Fear causes tears – perineal injuries in home birth settings : a Swedish interview study

Background: Perineal injury is a serious complication of vaginal delivery that has a severe impact on the quality of life of healthy women. The prevalence of perineal injuries among women who give birth in hospital has increased over the last decade, while it is lower among women who give birth at home. The aim of this study was to describe the practice of midwives in home birth settings with the focus on the occurrence of perineal injuries. Methods: Twenty midwives who had assisted home births for between one and 29 years were interviewed using an interview guide. The midwives also had experience of working in a hospital delivery ward. All the interviews were tape-recorded and transcribed. Content analysis was used. Results: The overall theme was "No rushing and tearing about", describing the midwives' focus on the natural process taking its time. The subcategories 1) preparing for the birth; 2) going along with the physiological process; 3) creating a sense of security; 4) the critical moment and 5) midwifery skills illuminate the management of labor as experienced by the midwives when assisting births at home. Conclusions: Midwives who assist women who give birth at home take many things into account in order to minimize the risk of complications during birth. Protection of the woman's perineum is an act of awareness that is not limited to the actual moment of the pushing phase but starts earlier, along with the communication between the midwife and the woman.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Vårdpersonalens kunskapsläge i hjärtlungräddning samt följsamhet till det svenska hjärtlungräddningsregistret på ett länssjukhus i Mellansverige : En kvantitativ tvärsnittsstudie

Syfte: Att kartlägga vårdpersonalens kunskapsläge samt utbildningsfrekvens i hjärtlungräddning på ett länssjukhus i Mellansverige, samt beskriva följsamheten till att registrera behandlade hjärtstopp till det svenska hjärt-lungräddningsregistret. Metod: Enkätstudie med kvantitativ ansats bestående av 177 respondenter samt även som en retrospektiv observationsstudie. Huvudresultat: Enskilda personer svarade rätt på alla kunskapsfrågorna men som grupp fanns det brister i kunskapen i hjärtlungräddning. Då man jämförde vårdpersonalens kunskap påvisades att i fyra av sju kunskapsfrågor fanns en signifikant skillnad i kunskap mellan den vårdpersonal som har mer regelbunden utbildning, än den som har mindre. De som hade mer regelbunden utbildning hade flera rätt. En signifikant skillnad påvisades även beroende på när man hade haft sin senaste HLR-utbildning, där de som haft sin utbildning nyligen hade flera rätt. Följsamheten hos vårdpersonalen till att registrera patienter som behandlats för hjärtstopp på sjukhus till det svenska hjärt-lungräddningsregistret, kan sammanfattas med att det brister i rapporteringen. Konklusion: Det är viktigt att skapa förutsättningar för frekventa utbildningar till vårdpersonal för att öka kunskap och beredskap i hjärt- och lungräddning, vilket även kan ses som ett kvalitetssäkringsarbete. Ett förbättringsarbete är nödvändigt för att förbättra följsamheten till registreringen.