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1.
Agressologie ; 31(2): 117-9, 1990 Feb.
Article in French | MEDLINE | ID: mdl-2240401

ABSTRACT

Thirty one cases of accidental hypothermia have been taken in care by the SAMU de Paris during the year of 1987. The accidental hypothermias happening in the cities are, most of the time, moderated and not very serious. The search for a cause is a prime necessity. The prognosis is based on that search to guide and advise the patients.


Subject(s)
Hypothermia/etiology , Mobile Health Units , Adult , Aged , Aged, 80 and over , Body Temperature , Female , Hot Temperature/therapeutic use , Humans , Hypothermia/therapy , Male , Middle Aged , Paris , Poisoning/complications , Prognosis
3.
Sem Hop ; 60(9): 598-601, 1984 Feb 23.
Article in French | MEDLINE | ID: mdl-6324365

ABSTRACT

In a previous paper, meteorological circumstances of myocardial infarctions, cerebrovascular attacks, and suicidal attempts were studied by a univariate method. The present work used the same clinical reports, collected by the Medical Emergency Assistance System (SAMU) in the Paris area from 1975 to 1977, but with multivariate calculations. 150 potential predictive indicators were submitted to "progressive ascending selection". Selected indicators were then combined into a composite index by "linear canonic discrimination". This index was tested in terms of successful prediction. The 150 indicators were: 1) meteorological variables, recorded at ground level, such as wind and temperature (expressed respectively in 28 and 24 ways), airpressure, moisture; 2) variables computed from data recorded in altitude; 3) pollutants; 4) non-meteorological indicators, such as day of the week, season, solar activity; 5) the "past of the predictand", i.e. the frequency of infarctions during the previous days; 6) types of weather, defined after confronting meteorological maps with clinical data. The coding of qualitative data required a new procedure. The event to be predicted, which occurred only one day a week, was an incidence of infarctions of at least twice the average. The percentage of successful prediction was 78.7%. The type of weather was by far the best indicator. Detrimental circumstances were changing weathers, with in the order of decreasing correlations, atmosphere fluxes coming from S-SE, E, SW, and NW. These results complete those of univariate analysis. They validate a simple and efficient predictive method, similar in its principle to that used in Germany.


Subject(s)
Meteorological Concepts , Myocardial Infarction/epidemiology , Epidemiologic Methods , Humans , Myocardial Infarction/etiology , Myocardial Infarction/prevention & control , Retrospective Studies
5.
Anesth Analg (Paris) ; 36(9-10): 485-9, 1979.
Article in French | MEDLINE | ID: mdl-533008

ABSTRACT

The economists analyse the facts of our everyday--or professional life to insert management--or anticipation rules from them. The progress of innovations and their obsolescence fall within these studies. Recent works have shown that the spreading of innovations in the medical fields was practically identical to that in the industrial field, and that its function in relation to time was written under the form of: P = K divided by 1 + e-(a+bt) P representing the proportion of departments which adopted an innovation at the time t, K representing the proportion of those which will adopt this innovation (a and b are constants). The derivated coefficient in relation to t, that is to say the variation of the proportion of departments adopting innovations in relation to time, measures the speed of diffusion of this innovation (Louise B. Russel, 1977). But can this equation be applied in the field of health, to organisational innovations as well as to those which have a material, therefore industrial support? On the other hand do techniques and equipments become obsolete simultaneously? Finally does the public or the private hospital slow down or speed up the appearance of innovations and their obsolescence? Such are the problems we will endeavour to set... before being able to solve them.


Subject(s)
Communication , Diffusion of Innovation , Medical Laboratory Science , Animals , Dogs , Drug Industry/economics , Humans , Materials Management, Hospital/economics , Materials Management, Hospital/organization & administration , Medical Laboratory Science/economics , Time Factors
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