| Literature DB >> 32642834 |
T Mathiesen1,2,3, M Arraez4, T Asser5, N Balak6, S Barazi7, C Bernucci8, C Bolger9, M L D Broekman10,11, A K Demetriades12, Z Feldman13, M M Fontanella14, N Foroglou15, J Lafuente16, A D Maier17,18, B Meyer19, M Niemelä20, P H Roche21, F Sala22, N Samprón23, U Sandvik24,25, K Schaller26, C Thome27, M Thys28, M Tisell29, P Vajkoczy30, M Visocchi31.
Abstract
BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or Covid-19), which began as an epidemic in China and spread globally as a pandemic, has necessitated resource management to meet emergency needs of Covid-19 patients and other emergent cases. We have conducted a survey to analyze caseload and measures to adapt indications for a perception of crisis.Entities:
Keywords: Covid-19; Epidemic; Europe; Healthcare management; Neurosurgery; Pandemic; SARS-CoV-2
Mesh:
Year: 2020 PMID: 32642834 PMCID: PMC7343382 DOI: 10.1007/s00701-020-04482-8
Source DB: PubMed Journal: Acta Neurochir (Wien) ISSN: 0001-6268 Impact factor: 2.216
Centers, catchment area, assessment whether all medical needs can be met, limitation of treatment indications between December and March, same, increased or decreased activity, and number of regular neurosurgical and intensive care beds. The national burden of Covid-19 is outlined below, as is the subjective evaluation of the local Covid-19 situation: stable/difficult, extreme, or desperate
| Center | Catchment area(in millions) | Care for all needs (yes = y, no = n) | Indications(same or limitedin March) | Activity (craniotomies in December vs. March) | Regular and intermediate beds (beds/catchment area in millions) | ICU beds (beds/catchment area in millions) | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| December | March | SAH | TBI | Tumor | December | March | December | March | |||
| 1# | 1.0 | y | n | Same | ↓ | ↓ | ↓ | 63 | 36 | 20 | 11 |
| 2# | 0.8 | y | n | Same | ↑ | ↓ | ↓ | 45 | 19 | Not available | |
| 3# | 1.0 | y | y | Same | → | → | → | 40 | 40 | 12 | 12 |
| 4# | 0.8′ | y | n | Same | → | ↓ | ↓ | 34 | 20 | 11 | 4 |
| 9# | 2.0 | y | n | Same | → | → | → | 15 | 10 | 4 | 4 |
| 15## | 1.0 | y | n | Limited | ↓ | ↓ | ↓ | 30 | 8 | 1 | 0.2 |
| 16# | 2.0 | n | n | Limited | → | ↓ | ↓ | 3 | 3 | 4 | 4 |
| 17# | 1.9 | n | n | Limited | ↑ | → | → | 13 | 9 | 3 | 3 |
| 18## | 0.5 | y | y | Limited | ↓ | ↓ | ↓ | 70 | 28 | 14 | 4 |
| 19# | 2.2 | y | y | Same | → | ↓ | ↓ | 22 | 22 | 6 | 5 |
| 20# | 2.5 | y | n | Same | ↑ | → | ↑ | 16 | 12 | 6 | 8 |
| 23## | 0.5 | y | n | Limited | ↓ | ↓ | ↓ | 60 | 20 | 16 | 4 |
| 24## | 4.0 | y | n | Same | → | → | ↑ | 18 | 18 | 5 | 5 |
| 25# | 3.7 | y | y | Same | ↓ | → | ↓ | 23 | 16 | 8 | 7 |
*= > 500 deaths by Covid-19 per million or > 4000 Covid-19 diagnoses per million
# = stable, manage with some measures; ## = extreme situation, manage with difficulties; ### = desperate situation