liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 3 of 3
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Engerström, Lars
    et al.
    Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Anaesthesiology and Intensive Care in Norrköping. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Nolin, Thomas
    Central Hospital Kristianstad, Sweden.
    Mårdh, Caroline
    Landstinget Värmland, Sweden.
    Sjöberg, Folke
    Linköping University, Department of Clinical and Experimental Medicine, Division of Surgery, Orthopedics and Oncology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Anaesthetics, Operations and Specialty Surgery Center, Department of Hand and Plastic Surgery.
    Karlström, Göran
    Landstinget Varmland, Sweden.
    Fredrikson, Mats
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences, Forum Östergötland.
    Walther, Sten
    Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Thoracic and Vascular Surgery.
    Impact of Missing Physiologic Data on Performance of the Simplified Acute Physiology Score 3 Risk-Prediction Model*2017In: Critical Care Medicine, ISSN 0090-3493, E-ISSN 1530-0293, Vol. 45, no 12, p. 2006-2013Article in journal (Refereed)
    Abstract [en]

    Objectives: The Simplified Acute Physiology 3 outcome prediction model has a narrow time window for recording physiologic measurements. Our objective was to examine the prevalence and impact of missing physiologic data on the Simplified Acute Physiology 3 models performance. Design: Retrospective analysis of prospectively collected data. Setting: Sixty-three ICUs in the Swedish Intensive Care Registry. Patients: Patients admitted during 2011-2014 (n = 107,310). Interventions: None. Measurements and Main Results: Model performance was analyzed using the area under the receiver operating curve, scaled Briers score, and standardized mortality rate. We used a recalibrated Simplified Acute Physiology 3 model and examined model performance in the original dataset and in a dataset of complete records where missing data were generated (simulated dataset). One or more data were missing in 40.9% of the admissions, more common in survivors and low-risk admissions than in nonsurvivors and high-risk admissions. Discrimination did not decrease with one to two missing variables, but accuracy was highest with no missing data. Calibration was best in the original dataset with a mix of full records and records with some missing values (area under the receiver operating curve was 0.85, scaled Brier 27%, and standardized mortality rate 0.99). With zero, one, and two data missing, the scaled Brier was 31%, 26%, and 21%; area under the receiver operating curve was 0.84, 0.87, and 0.89; and standardized mortality rate was 0.92, 1.05 and 1.10, respectively. Datasets where the missing data were simulated for oxygenation or oxygenation and hydrogen ion concentration together performed worse than datasets with these data originally missing. Conclusions: There is a coupling between missing physiologic data, admission type, low risk, and survival. Increased loss of physiologic data reduced model performance and will deflate mortality risk, resulting in falsely high standardized mortality rates.

  • 2.
    Nasr, Patrik
    et al.
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Fredrikson, Mats
    Linköping University, Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection. Linköping University, Faculty of Medicine and Health Sciences, Forum Östergötland.
    Ekstedt, Mattias
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    Kechagias, Stergios
    Linköping University, Department of Health, Medicine and Caring Sciences, Division of Diagnostics and Specialist Medicine. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Gastroentorology.
    The Amount of Liver Fat Predicts Mortality and Development of Type 2 Diabetes in Non-alcoholic Fatty Liver Disease.2020In: Liver international (Print), ISSN 1478-3223, E-ISSN 1478-3231Article in journal (Refereed)
    Abstract [en]

    BACKGROUND & AIMS: Non-alcoholic fatty liver disease (NAFLD) is a risk factor for development of type 2 diabetes mellitus (T2DM). We aimed to evaluate whether conventional histological grading of steatosis and accurate quantification of fat content in liver biopsies using stereological point counting (SPC) can predict mortality and future development of T2DM in NAFLD patients.

    METHODS: 129 patients with biopsy proven NAFLD, enrolled between 1988 and 1992, were re-evaluated on two occasions, after 13.7 (±1.5) and 23.2 (±6.8) years. In patients accepting to undergo the procedure, repeat liver biopsies were performed on each follow-up and were evaluated with conventional histopathological methodology and SPC.

    RESULTS: Of the 106 patients without T2DM at baseline, 66 (62%) developed T2DM during a mean follow-up of 23.2 (± 6.8) years. Steatosis grade and liver fat measured with SPC independently (adjusted for age, BMI, fibrosis stage) predicted development of T2DM with an aHR of 1.60 per grade and 1.03 for each SPC percentage increase, respectively. Overall mortality and development of T2DM was more common in patients with grade 3 steatosis compared to lower grades of steatosis. Liver fat measured with SPC was significant for overall mortality (aHR 1.04). In patients that underwent repeat biopsy, reduction of liver fat measured with SPC was associated with decreased risk of developing T2DM (aHR 0.91 for each SPC percentage decrease).

    CONCLUSION: Steatosis grade and liver fat measured with SPC predict mortality and the risk of developing T2DM in NAFLD. Reduction of liver fat decreases the risk of developing T2DM.

  • 3.
    Nordwall, Maria
    et al.
    Linköping University, Department of Clinical and Experimental Medicine, Center for Social and Affective Neuroscience. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, Department of Paediatrics in Norrköping. Vrinnevi Hosp, Sweden.
    Fredrikson, Mats
    Linköping University, Department of Clinical and Experimental Medicine, Division of Neuro and Inflammation Science. Linköping University, Faculty of Medicine and Health Sciences, Forum Östergötland.
    Ludvigsson, Johnny
    Linköping University, Department of Clinical and Experimental Medicine, Division of Children's and Women's health. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center of Paediatrics and Gynaecology and Obstetrics, H.K.H. Kronprinsessan Victorias barn- och ungdomssjukhus.
    Arnqvist, Hans
    Linköping University, Department of Clinical and Experimental Medicine, Division of Cell Biology. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Heart and Medicine Center, Department of Endocrinology.
    Impact of Age of Onset, Puberty, and Glycemic Control Followed From Diagnosis on Incidence of Retinopathy in Type 1 Diabetes: The VISS Study2019In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 42, no 4, p. 609-616Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE To evaluate sex, age at diabetes onset, puberty, and HbA1c, with subjects followed from diabetes diagnosis and during different time periods, as risk factors for developing diabetic simplex and proliferative retinopathy.

    RESEARCH DESIGN AND METHODS In a population-based observational study, HbA1c for 451 patients diagnosed with diabetes before 35 years of age during 1983–1987 in southeast Sweden was followed for up to 18–24 years from diagnosis. Long-term mean weighted HbA1c(wHbA1c) was calculated. Retinopathy was evaluated by fundus photography and analyzed in relation to wHbA1c levels.

    RESULTS Lower wHbA1c, diabetes onset ≤5 years of age, and diabetes onset before puberty, but not sex, were associated with longer time to appearance of simplex retinopathy. Proliferative retinopathy was associated only with wHbA1c. The time to first appearance of any retinopathy decreased with increasing wHbA1c. Lower wHbA1c after ≤5 years’ diabetes duration was associated with later onset of simplex retinopathy but not proliferative retinopathy. With time, most patients developed simplex retinopathy, except for those of the category wHbA1c≤50 mmol/mol (6.7%), for which 20 of 36 patients were without any retinopathy at the end of the follow-up in contrast to none of 49 with wHbA1c >80 mmol/mol (9.5%).

    CONCLUSIONS Onset at ≤5 years of age and lower wHbA1c the first 5 years after diagnosis are associated with longer duration before development of simplex retinopathy. There is a strong positive association between long-term mean HbA1c measured from diagnosis and up to 20 years and appearance of both simplex and proliferative retinopathy.

1 - 3 of 3
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf