Practical-Manual-Scores-Algorithms-Haemostasis-Thrombosis

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Deep Vein <strong>Thrombosis</strong> and Pulmonary EmbolismClinical probability models for Pulmonary EmbolismIndicationClinically suspected Pulmonary Embolism (PE).FeatureWells’ scoreScorePrevious DVT or PE 1.5Heart rate > 100 bpm 1.5Surgery or bedridden < 4 weeks 1.5Hemoptysis 1Active malignancy 1Clinical symptoms of DVT 3Alternative diagnosis less likely than PE 3Clinical probabilityPE unlikely ≤ 4PE likely > 410
FeatureGeneva scoresPoints(revised dichotomized score)Points(simplified score)Previous DVT or PE 3 1Heart rate:75-94 bpm≥ 95 bpm3512Surgery or fracture < 1 month 2 1Hemoptysis 2 1Active malignancy 2 1Unilateral lower limb pain 3 1Pain on lower limb deep venous palpationor unilateral oedema4 1Age > 65 1 1Clinical probabilityPE unlikely ≤ 5 ≤ 2PE likely > 5 > 2Deep Vein <strong>Thrombosis</strong> and Pulmonary EmbolismInterpretationThese models are very useful when incorporated into algorithms, to optimizepatient management in clinically suspected PE. Combined with a D-dimertest result below a validated threshold and/or an objective imaging test, a lowclinical probability can safely rule out the presence of PE.References• Ceriani E, Combescure C, Le Gal G, et al. Clinical prediction rules for pulmonaryembolism: a systematic review and meta-analysis. J Thromb Haemost. 2010;8:957-70.• Klok FA, Mos IC, Nijkeuter M, et al. Simplification of the revised Geneva scorefor assessing clinical probability of pulmonary embolism. Arch Intern Med.2008;168:2131-6.• Le Gal G, Righini M, Roy PM, et al. Prediction of Pulmonary Embolism in the EmergencyDepartment: The Revised Geneva Score. Ann Intern Med. 2006;144:165-71.• Lucassen W, Geersing GJ, Erkens PM, et al. Clinical decision rules for excludingpulmonary embolism: a meta-analysis. Ann Int Med. 2011;155:448-60.• Wells PS, Anderson DR, Rodger M, et al. Derivation of a simple clinical model tocategorize patients probability of pulmonary embolism: increasing the models utilitywith the SimpliRED D-dimer. Thromb Haemost. 2000;83:416-20.11
Page 1 and 2: Practical manualScores and Algorith
Page 3: Scientific boardHenri BounameauxDiv
Page 6 and 7: SummaryBleedingISTH bleeding assess
Page 9: Clinical probability model for deep
Page 13 and 14: InterpretationClinical decision rul
Page 15 and 16: 6 features with a similar validity.
Page 17 and 18: Prediction of recurrent deep vein T
Page 19 and 20: Outpatient versus inpatient care in
Page 21 and 22: Assessment of post-thrombotic syndr
Page 23 and 24: Diagnostic algorithm in suspected p
Page 25 and 26: Prediction of stroke risk in patien
Page 27 and 28: References• Camm AJ, Lip GY, De C
Page 29 and 30: References• Friberg L, Rosenqvist
Page 31 and 32: InterpretationThis score identifies
Page 33 and 34: Vienna score (Ay Model): DVT or PE
Page 35 and 36: Risk assessment modelsin hospitaliz
Page 37 and 38: References• Chopard P, Spirk D, B
Page 39 and 40: Recommendations for the determinati
Page 41 and 42: Template for scoring system for non
Page 43 and 44: Diagnosis of Thrombotic Thrombocyto
Page 45 and 46: Management of patientswith occlusio
Page 47 and 48: Symptoms(up to the time of diagnosi
Page 49 and 50: InterpretationA bleeding score > 3
Page 51 and 52: Pediatric Bleeding scoreSymptoms Sc
Page 53 and 54: Bleeding assessment tool for the ev
Page 55 and 56: The SMOG system (cont.)Type of blee
Page 57 and 58: The SMOG system (cont.)Type of blee
Page 59 and 60: Diagnostic and therapeutic algorith
Page 61 and 62:
Bridging strategies in patients on
Page 64:
Practical manualof scores and algor
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Practical-Manual-Scores-Algorithms-Haemostasis-Thrombosis

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