A pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion

Objective Levodopa in presence of decarboxylase inhibitors is following two-compartment kinetics and its effect is typically modelled using sigmoid Emax models. Pharmacokinetic modelling of the absorption phase of oral distributions is problematic because of irregular gastric emptying. The purpose of this work was to identify and estimate a population pharmacokinetic- pharmacodynamic model for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Methods The modelling involved pooling data from two studies and fixing some parameters to values found in literature (Chan et al. J Pharmacokinet Pharmacodyn. 2005 Aug;32(3-4):307-31). The first study involved 12 patients on 3 occasions and is described in Nyholm et al. Clinical Neuropharmacology 2003:26:156-63. The second study, PEDAL, involved 3 patients on 2 occasions. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Plasma samples and motor ratings (clinical assessment of motor function from video recordings on a treatment response scale between -3 and 3, where -3 represents severe parkinsonism and 3 represents severe dyskinesia.) were repeatedly collected until the clinical effect was back at baseline. At this point, the usual infusion rate was started and sampling continued for another two hours. Different structural absorption models and effect models were evaluated using the value of the objective function in the NONMEM package. Population mean parameter values, standard error of estimates (SE) and if possible, interindividual/interoccasion variability (IIV/IOV) were estimated. Results Our results indicate that Duodopa absorption can be modelled with an absorption compartment with an added bioavailability fraction and a lag time. The most successful effect model was of sigmoid Emax type with a steep Hill coefficient and an effect compartment delay. Estimated parameter values are presented in the table. Conclusions The absorption and effect models were reasonably successful in fitting observed data and can be used in simulation experiments.

Patientens upplevelser efter en gastric byass operation : en kvalitativ intervjustudie

Syftet med studien var att beskriva patientens upplevelser efter en gastric bypass operation. En empirisk studie med kvalitativ ansats genomfördes, där intervjuer skedde med sex personer som genomfört en gastric bypass operation. Data analyserades genom kvalitativ innehållsanalys. Under intervjuerna framkom att informanterna upplevde att operationen inte hade någon negativ inverkan på deras vardagliga liv. De upplevde en ökad livskvalitet och förbättrad hälsa som lett till ett mer fysiskt aktivt liv. Viktnedgången tillsammans med omgivningens positiva reaktioner på den nya kroppen hade stärkt deras självförtroende. Den största förändringen informanterna upplevde i det vardagliga livet var deras förändrade matvanor. De beskrev att maten var i fokus och att de planerade sin vardag efter måltiderna. De följder som framkom upplevdes inte som något stort problem, utan viktminskningen och de positiva hälsoupplevelserna dominerade. Informanterna kände sig välinformerade och hade realistiska förväntningar på operationen, samt var förberedda på de konsekvenser som kunde uppstå. Studien visar att den specialiserade vården på överviktskliniker kan bidra till att underlätta tiden efter operationen för patienten. Det framkom att informanterna upplevde en kunskapsbrist om gastric bypass operationer bland sjukvårdspersonal, inom primärvård och slutenvård. För att patienten ska känna trygghet och förtroende är det därför viktigt att öka kunskapen om överviktsoperationer bland hälso- och sjukvårdspersonal.

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.

Vuxna personers upplevelse av hälsorelaterad livskvalité efter en gastric bypass operation : –En litteraturöversikt

Bakgrund: Fetma och övervikt har blivit vanligare den senaste tiden och är idag ett stort hälsoproblem över hela världen. Många har svårt att gå ner i vikt på egen hand vilket har gjort att kirurgi har blivit allt vanligare de senaste åren. Gastric bypass är idag den vanligaste kirurgiska metoden för viktminskning och har visat goda resultat. Däremot kan den hälsorelaterade livskvalitén påverkas då operationen innebär en stor livsstilsförändring. Syfte: Syftet med denna studie var att beskriva vuxna personers upplevelse av hälsorelaterad livskvalité efter en gastric bypass operation. Metod: En litteraturöversikt med 11 kvantitativa och 3 kvalitativa vetenskapliga artiklar som ligger till grund för hur vuxna personer upplever sin hälsorelaterade livskvalité efter en gastric bypass operation. Resultat: Hälsorelaterad livskvalité (HRQOL) har visat en förbättring i samtliga studier efter en gastric bypass operation. HRQOL har haft sin topp efter 1 månad i samtliga skalor utifrån SF-36 frågeformulär. Slutsats: Den stora livsstilsförändringen som personer går igenom efter en gastric bypass operationen har visat förbättringar i HRQOL på både lång och kort sikt. Bidragande faktorer som kan påverka den förbättrade hälsorelaterade livskvalitén kan bland annat vara uppfyllda förväntningar av operationen och fysisk aktivitet.