Modeling the severity of illness of ICU patients. A systems update.
about
Validation of the Rockall risk scoring system in upper gastrointestinal bleedingAssessment of performance of four mortality prediction systems in a Saudi Arabian intensive care unitPerformance of the score systems Acute Physiology and Chronic Health Evaluation II and III at an interdisciplinary intensive care unit, after customizationAssessment of six mortality prediction models in patients admitted with severe sepsis and septic shock to the intensive care unit: a prospective cohort studyPrognostic categorization of intensive care septic patientsScoring systems in the intensive care unit: A compendiumClinical review: allocating ventilators during large-scale disasters--problems, planning, and processFailure of combination oral oseltamivir and inhaled zanamivir antiviral treatment in ventilator- and ECMO-treated critically ill patients with pandemic influenza A (H1N1)v.Automated physician order recommendations and outcome predictions by data-mining electronic medical records.Frequency of laboratory test utilization in the intensive care unit and its implications for large-scale data collection efforts.Predicting outcome after traumatic brain injury: development and international validation of prognostic scores based on admission characteristics.Support vector machine versus logistic regression modeling for prediction of hospital mortality in critically ill patients with haematological malignancies.Stratification of the severity of critically ill patients with classification trees.Critical Analysis of PIM2 Score Applicability in a Tertiary Care PICU in Western India.[Performance of the Pediatric Index of Mortality 2 in a pediatric intensive care unit]Complications, comorbidities, and mortality: improving classification and prediction.Predicting six-month mortality of patients with traumatic brain injury: usefulness of common intensive care severity scoresValidation of "Signs of Inflammation in Children that Kill" (SICK) score for immediate non-invasive assessment of severity of illness.Growth limits of Listeria monocytogenes as a function of temperature, pH, NaCl, and lactic acid.A Comparison of Intensive Care Unit Mortality Prediction Models through the Use of Data Mining TechniquesMortality prediction using SAPS II: an update for French intensive care unitsValidation of the pneumonia severity index. Importance of study-specific recalibration.Cancer history, bandemia, and serum creatinine are independent mortality predictors in patients with infection-precipitated hyperglycemic crises.Prognostic impact of alternative splicing-derived hMENA isoforms in resected, node-negative, non-small-cell lung cancer.Obstetric critical care: A prospective analysis of clinical characteristics, predictability, and fetomaternal outcome in a new dedicated obstetric intensive care unitExtracorporeal cell therapy of septic shock patients with donor granulocytes: a pilot study.Mapping physicians' admission diagnoses to structured concepts towards fully automatic calculation of acute physiology and chronic health evaluation score.A comparison of three scoring systems for mortality risk among retrieved intensive care patients.OrderRex: clinical order decision support and outcome predictions by data-mining electronic medical records.Outcomes and Health-related Quality of Life following Intensive Care Unit Stay in Barbados.Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.Prognostic performance of the Simplified Acute Physiology Score II in major Croatian hospitals: a prospective multicenter study.Consensus Statement on Electronic Health Predictive Analytics: A Guiding Framework to Address Challenges.Review of the acuity scoring systems for the pediatric intensive care unit and their use in quality improvement.Pulmonary leptospirosis: an excellent response to bolus methylprednisoloneComparison of P-POSSUM and O-POSSUM in predicting mortality after oesophagogastric resectionsImpact of major non-cardiac complications on outcome following cardiac surgery procedures: logistic regression analysis in a very recent patient cohortA modified sequential organ failure assessment score for critical care triage.Model for predicting short-term mortality of severe sepsisSociodemographic and clinical characteristics are not clinically useful predictors of refill adherence in patients with hypertension.
P2860
Q24670384-322B7BE8-BFEA-4E6D-85EF-839CD433FB39Q24791128-000DD244-451A-452E-B959-A9E1B1DE1273Q24795103-4639E8B8-DBD1-465C-B15C-AB5DE0B7D925Q24796183-73C62FFC-8908-4073-9D55-2704AD3F109CQ26825553-2A172400-FC20-45D1-8503-498BE84A5EE4Q27000953-002D98C8-17EF-40AB-9304-4FECDF5A6F60Q28755914-66FA2573-2DB5-4C1D-BDC5-92D7B34B07BFQ30399530-23AD754A-76C1-4EA4-8E8B-63F02A96EF10Q30900371-962B6BC3-1C29-4AAA-82DC-85AE9B47335BQ30977047-C7E4B45E-C0AC-4CFE-BE0F-A1DED67D3FACQ33358264-CF807A00-FA5E-4C42-8AF5-C633689837FDQ33390504-73FF0042-F59B-4677-846B-8203D86E597DQ33517867-BE0AE0F6-3639-41AE-9CC8-C15EB9E73FAAQ33608229-CC55DDBB-4A52-40AE-A4EC-5054C390E543Q33653381-A51601AD-342D-4EFF-A155-81EC867BEB92Q33726062-4423511A-EECC-4308-97F8-19D9B22CEB89Q33751176-C6BD548C-B6C3-49C7-B0FC-D981428E9DF0Q33864032-141A28BE-FA30-40AC-B312-ED6517177D9AQ33988116-B6A7F1F2-D45D-4E3E-BD82-41E6F44A2A4CQ34132956-4C0E41F1-F3FC-401A-A0B6-57858ECC5192Q34480769-951D7A91-3D39-467D-A4F6-4E7C1B7EB01AQ34749988-7A143C98-C000-4AD1-805B-EACF4FE69CF1Q34833819-FB33C1A3-945E-42D8-9046-C80F5531DEC8Q34957141-79DCD7EA-48F9-412A-AF8F-7A7F19D85C94Q35020328-25D15D9C-3220-47BE-9F95-3AD96C8C7C64Q35559371-F77B61A3-16C9-4D80-ABB3-A517D13F53D8Q35564897-9D3B30E4-5968-498B-AC65-47C6349B5F86Q35571313-D3C35110-AE6F-476A-BA33-9AC17A2D46EAQ35704072-88EFD3D2-1249-4E18-AF7C-8CCB8C0743FDQ36306486-153E27F3-6F2A-4018-BE14-0E8DD5FE7445Q36369595-FF2C50CC-FA77-43B6-8A7B-003F3B629192Q36375597-5D8B53D4-5BB9-45D4-AEA1-EE3E4EB1412BQ36816489-55433098-DDCE-47E9-9000-FB4748007015Q36847056-97CE8BAC-9260-42D5-A5CD-2D5814D92C80Q36979635-23ADD64D-79FE-45AE-81AD-87505F077055Q37008727-0D00D753-ED16-4388-ACB5-D33D7834DF35Q37024123-A666E2D2-BD5A-46BF-BABA-CC09CE435F37Q37265113-7E771AC0-0AAB-4339-AD40-9B0F59C2637AQ37279786-368C479C-A587-49CB-A039-E2922B90E638Q37401111-5B57F1BF-13D6-4A1A-BB0B-B7C586FD2D66
P2860
Modeling the severity of illness of ICU patients. A systems update.
description
1994 nî lūn-bûn
@nan
1994年の論文
@ja
1994年論文
@yue
1994年論文
@zh-hant
1994年論文
@zh-hk
1994年論文
@zh-mo
1994年論文
@zh-tw
1994年论文
@wuu
1994年论文
@zh
1994年论文
@zh-cn
name
Modeling the severity of illness of ICU patients. A systems update.
@en
type
label
Modeling the severity of illness of ICU patients. A systems update.
@en
prefLabel
Modeling the severity of illness of ICU patients. A systems update.
@en
P1476
Modeling the severity of illness of ICU patients. A systems update.
@en
P2093
J R Le Gall
S Lemeshow
P304
P356
10.1001/JAMA.1994.03520130087038
P407
P577
1994-10-01T00:00:00Z