| Literature DB >> 20958968 |
Nele Brusselaers1, Stan Monstrey, Dirk Vogelaers, Eric Hoste, Stijn Blot.
Abstract
INTRODUCTION: Burn injury is a serious pathology, potentially leading to severe morbidity and significant mortality, but it also has a considerable health-economic impact. The aim of this study was to describe the European hospitalized population with severe burn injury, including the incidence, etiology, risk factors, mortality, and causes of death.Entities:
Mesh:
Year: 2010 PMID: 20958968 PMCID: PMC3219295 DOI: 10.1186/cc9300
Source DB: PubMed Journal: Crit Care ISSN: 1364-8535 Impact factor: 9.097
States and territories of Europe (as reported by the Population Reference Bureau, used by the United Nations when categorizing geographic subregions)
| Country | Capital city or largest city | ||
|---|---|---|---|
| Belarus | 9.7 | 0.826 | Minsk |
| bBulgaria | 7.6 | 0.840 | Sofia |
| bCzech Republic | 10.5 | 0.903 | Prague |
| bHungary | 10.0 | 0.879 | Budapest |
| Moldova | 4.1 | 0.720 | Chisinau |
| bPoland | 38.1 | 0.880 | Warsaw |
| bRomania | 21.5 | 0.837 | Bucharest |
| Russian Federation | 141.8 | 0.817 | Moscow |
| bSlovakia | 5.4 | 0.880 | Bratislava |
| Ukraine | 46.0 | 0.796 | Kiev |
| bDenmark | 5.5 | 0.955 | Copenhagen |
| bEstonia | 1.3 | 0.883 | Tallinn |
| bFinland | 5.3 | 0.959 | Helsinki |
| cIceland | 0.3 | 0.969 | Reykjavik |
| bIreland | 4.5 | 0.965 | Dublin (City) |
| bLatvia | 2.3 | 0.866 | Riga |
| bLithuania | 3.3 | 0.870 | Vilnius |
| cNorway | 4.8 | 0.971 | Oslo |
| bSweden | 9.3 | 0.963 | Stockholm |
| bUnited Kingdom | 61.8 | 0.947 | London |
| Albania | 3.2 | 0.818 | Tirana |
| Andorra | 0.1 | 0.934 | Andorra la Vella |
| Bosnia and Herzegovina | 3.8 | 0.812 | Sarajevo |
| Croatia (Hrvatska) | 4.4 | 0.871 | Zagreb |
| bCyprus | 1.1 | 0.914 | Nicosia (Lefkosia) |
| bGreece | 11.3 | 0.942 | Athens |
| Vatican City State | 0.001 | - | Vatican City |
| bItaly | 60.3 | 0.951 | Rome, Milan (Metro) |
| Macedonia, Rep. of | 2.0 | 0.817 | Skopje |
| bMalta | 0.4 | 0.902 | Valletta |
| Montenegro | 0.6 | 0.834 | Podgorica |
| bPortugal | 10.6 | 0.909 | Lisbon |
| San Marino | 0.03 | - | San Marino |
| Serbia | 7.3 | 0.826 | Belgrade |
| bSlovenia | 2.0 | 0.929 | Ljubljana |
| bSpain | 46.9 | 0.955 | Madrid |
| Turkey | 74.8 | 0.806 | Ankara, Istanbul |
| bAustria | 8.4 | 0.955 | Vienna (Wien) |
| bBelgium | 10.8 | 0.953 | Brussels |
| bFrance | 62.6 | 0.961 | Paris |
| bGermany | 82.0 | 0.947 | Berlin |
| cLiechtenstein | 0.04 | 0.951 | Vaduz |
| bLuxembourg | 0.5 | 0.960 | Luxembourg |
| Monaco | 0.04 | - | Monaco |
| bNetherlands | 16.5 | 0.964 | Amsterdam |
| cSwitzerland | 7.8 | 0.960 | Bern, Zürich |
Population numbers mid 2009; bmember states of the European Union (EU); cmember states of European Free Trade Association (EFTA); dHDI, Human Development Index (2009) [12]: three European microstates are not ranked in the 2009 HDI, for being unable or unwilling to provide the necessary data at the time of publication of the HDI ranking (although it could be expected to fall within the 'very high' HDI category).
Figure 1PRISMA Flow Diagram: description of the literature search.
Number of included studies for each country
| Region | Country | Number of studies | HDI (rank) |
|---|---|---|---|
| Eastern Europe | Czech Republic | 6 | .903 (36)b |
| Hungary | 1 | .879 (43)a | |
| Romania | 1 | .837 (63)a | |
| Slovakia | 2 | .880 (42)a | |
| Northern Europe | Denmark | 4 | .955 (16)b |
| Finland | 4 | .959 (12)b | |
| Iceland | 1 | .969 (3)b | |
| Ireland | 2 | .965 (5)b | |
| Lithuania | 1 | .870 (46)a | |
| Norway | 2 | .971 (1)b | |
| United Kingdom | 14 | .947 (21)b | |
| Sweden | 1 | .963 (7)b | |
| Southern Europe | Greece | 1 | .942 (25)b |
| Italy | 2 | .951 (18)b | |
| Portugal | 1 | .909 (34)b | |
| Spain | 12 | .955 (15)b | |
| Turkey | 3 | .806 (79)a | |
| Western Europe | Austria | 3 | .955 (14)b |
| Belgium | 2 | .953(17)b | |
| France | 7 | .961 (8)b | |
| Germany | 2 | .947 (22)b | |
| The Netherlands | 4 | .964 (6)b | |
| 76 | |||
The Human Development Index (HDI) Ranking is a classification of all countries worldwide based on life expectancy, literacy, education, and standards of living. Higher numbers are related to a higher development index (*a 'high' HDI, **b 'very high' HDI).
Figure 2Etiology of severe burn injury, according to the age group (proportion of all burns). Forty-one studies provided sufficient data to compare the etiologies. In the 'All' group, two of the 19 studies consider only adults. The 'pediatric' box plots are based on 14 studies; the 'elderly' box plots, on eight studies.
Figure 3The correlation between risk factors for mortality and mortality. (a) Total and adult populations with severe burn injury: correlation between the mean total burned surface and mortality. (TBSA, total burned surface area). (b) Elderly populations with severe burn injury: correlation between the mean total burned surface and mortality. (c) Total and adult population with severe burn injury: correlation between the mean age and the associated mortality.
Distribution of studies by Human Development Index (HDI)
| HDI | Number of studies | Number of countriesa | Number of inhabitants (×106)a |
|---|---|---|---|
| Very high | 68 (89.5%) | 24 (52.2%) | 423 (52.2%) |
| High | 8 (10.5%) | 17 (37.0%) | 377 (41.6%) |
| Medium | 0 | 2 (4.3%) | 50.1 (6.2%) |
| Low | 0 | 0 | 0 |
| Not known | 0 | 3 (6.5%) | 0.07 (0.0) |
| Total | 76 | 46 | 810 |
HDI, Human Development Index. acf. Table 1.