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Richter, Manuel J.

https://orcid.org/0000-0003-0964-1931

Mayo Clinic

Universitätsklinikum Gießen und Marburg

Citations 3

Alterations in Kidney Venous Flow in the Prognosis of Heart Failure
Singam, Sharma, Viehman, Jason K., Schulte, Philip, Bauer, Pascall, Tello, Khodr , Richter, Manuel J. , Birk, Horst‐Walter, Husain‐Syed, Faeq , Bauer, Pascal , Seeger, Werner , Gall, Henning , Ghofrani, Hossein Ardeschir , Kashani, Kianoush , Ronco, Claudio

Journal of the American Society of Nephrology | May 17, 2024 | Volume: 33 | Issue: 11S | Pages: 817-818

10.1681/asn.20223311s1817d Get It

Changes in Doppler‐Derived Kidney Venous Flow and Adverse Cardiorenal Outcomes in Patients With Heart Failure
Husain‐Syed, Faeq , Viehman, Jason K., Vaughan, Lisa E. , Bauer, Pascal , Gall, Henning , Tello, Khodr , Richter, Manuel J. , Yogeswaran, Athiththan , Romero‐González, Gregorio , Rosner, Mitchell H. , Aßmus, Birgit , Seeger, Werner , Birk, Horst‐Walter, Singam, N Sarma V , Vaughan, Lisa , Gall, Henning , Tello, Khodr , Yogeswaran, Athiththan , Romero-González, Gregorio , Ghofrani, Hossein Ardeschir , Seeger, Werner , Kashani, Kianoush B , Husain-Syed, Faeq , Singam, Narayana Sarma V. , Ronco, Claudio , Ghofrani, Hossein Ardeschir , Kashani, Kianoush

Journal of the American Heart Association | August 14, 2023 | Volume: 12 | Issue: 16 | Pages: No page available

10.1161/jaha.123.030145 Get It

Background The impact of changes in Doppler‐derived kidney venous flow in heart failure (HF) is not well studied. We aimed to investigate the association of Doppler‐derived kidney venous stasis index (KVSI) and intrakidney venous‐flow (IKVF) patterns with adverse cardiorenal outcomes in patients with HF. Methods and Results In this observational cohort study, consecutive inpatients with HF referred to a nephrologist because of a history of diuretic resistance and abnormal kidney function (n=216) underwent spectral kidney assessments after admission (Doppler 1) and 25 to 35 days later (Doppler 2) to identify IKVF patterns (continuous/pulsatile/biphasic/monophasic) and KVSI levels. Cox proportional hazard regression models were used to evaluate the associations between KVSI/IKVF patterns at Doppler 1 as well as changes from Doppler 1 to Doppler 2 and risk of cardiorenal events up to 18 months after admission. Worsening HF or death occurred in 126 patients. Both baseline KVSI (hazard ratio [HR], 1.49 [95% CI, 1.37–1.61] per 0.1‐unit increase) and baseline IKVF pattern (HR, 2.47 [95% CI, 2.01–3.04] per 1 pattern severity increase) were significantly associated with worsening HF/death. Increases in both KVSI and IKVF pattern severity from Doppler 1 to 2 were also associated with an increased risk of worsening HF/death (HR, 3.00 [95% CI, 2.08–4.32] per 0.1‐unit increase change; and HR, 6.73 [95% CI, 3.27–13.86] per 1 pattern increase in severity change, respectively). Similar results were observed for kidney outcomes. Conclusions Baseline kidney venous flow predicted adverse cardiorenal events, and inclusion of serial kidney venous flow in cardiorenal risk stratification could facilitate clinical decision‐making for patients with HF. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03039959.
Pulmonary Vascular Research Institute GoDeep: A meta‐registry merging deep phenotyping datafrom international PH reference centers
Majeed, Raphael W. , Anthi, Anastasia , Cannon, John, Chan, Stephen Y. , Damonte, Victoria , Elwing, Jean , Förster, Kai , Ghouleh, Imad Al , Juaneda, Ernesto , Kiely, David G. , Orfanos, Stylianos E. , Pepe, Antonella, Sіrenko, Yu.M. , Swett, Andrew J., Zamanian, Roham T. , Marquardt, Kurt , Michel‐Backofen, Achim, Antoine, Tobiah, Wilhelm, Jochen , Barwick, Stephanie , Krieb, Phillipp, Fuenderich, Meike, Ghofrani, Hossein‐Ardeschir, Tello, Khodr , Richter, Manuel J. , Seeger, Werner , Sweatt, Andrew J. , Chan, Stephen Y , Frantz, Robert P , Jose, Arun , Lawrie, Allan , Gall, Henning , Seeger, Werner , Kiely, David , Majeed, Raphael W , Wilkins, Martin R. , Howard, Luke , Hassoun, Paul M. , Cajigas, Héctor , Frantz, Robert P. , Ghio, Stefano , Hilgendorff, Anne , Jose, Arun , Pepe, Antonella, Pepke‐Żaba, Joanna , Torbas, O.O. , Michel-Backofen, Achim, Barwick, Stephanie, Fünderich, Meike , Fischer, Patrick, Gall, Henning , Ghofrani, Hossein‐Ardeschir, Grimminger, Friedrich

Pulmonary Circulation | August 3, 2022 | Volume: 12 | Issue: 3 | Pages: No page available

10.1002/pul2.12123 Get It

AbstractThe Pulmonary Vascular Research Institute GoDeep meta‐registry is a collaboration of pulmonary hypertension (PH) reference centers across the globe. Merging worldwide PH data in a central meta‐registry to allow advanced analysis of the heterogeneity of PH and its groups/subgroups on a worldwide geographical, ethnical, and etiological landscape (ClinTrial. gov NCT05329714). Retrospective and prospective PH patient data (diagnosis based on catheterization; individuals with exclusion of PH are included as a comparator group) are mapped to a common clinical parameter set of more than 350 items, anonymized and electronically exported to a central server. Use and access is decided by the GoDeep steering board, where each center has one vote. As of April 2022, GoDeep comprised 15,742 individuals with 1.9 million data points from eight PH centers. Geographic distribution comprises 3990 enrollees (25%) from America and 11,752 (75%) from Europe. Eighty‐nine perecent were diagnosed with PH and 11% were classified as not PH and provided a comparator group. The retrospective observation period is an average of 3.5 years (standard error of the mean 0.04), with 1159 PH patients followed for over 10 years. Pulmonary arterial hypertension represents the largest PH group (42.6%), followed by Group 2 (21.7%), Group 3 (17.3%), Group 4 (15.2%), and Group 5 (3.3%). The age distribution spans several decades, with patients 60 years or older comprising 60%. The majority of patients met an intermediate risk profile upon diagnosis. Data entry from a further six centers is ongoing, and negotiations with >10 centers worldwide have commenced. Using electronic interface‐based automated retrospective and prospective data transfer, GoDeep aims to provide in‐depth epidemiological and etiological understanding of PH and its various groups/subgroups on a global scale, offering insights for improved management.