Laparoscopic versus open liver resection for intrahepatic cholangiocarcinoma: a multicenter propensity score-matched study

Background: The role of laparoscopy in the treatment of intrahepatic cholangiocarcinoma (ICC) remains unclear. This multicenter study examined the outcomes of laparoscopic liver resection for ICC. Methods: Patients with ICC who had undergone laparoscopic or open liver resection between 2012 and 2019 at four European expert centers were included in the study. Laparoscopic and open approaches were compared in terms of surgical and oncological outcomes. Propensity score matching was used for minimizing treatment selection bias and adjusting for confounders (age, ASA grade, tumor size, location, number of tumors and underlying liver disease). Results: Of 136 patients, 50 (36.7%) underwent laparoscopic resection, whereas 86 (63.3%) had open surgery. Median tumor size was larger (73.6 vs 55.1 mm, p¼ 0.01) and the incidence of bi-lobar tumors was higher (36.6 vs 6%, p< 0.01) in patients undergoing open surgery. After propensity score matching baseline characteristics were comparable although open surgery was associated with a larger fraction of major liver resections (74 vs 38%, p< 0.01), lymphadenectomy (60 vs 20%, p< 0.01) and longer operative time (294 vs 209 min, p< 0.01). Tumor characteristics were similar. Laparoscopic resection resulted in less complications (30 vs 52%, p¼ 0.025), fewer reoperations (4 vs 16%, p¼ 0.046) and shorter hospital stay (5 vs 8 days, p< 0.01). No differences were found in terms of recurrence, recurrence-free and overall survival. Conclusion: Laparoscopic resection seems to be associated with improved short-term and with similar long-term outcomes compared with open surgery in patients with ICC. However, possible selection criteria for laparoscopic surgery are yet to be defined

Wave-Current Interaction Effects on Airgap Calculations

The importance of wave-current interaction effects on the determination of mean drift forces on floating offshore structures is well documented. Wave-current interaction effects will also influence the first-order motions and loads as well as the diffracted and radiated waves around the structure. One of the significant contributions to the influence of wave-current interaction effects on the motion responses is the additional coupling between motion modes due to the current. These effects are well known from seakeeping calculations of ships with forward speed. A structure with fore-aft symmetry will have no hydrodynamic coupling between heave and pitch in regular waves only. Due to the presence of a current, the symmetry of the flow around the body is lost, resulting in hydrodynamic coupling between the modes. This will also occur for a moored structure with slowly varying motions in the horizontal plane. The most important couplings are from the heave motion into pitch and surge and from heave to roll and sway. These couplings are otherwise present only for asymmetric structures. Due to the presence of the heave resonance and cancellation periods, the motion responses in roll and pitch for a semi-submersible will be influenced by the wave-current interaction effects. Due to the differences in phase between the different motion modes, the hydrodynamic coupling may have significant influence on the rotational motions roll and pitch and thus significant influence on the prediction of airgap. This coupling between the heave and roll/pitch modes due to the current adds complexity to the numerical simulations since the structure responses are more sensitive to the actual orientation of the structure, mooring configuration etc. A three-dimensional linear potential flow code, MULDIF, has been developed by SINTEF Ocean. This code accounts for hydrodynamic interaction between waves and current from arbitrary directions. The code can be applied to single or multiple bodies in infinite or finite water depth. Verification studies have previously shown good agreement with other numerical codes, Hermundstad et.al. [1], Zhiyuan et.al [2]. Validation studies with emphasis on airgap and comparison with experimental results are presented and numerical results for airgap and upwell are visualized and discussed. It is demonstrated how MULDIF can be used in airgap studies.acceptedVersio

Funksjonsbasert N200 – Krav til ubundne materialer i bære- og forsterkningslag

Denne rapporten omhandler vurderinger knyttet til mulige funksjonskrav for ubundne materialer i bære- og forsterkningslag. SINTEF mener det er mest realistisk å stille funksjonskrav til vegbygging ved å stille krav til skadeutvikling og tilstand på vegoverflaten. Dette innebærer at det ikke stilles krav på de enkelte komponentene av en vegkonstruksjon, men på konstruksjonen i sin helhet. SINTEF mener at slike funksjonskrav bør innføres med en tilnærming der etterlevelse av funksjonskrav dokumenteres og sannsynliggjøres gjennom analytisk dimensjonering, men at fagområdet enda ikke kommet langt nok til at det kan gjennomføres på en god og sikker måte i løpet av kort tid.publishedVersio

Funksjonsbasert N200 Vegbygging

Denne rapporten omhandler vurderinger knyttet til videreutvikling av håndbok N200 Vegbygging i en mer funksjonsbasert retning. Gjennom litteratursøk er det sett på erfaringer med funksjonskrav i andre samfunnsområder og ved vegbygging i andre land. Med basis i dette er det foretatt en generell diskusjon av viktige aspekter knyttet til funksjonskrav. Det er i tillegg foretatt en konkret diskusjon av mulige funksjonskrav for frostsikting

Femårig grunnskolelærerutdanning på masternivå – ny og utfordrende : Et følgeforskningsprosjekt ved Høgskolen i Østfold : Delrapport 2

Følgeforskningsprosjektet MAGLU-forsk ble igangsatt sommeren 2018. Prosjektet ser på innføring av femårige grunnskolelærerutdanninger ved HiØ, og vil pågå til det første studentkullet som startet på MAGLU høsten 2017, har gjennomført sitt studium våren 2022. Dette er den andre delrapporten fra prosjektet. På oppdrag fra dekan ved avdeling for lærerutdanning skal prosjektgruppen gjennomføre et følgeforskningsprosjekt på implementering av nye femårige grunnskolelærerutdanninger ved Høgskolen i Østfold Grunnskolelærerutdanningene for 1-7 og 5-10 ble fra høsten 2017 utvidet med ett år fra fireårige til femårige utdanninger. Formålet med innføring av femårige grunnskolelærerutdanninger er at neste generasjon lærere skal få mer forskningsbasert kunnskap, mer faglig fordypning og mer praksis før de skal ut i jobb. Prosjektet ser på hvilken betydning innføring av femårig utdanning har for opplæringen (undervisning, arbeidsformer, vurderingsformer, praksisopplæring), samt hvordan studenter, faglærere, programkoordinatorer og praksislærere opplever de femårige MAGLU-masterne ved HiØ. Den første delrapporten fra prosjektet kom i august 2019, og var basert på en spørreundersøkelse blant studentene som startet på MAGLU høsten 2017, gruppeintervjuer med studenter og individuelle intervjuer med programkoordinatorer (Afdal og Bjordal 2019). Denne delrapporten er basert på intervjuer med faglærere og praksiskoordinatorer fra HiØ og praksislærere ved skoler der studentene har hatt praksisstudier. Rapporten er utformet av Hilde Afdal, Fred Rune Bjordal og Reidun Hoff-Jenssen. I arbeidet med rapporten har vi hatt samarbeid med Eva Maagerø, Ellen Rye og Birte Simonsen ved Universitetet i Sørøst-Norge (USN). Den samme intervjuguiden er brukt ved begge institusjonene, og en tilsvarende rapport som denne foreligger fra USN (Maagerø, E., Rye, E. & Simonsen, B. (2020)

Landmark estimation of transition probabilities in non-Markov multi-state models with covariates

In non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested by Putter and Spitioni, is to analyse a subsample of the full data, consisting of the individuals present in a specific state at a given landmark time-point. The AJ estimator of occupation probabilities is then applied to the landmark subsample. Exploiting the result by Datta and Satten, that the AJ estimator is consistent for state occupation probabilities even in non-Markov models given that censoring is independent of state occupancy and times of transition between states, the landmark Aalen–Johansen (LMAJ) estimator provides consistent estimates of transition probabilities. So far, this approach has only been studied for non-parametric estimation without covariates. In this paper, we show how semi-parametric regression models and inverse probability weights can be used in combination with the LMAJ estimator to perform covariate adjusted analyses. The methods are illustrated by a simulation study and an application to population-wide registry data on work, education and health-related absence in Norway. Results using the traditional AJ estimator and the LMAJ estimator are compared, and show large differences in estimated transition probabilities for highly non-Markov multi-state models

Landmark estimation of transition probabilities in non-Markov multi-state models with covariates

In non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested by Putter and Spitioni, is to analyse a subsample of the full data, consisting of the individuals present in a specific state at a given landmark time-point. The AJ estimator of occupation probabilities is then applied to the landmark subsample. Exploiting the result by Datta and Satten, that the AJ estimator is consistent for state occupation probabilities even in non-Markov models given that censoring is independent of state occupancy and times of transition between states, the landmark Aalen–Johansen (LMAJ) estimator provides consistent estimates of transition probabilities. So far, this approach has only been studied for non-parametric estimation without covariates. In this paper, we show how semi-parametric regression models and inverse probability weights can be used in combination with the LMAJ estimator to perform covariate adjusted analyses. The methods are illustrated by a simulation study and an application to population-wide registry data on work, education and health-related absence in Norway. Results using the traditional AJ estimator and the LMAJ estimator are compared, and show large differences in estimated transition probabilities for highly non-Markov multi-state models

Estimating the treatment effect on the treated under time-dependent confounding in an application to the Swiss HIV Cohort Study

When comparing time varying treatments in a non‐randomized setting, one must often correct for time‐dependent confounders that influence treatment choice over time and that are themselves influenced by treatment. We present a new two‐step procedure, based on additive hazard regression and linear increments models, for handling such confounding when estimating average treatment effects on the treated. The approach can also be used for mediation analysis. The method is applied to data from the Swiss HIV Cohort Study, estimating the effect of antiretroviral treatment on time to acquired immune deficiency syndrome or death. Compared with other methods for estimating the average treatment effects on the treated the method proposed is easy to implement by using available software packages in R. © 2017 Wile

A hybrid landmark Aalen-Johansen estimator for transition probabilities in partially non-Markov multi-state models

Multi-state models are increasingly being used to model complex epidemiological and clinical outcomes over time. It is common to assume that the models are Markov, but the assumption can often be unrealistic. The Markov assumption is seldomly checked and violations can lead to biased estimation of many parameters of interest. This is a well known problem for the standard Aalen-Johansen estimator of transition probabilities and several alternative estimators, not relying on the Markov assumption, have been suggested. A particularly simple approach known as landmarking have resulted in the Landmark-Aalen-Johansen estimator. Since landmarking is a stratification method a disadvantage of landmarking is data reduction, leading to a loss of power. This is problematic for “less traveled” transitions, and undesirable when such transitions indeed exhibit Markov behaviour. Introducing the concept of partially non-Markov multi-state models, we suggest a hybrid landmark Aalen-Johansen estimator for transition probabilities. We also show how non-Markov transitions can be identified using a testing procedure. The proposed estimator is a compromise between regular Aalen-Johansen and landmark estimation, using transition specific landmarking, and can drastically improve statistical power. We show that the proposed estimator is consistent, but that the traditional variance estimator can underestimate the variance of both the hybrid and landmark estimator. Bootstrapping is therefore recommended. The methods are compared in a simulation study and in a real data application using registry data to model individual transitions for a birth cohort of 184 951 Norwegian men between states of sick leave, disability, education, work and unemployment