To defer or not to defer? A German longitudinal multicentric assessment of clinical practice in urology during the COVID-19 pandemic

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Abstract

Introduction

After the outbreak of COVID-19 unprecedented changes in the healthcare systems worldwide were necessary resulting in a reduction of urological capacities with postponements of consultations and surgeries.

Material and methods

An email was sent to 66 urological hospitals with focus on robotic surgery (RS) including a link to a questionnaire (e.g. bed/staff capacity, surgical caseload, protection measures during RS) that covered three time points: a representative baseline week prior to COVID-19, the week of March 16 ^th-22 ^nd and April 20 ^th-26 ^th 2020. The results were evaluated using descriptive analyses.

Results

27 out of 66 questionnaires were analyzed (response rate: 41%). We found a decrease of 11% in hospital beds and 25% in OR capacity with equal reductions for endourological, open and robotic procedures. Primary surgical treatment of urolithiasis and benign prostate syndrome (BPS) but also of testicular and penile cancer dropped by at least 50% while the decrease of surgeries for prostate, renal and urothelial cancer (TUR-B and cystectomies) ranged from 15 to 37%. The use of personal protection equipment (PPE), screening of staff and patients and protection during RS was unevenly distributed in the different centers–however, the number of COVID-19 patients and urologists did not reach double digits.

Conclusion

The German urological landscape has changed since the outbreak of COVID-19 with a significant shift of high priority surgeries but also continuation of elective surgical treatments. While screening and staff protection is employed heterogeneously, the number of infected German urologists stays low.

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Most cited references 24

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Clinical Characteristics of Coronavirus Disease 2019 in China

Wei-jie Guan, Zheng-yi Ni, Yu Hu … (2020)

Abstract Background Since December 2019, when coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China, data have been needed on the clinical characteristics of the affected patients. Methods We extracted data regarding 1099 patients with laboratory-confirmed Covid-19 from 552 hospitals in 30 provinces, autonomous regions, and municipalities in mainland China through January 29, 2020. The primary composite end point was admission to an intensive care unit (ICU), the use of mechanical ventilation, or death. Results The median age of the patients was 47 years; 41.9% of the patients were female. The primary composite end point occurred in 67 patients (6.1%), including 5.0% who were admitted to the ICU, 2.3% who underwent invasive mechanical ventilation, and 1.4% who died. Only 1.9% of the patients had a history of direct contact with wildlife. Among nonresidents of Wuhan, 72.3% had contact with residents of Wuhan, including 31.3% who had visited the city. The most common symptoms were fever (43.8% on admission and 88.7% during hospitalization) and cough (67.8%). Diarrhea was uncommon (3.8%). The median incubation period was 4 days (interquartile range, 2 to 7). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (CT) (56.4%). No radiographic or CT abnormality was found in 157 of 877 patients (17.9%) with nonsevere disease and in 5 of 173 patients (2.9%) with severe disease. Lymphocytopenia was present in 83.2% of the patients on admission. Conclusions During the first 2 months of the current outbreak, Covid-19 spread rapidly throughout China and caused varying degrees of illness. Patients often presented without fever, and many did not have abnormal radiologic findings. (Funded by the National Health Commission of China and others.)

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Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

Joel Hellewell, Sam Abbott, Amy Gimma … (2020)

Summary Background Isolation of cases and contact tracing is used to control outbreaks of infectious diseases, and has been used for coronavirus disease 2019 (COVID-19). Whether this strategy will achieve control depends on characteristics of both the pathogen and the response. Here we use a mathematical model to assess if isolation and contact tracing are able to control onwards transmission from imported cases of COVID-19. Methods We developed a stochastic transmission model, parameterised to the COVID-19 outbreak. We used the model to quantify the potential effectiveness of contact tracing and isolation of cases at controlling a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-like pathogen. We considered scenarios that varied in the number of initial cases, the basic reproduction number (R 0), the delay from symptom onset to isolation, the probability that contacts were traced, the proportion of transmission that occurred before symptom onset, and the proportion of subclinical infections. We assumed isolation prevented all further transmission in the model. Outbreaks were deemed controlled if transmission ended within 12 weeks or before 5000 cases in total. We measured the success of controlling outbreaks using isolation and contact tracing, and quantified the weekly maximum number of cases traced to measure feasibility of public health effort. Findings Simulated outbreaks starting with five initial cases, an R 0 of 1·5, and 0% transmission before symptom onset could be controlled even with low contact tracing probability; however, the probability of controlling an outbreak decreased with the number of initial cases, when R 0 was 2·5 or 3·5 and with more transmission before symptom onset. Across different initial numbers of cases, the majority of scenarios with an R 0 of 1·5 were controllable with less than 50% of contacts successfully traced. To control the majority of outbreaks, for R 0 of 2·5 more than 70% of contacts had to be traced, and for an R 0 of 3·5 more than 90% of contacts had to be traced. The delay between symptom onset and isolation had the largest role in determining whether an outbreak was controllable when R 0 was 1·5. For R 0 values of 2·5 or 3·5, if there were 40 initial cases, contact tracing and isolation were only potentially feasible when less than 1% of transmission occurred before symptom onset. Interpretation In most scenarios, highly effective contact tracing and case isolation is enough to control a new outbreak of COVID-19 within 3 months. The probability of control decreases with long delays from symptom onset to isolation, fewer cases ascertained by contact tracing, and increasing transmission before symptoms. This model can be modified to reflect updated transmission characteristics and more specific definitions of outbreak control to assess the potential success of local response efforts. Funding Wellcome Trust, Global Challenges Research Fund, and Health Data Research UK.

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Elective surgery cancellations due to the COVID ‐19 pandemic: global predictive modelling to inform surgical recovery plans

Dmitri Nepogodiev, Aneel Bhangu, Savino Spadaro … (2020)

Background The COVID‐19 pandemic has disrupted routine hospital services globally. This study estimated the total number of adult elective operations that would be cancelled worldwide during the 12 weeks of peak disruption due to COVID‐19. Methods A global expert‐response study was conducted to elicit projections for the proportion of elective surgery that would be cancelled or postponed during the 12 weeks of peak disruption. A Bayesian beta‐regression model was used to estimate 12‐week cancellation rates for 190 countries. Elective surgical case‐mix data, stratified by specialty and indication (cancer versus benign surgery), was determined. This case‐mix was applied to country‐level surgical volumes. The 12‐week cancellation rates were then applied to these figures to calculate total cancelled operations. Results The best estimate was that 28,404,603 operations would be cancelled or postponed during the peak 12 weeks of disruption due to COVID‐19 (2,367,050 operations per week). Most would be operations for benign disease (90.2%, 25,638,922/28,404,603). The overall 12‐week cancellation rate would be 72.3%. Globally, 81.7% (25,638,921/31,378,062) of benign surgery, 37.7% (2,324,069/6,162,311) of cancer surgery, and 25.4% (441,611/1,735,483) of elective Caesarean sections would be cancelled or postponed. If countries increase their normal surgical volume by 20% post‐pandemic, it would take a median 45 weeks to clear the backlog of operations resulting from COVID‐19 disruption. Conclusions A very large number of operations will be cancelled or postponed due to disruption caused by COVID‐19. Governments should mitigate against this major burden on patients by developing recovery plans and implementing strategies to safely restore surgical activity. This article is protected by copyright. All rights reserved.

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Author and article information

Contributors

Nina N. Harke:

ORCID: http://orcid.org/0000-0002-6154-7101

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draft

Jan P. Radtke: Role: Data curationRole: SupervisionRole: Writing – review & editing

Boris A. Hadaschik: Role: SupervisionRole: Writing – review & editing

Christian Bach: Role: Data curationRole: Writing – review & editing

Frank P. Berger: Role: Data curationRole: Writing – review & editing

Andreas Blana: Role: Data curationRole: Writing – review & editing

Hendrik Borgmann: Role: Data curationRole: Writing – review & editing

Florian A. Distler: Role: Data curationRole: Writing – review & editing

Sebastian Edeling: Role: Data curation

Tobias Egner: Role: Data curationRole: Writing – review & editing

Christina L. Engels: Role: Data curationRole: Writing – review & editing

Mahmoud Farzat: Role: Data curationRole: Writing – review & editing

Alexander Haese: Role: Data curationRole: Writing – review & editing

Rainer Hein: Role: Data curationRole: Writing – review & editing

Markus A. Kuczyk: Role: SupervisionRole: Writing – review & editing

Andreas Manseck:

ORCID: http://orcid.org/0000-0001-7366-4586

Role: Data curationRole: Writing – review & editing

Rudolf Moritz: Role: Data curationRole: Writing – review & editing

Michael Musch: Role: Data curationRole: Writing – review & editing

Inga Peters: Role: Data curationRole: Writing – review & editing

Sasa Pokupic: Role: Data curationRole: Writing – review & editing

Bernardo Rocco: Role: ConceptualizationRole: Writing – review & editing

Andreas Schneider: Role: Data curationRole: Writing – review & editing

André Schumann: Role: Data curationRole: Writing – review & editing

Christian Schwentner: Role: Data curationRole: Writing – review & editing

Chiara M. Sighinolfi: Role: ConceptualizationRole: Writing – review & editing

Stephan Buse: Role: Data curationRole: Writing – review & editing

Jens-Uwe Stolzenburg: Role: Data curationRole: Writing – review & editing

Michael C. Truß: Role: Data curationRole: Writing – review & editing

Michael Waldner: Role: Data curationRole: Writing – review & editing

Christian Wülfing: Role: Data curationRole: Writing – review & editing

Volker Zimmermanns: Role: Data curationRole: Writing – review & editing

Jörn H. Witt: Role: ConceptualizationRole: Data curationRole: SupervisionRole: Writing – review & editing

Christian Wagner: Role: ConceptualizationRole: SupervisionRole: Writing – review & editing

Neal Shore: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 15 September 2020

Publication date Collection: 2020

Publication date PMC-release: 15 September 2020

Volume: 15

Issue: 9

Electronic Location Identifier: e0239027

Affiliations

[1 ] Department of Urology and Urologic Oncology, Hanover Medical School, Hanover, Germany

[2 ] Department of Urology, University of Duisburg-Essen, Essen, Germany

[3 ] Department of Urology, RWTH Aachen University, Aachen, Germany

[4 ] Department of Urology, University of Jena, Jena, Germany

[5 ] Department of Urology, Fürth Hospital, Fürth, Germany

[6 ] Department of Urology, Johannes Gutenberg University Medical Center, Mainz, Germany

[7 ] Department of Urology, Paracelsus Medical University, Nuremberg, Germany

[8 ] Department of Urology, Da Vinci Zentrum, Hanover, Germany

[9 ] Department of Urology, Klinikum Würzburg Mitte, Würzburg, Germany

[10 ] Department of Urology, Municipal Hospital Karlsruhe, Karlsruhe, Germany

[11 ] Department of Urology, Diakonie Klinikum, Siegen, Germany

[12 ] Martini-Klinik Prostate Cancer Center, University Clinic Hamburg-Eppendorf, Hamburg, Germany

[13 ] Department of Urology, Klinikum Magdeburg, Magdeburg, Germany

[14 ] Department of Urology, Klinikum Ingolstadt, Ingolstadt, Germany

[15 ] Department of Urology, Marien Hospital, Ruhr-University Bochum, Herne, Germany

[16 ] Department of Urology, Pediatric Urology and Urologic Oncology, Kliniken Essen-Mitte, Essen, Germany

[17 ] Department of Urology, Asklepios Klinikum Harburg, Hamburg, Germany

[18 ] Department of Urology, University of Modena and Reggio Emilia, Modena, Italy

[19 ] Department of Urology, Main-Kinzig-Kliniken Standort Gelnhausen, Gelnhausen, Germany

[20 ] Department of Urology and Kidney Transplantation, Martin Luther University, Halle (Saale), Germany

[21 ] Department of Urology, Diakonieklinikum Stuttgart, Stuttgart, Germany

[22 ] Department of Urology and Urologic Oncology, Alfried Krupp Krankenhaus, Essen, Germany

[23 ] Department of Urology, University of Leipzig, Leipzig, Germany

[24 ] Department of Urology, Klinikum Dortmund, Dortmund, Germany

[25 ] Department of Urology, St. Elisabeth Krankenhaus Köln-Hohenlind, Köln, Germany

[26 ] Department of Urology, Asklepios Klinik Altona, Hamburg, Germany

[27 ] Department of Urology, Siloah St. Trudpert Klinikum, Pforzheim, Germany

[28 ] Department of Urology, Pediatric Urology and Urologic Oncology, Prostate Center Northwest, St. Antonius Hospital Gronau, Gronau, Germany

Carolina Urologic Research Center, UNITED STATES

Author notes

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: harkenina@ 123456gmail.com

Author information

Nina N. Harke http://orcid.org/0000-0002-6154-7101

Andreas Manseck http://orcid.org/0000-0001-7366-4586

Article

Publisher ID: PONE-D-20-20369

DOI: 10.1371/journal.pone.0239027

PMC ID: 7491711

PubMed ID: 32931510

SO-VID: 3c48b6d9-1ba9-4f44-b478-f7b2e0d34f89

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 1 July 2020

Date accepted : 30 August 2020

Page count

Figures: 4, Tables: 0, Pages: 11

Funding

The author(s) received no specific funding for this work

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Data Availability All relevant data are within the manuscript and its Supporting Information files.

Outbreaks COVID-19

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To defer or not to defer? A German longitudinal multicentric assessment of clinical practice in urology during the COVID-19 pandemic

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Abstract

Introduction

Material and methods

Results

Conclusion

Related collections

PLOS: COVID-19 pandemic

Most cited references 24

Clinical Characteristics of Coronavirus Disease 2019 in China

Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts

Elective surgery cancellations due to the COVID ‐19 pandemic: global predictive modelling to inform surgical recovery plans

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Cited by 5

Most referenced authors 1,577