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Original Research

Use of photoplethysmography to predict mortality in intensive care units

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Pages 311-320 | Published online: 31 Oct 2018

References

  • GolzariSEMahmoodpoorACare bundles in intensive care unitsLancet Infect Dis2014145371372
  • RapsangAGShyamDCScoring systems in the intensive care unit: a compendiumIndian J Crit Care Med201418422022824872651
  • VincentJLMorenoRClinical review: scoring systems in the critically illCrit Care201014220720392287
  • NilssonLMRespiration signals from photoplethysmographyAnesth Analg2013117485986523449854
  • PirneskoskiJHarjolaVPJeskanenPLinnamurtoLSaikkoSNurmiJCritically ill patients in emergency department may be characterized by low amplitude and high variability of amplitude of pulse photoplethysmographyScand J Trauma Resusc Emerg Med2013214823799988
  • MuhadiMNasutionSAPutrantoRHarimurtiKThe ability of detecting heart rate variability with the photoplethysmography to predict major adverse cardiac event in acute coronary syndromeActa Med Indones2016481485327241544
  • ElgendiMOn the analysis of fingertip photoplethysmogram signalsCurr Cardiol Rev201281142522845812
  • KohjitaniAMiyataMIwaseYAssociations between the autonomic nervous system and the second derivative of the finger photoplethysmogram indicesJ Atheroscler Thromb201421550150824430785
  • MillasseauSCKellyRPRitterJMChowienczykPJDetermination of age-related increases in large artery stiffness by digital pulse contour analysisClin Sci (Lond)2002103437137712241535
  • OtsukaTKawadaTKatsumataMIbukiCUtility of second derivative of the finger photoplethysmogram for the estimation of the risk of coronary heart disease in the general populationCirc J200670330431016501297
  • LimaABakkerJNoninvasive monitoring of peripheral perfusionIntensive Care Med200531101316132616170543
  • BrochOBeinBGruenewaldMAccuracy of the pleth variability index to predict fluid responsiveness depends on the perfusion indexActa Anaesthesiol Scand201155668669321480831
  • GandhiPGRaoGHThe spectral analysis of photoplethysmography to evaluate an independent cardiovascular risk factorInt J Gen Med2014753954725525382
  • TrujillanoJMarchJSorribasAMethodological approach to the use of artificial neural networks for predicting results in medicineMed Clin (Barc)2004122Suppl 1596714980162
  • ClermontGAngusDCDiRussoSMGriffinMLinde-ZwirbleWTPredicting hospital mortality for patients in the intensive care unit: a comparison of artificial neural networks with logistic regression modelsCrit Care Med200129229129611246308
  • Hajian-TilakiKSample size estimation in diagnostic test studies of biomedical informaticsJ Biomed Inform20144819320424582925
  • KnausWADraperEAWagnerDPZimmermanJEAPACHE II: a severity of disease classification systemCrit Care Med198513108188293928249
  • JeyhaniVMahdianiSPeltokangasMVehkaojaAComparison of HRV parameters derived from photoplethysmography and electrocardiography signalsConf Proc IEEE Eng Med Biol Soc201520155952596526737647
  • RauHHHsuCYLinYADevelopment of a web-based liver cancer prediction model for type II diabetes patients by using an artificial neural networkComput Methods Programs Biomed2016125586526701199
  • DeLongERDeLongDMClarke-PearsonDLComparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approachBiometrics19884438378453203132
  • El-FakhouriSCarrascoHVAraújoGCFriniICEpidemiological profile of ICU patients at Faculdade de Medicina de MaríliaRev Assoc Med Bras (1992)201662324825427310549
  • CapuzzoMVoltaCATassinatiTWorking Group on Health Economics of the European Society of Intensive Care MedicineHospital mortality of adults admitted to intensive care units in hospitals with and without intermediate care units: a multicentre European cohort studyCrit Care201418555125664865
  • SiddiquiSMortality profile across our intensive care units: a 5-year database report from a Singapore restructured hospitalIndian J Crit Care Med2015191272672726816448
  • IwuaforAAOgunsolaFTOladeleROIncidence, clinical outcome and risk factors of intensive care unit infections in the Lagos University Teaching Hospital (LUTH), Lagos, NigeriaPLoS ONE20161110e016524227776162
  • VezzaniAMancaCErmioCGender disparities in the intensive care unitItal J Gender Specific Med2016212227
  • LipesJMardiniLJayaramanDSex and mortality of hospitalized adults after admission to an intensive care unitAm J Crit Care201322431431923817820
  • MahmoodKEldeirawiKWahidiMMAssociation of gender with outcomes in critically ill patientsCrit Care2012163R9222617003
  • ColpanAAkinciEErbayABalabanNBodurHEvaluation of risk factors for mortality in intensive care units: a prospective study from a referral hospital in TurkeyAm J Infect Control200533142715685134
  • Santana-CabreraLLorenzo-TorrentaRSánchez-PalaciosaMMartín SantanabJDHernández HernándezbJRInfluencia de la edad en la duración de la estancia y en la mortalidad de los pacientes que permanecen de forma prolongada en una Unidad de Cuidados IntensivoRevista Clínica Española (English Edition)201421427478
  • SalluhJISoaresMICU severity of illness scores: APACHE, SAPS and MPMCurr Opin Crit Care201420555756525137401
  • Ferrando-VivasPJonesARowanKMHarrisonDADevelopment and validation of the new ICNARC model for prediction of acute hospital mortality in adult critical careJ Crit Care20173833533927899205
  • KaraDAkinciSBBabaogluGAyparUIncreased heart rate on first day in intensive care unit is associated with increased mortalityPak J Med Sci20163261402140728083034
  • ErdurHGrittnerUScheitzJFLaufsUEndresMNolteCHHeart rate on admission independently predicts in-hospital mortality in acute ischemic stroke patientsInt J Cardiol2014176120621025049007
  • NolteCHErdurHGrittnerUImpact of heart rate on admission on mortality and morbidity in acute ischaemic stroke patients – results from VISTAEur J Neurol201623121750175627516056
  • KarmaliSNSciuscoAMaySMAcklandGLHeart rate variability in critical care medicine: a systematic reviewIntensive Care Med Exp2017513328702940
  • LuGYangFTaylorJASteinJFA comparison of photoplethysmography and ECG recording to analyse heart rate variability in healthy subjectsJ Med Eng Technol200933863464119848857
  • SchäferAVagedesJHow accurate is pulse rate variability as an estimate of heart rate variability? A review on studies comparing photoplethysmographic technology with an electrocardiogramInt J Cardiol20131661152922809539
  • BaekHJChoCHChoJWooJMReliability of ultra-short-term analysis as a surrogate of standard 5-min analysis of heart rate variabilityTelemed J E Health201521540441425807067
  • MillasseauSCRitterJMTakazawaKChowienczykPJContour analysis of the photoplethysmographic pulse measured at the fingerJ Hypertens20062481449145616877944
  • VlachopoulosCAznaouridisKStefanadisCPrediction of cardiovascular events and all-cause mortality with arterial stiffness: a systematic review and meta-analysisJ Am Coll Cardiol201055131318132720338492
  • Biering-SørensenTQuerejeta RocaGHegdeSMLeft ventricular ejection time is an independent predictor of incident heart failure in a community-based cohortEur J Heart Fail20182071106111428872225
  • HeHLongYLiuDWangXZhouXClinical classification of tissue perfusion based on the central venous oxygen saturation and the peripheral perfusion indexCrit Care20151933026369784
  • AcarYYamanelLCinarOCevikEKilicSYasarMPerfusion index from pulse oximetry predicts mortality and correlates with illness severity scores in intensive care unit patientsActa Medica Mediterranea201531237242
  • OskayAErayODinçSEAydınAGEkenCPrognosis of critically ill patients in the ED and value of perfusion index measurement: a cross-sectional studyAm J Emerg Med20153381042104425957144
  • SandroniCCavallaroFMaranoCFalconeCDe SantisPAntonelliMAccuracy of plethysmographic indices as predictors of fluid responsiveness in mechanically ventilated adults: a systematic review and meta-analysisIntensive Care Med20123891429143722732902
  • LaFaroRJPothulaSKubalKPNeural network prediction of ICU length of stay following cardiac surgery based on pre-incision variablesPLoS ONE20151012e014539526710254
  • GholipourCRahimFFakhreeAZiapourBUsing an artificial neural networks (ANNs) model for prediction of intensive care unit (ICU) outcome and length of stay at hospital in traumatic patientsJ Clin Diagn Res201594OC19OCT23