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Items: 1 to 20 of 41

1.

Predicting the Ability of Wounds to Heal Given Any Burn Size and Fluid Volume: An Analytical Approach.

Liu NT, Rizzo JA, Shields BA, Serio-Melvin ML, Christy RJ, Salinas J.

J Burn Care Res. 2018 Aug 17;39(5):661-669. doi: 10.1093/jbcr/iry021.

PMID:
29757400
2.

Trend Analysis of Current Modalities for Monitoring Fluid Therapy in Patients With Large Burns: Echoing the Call for Better Resuscitation Indices.

Liu NT, Cancio LC, Serio-Melvin ML, Salinas J.

J Burn Care Res. 2018 Oct 23;39(6):970-976. doi: 10.1093/jbcr/iry015.

PMID:
29635631
3.

Simulation of carotid artery stenting reduces training procedure and fluoroscopy times.

Gosling AF, Kendrick DE, Kim AH, Nagavalli A, Kimball ES, Liu NT, Kashyap VS, Wang JC.

J Vasc Surg. 2017 Jul;66(1):298-306. doi: 10.1016/j.jvs.2016.11.066. Epub 2017 May 19.

PMID:
28533078
4.

Machine Learning for Predicting Outcomes in Trauma.

Liu NT, Salinas J.

Shock. 2017 Nov;48(5):504-510. doi: 10.1097/SHK.0000000000000898.

PMID:
28498299
5.

The impact of patient weight on burn resuscitation.

Liu NT, Fenrich CA, Serio-Melvin ML, Peterson WC, Cancio LC, Salinas J.

J Trauma Acute Care Surg. 2017 Jul;83(1 Suppl 1):S112-S119. doi: 10.1097/TA.0000000000001486.

PMID:
28452888
6.

Inefficacy of standard vital signs for predicting mortality and the need for prehospital life-saving interventions in blunt trauma patients transported via helicopter: A repeated call for new measures.

Liu NT, Holcomb JB, Wade CE, Salinas J.

J Trauma Acute Care Surg. 2017 Jul;83(1 Suppl 1):S98-S103. doi: 10.1097/TA.0000000000001482.

PMID:
28452878
7.

Predicting the proportion of full-thickness involvement for any given burn size based on burn resuscitation volumes.

Liu NT, Salinas J, Fenrich CA, Serio-Melvin ML, Kramer GC, Driscoll IR, Schreiber MA, Cancio LC, Chung KK.

J Trauma Acute Care Surg. 2016 Nov;81(5 Suppl 2 Proceedings of the 2015 Military Health System Research Symposium):S144-S149.

PMID:
27768662
8.

Machine learning and new vital signs monitoring in civilian en route care: A systematic review of the literature and future implications for the military.

Liu NT, Salinas J.

J Trauma Acute Care Surg. 2016 Nov;81(5 Suppl 2 Proceedings of the 2015 Military Health System Research Symposium):S111-S115. Review.

PMID:
26670115
9.

Genome Sequences of Ralstonia insidiosa Type Strain ATCC 49129 and Strain FC1138, a Strong Biofilm Producer Isolated from a Fresh-Cut Produce-Processing Plant.

Xu Y, Nagy A, Yan X, Haley BJ, Kim SW, Liu NT, Nou X.

Genome Announc. 2016 Aug 18;4(4). pii: e00847-16. doi: 10.1128/genomeA.00847-16.

10.

Closed-Loop Control of FiO2 Rapidly Identifies Need For Rescue Ventilation and Reduces ARDS Severity in a Conscious Sheep Model of Burn and Smoke Inhalation Injury.

Liu NT, Salter MG, Khan MN, Branson RD, Enkhbaatar P, Kramer GC, Salinas J, Marques NR, Kinsky MP.

Shock. 2017 Feb;47(2):200-207. doi: 10.1097/SHK.0000000000000686.

PMID:
27392155
11.

Acute Respiratory Distress Syndrome in Burn Patients: A Comparison of the Berlin and American-European Definitions.

Sine CR, Belenkiy SM, Buel AR, Waters JA, Lundy JB, Henderson JL, Stewart IJ, Aden JK, Liu NT, Batchinsky A, Cannon JW, Cancio LC, Chung KK.

J Burn Care Res. 2016 Sep-Oct;37(5):e461-9. doi: 10.1097/BCR.0000000000000348.

PMID:
27070223
12.

Endovascular aneurysm repair simulation can lead to decreased fluoroscopy time and accurately delineate the proximal seal zone.

Kim AH, Kendrick DE, Moorehead PA, Nagavalli A, Miller CP, Liu NT, Wang JC, Kashyap VS.

J Vasc Surg. 2016 Jul;64(1):251-8. doi: 10.1016/j.jvs.2016.01.050. Epub 2016 Mar 19.

13.
14.

Machine learning in burn care and research: A systematic review of the literature.

Liu NT, Salinas J.

Burns. 2015 Dec;41(8):1636-1641. doi: 10.1016/j.burns.2015.07.001. Epub 2015 Jul 29. Review.

PMID:
26233900
15.

Is heart-rate complexity a surrogate measure of cardiac output before, during, and after hemorrhage in a conscious sheep model of multiple hemorrhages and resuscitation?

Liu NT, Kramer GC, Khan MN, Kinsky MP, Salinas J.

J Trauma Acute Care Surg. 2015 Oct;79(4 Suppl 2):S93-100. doi: 10.1097/TA.0000000000000573.

PMID:
26131782
16.

Data quality of a wearable vital signs monitor in the pre-hospital and emergency departments for enhancing prediction of needs for life-saving interventions in trauma patients.

Liu NT, Holcomb JB, Wade CE, Darrah MI, Salinas J.

J Med Eng Technol. 2015;39(6):316-21. doi: 10.3109/03091902.2015.1054524. Epub 2015 Jun 19.

PMID:
26088543
17.
18.

Effects of environmental parameters on the dual-species biofilms formed by Escherichia coli O157:H7 and Ralstonia insidiosa, a strong biofilm producer isolated from a fresh-cut produce processing plant.

Liu NT, Nou X, Bauchan GR, Murphy C, Lefcourt AM, Shelton DR, Lo YM.

J Food Prot. 2015 Jan;78(1):121-7. doi: 10.4315/0362-028X.JFP-14-302.

PMID:
25581186
19.

MicroRNA-181 inhibits glioma cell proliferation by targeting cyclin B1.

Wang F, Sun JY, Zhu YH, Liu NT, Wu YF, Yu F.

Mol Med Rep. 2014 Oct;10(4):2160-4. doi: 10.3892/mmr.2014.2423. Epub 2014 Jul 28.

PMID:
25070000
20.

Evaluation of standard versus nonstandard vital signs monitors in the prehospital and emergency departments: results and lessons learned from a trauma patient care protocol.

Liu NT, Holcomb JB, Wade CE, Darrah MI, Salinas J.

J Trauma Acute Care Surg. 2014 Sep;77(3 Suppl 2):S121-6. doi: 10.1097/TA.0000000000000192.

PMID:
24770560

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