Tabla I. Análisis descriptivo de los ingresos hospitalarios con el diagnóstico principal de la CIE-9-MC 340, en los 278 municipios de Portugal continental, global y anualmente, entre 2002 y 2013. |
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n |
Tasa máxima |
Tasa mínima |
Tasa |
Tasa |
DE de |
|
2002 |
789 (8,5%) |
596 (Vila Nova de Paiva; 3) |
0 (125; 45%) |
77 |
37 |
103 |
2003 |
912 (9,8%) |
1.229 (Figueiró dos Vinhos; 8) |
0 (117; 42,1%) |
97 |
42 |
154 |
2004 |
1.044 (11,3%) |
1.146 (Batalha; 18) |
0 (106; 38,1%) |
107 |
60 |
156 |
2005 |
970 (10,5%) |
1.635 (Marinha Grande; 19) |
0 (112; 40,3%) |
108 |
45 |
186 |
2006 |
731 (7,9%) |
1.079 (Fornos de Algodres; 6) |
0 (126; 45,3%) |
80 |
26 |
144 |
2007 |
809 (8,7%) |
584 (Sever do Vouga; 7) |
0 (130, 46,8%) |
70 |
22 |
104 |
2008 |
782 (8,4%) |
1.441 (Castanheira de Pêra; 5) |
0 (120; 43,2%) |
72 |
29 |
141 |
2009 |
666 (7,2%) |
835 (Belmonte; 9) |
0 (135; 48,6%) |
60 |
17 |
104 |
2010 |
680 (7,3%) |
661 (Mangualde; 13) |
0 (117; 42,1%) |
66 |
36 |
92 |
2011 |
681 (7,4%) |
1.381 (Torre de Moncorvo; 12) |
0 (136; 48,9%) |
67 |
11 |
134 |
2012 |
630 (6,8%) |
729 (Belmonte; 7) |
0 (148; 53,2%) |
53 |
0 |
91 |
2013 |
568 (6,1%) |
750 (Belmonte; 7) |
0 (150; 54%) |
52 |
0 |
93 |
Global |
9.262 (100%) |
417 (Belmonte; 53) |
0 (17 c; 6,1%) |
75 |
55 |
69 |
DE: desviación estándar. a Por 100.000 ingresos (n = 11.273.431); b Los nombres de los municipios no se presentan por el elevado número de municipios con valor mínimo de ingresos; c Alcoutim, Arronches, Boticas, Barrancos, Montalegre, Fronteira, Mértola, Terras de Bouro, Vila de Rei, Marvão, Sabrosa, Monforte, Pedrógão Grande, Vidigueira, São João da Pesqueira, Sernancelhe, Tabuaço. |
Tabla II. Clusters espaciotemporales identificados en los ingresos hospitalarios con el diagnóstico principal de la CIE-9-MC 340, considerando los 278 municipios de Portugal continental entre 2002 y 2013. |
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Cluster |
N.º de casos |
Observaciones |
Riesgo |
Tasa anual |
|
2002-2006 |
Arco Ribeirinho a |
288 (6) |
2,45 |
2,50 |
201,5 |
2002-2007 |
Castro Daire, S. Pedro |
48 (3) |
2,51 |
2,52 |
206,2 |
2003-2006 |
Centro b |
1.506 (69) |
2,54 |
2,80 |
208,4 |
2004-2009 |
Guimarães |
319 (1) |
4,12 |
4,23 |
338,3 |
2004-2009 |
Algarve c |
312 (10) |
2,05 |
2,09 |
168,4 |
2008-2013 |
Sintra |
494 (1) |
3,13 |
3,25 |
256,8 |
2009-2010 |
Almada-Seixal |
93 (2) |
2,25 |
2,27 |
185,2 |
a Alcochete, Moita, Palmela, Barreiro, Benavente, Montijo; b Penela, Ansião, Miranda do Corvo, Figueiró dos Vinhos, Condeixa-a-Nova, Castanheira de Pêra, Pedrogão Grande, Lousã, Alvaiázere, Soure, Coimbra, Vila Nova de Poiares, Gois, Pombal, Sertã, Ferreira do Zêzere, Penacova, Montemor-o-Velho, Mealhada, Ourem, Pampilhosa da Serra, Arganil, Vila de Rei, Figueira da Foz, Oleiros, Leiria, Cantanhede, Tomar, Mortágua, Tabua, Santa Comba Dão, Anadia, Proença-a-Nova, Sardoal, Batalha, Marinha Grande, Mação, Mira, Torres Novas, Oliveira do Bairro, Carregal do Sal, Oliveira do Hospital, Vila Nova da Barquinha, Entroncamento, Vagos, Tondela, Porto de Mós, Águeda, Constância, Alcanena, Abrantes, Seia, Golegã, Vila Velha de Rodão, Nelas, Ílhavo, Alcobaça, Aveiro, Nazaré, Covilhã, Gavião, Castelo Branco, Vouzela, Fundão, Albergaria-a-Velha, Oliveira de Frades, Sever do Vouga, Santarém, Nisa; c Lagoa, Portimão, Silves, Albufeira, Monchique, Lagos, Aljezur, Loulé, Vila do Bispo, Faro. |
Tabla III. Análisis de la variación espacial en tendencias temporales de ingreso con el diagnóstico principal de la CIE-9-MC 340, en Portugal continental entre 2002 y 2013. |
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Nº de casos (n.º de municipios) |
Tendencia |
Tasa de ingreso anual |
|
Sintra, Cascais, Amadora |
1.058 (3) |
+11,5% |
132,5 |
Serra da Estrela a |
465 (6) |
+8,05% |
202,9 |
Alentejo e Algarve b |
1.150 (37) |
+0,17% |
107,8 |
Trás-os-Montes c |
101 (10) |
+10,66% |
69,6 |
a Covilhã, Manteigas, Fundão, Seia, Belmonte, Gouveia; b Aljezur, Lagos, Monchique, Portimão, Vila do Bispo, Lagoa, Odemira, Silves, Albufeira, Ourique, Almodôvar, Loulé, Sines, Santiago do Cacém, Castro Verde, São Brás de Alportel, Faro, Aljustrel, Olhão, Tavira, Grândola, Alcoutim, Ferreira do Alentejo, Mértola, Beja, Castro Marim, Vila Real de Santo António, Alcácer do Sal, Alvito, Cuba, Viana do Alentejo, Serpa, Sesimbra, Vidigueira, Setúbal, Palmela, Seixal; c Vila Flor, Carrazeda de Ansiães, Alfandega da Fé, Torre de Moncorvo, Mirandela, Murça, Alijó, Vila Nova de Foz Côa, Macedo de Cavaleiros, São João da Pesqueira. |
Figura. Mapeo de clusters de variaciones espaciales en tendencias temporales de la tasa anual de ingresos con el diagnóstico principal de la CIE-9-MC 340, por 100.000 casos en Portugal continental, de los años 2002 a 2013.
Multiple sclerosis in continental Portugal: analysis of spatio-temporal clusters and spatial variations in time trends of hospitalised patients between 2002 and 2013 Introduction. Multiple sclerosis (MS) is a demyelinating and autoimmune disease with variable progression and high risk of hospital admission. In some studies these hospitalizations may be used as surrogate markers of disease progression, however in Portugal, due to organizational asymmetries and clinical safety choices this relationship is not linear. The admission patterns for this pathology can provide relevant data to the design of disease’s management strategies and resource allocation. Aim. To characterize hospital admissions for MS in mainland Portugal between 2002 and 2013 through the cases included in the hospital morbidity database with the code ICD-9-CM 340 as primary diagnosis. Patients and methods. In this study mapping techniques, analysis of spatio-temporal clusters and analysis of spatial variations in temporal trends of hospital admission rates for MS were used. Results. Between 2002 and 2013 the rate of annual hospital admission for MS was 82.2/100,000 hospitalizations, with a decreasing trend of 3.73%/year. Seven spatial-temporal clusters were identified with hospital admission rates for this pathology ranging from 2.27 to 4.23 higher than the national rate. In addition, in this time period four areas with increasing trend in hospital admission rate (+ 0.17 to +11.5%) were detected: Sintra-Cascais-Amadora, Serra da Estrela, Alentejo-Algarve and Trás-os-Montes. Conclusion. These data demonstrate the expected asymmetry of organizational differences, environmental, genetic and clinical safety choices. This study allowed the identification of areas and evolutionary trends of hospital admission rates for MS, enabling the design of more focused health interventions. Key words. Hospital planning. Length of stay. Multiple sclerosis. Patient admission. Space-time clustering. Spatio-temporal analysis. |