A. Podtschaske

827 total citations
28 papers, 595 citations indexed

About

A. Podtschaske is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Emergency Medicine. According to data from OpenAlex, A. Podtschaske has authored 28 papers receiving a total of 595 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 9 papers in Cardiology and Cardiovascular Medicine and 6 papers in Emergency Medicine. Recurrent topics in A. Podtschaske's work include Cardiac Arrest and Resuscitation (6 papers), Cardiac, Anesthesia and Surgical Outcomes (5 papers) and Hemodynamic Monitoring and Therapy (5 papers). A. Podtschaske is often cited by papers focused on Cardiac Arrest and Resuscitation (6 papers), Cardiac, Anesthesia and Surgical Outcomes (5 papers) and Hemodynamic Monitoring and Therapy (5 papers). A. Podtschaske collaborates with scholars based in Germany, United States and Italy. A. Podtschaske's co-authors include G. Kemming, O. Häbler, J. Hütter, M. Kleen, K. Meßmer, Carlos Otávio Corso, M. Welte, Simone Maria Kagerbauer, Jan Martin and Peter E. Keipert and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Applied Physiology.

In The Last Decade

A. Podtschaske

27 papers receiving 567 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
A. Podtschaske Germany 14 153 149 129 113 109 28 595
Michelle H. Scerbo United States 9 304 2.0× 65 0.4× 118 0.9× 350 3.1× 9 0.1× 12 710
Debra D. Pulley United States 8 85 0.6× 101 0.7× 17 0.1× 38 0.3× 6 0.1× 12 587
Naomi Nussinovitch Israel 14 14 0.1× 61 0.4× 18 0.1× 14 0.1× 19 0.2× 38 769
Rune Skovgaard Rasmussen Denmark 16 41 0.3× 10 0.1× 20 0.2× 22 0.2× 10 0.1× 45 690
Gregory J. Zarow United States 14 402 2.6× 17 0.1× 7 0.1× 277 2.5× 10 0.1× 33 805
Gillian Burrows United Kingdom 14 33 0.2× 14 0.1× 6 0.0× 68 0.6× 8 0.1× 26 683
R. D. Piper Australia 11 81 0.5× 4 0.0× 14 0.1× 26 0.2× 9 0.1× 16 539
Lini Zhang United States 13 393 2.6× 59 0.4× 3 0.0× 39 0.3× 12 0.1× 16 1.4k
Youn Jin Kim South Korea 16 20 0.1× 7 0.0× 54 0.4× 9 0.1× 59 0.5× 86 778
Miłośz Czuba Poland 19 18 0.1× 4 0.0× 341 2.6× 15 0.1× 14 0.1× 59 1.2k

Countries citing papers authored by A. Podtschaske

Since Specialization
Citations

This map shows the geographic impact of A. Podtschaske's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by A. Podtschaske with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Podtschaske more than expected).

Fields of papers citing papers by A. Podtschaske

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. Podtschaske. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by A. Podtschaske. The network helps show where A. Podtschaske may publish in the future.

Co-authorship network of co-authors of A. Podtschaske

This figure shows the co-authorship network connecting the top 25 collaborators of A. Podtschaske. A scholar is included among the top collaborators of A. Podtschaske based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with A. Podtschaske. A. Podtschaske is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kagerbauer, Simone Maria, Bernhard Ulm, Gerhard Schneider, et al.. (2024). Implementation of a software-based decision support tool for guideline-appropriate preoperative evaluation: a prospective agreement study. British Journal of Anaesthesia. 133(3). 519–529. 1 indexed citations
2.
Kagerbauer, Simone Maria, et al.. (2024). Susceptibility of AutoML mortality prediction algorithms to model drift caused by the COVID pandemic. BMC Medical Informatics and Decision Making. 24(1). 34–34. 1 indexed citations
3.
Kagerbauer, Simone Maria, Manfred Blobner, Gerhard Schneider, et al.. (2024). Anaesthesiologists’ guideline adherence in pre-operative evaluation: a retrospective observational study. SHILAP Revista de lepidopterología. 13(1). 64–64. 1 indexed citations
4.
Jungwirth, Bettina, Stefan J. Schaller, E. Kochs, et al.. (2023). Enabling personalized perioperative risk prediction by using a machine-learning model based on preoperative data. Scientific Reports. 13(1). 7128–7128. 10 indexed citations
5.
Ulm, Bernhard, et al.. (2023). Impact of the Covid-19 pandemic on the performance of machine learning algorithms for predicting perioperative mortality. BMC Medical Informatics and Decision Making. 23(1). 67–67. 4 indexed citations
6.
Lange, Nicole, A. Podtschaske, Jan Martin, et al.. (2022). Anterior Pituitary Hormones in Blood and Cerebrospinal Fluid of Patients in Neurocritical Care. PubMed. 18(1). 71–71. 1 indexed citations
7.
Podtschaske, A., Jan Martin, Bernhard Ulm, Bettina Jungwirth, & Simone Maria Kagerbauer. (2022). Sex-specific issues of central and peripheral arginine-vasopressin concentrations in neurocritical care patients. BMC Neuroscience. 23(1). 69–69.
8.
Kagerbauer, Simone Maria, et al.. (2019). Influence of sex and hormonal status on initial impact and neurocognitive outcome after subarachnoid haemorrhage in rats. Behavioural Brain Research. 363. 13–22. 3 indexed citations
9.
Martin, Jan, et al.. (2019). Weak correlations between serum and cerebrospinal fluid levels of estradiol, progesterone and testosterone in males. BMC Neuroscience. 20(1). 53–53. 13 indexed citations
10.
Kagerbauer, Simone Maria, Jan Martin, Jens Gempt, et al.. (2019). Absence of a diurnal rhythm of oxytocin and arginine-vasopressin in human cerebrospinal fluid, blood and saliva. Neuropeptides. 78. 101977–101977. 27 indexed citations
11.
Kubitz, Jens C., et al.. (2006). The influence of PEEP and tidal volume on central blood volume. European Journal of Anaesthesiology. 23(11). 954–961. 14 indexed citations
12.
Kubitz, Jens C., et al.. (2005). The influence of cardiac preload and positive end-expiratory pressure on the pre-ejection period. Physiological Measurement. 26(6). 1033–1038. 7 indexed citations
13.
Häbler, O., M. Kleen, A. Podtschaske, et al.. (2000). Akute normovolämische Hämodilution (ANH). Der Anaesthesist. 49(11). 939–948. 9 indexed citations
14.
Podtschaske, A., et al.. (1998). Normovolaemic haemodilution and hyperoxia have no effect on fractal dimension of regional myocardial perfusion in dogs. Acta Physiologica Scandinavica. 162(4). 439–446. 10 indexed citations
15.
Häbler, O., M. Kleen, J. Hütter, et al.. (1998). Effects of hyperoxic ventilation on hemodilution‐induced changes in anesthetized dogs. Transfusion. 38(2). 135–144. 62 indexed citations
16.
17.
Häbler, O., M. Kleen, J. Hütter, et al.. (1997). IV Perflubron emulsion versus autologous transfusion in severe normovolemic anemia: effects on left ventricular perfusion and function. Research in Experimental Medicine. 197(6). 301–318. 34 indexed citations
18.
Kleen, M., O. Häbler, J. Hütter, et al.. (1997). Effects of hemodilution on splanchnic perfusion and hepatorenal function. I. Splanchnic perfusion.. PubMed. 2(10). 413–8. 27 indexed citations
19.
Häbler, O., M. Kleen, A. Podtschaske, et al.. (1996). The Effect of Acute Normovolemic Hemodilution (ANH) on Myocardial Contractility in Anesthetized Dogs. Anesthesia & Analgesia. 83(3). 451–458. 56 indexed citations
20.
Kleen, M., O. Häbler, J. Hütter, et al.. (1996). Effects of hemodilution on gastric regional perfusion and intramucosal pH. American Journal of Physiology-Heart and Circulatory Physiology. 271(5). H1849–H1855. 15 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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