Profiles

Michael Ingre

FD

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Arbetar vid Psykologiska institutionen
E-post michael.ingre@su.se
Besöksadress Frescati hagväg 16 A
Rum 337
Postadress Psykologiska institutionen 106 91 Stockholm

Publikationer

I urval från Stockholms universitets publikationsdatabas
  • 2016. Gustav Nilsonne (et al.). PLoS ONE 11 (11)

    The pleiotropic cytokine interleukin-6 (IL-6) has been proposed to contribute to circadian regulation of sleepiness by increasing in the blood at night. Earlier studies have reported diurnal variation of IL-6, but phase estimates are conflicting. We have therefore performed a meta-analysis on the diurnal variation of circulating IL-6. Studies were included if they reported IL-6 in plasma or serum recorded at least twice within 24 hours in the same individual. A systematic search resulted in the inclusion of 43 studies with 56 datasets, for a total of 1100 participants. Individual participant data were available from 4 datasets with a total of 56 participants. Mixed-effects meta-regression modelling confirmed that IL-6 varied across the day, the most conspicuous effect being a trough in the morning. These results stand in contrast to earlier findings of a peak in the evening or night, and suggest that diurnal variation should be taken into account in order to avoid confounding by time of day in studies of IL-6 in plasma or serum.

  • 2014. Göran Kecklund (et al.).
  • 2014. A. Anund (et al.).
  • 2014. Igor Radun (et al.). Journal of sleep research, Special issue
  • 2014. Michael Ingre (et al.). PLoS ONE 9 (10), e108679

    Sleepiness and fatigue are important risk factors in the transport sector and bio-mathematical sleepiness, sleep and fatigue modeling is increasingly becoming a valuable tool for assessing safety of work schedules and rosters in Fatigue Risk Management Systems (FRMS). The present study sought to validate the inner workings of one such model, Three Process Model (TPM), on aircrews and extend the model with functions to model jetlag and to directly assess the risk of any sleepiness level in any shift schedule or roster with and without knowledge of sleep timings. We collected sleep and sleepiness data from 136 aircrews in a real life situation by means of an application running on a handheld touch screen computer device (iPhone, iPod or iPad) and used the TPM to predict sleepiness with varying level of complexity of model equations and data. The results based on multilevel linear and non-linear mixed effects models showed that the TPM predictions correlated with observed ratings of sleepiness, but explorative analyses suggest that the default model can be improved and reduced to include only two-processes (S+C), with adjusted phases of the circadian process based on a single question of circadian type. We also extended the model with a function to model jetlag acclimatization and with estimates of individual differences including reference limits accounting for 50%, 75% and 90% of the population as well as functions for predicting the probability of any level of sleepiness for ecological assessment of absolute and relative risk of sleepiness in shift systems for safety applications.

  • 2014. Michael Ingre (et al.). Journal of Sleep Research 23 (S1), 264-264
Visa alla publikationer av Michael Ingre vid Stockholms universitet

Senast uppdaterad: 24 maj 2017

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