Matthias Borowski

Complex, often high-dimensional time series are observed in medical applications such as intensive care. We review statistical tools for intelligent alarm systems, which are helpful for guiding medical decision-making in time-critical situations. The procedures described can also be applied for decision support or in closed-loop controllers. Robust time series filters allow one to extract a signal in the form of a time-varying trend with little or no delay. Additional rules—based, for instance, on suitably designed statistical tests—can be incorporated to preserve or detect interesting patterns such as level shifts or trend changes. Statistical pattern detection is a useful preprocessing step for decision-support systems. Dimension reduction techniques allow the compression of the often high-dimensional time series into a few variables containing most of the information inherent in the observed data. Combining such techniques with tools for analyzing the relationships among the variables in the form of large partial correlations or similar trend behavior improves the interpretability of the extracted variables and provides information that is thus meaningful to physicians.

Background: Sudden sensorineural hearing loss (SSHL) is a disease, which severely affects the patient's social and relational life. The underlying pathomechanisms have not been finally clarified yet and outcome is not predictable. Methods: We conducted a retrospective study in order to identify parameters that influence hearing recovery. The data base contains results of basic otoneurological tests and clinical parameters of 198 patients with idiopathic SSHL of at least 60 dB in at least four frequencies, diagnosed and treated at the University Hospital of Münster, Germany, between 1999 and 2015. Hearing recovery was measured by pure tone audiometry. Results: Multivariate linear and logistic regression analyses indicate that the chance as well as the magnitude of hearing recovery is higher for patients with normal caloric testing than for patients with pathological caloric testing. However, for the subgroup of patients who attained a hearing recovery, the caloric testing result was not found to influence the magnitude. Instead, the magnitude was noticeably lower for patients within this subgroup who had a previous hearing loss. Furthermore, we found indications that the magnitude is higher for men than for women and that receiving a high-dose steroid therapy is associated with a higher chance and magnitude of a hearing recovery. Conclusions: We conclude that SSHL associated with disorders of the vestibular system or previous hearing loss represent special sub-entities of SSHL that may be caused by unique pathophysiological mechanisms and are associated with worse outcome. Furthermore, our data support the importance of elevated dosage of steroids in SSHL therapy.

Non-vitamin K antagonist oral anticoagulants (NOACs) such as dabigatran or rivaroxaban are alternatives to vitamin K antagonists (VKAs) for prevention of stroke and systemic embolism in patients with atrial fibrillation (AF) and atrial flutter (AFL). Incidences of risk factors for left atrium (LA) and left atrial appendage (LAA) thrombus formation, such as dense spontaneous echo contrast (SEC), low LAA velocity (LAAV) <20 cm/s under treatment with dabigatran and rivaroxaban in comparison with VKAs are unknown. We studied 306 patients with AF (94 %) and AFL (6 %) undergoing transesophageal echocardiography. Patients received VKAs (n = 138), dabigatran (n = 68), or rivaroxaban (n = 100) for at least 3 weeks prior to investigation. Time in therapeutic range was 67 % for VKA. Mean CHADS2 score and CHA2DS2-VASc score were 1.3 and 2.5, respectively. Left atrial abnormality was defined as either dense SEC, low LAAV <20 cm/s, or thrombus. Any LA abnormality occurred in 9, 3, and 5 % of patients receiving VKA, dabigatran, and rivaroxaban, respectively. The most frequent abnormality was LAA thrombus (VKA: 4 %, dabigatran: 0 %, rivaroxaban: 2 %) and low LAAV of less than 20 cm/s (VKA: 4 %, dabigatran: 1 %, rivaroxaban: 1 %), followed by dense SEC (VKA: 2 %, dabigatran: 1 %, rivaroxaban: 2 %). Results of uni- and multivariate analyses revealed a numerically lower but not significantly different frequency of any LA abnormality under dabigatran (OR 0.4, 95 % Cl 0.08 − 1.88, p = 0.25) and rivaroxaban (OR 0.65, 95 % Cl 0.22 − 1.98, p = 0.45) compared to VKA. With respect to the incidence of LA abnormalities, dabigatran and rivaroxaban are not inferior to VKA.

We investigate and develop methods for structural break detection, considering time series from thermal spraying process monitoring. Since engineers induce technical malfunctions during the processes, the time series exhibit structural breaks at known time points, giving us valuable information to conduct the investigations. First, we consider a recently developed robust online (also real-time) filtering (i.e. smoothing) procedure that comprises a test for local linearity. This test rejects when jumps and trend changes are present, so that it can also be useful to detect such structural breaks online. Second, based on the filtering procedure we develop a robust method for the online detection of ongoing trends. We investigate these two methods as to the online detection of structural breaks by simulations and applications to the time series from the manipulated spraying processes. Third, we consider a recently developed fluctuation test for constant variances that can be applied offline, i.e. after the whole time series has been observed, to control the spraying results. Since this test is not reliable when jumps are present in the time series, we suggest data transformation based on filtering and demonstrate that this transformation makes the test applicable.