Introducing a nationwide registry: the Swiss study on aneurysmal subarachnoid haemorrhage (Swiss SOS)

Background: Aneurysmal subarachnoid haemorrhage (aSAH) is a haemorrhagic form of stroke and occurs in a younger population compared with ischaemic stroke or intracerebral haemorrhage. It accounts for a large proportion of productive life-years lost to stroke. Its surgical and medical treatment represents a multidisciplinary effort. Due to the complexity of the disease, the management remains difficult to standardise and quality of care is accordingly difficult to assess. Objective: To create a registry to assess management parameters of patients treated for aSAH in Switzerland. Methods: A cohort study was initiated with the aim to record characteristics of patients admitted with aSAH, starting January 1st 2009. Ethical committee approval was obtained or is pending from the institutional review boards of all centres. In the study period, seven Swiss hospitals (five university [U], two non-university medical centres) harbouring a neurosurgery department, an intensive care unit and an interventional neuroradiology team so far agreed to participate in the registry (Aarau, Basel [U], Bern [U], Geneva [U], Lausanne [U], St. Gallen, Zürich [U]). Demographic and clinical parameters are entered into a common database. Discussion: This database will soon provide (1) a nationwide assessment of the current standard of care and (2) the outcomes for patients suffering from aSAH in Switzerland. Based on data from this registry, we can conduct cohort comparisons or design diagnostic or therapeutic studies on a national level. Moreover, a standardised registration system will allow healthcare providers to assess the quality of car

Third-generation cephalosporins as antibiotic prophylaxis in neurosurgery: what's the evidence?

To analyze the role of third-generation cephalosporins as prophylactic antibiotics in neurosurgery. We reviewed the literature for data from randomized controlled trials (RCTs) on third-generation cephalosporins compared to other antibiotic regimen in neurosurgery. End point of the RCTs was the occurrence of surgical site infections (SSIs)--data were pooled in a fixed-effects meta-analysis. Five randomized controlled trials enrolling a total of 2209 patients were identified. The pooled odds ratio for SSIs (overall) with third-generation cephalosporins prophylaxis in the five RCTs was 0.94 (95% CI, 0.59-1.52; P=0.81). No significant difference between third-generation cephalosporins and alternative regimen was identified. When analyzing organ SSIs (osteomyelitis, meningitis, and others intracranial infections) in data derived from four RCTs (1596 patients), third-generation cephalosporins failed to show superiority (pooled odds ratio 0.88; 95% CI 0.45-1.74; P=0.72). Third-generation cephalosporin antibiotic prophylaxis fails to show superiority over conventional regimens regarding both incisional and organ related SSIs in neurosurgery

Ruptured rathke cleft cyst mimicking pituitary apoplexy

Rathke cleft cysts (RCCs) are benign cystic lesions of the sellar and suprasellar region that are asymptomatic in most cases. Occasionally, compression of the optic pathway and hypothalamo-pituitary structures may cause clinical symptoms, such as headaches, visual deficits and endocrinopathies. Acute presentation caused by hemorrhage into an RCC have been described in the literature, and the term "Rathke cleft cyst apoplexy" has been coined. We present the case of a 32-year-old man with acute onset of meningitis-type symptoms and imaging findings resembling hemorrhagic pituitary tumor apoplexy. In retrospect, clinical symptoms, intraoperative appearance, and histologic examination were compatible with the diagnosis of nonhemorrhagic rupture of an RCC. Thus, the clinical presentation of "Rathke cleft cyst apoplexy" is not necessarily caused by hemorrhage

Meteorological influences on the incidence of aneurysmal subarachnoid hemorrhage - a single center study of 511 patients.

OBJECTIVE: To assess the potential meteorological influence on the incidence of aneurysmal subarachnoid hemorrhage (SAH). Previous studies used inhomogeneous patient groups, insufficient study periods or inappropriate statistics. PATIENTS AND METHODS: We analyzed 511 SAH admissions between 2004 and 2012 for which aneurysmal rupture occurred within the Zurich region. The hourly meteorological parameters considered are: surface pressure, 2-m temperature, relative humidity and wind gusts, sunshine, and precipitation. For all parameters we investigate three complementary statistical measures: i) the time evolution from 5 days before to 5 days after the SAH occurrence; ii) the deviation from the 10-year monthly mean; and iii) the change relative to the parameter's value two days before SAH occurrence. The statistical significance of the results is determined using a Monte Carlo simulation combined with a re-sampling technique (1000×). RESULTS: Regarding the meteorological parameters considered, no statistically significant signal could be found. The distributions of deviations relative to the climatology and of the changes during the two days prior to SAH events agree with the distributions for the randomly chosen days. The analysis was repeated separately for winter and summer to exclude compensating effects between the seasons. CONCLUSION: By using high-quality meteorological data analyzed with a sophisticated and robust statistical method no clearly identifiable meteorological influence for the SAH events considered can be found. Further studies on the influence of the investigated parameters on SAH incidence seem redundant

Seasonal distribution of SAH events.

<p>The seasonal distribution of SAH events between 2005 and 2011 (whole-year data sets) is depicted for individual years (A) and for the entire studied time period (B). While there are monthly peaks in individual years (A), no obvious peak can be identified when analyzing the entire studied time period (B).</p

Time evolution of meteorological parameters (gust, precipitation, relative humidity and sunshine) around the SAH day, as in <b>Figure 1A and B</b>.

<p>The boxplots are for site SMA.</p

Deviation from the 10-year monthly mean for humidity and pressure.

<p>Statistical analysis as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081621#pone-0081621-g002" target="_blank">Figure 2B</a> for relative humidity (A) and pressure (B), corresponding to the parameters with highest statistical signal. The right panels compare the observed value (green line) with the distribution from a Monte Carlo simulation with 1000 members (see text for details).</p

Short-time changes in humidity and sunshine.

<p>A statistical analysis as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0081621#pone-0081621-g002" target="_blank">Figure 2D</a> for the short-time change in relative humidity (A) and sunshine (B) is depicted. The observed changes (green line) are compared to the distribution from a Monte Carlo simulation with 1000 members (see text for details).</p

Time evolution from 5 days before to 5 days after SAH occurrence.

<p>The statistical analysis for measurement site SMA and for temperature (A) and pressure (B) is depicted.</p

Temperature deviation from the 10-year monthly mean and temperature changes relative to two days before SAH occurrence.

<p>Panel (A) shows a histogram of observed temperatures on SAH days relative to the 10-year monthly means. The green value gives the mean over all observed temperature anomalies on SAH days; (B) the green line corresponds to the observed mean given in panel (A) and the blue distribution results from a Monte Carlo simulation with 1000 members, assuming that no relationship between SAH and temperature exists. Panels (C) and (D) show correspondingly the short-term change in temperature relative to the SAH day. Hence, (C) shows the distribution of the observed temperature changes from 2 days before to the SAH day (see text for details) - in the mean, no temperature change is discernible (green line); (D) shows the observed mean from panel (C) as a green line and the distribution from the Monte Carlo simulations. The P-value gives the number of Monte Carlo members to the right of the observed value.</p