Int J Biometeorol DOI 10.1007/s00484-015-1032-8
ORIGINAL PAPER
Evaluation of meteorological and epidemiological characteristics of fatal pulmonary embolism Klára Törő 1 & Rita Pongrácz 2 & Judit Bartholy 2 & Aletta Váradi-T 1 & Boglárka Marcsa 1 & Brigitta Szilágyi 3 & Attila Lovas 3 & György Dunay 1 & Péter Sótonyi 4
Received: 1 October 2014 / Revised: 22 June 2015 / Accepted: 23 June 2015 # @ European Union 2015
Abstract The objective of the present study was to identify risk factors among epidemiological factors and meteorological conditions in connection with fatal pulmonary embolism. Information was collected from forensic autopsy records in sudden unexpected death cases where pulmonary embolism was the exact cause of death between 2001 and 2010 in Budapest. Meteorological parameters were detected during the investigated period. Gender, age, manner of death, cause of death, place of death, post-mortem pathomorphological changes and daily meteorological conditions (i.e. daily mean temperature and atmospheric pressure) were examined. We detected that the number of registered pulmonary embolism (No 467, 211 male) follows power law in time regardless of the manner of death. We first described that the number of registered fatal pulmonary embolism up to the nth day can be
expressed as Y(n)= α⋅nβ where Y denotes the number of fatal pulmonary embolisms up to the nth day and α > 0 and β > 1 are model parameters. We found that there is a definite link between the cold temperature and the increasing incidence of fatal pulmonary embolism. Cold temperature and the change of air pressure appear to be predisposing factors for fatal pulmonary embolism. Meteorological parameters should have provided additional information about the predisposing factors of thromboembolism.
Keywords Pulmonary embolism . Venous thrombosis . Meteorological parameters . Medico-legal investigation . Power law relation . Poisson point process . Bayesian estimation
* Klára Törő
[email protected]
György Dunay
[email protected]
Rita Pongrácz
[email protected] Judit Bartholy
[email protected] Aletta Váradi-T
[email protected]
Péter Sótonyi
[email protected] 1
Department of Forensic and Insurance Medicine, Semmelweis University, BudapestÜllői st. 93, 1091, Hungary
2
Department of Meteorology, Eötvös Loránd University, BudapestPázmány st. 1/a, 1117, Hungary
3
Department of Geometry, Budapest University of Technology and Economics, BudapestEgry József st. 1, 1111, Hungary
4
Department of Vascular Surgery, Semmelweis University, BudapestVárosmajor st. 68, 1122, Hungary
Boglárka Marcsa
[email protected] Brigitta Szilágyi
[email protected] Attila Lovas
[email protected]
Int J Biometeorol
Pulmonary embolism (PE) is an acute, occlusive, thromboembolic disorder. The thrombus usually arises in the lower limbs; however, they rarely also originate in the pelvic, renal, or upper extremity veins or the right heart chambers. They can get into the lung and cause hemodynamic compromise. Therefore, PE represents a main public health problem worldwide with a great mortality, in about 25 % of victims, and it could be the first manifestation of sudden death (Stein et al. 2005; Lucena et al. 2009). The national statistical database suggests that in Hungary, the average mortality is about 130.000 per year (Statinfo, WHO), and the number of fatal PE cases were nearly 1000–1500 per year in the last decades. Venous thromboembolism (VTE) includes deep vein thrombosis (DVT) and pulmonary embolism, which is practically a consequence of the DVT. PE has complex pathophysiology with several risk factors including genetics, environmental, social-economic parameters and physical activities changing in different seasons with different meteorological conditions (Clauss et al. 2005; Dentali et al. 2009; Dales et al 2010; Soria et al 2014). Over and above PE is a severe complication after traumatic injuries or surgical treatment. Venous thromboembolism (VTE) frequently complicates the recovery of trauma patients and contributes to morbidity and mortality (Orlik and McVey 2011). Studies investigate epidemiological and pathological characteristics of PE (Stein et al 2005; Dentali et al 2009). It is a well-known fact that meteorological parameters or cold or wet conditions may cause significant impact on the occurrence of accidents. Frequency of traumatic injuries has been influenced by different environmental factors, like slippery roads in traffic accidents during wet seasons or winter time. There are well-defined predisposing conditions such as immobilisation, surgery and malignancy that can significantly increase the risks of VTE. All of the meteorological parameters have complex biological effects on human bodies (Braga et al 2002; Cagle and Hubbard 2005; Gyllerup 2000); therefore, there is an increasing interest in the connection between environmental-meteorological factors and vascular disease’s morbidity and mortality. Reports in the literature suggest that weather changes may play a role in venous thrombotic disease (Stein et al 2004; Boulay et al 2001) and in the occurrence of PE as well (Öztuna et al. 2008; Gallerani et al. 2007). According to the Hungarian jurisdiction, in cases of natural sudden unexpected deaths and in cases when there is a possibility that the cause of death is not natural, performance of forensic autopsy is suggested. Post-mortem forensic investigations have frequently detected pathomorphological characteristics of PE in natural sudden death cases and after traumatic injuries as fatal complication. Evaluation of linkage back to the initiating accidental injury and violent death represents a challenge for medico-legal consideration. The purposes of this study are to examine epidemiological and pathological patterns detected during medico-legal autopsies in PE cases, to identify the meteorological risk factors for the occurrence of
PE death, to predict the expected mortality of PE as a function of meteorological elements and to provide a descriptive temporal analysis of cumulated number of fatal PE cases.
Methods Mortality data The survey target groups included cases of PE in the capital Budapest. Based on the database of the Department of Forensic and Insurance Medicine, Semmelweis University, there were 23.892 cases autopsied between 1 January 2001 and 31 December 2010 in our institute. Among these cases, there were 467 (1.95 %) PE defined as cause of death in this time period. We collected PE cases when death happened as sudden unexpected death even if it was after suffering traumatic injuries. PE was determined based on the autopsy pathomorphological findings as large thrombi lodged at the bifurcation of the main pulmonary artery or the lobar branches, and the thrombi originated in the deep venous system of the lower extremities. Histological assessment of the embolus samples was also performed in conjunction with the venous sites of thrombosis. Histological investigation of fat emboli (Sudan III) has been performed in every case when long bone fractures or massive blunt injury soft tissue was found during the medico-legal autopsy. Cases with fat emboli were excluded from our study. Based on the macroscopic and histological findings, the post-mortem changes were excluded. In PE cases, we reviewed the autopsy reports that contained the information of age, gender, manner of death, place of death, cause of death, clinical anamnestic data and previous diseases, traumatic injuries, survival period, immobilisation, surgery, and source and severity of emboli. The following post-mortem data were also obtained: scene investigation, macroscopic and histological findings, post-mortem BAC tests and toxicology. Regarding to the manner of death, we investigated cases in four different groups, as natural death, accidents, suicides and homicides. In our material, we categorised the studded cases in two groups based on the manner of death. We sorted into the natural death group those cases where no previous violent event happened. The violent death group contains the cases where accident, suicide, or homicide resulted in injury and led to pulmonary embolism. Based on the existence of the wellknown risk factors in the anamnestic data, we separated the idiopathic VTE cases (in the absence of any known risk factors) from the associated VTE cases (cases with risk factors). The 10th revision of the International Classification of Diseases (ICD) was used for the determination of cause of death. Based on the post-mortem retrospective data collecting study, ethics approval is not required.
Int J Biometeorol
characterises the effect of the weather parameters on PE deaths. The corresponding conditional probabilities can be computed by using the following Bayesian estimation:
(Cox 1955). A medical application of Cox processes can be found in (Krumin and Shoham 2009). The number of registered PE deaths up to the nth day can be interpreted as a Cox process which intensity parameter is modulated by the weather. A statistical prediction model for fatal PE was obtained by this way which enables us to express the expected number of fatal PE cases in a day (E(ξ|X=x)). The conditional expectation extrapolated to 300 days E300 =300⋅E(ξ|X=x) was introduced as a new quantity to measure the effect of weather on the incidence of fatal PE because the monthly number of fatal PE during 10 years was considered and E300 is comparable to the magnitude of this quantity. E300 values are presented in Figs. 6 and 7. Local or seasonal changes in incidence of fatal PE can be accurately modelled, but global trends (over 10 years) are not in general because it is possible that there are some unknown effects which are not taken into consideration in the model. For that reason, in the second phase of the statistical analysis, we performed a crude power law regression to detect global trends. For functional form for the fitted function, power law was chosen. Power law can indicate a hierarchy of stochastic processes. Power law behaviour produces the linear relationship when logarithms are taken of both the number of PE deaths and time. This phenomenon is often called the signature of a power law. Statistical methods related to power law regression is not detailed in this paper because log–log transform originates the problem to a simple linear regression. Confidence intervals of model parameters corresponding to significance level 0.95 are given in Table 2, and the fitted power law graphs are presented in Fig. 4. One can see that there is no systematic trends in fit residuals (Fig. 5). Computations were done by Wolfram® Mathematica 9.0.1.0.
Pðξ > 0j−jX ¼ x−jÞ ¼ 1 = 1 þ Pðξ ¼ 0Þ=Pðξ > 0Þ⋅ f ↓ X jξ ¼ 0−j
Results
Meteorological parameters Meteorological data were obtained from the gridded E-OBS datasets (Haylock et al. 2008; van den Besselaar et al. 2011). Meteorological data were analysed from the region of capital Budapest. The following variables were used: daily maximum, minimum and mean temperature; temperature change between days with PE death and the previous days; daily atmospheric air pressure; and atmospheric air pressure change between days with PE death and the previous days.
Statistical methods The statistical analysis of data can be divided into two phases. In the first phase, we performed a Bayesian estimation for detecting the relationship between PE deaths and weather; then, we studied the growth of registered PE deaths depending on the time. Let us denote by ξ the random variable which means the number of registered PE deaths in a day and X, which is assumed to be a continuously distributed random variable, represents the observed meteorological parameters such as daily average temperature atmospheric air pressure change between days with PE death and the previous days. The relative change of conditional probability with respect to its value at the expectation of the influencing variable χðxÞ :¼
Pðξ > 0jX ¼ xÞ −1 Pðξ > 0jX ¼ E ðX ÞÞ
ðxÞ = f ↓ X jξ > 0−j
ðx Þ
;
where fx denotes the a priori probability density function of X, and fX|ξ>0 and fX|ξ=0 are the corresponding a priori conditional probability density functions. Bayesian statistics minimises the mean square error, and it can be expressed as a function of the minimal sufficient statistics. In our cases, normal distribution was applied to approximate the conditional probability density functions fX|ξ>0 and fX|ξ=0. The conditional probability P(ξ>0|X=x) as a function of the considered meteorological parameters (X) acts like a forecast function. It gives the likelihood of the event that fatal PE is happening on a day if the considered meteorological parameter is equal to x. Relative change of conditional probability (χ) is presented in Figs. 1 and 2. Cox processes are adequate models for the number of registered PE deaths in time. A Cox process is a generalised Poisson point process introduced by David Cox in 1955
There were 467 (211 males, 256 females) fatal PE cases investigated in the study period. However, we did not examine the statistical relationship between seasons and PE deaths; we present the monthly distribution on Fig. 1. VTE caused fatal PE in 2.51 % (No 320/12749) of natural death cases, in 2.18 % (No 136/6231) after accidents, in 0.22 % (No 10/4453) after suicides and in 0.21 % (No 1/459) after homicidal injuries. We compared the risks and pathological characteristics of PE between the natural and the violent death groups (Table 1). In most cases, the source of embolism could be found; the most frequent locations were the lower limb (No. 276) and the pelvic venous plexus (No. 34). In 151 cases, source of emboli was not found as the thrombus probably completely moved to pulmonary arteries. The average age was higher in the violent death group (74 years) than in natural death group (68 years). In natural sudden unexpected death cases, the death occurred mostly at home (No 182); second, in an ambulance (No 52), or
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Fig 1 Monthly distribution of pulmonary embolism cases
in hospital (No 46), or at public place (No 39), or at work place, only one case was registered. All the trauma patients died in hospital, and as expected, immobilisation, surgery and antithrombotic prophylaxis were more frequent in this group. We did not find any relevant differences in the source and in severity of embolism, or in the incidence of obesity or malignancy between the two groups. In our study, there were more long bone fractures among trauma patients (81/147 in lower extremities, 21/147 in upper extremities); however, in these cases, fat emboli investigation showed a negative result. Fatal fat embolism cases were excluded from this material as previously mentioned. In the violent death group, 7 (4.76 %) of the patients died in the first 24 h, 25 (17.01 %) died between 1 and 7 days, 82 (55.78 %) deaths occurred in 1 to 4 weeks after
Fig 2 Relative growth of conditional probability of fatal PE as a function of the daily average temperature
the traumatic injury, and 33 (22.45 %) died after 1 month. In our material, 228 idiopathic VTE and 239 associated VTE cases have been found. In violent death cases with high rate of immobilisation and surgical treatment, combined aetiology of PE has been frequently detected (No.131). In our material, the average monthly temperature was between 0.2 and 22.9 °C. We detected seasonal distribution with fewer number of PE death cases during summer period than in other seasons. The relative growth of conditional probability of PE against average daily temperature is presented in Fig. 2. One can see that a 5 °C decrease in the daily mean temperature increases the odds of PE death by at least 10 % in natural death group and by 20 % in violent non-natural death group (p= 0.95). Daily atmospheric air pressure and changes in air pressure between days with PE death and the previous days were detected. The relative growth of conditional probability of fatal PE as a function of the change of air pressure is presented in Fig. 3. It could be said that the change of air pressure has a weak effect on the incidence of PE death (p=0.34); however, we found that in natural death group, the air pressure increases the risk of PE death. The difference between the qualitative behaviours of forecast functions is originated to the difference between the estimated variances of conditional distributions. The possible qualitative behaviours of forecast functions can be easily deduced when the conditional probability density functions (f X jξ¼0ðxÞ and f X jξ>0ðxÞ ) are Gaussian functions.
Int J Biometeorol Table 1 Comparison of epidemiological factors, pathomorphological characteristics and anamnestic data among PE cases in natural and violent deaths Natural death (No)
Violent death (No)
Total number Gender (M/F) Mean age Age >65 Source of embolism Lower limb Pelvic venous plexus Right atrium Upper limb
320 143/177 68±32 199
147 68/79 74±30 115
181 28 1 1
95 6 2 1
Inferior caval vein Not found Severity One-sided Two-sided Pulmonary infarction Pulmonary hypertension Alcoholism Proven Fatty liver Cirrhotic liver Obesity Malignancy Immobilisation Surgery Antithrombotic prophylaxis
0 109
1 42
69 241 13 90
37 120 5 46
9 87 9 96 34 65 8 4
11 36 7 35 15 127 75 39
We noticed that the number of registered PE deaths represents power law behaviour over time. This means that the following functional relationship holds for the number of registered PE deaths (Y) up to the nth day: Y ðnÞ ¼ α⋅nβ where Y denotes the number of fatal pulmonary embolisms up to the nth day and α>0 and β>1.
Fig 3 Relative growth of conditional probability of fatal PE as a function of the change of air pressure
Trend lines of the number of registered PE death against time are presented in Fig. 4. Power law behaviour can be recognised in cumulative number of fatal PE cases. Estimated parameters and confidence intervals are presented in Table 2. Probability 0.9999 confidence intervals are computed for model parameters. The high confidence level confirms the power law relationship between registered PE deaths and time in both of groups. There were no systematic trends with the goodness of fit in the fit residuals, i.e. differences between actual and predicted responses (Fig. 5). Expected numbers of fatal PE extrapolated to 300 days for natural and violent death cases are presented in Figs. 6 and 7, respectively. These results clearly suggest that in case of lower daily mean temperature, more fatal PEs (natural death) can be expected. Moreover, the number of fatal PE cases (natural death) is larger when day-to-day air pressure change is increasing than when it is decreasing. For violent death cases, tendency in air pressure is not such a clear determining factor, and lower temperature values do not imply significantly more fatal PE cases, either.
Discussion In this study, we analysed the epidemiological factors of fatal pulmonary embolism, and meteorological conditions on days when PE death occurred among sudden unexpected death cases investigated in the Department of Forensic and Insurance Medicine, Semmelweis University, between 2001 and 2010. Connected to the new guidelines, VTE is considered to be a consequence of the interaction between patientrelated (usually permanent) and setting-related (usually temporary/reversible) risk factors (Konstantinides et al. 2014). VTE can be Bprovoked^ in the presence of the temporary risk factors (such as surgery, trauma, immobilisation, pregnancy, oral contraceptive use or hormone replacement therapy, and malignancy) within the last 6 weeks to 3 months before PE or Bunprovoked^ (idiopathic) in the absence of the listed (Bartholomew et al. 2011; Dentali et al. 2011; Kearon and Akl 2014). In our material, 228 cases were considered to idiopathic, because we did not find any mentioned risk factors in the anamnestic data. On the other hand, when risk factors were detected, these mostly co-occurred. This is particularly true in the violent death cases, where the injury and immobilisation and surgery almost always took place together. In the two tested groups, obesity was the main natural risk factor; in addition to this, in the violent death group, injury and immobilisation further increased the danger. We confirmed previous results that showed most of the PE arises as a result of embolism from deep vein thrombosis, most commonly from veins in the leg or pelvic region (Lucena et al. 2009; Meral et al. 2005; Dentali et al. 2011). In 59.1 % of our cases, the source of
Int J Biometeorol
Fig 4 Power law behaviour can be recognised in cumulated number of fatal PE death cases. Trend lines in PE deaths. Ba^ curve: natural death; Bb^ curve: violent death
embolism could be found in the lower extremities, mostly in deep iliofemoral veins, which form has a worse prognosis (Jenkins and Michael. 2014). By contrast, in 32.3 %, the source was not found; in these cases, the total breakaway of the thrombus assumed. There are several factors influencing the pathophysiological processes of PE. The occlusion of the pulmonary arteries due to right ventricular pressure increases, which causes muscle stretching, increased wall tension, elevated heart rate and decreased coronary perfusion. Mortality is correlated with an extent of right ventricle dysfunction (Bilora et al. 2001). Micro-embolus occlusion of pulmonary arterioles is rarely diagnosed; however, a biomechanical study (Clark et al. 2011) found that it can have a great impact on PE, and emboli lodged near proximal capillary beds have a greater effect on pulmonary vascular resistance—regardless of their size—than emboli occluding bigger arterioles. VTE frequently complicates the recovery of patients suffering from injuries and contributes significantly to trauma mortality (Menaker et al. 2009). Although PE is usually thought to occur between days 5 and 7 after injury, Menaker et al. (2007) found that PE was diagnosed on days 1 to 4 in 37 % among trauma patients. Öztuna et al. (2008) found statistical difference in the diagnosis duration lag period between symptoms to diagnosis of PE. It was 5.5 days in surgical cases and 10.9 days in non-surgical cases. However, in our material, only 17.7 % of trauma victims died in the first 7 days after injuries, and 82.3 % after more than a week of survival due to PE. The approach to the prevention and management of VTE in trauma is to ensure that optimal thromboprophylaxis is started as soon as possible after injury in all major trauma patients. Among our cases, Table 2
Estimated parameters and confidence intervals Natural death
α β
82 % received thromboprophylaxis soon after the injury; however, PE caused fatal complication. In some cases, evidence of a proximal DVT was detected and these patient were treated with therapeutic anticoagulation; nevertheless, fatal outcome has not been avoided. Based on the climate change worldwide, the question has been arisen whether meteorological parameters may influence thromboembolism or not. Climatic and seasonal triggering factors on human life have received an increasing public and social interest, and the relationship between meteorological conditions and their effects on human health has been investigated (McMichael et al. 2006). Several studies demonstrated the VTE and PE have connections with monthly or seasonal variation (Boulay et al. 2001; Dentali et al. 2011; Gallerani et al. 2004; Kosacka et al. 2015), and circadian and circannual rhythms (Cox 1955) were observed for fatal and non-fatal PE. Most of the epidemiological studies emphasised seasonal distribution of these disease (Staskiewicz et al 2011; Manfredini et al. 2009; Öztuna et al. 2008). There are some results demonstrated that additional meteorological factors, e.g. humidity (Öztuna et al. 2008; Staskiewicz et al. 2010), and the effects of the air quality and air pollution (Clauss et al. 2005) could affect PE incidence. In our material, the average monthly temperature was between 0.2 and 22.9 °C during the examined 10-year period. We found by Bayesian statistics and hypothesis tests that the cold temperature increases the odds of fatal pulmonary embolism. In addition, the increasing tendency of air pressure is also likely to result in more PE deaths. This latter effect is much less pronounced in the violent death group, and then in natural death cases. Based on our results, we concluded that rapid decrease in daily mean temperature and change in air pressure increase the risk for fatal PE. We found that the number of registered PE follows a power law in time regardless of the manner of death. A systematic review meta-analysis of the literature showed an increased incidence of VTE in winter, and in January (Dentali et al. 2011). Öztuna et al. (2008) suggested that cooler weather would increase blood viscosity and the risk of PE. A hypercoagulable state which is due to an elevated fibrinogen level also demonstrates a great seasonal variation, with a significant increase during the colder months (Manfredini et al. 2011). The theory of increased coagulability resulted from cold may also explain our results. Moreover, as a consequence of colder temperature, physical activity is drastically limited, especially in elderly
Violent death
Estimate
Standard error
Confidence interval
Estimate
Standard error
Confidence interval
1.38969 0.00364759
0.001012 2.93⋅10−5
(1.3857;1.3936) (0.003533;0.003762)
1.65440 0.000186413
0.00353 5.24⋅10−6
(1.641;1.668) (0.000166;0.000207)
Int J Biometeorol
Fig 5 Fit residuals (i.e. differences between actual and predicted responses) time series, 2001–2010 (continuous and dotted lines refer to natural and violent death cases, respectively)
subjects, and this could further lead to prothrombotic changes (Sumukadas et al. 2009). Potential effects of atmospheric pressure had been investigated in earlier studies (Staskiewicz et al. 2010; Meral et al 2005). In 1940, de Takats et al. (1940) reported that the incidence of PE was higher during the spring months and during periods of low atmospheric pressure. Meral et al. (2005) found the PE incidence to be significantly higher also in the spring months when atmospheric pressure was low. Similarly, Staskiewicz et al. (2010) ascertained that episodes of more severe pulmonary embolism were preceded by periods of lower atmospheric pressure; however, in their study, no significant differences in seasonal distribution of PE episodes were observed. For explanation of the phenomenon, previous ex vivo experiments have shown that human platelet aggregation is induced by reduced pressure, and hyperprothrombinemia may occur at lower atmospheric pressure (Murayama and Kumaroo 1986). In contrast, in our analysis, we resulted that increasing air pressure raises the risk for PE deaths. Nimako et al. (2012) stated that there is a presence of seasonal variations in idiopathic PE and that the incidence of PE was related to decreased atmospheric pressure and increased temperature. These conflicting results may be
Fig 7 Expected number of fatal PE extrapolated to 300 days (violent death)
explained with the facts that, in our sample, not only idiopathic cases occurred, and we examined only fatal PE cases. Our results suggest that there are differences between characteristics of PE followed by a traumatic injury and PE without any external damage. The significant (p=0.9999) power law relation between PE deaths and time in both of groups suggests that there is a hidden external effect which increases the incidence of PE death among population of Budapest City. Based on the contradictory results in different study materials, we have to emphasise the importance of further investigation in connection with meteorological parameters and sudden unexpected death cases. Further studies are necessary to clarify whether meteorological factors represent real risk or only an indirect marker leading to PE death. Mortality database on detailed forensic autopsy has several advantages. The large number of detailed medico-legal autopsies of sudden death cases is essential to determine the exact cause of death and to characterise the pathomorphology of a possible symptomfree disease (Gong et al. 2013; Lin and Gill 2009; Rosenfeld et al. 2012).
Conclusion
Fig 6 Expected number of fatal PE extrapolated to 300 days (natural death)
We concluded that in case of lower temperature (i.e. winter time), more fatal PE cases are predicted to occur. In addition, the increasing tendency of air pressure is also likely to result in more PE deaths. This latter effect is much less pronounced in the violent death group and then in natural death cases. Thanks to the Bayesian statistical model, the relative growth of the probability of fatal PE can be expressed as a function of the considered weather parameters. The conditional probability function acts like a so-called forecast function. The number of fatal PE follows a power law. From this fact, we deduced
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that the population of Budapest City is exposed to an unknown thrombotic effect which is still unknown. We successfully quantified the main meteorological risk factors of PE death using Cox process based on Bayesian statistical model. The math model constructed in this study has a great potential to other epidemiological investigations aiming to detect significant connection between different time series.
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