 52(6):494-502. PMID: 23986268.
    View in: PubMed
  46. Celi LA, Mark RG, Stone DJ, Montgomery RA. "Big data" in the intensive care unit. Closing the data loop. Am J Respir Crit Care Med. 2013 Jun 01; 187(11):1157-60. PMID: 23725609; PMCID: PMC3734609.
  47. Nair SM, Mishra P, McLennan S, Lee J, Tsao CH, Celi LA. Alcohol-related injuries requiring surgery. N Z Med J. 2013 May 10; 126(1374):92-5. PMID: 23799389.
    View in: PubMed
  48. Mayaud L, Lai PS, Clifford GD, Tarassenko L, Celi LA, Annane D. Dynamic data during hypotensive episode improves mortality predictions among patients with sepsis and hypotension. Crit Care Med. 2013 Apr; 41(4):954-62. PMID: 23385106; PMCID: PMC3609896.
  49. Moses C, Celi LA, Marshall J. Pharmacovigilance: an active surveillance system to proactively identify risks for adverse events. Popul Health Manag. 2013 Jun; 16(3):147-9. PMID: 23530466.
    View in: PubMed
  50. Perry WR, Kwok AC, Kozycki C, Celi LA. Disparities in end-of-life care: a perspective and review of quality. Popul Health Manag. 2013 Apr; 16(2):71-3. PMID: 23405874.
    View in: PubMed
  51. Danziger J, William JH, Scott DJ, Lee J, Lehman LW, Mark RG, Howell MD, Celi LA, Mukamal KJ. Proton-pump inhibitor use is associated with low serum magnesium concentrations. Kidney Int. 2013 Apr; 83(4):692-9. PMID: 23325090.
    View in: PubMed
  52. Scott DJ, Lee J, Silva I, Park S, Moody GB, Celi LA, Mark RG. Accessing the public MIMIC-II intensive care relational database for clinical research. BMC Med Inform Decis Mak. 2013 Jan 10; 13:9. PMID: 23302652; PMCID: PMC3598967.
  53. Cismondi F, Celi LA, Fialho AS, Vieira SM, Reti SR, Sousa JM, Finkelstein SN. Reducing unnecessary lab testing in the ICU with artificial intelligence. Int J Med Inform. 2013 May; 82(5):345-58. PMID: 23273628.
    View in: PubMed
  54. Celi LA, Galvin S, Davidzon G, Lee J, Scott D, Mark R. A Database-driven Decision Support System: Customized Mortality Prediction. J Pers Med. 2012 Sep 27; 2(4):138-48. PMID: 23766893; PMCID: PMC3678286.
  55. Fuchs L, Chronaki CE, Park S, Novack V, Baumfeld Y, Scott D, McLennan S, Talmor D, Celi L. ICU admission characteristics and mortality rates among elderly and very elderly patients. Intensive Care Med. 2012 Oct; 38(10):1654-61. PMID: 22797350.
    View in: PubMed
  56. Lee J, Kothari R, Ladapo JA, Scott DJ, Celi LA. Interrogating a clinical database to study treatment of hypotension in the critically ill. BMJ Open. 2012; 2(3). PMID: 22685222; PMCID: PMC3371576.
  57. Hunziker S, Celi LA, Lee J, Howell MD. Red cell distribution width improves the simplified acute physiology score for risk prediction in unselected critically ill patients. Crit Care. 2012 May 18; 16(3):R89. PMID: 22607685; PMCID: PMC3580634.
  58. Celi LA, Mark RG, Lee J, Scott DJ, Panch T. Collective Experience: A Database-Fuelled, Inter-Disciplinary Team-Led Learning System. J Comput Sci Eng. 2012 Mar 01; 6(1):51-59. PMID: 23766887.
    View in: PubMed
  59. Costa CM, Gondim DD, Gondim DD, Soares HB, Ribeiro AG, Silva I, Winkler E, Celi L, Guerreiro AM, Leite CR. S2DIA: a diagnostic system for Diabetes mellitus using SANA platform. Conf Proc IEEE Eng Med Biol Soc. 2012; 2012:6078-81. PMID: 23367315.
    View in: PubMed
  60. Celi LA, Tang RJ, Villarroel MC, Davidzon GA, Lester WT, Chueh HC. A Clinical Database-Driven Approach to Decision Support: Predicting Mortality Among Patients with Acute Kidney Injury. J Healthc Eng. 2011 Mar; 2(1):97-110. PMID: 22844575.
    View in: PubMed
  61. Kett DH, Azoulay E, Echeverria PM, Vincent JL. Candida bloodstream infections in intensive care units: analysis of the extended prevalence of infection in intensive care unit study. Crit Care Med. 2011 Apr; 39(4):665-70. PMID: 21169817.
    View in: PubMed
  62. Galvin SD, Celi LA, Thomas KN, Clendon TR, Galvin IF, Bunton RW, Ainslie PN. Effects of age and coronary artery disease on cerebrovascular reactivity to carbon dioxide in humans. Anaesth Intensive Care. 2010 Jul; 38(4):710-7. PMID: 20715736.
    View in: PubMed
  63. McLennan S, Celi LA, Gillett G, Penney J, Foss M. Nurses share their views on end-of-life issues. Nurs N Z. 2010 May; 16(4):12-4. PMID: 20572537.
    View in: PubMed
  64. Endre ZH, Walker RJ, Pickering JW, Shaw GM, Frampton CM, Henderson SJ, Hutchison R, Mehrtens JE, Robinson JM, Schollum JB, Westhuyzen J, Celi LA, McGinley RJ, Campbell IJ, George PM. Early intervention with erythropoietin does not affect the outcome of acute kidney injury (the EARLYARF trial). Kidney Int. 2010 Jun; 77(11):1020-30. PMID: 20164823.
    View in: PubMed
  65. McLennan S, Vollweiler M, Celi LA. How can nurses' flu vaccination rates be boosted? Nurs N Z. 2009 May; 15(4):12-4. PMID: 19552123; PMCID: PMC2908019.
  66. Celi LA, Sarmenta L, Rotberg J, Marcelo A, Clifford G. Mobile Care (Moca) for Remote Diagnosis and Screening. J Health Inform Dev Ctries. 2009 Jan 01; 3(1):17-21. PMID: 21822397.
    View in: PubMed
  67. Celi LA, Hinske LC, Alterovitz G, Szolovits P. An artificial intelligence tool to predict fluid requirement in the intensive care unit: a proof-of-concept study. Crit Care. 2008; 12(6):R151. PMID: 19046450; PMCID: PMC2646316.
  68. Glasgow JL, McLennan SR, High KJ, Celi LA. Quality of dying in a New Zealand teaching hospital. Qual Saf Health Care. 2008 Aug; 17(4):244-8. PMID: 18678719.
    View in: PubMed
  69. Ainslie PN, Celi L, McGrattan K, Peebles K, Ogoh S. Dynamic cerebral autoregulation and baroreflex sensitivity during modest and severe step changes in arterial PCO2. Brain Res. 2008 Sep 16; 1230:115-24. PMID: 18680730.
    View in: PubMed
  70. Peebles KC, Richards AM, Celi L, McGrattan K, Murrell CJ, Ainslie PN. Human cerebral arteriovenous vasoactive exchange during alterations in arterial blood gases. J Appl Physiol (1985). 2008 Oct; 105(4):1060-8. PMID: 18617625.
    View in: PubMed
  71. Khan E, Huggan P, Celi L, MacGinley R, Schollum J, Walker R. Sustained low-efficiency dialysis with filtration (SLEDD-f) in the management of acute sodium valproate intoxication. Hemodial Int. 2008 Apr; 12(2):211-4. PMID: 18394052.
    View in: PubMed
  72. Carden GP, Graham JW, McLennan S, Celi LA. Long-Term Outcome of Long Stay ICU and HDU Patients in a New Zealand Hospital. Crit Care Shock. 2008 Mar; 11(1):26-34. PMID: 23766668.
    View in: PubMed
  73. McLennan S, Gillett G, Celi LA. Healer, heal thyself: health care workers and the influenza vaccination. Am J Infect Control. 2008 Feb; 36(1):1-4. PMID: 18241729.
    View in: PubMed
  74. Yap J, Celi LA. Elderly access to medical care: should age be a factor in deciding management? N Z Med J. 2007 Nov 30; 120(1266):U2838. PMID: 18264207.
    View in: PubMed
  75. Ainslie PN, Ogoh S, Burgess K, Celi L, McGrattan K, Peebles K, Murrell C, Subedi P, Burgess KR. Differential effects of acute hypoxia and high altitude on cerebral blood flow velocity and dynamic cerebral autoregulation: alterations with hyperoxia. J Appl Physiol (1985). 2008 Feb; 104(2):490-8. PMID: 18048592.
    View in: PubMed
  76. Conlon NP, Redmond KC, Celi LA. Spontaneous hemothorax in a patient with neurofibromatosis type 1 and undiagnosed pheochromocytoma. Ann Thorac Surg. 2007 Sep; 84(3):1021-3. PMID: 17720427.
    View in: PubMed
  77. Peebles K, Celi L, McGrattan K, Murrell C, Thomas K, Ainslie PN. Human cerebrovascular and ventilatory CO2 reactivity to end-tidal, arterial and internal jugular vein PCO2. J Physiol. 2007 Oct 01; 584(Pt 1):347-57. PMID: 17690148; PMCID: PMC2277051.
  78. McLennan S, Celi LA, Roth P. The Health and Safety in Employment Act and the influenza vaccination of healthcare workers. N Z Med J. 2007 Mar 02; 120(1250):U2442. PMID: 17339898.
    View in: PubMed
  79. Wu G, Sijnja B, Celi L, Wright P, Van Rij A. Patient with a leg ulcer. Aust Fam Physician. 2003 Sep; 32(9):739-40. PMID: 14524216.
    View in: PubMed
  80. Celi LA, Hassan E, Marquardt C, Breslow M, Rosenfeld B. The eICU: it's not just telemedicine. Crit Care Med. 2001 Aug; 29(8 Suppl):N183-9. PMID: 11496041.
    View in: PubMed
  81. Teoh G, Chen L, Urashima M, Tai YT, Celi LA, Chen D, Chauhan D, Ogata A, Finberg RW, Webb IJ, Kufe DW, Anderson KC. Adenovirus vector-based purging of multiple myeloma cells. Blood. 1998 Dec 15; 92(12):4591-601. PMID: 9845525.
    View in: PubMed
  82. Bergelson JM, Krithivas A, Celi L, Droguett G, Horwitz MS, Wickham T, Crowell RL, Finberg RW. The murine CAR homolog is a receptor for coxsackie B viruses and adenoviruses. J Virol. 1998 Jan; 72(1):415-9. PMID: 9420240; PMCID: PMC109389.
  83. Celi L, Fisher C. Textbook of Critical Care, Shoemaker W, Ayres S, et al. eds. Toxic Shock Syndrome. 1995.
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