# Influence of meteorological changes on the occurrence of cerebral aneurysm rupture in the Montpellier region: A retrospective study

Camille Desbordes, Vivien Szabo, Frédéric Greco, Kevin Chalard, Cyril Dargazanli, Nicolas Molinari, Eric Matzner, Valérie Macioce, Joana Pissarra, Gerald Chanques, et al.

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Camille Desbordes, Vivien Szabo, Frédéric Greco, Kevin Chalard, Cyril Dargazanli, et al. Influence of meteorological changes on the occurrence of cerebral aneurysm rupture in the Montpellier region: A retrospective study. Neurochirurgie, 2025, 71 (2), pp.101630. 10.1016/j.neuchi.2025.101630. hal-04882378

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Original Article

# Influence of meteorological changes on the occurrence of cerebral aneurysm rupture in the Montpellier region: A retrospective study

Camille Desbordes<sup>a,*</sup>, Vivien Szabo<sup>a,f</sup>, Frédéric Greco<sup>a</sup>, Kévin Chalard<sup>a</sup>, Cyril Dargazanli<sup>b,f</sup>, Nicolas Molinari<sup>c</sup>, Eric Matzner<sup>c</sup>, Valérie Macioce<sup>d</sup>, Joana Pissarra<sup>d</sup>, Gérald Chanques<sup>e</sup>, Pierre Francois Perrigault<sup>a</sup>

ARTICLE INFO

Keywords:

Aneurysm

Subarachnoid hemorrhage

Neurology

Meteorology

Retrospective

Observational

ABSTRACT

**Background context:** Aneurysmal subarachnoid hemorrhage (aSAH) is a sudden and potentially serious event. Recognized risk factors of aSAH include smoking, high blood pressure, and alcohol consumption. Some studies have reported associations between risk of aSAH and climatic conditions, but no consensus exists. This study aimed to investigate the association between aSAH and meteorological conditions.

**Methods:** We retrospectively included patients admitted for aSAH at Montpellier University Hospital between 2018-2022. We analyzed the correlation between the occurrence of aSAH and several meteorological factors, including precipitation, temperature, barometric pressure, wind speed, humidity, sunshine duration, and storms, within 24 h and 7 days before symptom onset. We collected meteorological data for days without aSAH cases as controls. A multivariate logistic regression with 10-block cross-validation and a penalty lasso method was performed.

**Results:** For the 5-year period, 492 patients were analyzed. Incident cases per month in this period was higher in February and August and the highest in winter. Diagnoses were made predominantly between noon and midnight. The multivariate model based on 9 weather variables on the days preceding the aSAH event had an accuracy of 0.55. The area under the curve was 0.58 (95% CI 0.55-0.62). The barometric pressure was similar between aSAH days and the mean of the 5 preceding days.

**Conclusion:** Due to the low accuracy of the statistical model, our study could not provide evidence of a link between weather variables and occurrence of aSAH. This issue requires further investigation and reliable epidemiological data to fully understand the pathophysiology and real impact of weather on aSAH.

1. Introduction

Subarachnoid hemorrhage (SAH) is a sudden and potentially serious medical condition. Its mortality rate varies depending on the initial clinical condition from 28 to 42% [1,2]. Aneurysmal SAH (aSAH) occurs in young subjects with a median age of 55 years and can result in severe sequelae in one-third of cases, leading to significant socio-economic consequences [3]. Currently, recognized risk factors leading to aSAH

are smoking, excessive alcohol consumption, and high blood pressure [4,5].

Various research teams have attempted to evaluate the potential impact of meteorological parameters on the occurrence of aSAH, with different findings depending on the geographical regions (Supplementary Figure A and Table A) and methodologies employed. Several studies found that the occurrence of aSAH was associated with low temperatures or temperature drops [6-9] and/or excessive barometric pressure

<footnote><sup>a</sup> Department of Anesthesia and Intensive Care Unit of Gui De Chauliac - University Hospital of Montpellier, France</footnote>

<footnote><sup>b</sup> Department of Neuroradiology- University Hospital of Montpellier, France</footnote>

<footnote><sup>c</sup> IDESP, INSERM, PreMEDical INRIA, CHU Montpellier, Univ Montpellier, Montpellier, France</footnote>

<footnote><sup>d</sup> Clinical Research and Epidemiology Unit, CHU Montpellier, Univ Montpellier, Montpellier, France</footnote>

<footnote><sup>e</sup> Department of Anesthesia and Intensive Care Unit of Saint Eloi - University Hospital of Montpellier, PhyMedExp, Montpellier University, France</footnote>

<footnote><sup>f</sup> IGF, CNRS, INSERM, Univ Montpellier, France</footnote>

<footnote>Abbreviations: SAH, Subarachnoid hemorrhage; aSAH, Aneurysmal subarachnoid hemorrhage.</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: camille.desbordes@chu-montpellier.fr, camille.desbordes@free.fr (C. Desbordes).</footnote>
or barometric pressure variation [6,9,10]. It may be attributable to abrupt alterations in blood pressure, resulting from a stimulation of the sympathetic nervous system or a disruption to endothelium-dependent vasodilation by a decrease in temperature. Abrupt drops in barometric pressure have been linked to an increase in intracranial pressure. The underlying mechanisms remain unclear and may involve alterations in inflammatory mediators. However, others did not reveal any relationship between the occurrence of aSAH and the studied meteorological data [11,12].

Considering the contradictory results of the publications according to the studied region, providing an overview of the population, geographical specificities, and meteorological factors is key.

The climate of our administrative health region is characterized by four distinct seasons: a hot and dry summer, a mild winter, and sometimes very rainy spring and autumn. It is noteworthy that the region experiences ‘Cevenol episodes’, which are defined as episodes of violent thunderstorm systems that bring intense precipitation to the Mediterranean regions. These episodes are associated with the upward movement of warm, humid, and unstable air from the Mediterranean. They occur primarily in the fall (September–December).

The primary objective of our study was to investigate the relationship between meteorological conditions and the occurrence of aSAH in our administrative health region. To identify potential leads for future studies, a secondary objective was to describe meteorological factors on the days preceding the aSAH along with the average annual values for the area.

## 2. Materials and methods

### 2.1. Study design

This retrospective, monocentric, observational study was conducted in collaboration with the meteorological services of ‘Météo-France’ and ‘Météo-Orage’. The study received approval from the local ethics committee of the University Hospital Center of Montpellier (Institutional Review Board number 202301399) and complies with the French Data Protection Act (Loi Informatique et Libertés) and the reference methodology MR-004 relating to the processing of personal data in the context of health-related research (Compliance with the General Data Protection Regulation). According to French law, this anonymous retrospective observational study did not require patient informed consent. Non-opposition from all participants was confirmed.

### 2.2. Participants

All adult patients admitted to Gui de Chauliac Hospital, Montpellier, France, for aSAH between April 2018 and December 2022 were included in the study. The university hospital of Montpellier served as the reference center for our administrative health region. Our region includes the following departments: LOZÈRE, AVEYRON, GARD, HÉRAULT, AUDE, and PYRÉNÉES ORIENTALES (Supplementary Figure B). We excluded patients under legal protection or minors, patients with non-aneurysmal SAH, those who refused data usage, or those who died before reaching the hospital and therefore did not undergo a CT scan.

### 2.3. Medical and demographic data

Demographic characteristics, including age, sex, weight, and height, were collected.

Medical data for each case included the modified Fisher score [13], rupture date, time, and geographical location, diagnosis date and time, aneurysm subtype, size, and location.

The date of symptoms onset was obtained from the patient or, if unavailable, from relatives. When the date of symptoms onset was not specified, it was estimated to be the same as the diagnosis date. If the patient was from our administrative health region the location of

symptom onset was defined as their municipality of residence. For patients from other regions or non-French, this information was obtained by analyzing medical records and emergency intervention reports.

The diagnosis of SAH was confirmed by a non-contrast brain CT scan, and the location of the aneurysm was determined with angioCT.

The diagnostic sequence included arteriography if there was any doubt or if the aneurysm did not show up on the CT scan. The location of the aneurysm was confirmed during endovascular treatment or surgery.

### 2.4. Meteorological data

Weather data were sourced from the services of Météo-France and Météo-Orage. They were collected from 45 different weather stations, along with their location coordinates.

A time window of 24 h up to 7 days before aSAH occurrence was chosen due to observed diagnostic delays between symptom onset and completion of diagnostic scans or hospitalization, as previously described [10,12,14,15]. Hence, our analysis involved three sets of meteorological data collected at 7 days, 3 days or 1 day prior to the event.

The meteorological parameters studied in this research included daily precipitation, daily minimum temperature, daily maximum temperature, daily average temperature, amplitude between daily minimum and maximum temperatures, daily average barometric pressure, daily minimum barometric pressure, average wind speeds at 10 m above ground level, daily maximum wind speed, daily minimum and maximum relative humidity, duration of daily humidity, average relative humidity, duration of daily sunshine, daily global radiation, daily insolation ratio, and pressure and temperature variations. Additionally, the study recorded the occurrence of thunderstorms, including the occurrence of every lightning arc and their intensity. In most cases (75%), the intensity of a thunderstorm is between 0 and 20 kA and almost every time below 50 kA. It may be considered to have a low intensity above 15 kA, a moderate intensity between 15 and 35 kA, and a severe intensity greater than 35 kA. ‘Cevenol episodes’ are officially defined as episodes of thunderstorm with intense precipitation (>200 mm over 24 h).

### 2.5. Outcome

The primary outcome was the occurrence of aSAH. The secondary outcome was the association between aSAH occurrence and meteorological conditions.

### 2.6. Statistical analysis

To determine the weather conditions for each aSAH case occurring in our region, the closest weather station to the patient’s home was identified. To accomplish this, we obtained the GPS coordinates of each residence based on its postal code and determined the closest station.

To investigate the potential factors contributing to aSAH, we included weather conditions from the preceding days as variables. To generate meteorological control data for days with no aSAH cases recorded, we selected a control day with weather data 182 days before and 182 days after each case. Consequently, we had two control days for each aSAH case, except for subjects at the beginning or end of the observation period, for whom we had only one control day. As a sensitivity analysis, the same model was run using an alternative approach based on a single control day, randomly selected within 182 days before and after the case.

Multivariate logistic regression was used to predict aSAH occurrence. A 10-block cross-validation and a penalty lasso method were performed on a selection of variables.

The accuracy of aSAH prediction reflects the extent to which weather variables explain the occurrence of an aSAH. The model’s accuracy ranges from 100% when the weather variables fully explain the
occurrence of an aSAH, to 50% when they fail to predict it.

A complementary descriptive analysis was conducted to examine meteorological factors on the day of the event and the five preceding days, as compared with the average annual values for the area. This analysis focused on barometric pressure, humidity, and thunderstorms.

# 3. Results

## 3.1. Population description

A total of 492 patients residing in 188 municipalities were included. Mean age was 56 years (±13.4) (Table 1). There was a female predominance with a gender ratio of 1.67 (F/M), and a tendency towards overweight with a mean BMI of 25.3 kg/m² (±0.8). The mortality rate

<table><caption>**Table 1**

Patient baseline characteristics.</caption><thead><tr><th>Characteristics</th><th>n = 492</th></tr></thead><tbody><tr><td>Age (years), mean (±SD)</td><td>56 (±13.4)</td></tr><tr><td>Sex (Female), n (%)</td><td>308 (62)</td></tr><tr><td>BMI (kg/m²), mean (±SD)</td><td>25.3 (0.8)</td></tr><tr><td>Mortality, n (%)</td><td>95 (19.4)</td></tr><tr><td>Fisher Grade, n (%)</td><td>n = 490</td></tr><tr><td>Grade 1</td><td>44 (8.9)</td></tr><tr><td>Grade 2</td><td>60 (12.2)</td></tr><tr><td>Grade 3</td><td>168 (34.3)</td></tr><tr><td>Grade 4</td><td>218 (44.5)</td></tr><tr><td>WFNS Grade, n (%)</td><td>n = 492</td></tr><tr><td>Grade 1</td><td>188 (38.2)</td></tr><tr><td>Grade 2</td><td>74 (15)</td></tr><tr><td>Grade 3</td><td>26 (5.2)</td></tr><tr><td>Grade 4</td><td>70 (14.2)</td></tr><tr><td>Grade 5</td><td>134 (27.2)</td></tr><tr><td>Time to diagnosis (days), mean (±SD)</td><td>1.07 (2.1)</td></tr><tr><td>Aneurysm size (mm), mean (±SD)</td><td>n = 467</td></tr><tr><td>≤5</td><td>162 (34.7)</td></tr><tr><td>≥10</td><td>86 (18.4)</td></tr><tr><td>5–10</td><td>219 (46.9)</td></tr><tr><td>Aneurysm location</td><td>n = 489</td></tr><tr><td>Anterior circulation</td><td></td></tr><tr><td>Right Anterior Cerebral Artery</td><td>18 (3.7)</td></tr><tr><td>Left Anterior Cerebral Artery</td><td>32 (6.65)</td></tr><tr><td>Right Middle Cerebral Artery</td><td>65 (13.3)</td></tr><tr><td>Left Middle Cerebral Artery</td><td>45 (9.2)</td></tr><tr><td>Anterior communicating artery</td><td>138 (28.2)</td></tr><tr><td>Right Internal Carotid Artery</td><td>33 (6.8)</td></tr><tr><td>Left Internal Carotid Artery</td><td>32 (6.5)</td></tr><tr><td>Posterior circulation</td><td></td></tr><tr><td>Right Posterior Cerebral Artery</td><td>17 (3.5)</td></tr><tr><td>Left Posterior Cerebral Artery</td><td>27 (5.5)</td></tr><tr><td>Right Posterior Inferior Cerebellar Artery</td><td>7 (1.4)</td></tr><tr><td>Left Posterior Inferior Cerebellar Artery</td><td>13 (2.7)</td></tr><tr><td>Basilar Artery</td><td>27 (5.5)</td></tr><tr><td>Right Vertebral Artery</td><td>4 (0.8)</td></tr><tr><td>Left Vertebral Artery</td><td>4 (0.8)</td></tr><tr><td>Others</td><td>27 (5.5)</td></tr><tr><td>Aneurysm treatment, n (%)</td><td>n = 492</td></tr><tr><td>Coiling (radiological)</td><td>398 (80.1)</td></tr><tr><td>Clipping (surgical)</td><td>55 (11.1)</td></tr><tr><td>No treatment</td><td>38 (7.7)</td></tr><tr><td>Unsuccessful treatment</td><td>1 (0.2)</td></tr><tr><td>Department</td><td>n = 492</td></tr><tr><td>11 (Aude)</td><td>34 (6.9)</td></tr><tr><td>12 (Aveyron)</td><td>9 (1.8)</td></tr><tr><td>30 (Gard)</td><td>134 (27.2)</td></tr><tr><td>34 (Herault)</td><td>200 (40.6)</td></tr><tr><td>48 (Lozère)</td><td>17 (3.5)</td></tr><tr><td>66 (Pyrenees Orientales)</td><td>98 (19.9)</td></tr><tr><td>Time period at diagnosis</td><td>n = 436</td></tr><tr><td>00:00–06:00</td><td>58 (13.3)</td></tr><tr><td>06:00–12:00</td><td>96 (22)</td></tr><tr><td>12:00–18:00</td><td>143 (32.7)</td></tr><tr><td>18:00–00:00</td><td>137 (31.4)</td></tr></tbody></table>

BMI: Body Mass Index.

was 19.4%. The majority of aSAH cases in our study were represented by Fisher Grades 3 and 4, accounting for 34.3% and 44.5%, respectively and WFNS Grades 1 and 5, accounting for 38.2% and 27.2% respectively. The mean diagnostic delay was 1.07 days, corresponding to the time between symptom onset and the date of the diagnostic CT scan.

A total of 162 aneurysms (34.7%) had a size lower than 5 mm, 219 (46.9%) had a size ranging from 5 to 10 mm, and 86 (18.4%) were greater than 10 mm. The anterior communicating artery was the most represented site, accounting for 28.2% of cases, followed by the right middle cerebral artery (13.3%). The majority (80.1%) of our aSAH cases were treated with a radiological approach (coiling). Most patients were from the Hérault department (40.6%), followed by the Gard (27.2%) and the Pyrenees Orientales (19.9%) (Supplementary Figure C). Most cases occurred between noon and midnight.

## 3.2. Monthly incidence by year and season

aSAH cumulative incidence over 5 years was highest in February (n = 62; 11.5%) and August (n = 54; 10%), and lowest in April and June (n = 36 and 38; 6.6 and 7%) (Fig. 1). The season with the highest aSAH cumulative incidence rate was winter (n = 150; 27.8%), while spring had the lowest rate (n = 129; 23%). Monthly distribution was consistent across the 5-year study period, except for a peak in August 2018 with 20 recorded cases and a lower overall incidence in 2022 compared to other years, with only 84 cases.

## 3.3. Multivariate logistic lasso regression

Table 2 presents the results of the multivariate logistic regression model for the occurrence of aSAH according to weather variables.

The multivariate analysis including two control days had an accuracy of 0.56 (95% CI 0.53–0.59) (sensitivity 51.0% and specificity 60.1%). Area under the curve was 0.58 (95% CI 0.55–0.62). Given the low predictive value of the model, we could not put forward any weather parameter associated with the occurrence of aSAH (Table 2). Therefore, despite significant results with some of the weather variables, they remain inconclusive (Table 2).

The sensitivity analysis model using one randomly selected control day provided similar results and was also inconclusive.

## 3.4. Complementary descriptive analysis

### 3.4.1. Barometric pressure

Fig. 2 shows the distribution of mean pressure on days with aSAH compared to national average pressure (1013.25 hPa) and our administrative health region average pressure (1016.97 hPa). The average pressure on days with aSAH (1017.60 hPa) was not statistically different from our administrative health region average pressure.

Also, no clear pattern was found comparing barometric pressure between aSAH days and the mean of the 5 preceding days.

### 3.4.2. Humidity

Relative humidity between 40% and 60% corresponds to the comfort zone, and the average relative humidity for aSAH days was above this range (67.38%). It is worth noting that 66.4% of aSAH occurred in high humidity conditions (>60%), with 23.6% in humidity level >80%, 29.3% of aSAH occurred in normal humidity conditions (40–60%), and only 4.2% of aSAH occurred in low humidity conditions (<40%) (Fig. 3).

### 3.4.3. Thunderstorms

A total of 18% of aSAH events occurred within 3 days after a thunder event. This percentage increased to 25.41% if we consider the 5 days prior to the aSAH onset.

There seems to be a varied distribution between the occurrence of aSAH and the number of lightnings associated with the storm event. Yet most thunderstorms that occurred in the days preceding the aSAH were
<figure><img src="image_3.png" /><figcaption>**Fig. 1.** Comparison of incidence of aneurysmal subarachnoid hemorrhage on to a monthly scale between April 1st, 2018, and December 31st, 2022 and seasonal frequency of aSAH in our sanitary region.</figcaption></figure>

**Table 2**

Multiple logistic regression test for the occurrence of aSAH according to weather variables selected according to the AIC criterion.

<table><thead><tr><th></th><th>Estimate</th><th>Standard Error</th><th>p</th></tr></thead><tbody><tr><td>Minimum temperature (D-1)</td><td>-0.104</td><td>0.047</td><td>0.025</td></tr><tr><td>Maximum temperature (D-1)</td><td>-0.181</td><td>0.064</td><td>0.005</td></tr><tr><td>Average temperature (D-1)</td><td>0.257</td><td>0.100</td><td>0.010</td></tr><tr><td>Minimum humidity (D-1)</td><td>-0.032</td><td>0.014</td><td>0.018</td></tr><tr><td>Maximum humidity (D-1)</td><td>-0.021</td><td>0.012</td><td>0.089</td></tr><tr><td>Duration of ≤40% humidity (D-1)</td><td>0.001</td><td>0.0004</td><td>0.090</td></tr><tr><td>Average humidity (D-1)</td><td>0.060</td><td>0.020</td><td>0.002</td></tr><tr><td>Average temperature (D-3)</td><td>0.035</td><td>0.024</td><td>0.145</td></tr><tr><td>Average wind speed (D-3)</td><td>-0.059</td><td>0.030</td><td>0.051</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Distribution of the mean barometric pressure in hectopascals (hPa) the days of aSAH. Red dotted line indicates France normal pressure (1013.25 hPa). Green dotted line indicates the average pressure for our region (1016.97 hPa). Black dotted line indicates the average pressure for aSAH days (1017.60 hPa).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Distribution of the relative humidity (%) on the days with aSAH. The average relative humidity for aSAH days is 67.38% (red dotted line).</figcaption></figure>

of low intensity (between 0 and 10 kA).

## 4. Discussion

Our study analyzed a large number of aSAH cases and meteorological parameters over a 5-year period in a geographical region characterized by particular thunderstorm events. The main multivariate model's accuracy was poor, meaning it does not provide any evidence regarding the association between meteorological parameters and the occurrence of aSAH. The large number of weather variables measured represents a strength of this study. Nevertheless, this lead to a prediction model which found significant associations that should not be retained.

### 4.1. Seasonality

Studies in the 1990s and 2000s attempted to demonstrate seasonality in the prevalence of aneurysmal subarachnoid hemorrhages [16–18]. However, the results were mostly nonsignificant, despite noting peaks in

<footnote>*Significant p values are indicated (p < 0.05). Variables are daily, D-1 = 1 day prior to the event, D-3 = 3 days prior to the event.</footnote>
incidence during autumn and spring.

Our study, on the other hand, did not indicate any seasonality in the
occurrence of aSAH.

SARS-CoV-2 infection did not appear to have had any impact on our
results, as the annual incidence of aSAH was comparable between the
five years of the study, apart from a slightly lower incidence in 2022.
Also, the incidence of aSAH cases remained unchanged during the suc-
cessive periods of confinement between 2020 and 2021.

## 4.2. Impact of meteorological factors

Recent studies suggested that drops in temperature and barometric
pressures greater than 10 hectopascals (hPa) may be responsible for an
increased prevalence of aSAH in the days that follow [18–21]. Other
meteorological factors such as precipitation, wind speed, clouds and
lunar cycles have not shown significance [9,11]. As regards humidity,
contradictory results have been reported [7,8]. The absence of statistical
association in these studies may be attributed to the analysis of monthly
data and the examination of different types of SAH, rather than focusing
solely on aneurysmal cases [22–24].

Our study does not provide evidence for any association with
weather variables. Obtaining reliable and representative meteorological
data for this vast geographical area is challenging. To improve coverage,
meteorological data were collected from 45 stations across the area.
Each case of aSAH was associated with the closest station to the onset
symptom location to improve accuracy. However, the geographical
location was imprecise, as it was mostly defined as the patient munici-
pality of residence. Yet it is possible that patients ruptured their aneu-
rysm at their workplace or during travel. It may be advisable to obtain
data through the study of rescue team intervention reports. Also, the
closest meteorological station to the patients’ residence may introduce
bias due to potentially large distance from this station and meteoro-
logical phenomena are, by definition, very localized spatially and
temporally. The study of daily average data does not allow for the ex-
amination of epiphenomena.

To determine the day of aneurysm rupture, we considered the onset
of symptoms as the primary event. In most cases, the day of diagnosis
does not align with the day of symptom onset or the exact day of
aneurysmal rupture, with a several days delay. Therefore, our approach
to study meteorological changes in the days preceding the symptom
onset allowed to mitigate this bias. In our study, we found a delay be-
tween symptom onset and aSAH of 1.07 days. This delay is likely
underestimated as the date of symptom onset was approximate. It was
either self-reported by the patient or estimated based on the date of the
diagnostic scan.

One of the strengths of our study is the statistical methodology used.
We used a multivariate logistic regression test, well-suited to study the
association between an event and multiple variables. In addition, we
explored a large cohort of more than 490 patients, covering a 5-year
period. Also, our center serves as the reference for our administrative
health region and receives all aSAH cases across six different de-
partments, thereby limiting potential selection bias. Our study covered
the eastern part of the second-largest territory in Metropolitan France,
spanning over 36,111 km². Our meteorological database had missing
data, as some variables were not measured by all stations. Nevertheless,
the meteorological database contained 1,081,078 measures.

## 4.3. Impact of climate events

The study in Yamaguchi, Japan has shown an increase in aSAH
prevalence in the days preceding and following typhoons [14]. How-
ever, hurricanes studied in Florida did not demonstrate a significant
relationship [25]. Our study is one of the few to investigate the corre-
lation between thunderstorm activity and aSAH. However, the logistic
regression analysis did not include thunderstorms due to missing data.
We aimed to investigate the association between aSAH and ‘Cevenol

episodes’, but we could not identify events that met the official defini-
tion. Only around ten cases of aSAH were associated with intense pre-
cipitation and a thunderstorm event, suggesting no link between the
‘Cevenol episodes’ and aSAH. Missing precipitation data may explain
this result. This remains an area for further research or future studies.

In future studies, it may be crucial to focus on the emergence of
clusters, as climatic phenomena alone cannot fully explain the prevalence of aSAH.

## 4.4. Pathophysiological explanation

The mechanisms behind aneurysmal rupture are still unknown. It
could be caused by sudden changes in blood pressure, which may be
influenced by meteorological factors such as temperature and baro-
metric pressure. The study of Yaqin Ni et al. (2020) showed that indoor
and outdoor temperature was negatively correlated with blood pressure
[26]. In turn, barometric pressure was positively correlated with blood
pressure but not with humidity [26]. Currently, the mechanisms behind
the correlation between temperature and blood pressure are unclear. A
temperature decrease could stimulate the sympathetic nervous system,
causing a rise in heart rate and subsequent increase in blood pressure.
Additionally, it may lead to elevated blood pressure by constricting
blood vessels or impairing endothelium-dependent vasodilation [27,
28]. These mechanisms have also been suspected in ruptured aortic
aneurysms where the primary meteorological factor associated with
their occurrence is a sudden decrease in temperature [29].

Barometric pressure can increase aneurysmal transmural pressure by
decreasing intracranial/intraventricular pressure or increasing blood
pressure. A study from Poland suggested that abrupt drops in barometric
pressure might increase intracranial pressure. Mechanisms remain un-
clear, and may involve alterations in inflammation mediators [30].

## 5. Conclusion

Based on a large cohort of aSAH cases in Southern France and a large
meteorological database, our study did not provide evidence regarding
the association between weather parameters and the occurrence of
aSAH.

Additional research with high-quality geolocalisation data, as well as
large meta-analyses are required to shed light on this much debated
issue and better understand the pathophysiology and actual effects of
weather conditions on cerebral aneurysm rupture.

## Credit authorship contribution statement

Conceptualization: CD, FG Methodology: EM, NM Data collection: CD, FG Formal analysis: EM, NM, CD Investigation: CD, FG, Writing – original draft: CD, FG, PFP, VM, JP. / Writing - review : all authors Visualization and Supervision : FG, KC, VS, PFP, GC, CD, CD.

## Funding

This research did not receive any specific grant from funding
agencies in the public, commercial, or not-for-profit sectors.

## Declaration of competing interest

Authors declare no conflict of interest.

## Acknowledgements

We would like to thank not only all the patients for their collabo-
ration but also the associations of help and support which allowed us to
contact them: Mr. FIFRE Gregory (Météo France), Mrs. SOUBIELLE
Florence and Mr. SCHMITT Stéphane (Météorage) for the collect of all
our meteorological data, Mrs. GARNIER Océane, Mr. MESNILDREY
Quentin for the assistance in preparing this manuscript.

## Appendix A. Supplementary data

Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.neuchi.2025.101630.

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