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Book ; Thesis: Energieumsatz und Substratstoffwechsel im Rahmen des Postaggressionssyndroms bei Kindern nach korrigierenden Herzoperationen

Hinterseer, Martin

1996

Author's details	vorgelegt von Martin Hinterseer
Language	German
Size	82 Bl. : graph. Darst.
Edition	[Mikrofiche-Ausg.]
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Erlangen-Nürnberg, Univ., Diss., 1996
Note	Mikrofiche-Ausg.: 1 Mikrofiche : 24x
HBZ-ID	HT007389616
Database	Catalogue ZB MED Medicine, Health

In stock of ZB MED Cologne/Königswinter

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1997 MB 59	order for loan	Magazin

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Article ; Online: App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data.

Zens, Martin / Brammertz, Arne / Herpich, Juliane / Südkamp, Norbert / Hinterseer, Martin

Journal of medical Internet research

2020 Volume 22, Issue 9, Page(s) e21956

Abstract: Background: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients.: Objective: To determine the distribution ... ...

Abstract	Background: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. Objective: To determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. Methods: The COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. Results: In total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. Conclusions: Self-reported symptom tracking helps to identify novel symptoms of COVID-19 and to estimate the predictive value of certain symptoms. This aids in the development of reliable screening tools. Clinical screening with a high pretest probability allows for the rapid identification of infections and the cost-effective use of testing resources. Based on our results, we suggest that loss of smell and taste be considered cardinal symptoms; we also stress that diabetes is a risk factor for a highly symptomatic course of COVID-19 infection.
MeSH term(s)	Adult ; Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnosis ; Diabetes Mellitus ; Early Diagnosis ; Female ; Humans ; Male ; Mass Screening/methods ; Middle Aged ; Mobile Applications ; Pandemics ; Pneumonia, Viral/diagnosis ; Risk Factors ; SARS-CoV-2 ; Self Report
Keywords	covid19
Language	English
Publishing date	2020-09-09
Publishing country	Canada
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2028830-X
ISSN	1438-8871 ; 1439-4456
ISSN (online)	1438-8871
ISSN	1439-4456
DOI	10.2196/21956
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: App-Based Tracking of Self-Reported COVID-19 Symptoms

Zens, Martin / Brammertz, Arne / Herpich, Juliane / Südkamp, Norbert / Hinterseer, Martin

Journal of Medical Internet Research, Vol 22, Iss 9, p e

Analysis of Questionnaire Data

2020 Volume 21956

Abstract: BackgroundCOVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. ObjectiveTo determine the distribution pattern of ...

Abstract	BackgroundCOVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. ObjectiveTo determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. MethodsThe COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. ResultsIn total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. ...
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Public aspects of medicine ; RA1-1270
Subject code	150
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data

Zens, Martin / Brammertz, Arne / Herpich, Juliane / Südkamp, Norbert / Hinterseer, Martin

J Med Internet Res

Abstract: BACKGROUND: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. OBJECTIVE: To determine the distribution ... ...

Abstract	BACKGROUND: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. OBJECTIVE: To determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. METHODS: The COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. RESULTS: In total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. CONCLUSIONS: Self-reported symptom tracking helps to identify novel symptoms of COVID-19 and to estimate the predictive value of certain symptoms. This aids in the development of reliable screening tools. Clinical screening with a high pretest probability allows for the rapid identification of infections and the cost-effective use of testing resources. Based on our results, we suggest that loss of smell and taste be considered cardinal symptoms; we also stress that diabetes is a risk factor for a highly symptomatic course of COVID-19 infection.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #714499
Database	COVID19

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Article ; Online: App-based tracking of self-reported COVID-19 symptoms

Zens, Martin / Brammertz, Arne / Herpich, Juliane / Südkamp, Norbert / Hinterseer, Martin

Journal of medical internet research. - 22,

analysis of questionnaire data

2020 Volume 9, Issue , e21956, ISSN: 1438-8871

Abstract	Background: COVID-19 is an infectious disease characterized by various clinical presentations. Knowledge of possible symptoms and their distribution allows for the early identification of infected patients. Objective: To determine the distribution pattern of COVID-19 symptoms as well as possible unreported symptoms, we created an app-based self-reporting tool. Methods: The COVID-19 Symptom Tracker is an app-based daily self-reporting tool. Between April 8 and May 15, 2020, a total of 22,327 individuals installed this app on their mobile device. An initial questionnaire asked for demographic information (age, gender, postal code) and past medical history comprising relevant chronic diseases. The participants were reminded daily to report whether they were experiencing any symptoms and if they had been tested for SARS-CoV-2 infection. Participants who sought health care services were asked additional questions regarding diagnostics and treatment. Participation was open to all adults (≥18 years). The study was completely anonymous. Results: In total, 11,829 (52.98%) participants completed the symptom questionnaire at least once. Of these, 291 (2.46%) participants stated that they had undergone an RT-PCR (reverse transcription-polymerase chain reaction) test for SARS-CoV-2; 65 (0.55%) reported a positive test result and 226 (1.91%) a negative one. The mean number of reported symptoms among untested participants was 0.81 (SD 1.85). Participants with a positive test result had, on average, 5.63 symptoms (SD 2.82). The most significant risk factors were diabetes (odds ratio [OR] 8.95, 95% CI 3.30-22.37) and chronic heart disease (OR 2.85, 95% CI 1.43-5.69). We identified chills, fever, loss of smell, nausea and vomiting, and shortness of breath as the top five strongest predictors for a COVID-19 infection. The odds ratio for loss of smell was 3.13 (95% CI 1.76-5.58). Nausea and vomiting (OR 2.84, 95% CI 1.61-5.00) had been reported as an uncommon symptom previously; however, our data suggest a significant predictive value. Conclusions: Self-reported symptom tracking helps to identify novel symptoms of COVID-19 and to estimate the predictive value of certain symptoms. This aids in the development of reliable screening tools. Clinical screening with a high pretest probability allows for the rapid identification of infections and the cost-effective use of testing resources. Based on our results, we suggest that loss of smell and taste be considered cardinal symptoms; we also stress that diabetes is a risk factor for a highly symptomatic course of COVID-19 infection.
Keywords	COVID-19 ; Symptom ; Verfolgung ; App (Programm) ; Überwachung ; Verteilung ; Screening ; covid19
Subject code	150
Language	English
Publishing country	de
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Acute myocardial infarction due to coronary stent thrombosis in a symptomatic COVID-19 patient.

Hinterseer, Martin / Zens, Martin / Wimmer, Roland Jean / Delladio, Simon / Lederle, Susanne / Kupatt, Christian / Hartmann, Bernd

Clinical research in cardiology : official journal of the German Cardiac Society

2020 Volume 110, Issue 2, Page(s) 302–306

MeSH term(s)	Aged ; COVID-19/physiopathology ; Coronary Disease/therapy ; Coronary Thrombosis/complications ; Humans ; Male ; Myocardial Infarction/etiology ; Stents
Keywords	covid19
Language	English
Publishing date	2020-05-19
Publishing country	Germany
Document type	Case Reports ; Letter ; Research Support, Non-U.S. Gov't
ZDB-ID	2213295-8
ISSN	1861-0692 ; 1861-0684
ISSN (online)	1861-0692
ISSN	1861-0684
DOI	10.1007/s00392-020-01663-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Acute myocardial infarction due to coronary stent thrombosis in a symptomatic COVID-19 patient

Hinterseer, Martin / Zens, Martin / Wimmer, Roland Jean / Delladio, Simon / Lederle, Susanne / Kupatt, Christian / Hartmann, Bernd

Clin. res. cardiol

Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #306139
Database	COVID19

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Article ; Online: Acute myocardial infarction due to coronary stent thrombosis in a symptomatic COVID-19 patient

Hinterseer, Martin / Zens, Martin / Wimmer, Roland Jean / Delladio, Simon / Lederle, Susanne / Kupatt, Christian / Hartmann, Bernd

Clinical Research in Cardiology ; ISSN 1861-0684 1861-0692

2020

Keywords	Cardiology and Cardiovascular Medicine ; General Medicine ; covid19
Language	English
Publisher	Springer Science and Business Media LLC
Publishing country	us
Document type	Article ; Online
DOI	10.1007/s00392-020-01663-4
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Thesis: Energieumsatz und Substratstoffwechsel im Rahmen des Postaggressionssyndroms bei Kindern nach korrigierenden Herzoperationen

Hinterseer, Martin

1996

Author's details	Martin Hinterseer
Language	German
Size	1 Mikrofiche, graph. Darst
Document type	Book ; Thesis
Thesis / German Habilitation thesis	Nürnberg, Univ., Diss.--Erlangen, 1996
Database	Former special subject collection: coastal and deep sea fishing

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Article: Sotalol testing unmasks altered repolarization in patients with suspected acquired long-QT-syndrome--a case-control pilot study using i.v. sotalol.

Kääb, Stefan / Hinterseer, Martin / Näbauer, Michael / Steinbeck, Gerhard

European heart journal

2003 Volume 24, Issue 7, Page(s) 649–657

Abstract: Aims: The aim of this pilot study was to evaluate provocative sotalol testing to unmask abnormal repolarization due to altered myocardial electrical properties as the key feature in acquired Long-QT-Syndrome. Reliable diagnosis and risk stratification ... ...

Abstract	Aims: The aim of this pilot study was to evaluate provocative sotalol testing to unmask abnormal repolarization due to altered myocardial electrical properties as the key feature in acquired Long-QT-Syndrome. Reliable diagnosis and risk stratification for the individual patient are complicated by the multitude of mechanisms involved in acquired QT-prolongation. The combined influence of all components determines susceptibility to arrhythmias related to QT-prolongation. Methods: Twenty consecutive patients who had experienced torsades de pointes in association with QT-prolonging drugs were tested with i.v. D,L-sotalol (2mg/kg) with 24-h intensive care monitoring to evaluate the repolarization process by determining QT- and QTc-prolongations. Results were compared to age and sex matched controls. Results: At baseline, no differences between control and study population with regard to QT and QTc were detected. After sotalol infusion, QTc increased from 422+/-17 to 450+/-22ms in controls and from 434+/-20 to 541+/-37ms in the study population. Torsades de pointes occurred in three out of 20 patients (15%) in the study population but in none of the control patients following i.v. sotalol testing. Conclusions: Controlled exposure to sotalol successfully identifies patients with normal QTc intervals but altered myocardial repolarization. This may be useful for clarifying diagnosis and pathogenesis of acquired Long-QT-Syndrome.
MeSH term(s)	Adrenergic beta-Antagonists ; Adult ; Aged ; Case-Control Studies ; Electrocardiography ; Female ; Humans ; Long QT Syndrome/diagnosis ; Long QT Syndrome/physiopathology ; Male ; Middle Aged ; Pilot Projects ; Sotalol ; Statistics, Nonparametric
Chemical Substances	Adrenergic beta-Antagonists ; Sotalol (A6D97U294I)
Language	English
Publishing date	2003-01-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	603098-1
ISSN	1522-9645 ; 0195-668X
ISSN (online)	1522-9645
ISSN	0195-668X
DOI	10.1016/s0195-668x(02)00806-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

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