2023
Differentiation of Spontaneous Bacterial Peritonitis from Secondary Peritonitis in Patients with Liver Cirrhosis: Retrospective Multicentre Study
Würstle S, Hapfelmeier A, Karapetyan S, Studen F, Isaakidou A, Schneider T, Schmid R, von Delius S, Gundling F, Burgkart R, Obermeier A, Mayr U, Ringelhan M, Rasch S, Lahmer T, Geisler F, Turner P, Chan B, Spinner C, Schneider J. Differentiation of Spontaneous Bacterial Peritonitis from Secondary Peritonitis in Patients with Liver Cirrhosis: Retrospective Multicentre Study. Diagnostics 2023, 13: 994. PMID: 36900138, PMCID: PMC10000989, DOI: 10.3390/diagnostics13050994.Peer-Reviewed Original ResearchSpontaneous bacterial peritonitisRetrospective multicentre studySecondary peritonitisLiver cirrhosisSBP episodesBacterial peritonitisMulticentre studySeverity of illnessHigh-risk groupAscitic fluid infectionSelection operator (LASSO) regression modelPeritonitis episodesLaboratory parametersFluid infectionSerious complicationsUnivariable analysisInfected ascitesClinicopathological parametersPeritonitisTreatment approachesCirrhosisAscitesPatientsGerman hospitalsPoint score
2022
Inhaled Bacteriophage Therapy for Multi-Drug Resistant Achromobacter.
Winzig F, Gandhi S, Lee A, Würstle S, Stanley G, Capuano I, Neuringer I, Koff J, Turner P, Chan B. Inhaled Bacteriophage Therapy for Multi-Drug Resistant Achromobacter. The Yale Journal Of Biology And Medicine 2022, 95: 413-427. PMID: 36568830, PMCID: PMC9765334.Peer-Reviewed Original ResearchConceptsCF patientsCystic fibrosisChronic pulmonary infectionGlobal public health threatBacterial lung infectionsChallenging clinical problemPublic health threatChronic bacterial lung infectionsPulmonary infectionRespiratory statusLung infectionClinical problemBacteriophage therapyInfectionAntimicrobial-resistant bacteriaTherapyHealth threatPhage therapyPatientsAMR infectionsResistant bacteriaLytic bacteriophagesPossible benefitsChemical antibioticsCurrent studyA Novel Machine Learning-Based Point-Score Model as a Non-Invasive Decision-Making Tool for Identifying Infected Ascites in Patients with Hydropic Decompensated Liver Cirrhosis: A Retrospective Multicentre Study
Würstle S, Hapfelmeier A, Karapetyan S, Studen F, Isaakidou A, Schneider T, Schmid R, von Delius S, Gundling F, Triebelhorn J, Burgkart R, Obermeier A, Mayr U, Heller S, Rasch S, Lahmer T, Geisler F, Chan B, Turner P, Rothe K, Spinner C, Schneider J. A Novel Machine Learning-Based Point-Score Model as a Non-Invasive Decision-Making Tool for Identifying Infected Ascites in Patients with Hydropic Decompensated Liver Cirrhosis: A Retrospective Multicentre Study. Antibiotics 2022, 11: 1610. PMID: 36421254, PMCID: PMC9686825, DOI: 10.3390/antibiotics11111610.Peer-Reviewed Original ResearchDecompensated liver cirrhosisInfected ascitesLiver cirrhosisPredictive valueHigh negative predictive valueRetrospective multicentre studySimilar predictive valuePre-test probabilityEpisodes of patientsFurther external validationNegative predictive valuePositive predictive valuePromising non-invasive approachLaboratory featuresMulticentre studyProspective studyAscitesCirrhosisPatientsNon-invasive approachClinical routineLASSO regression modelExternal validationAbdominocentesisRegression models