Espen Svendsen Gjevestad

• Berge, Jarle; Nunavath, Vimala; Asbjørnsen, Rikke Aune; Borgeraas, Heidi; Hertel, Jens Kristoffer & Linge, Anita Dyb [Show all 15 contributors for this article] (2025). Machine learning for estimating cardiorespiratory fitness in patients with obesity: protocol for a retrospective and prospective multi - center cohort study (Preprint). JMIR Research Protocols. doi: 10.2196/preprints.85069. Full text in Research Archive Show summary

  BACKGROUND Cardiorespiratory fitness (VO2max) is a key predictor of cardiovascular and other health-related diseases and is often impaired in individuals with obesity due to functional and structural limitations. Improving cardiorespiratory fitness enhances overall health and reduces mortality, making it an important indicator for preventing and treating obesity. OBJECTIVE The primary aim of this study is to develop an obesity-specific machine learning (ML) model that can accurately estimate VO2max, a key indicator of cardiovascular fitness, and make it accessible through a web-based application. METHODS A ML model will be trained to estimate VO2max in individuals with obesity using retrospective data combining assessments of VO2max tests and clinical parameters from adult patients with severe obesity body mass index (BMI ≥40.0 kg/m2, or 35.0-39.9 kg/m2 with at least one obesity-related comorbidity) from Vestfold Hospital Trust, Muritunet Rehabilitation Institution and Norwegian School of Sport Sciences. The ML-based VO2max estimation model will be presented as a web application, allowing easy access and interaction. The model’s estimations will be compared against direct VO2max measurements obtained from medical equipment across institutions as part of a prospective validation. Ethical approval has been obtained for the use of two databases in the initial model development; approval for the remaining data and prospective phase is pending. RESULTS Vestfold Hospital Trust, the Norwegian School of Sport Medicine, and Muritunet Rehabilitation have from 2013 to 2025 conducted > 2623 VO2max test and clinical parameters from 1,279 adults with severe obesity, both before, during and after lifestyle interventions. This comprehensive data set serves as the foundation for developing the ML model, which is presented through a user-friendly web application. A web application has been developed and will be tested with patients and healthcare personnel. The first scientific publication of the ML model is expected to be published in 2026. The results of the overall project are expected to be completed in 2028. CONCLUSIONS This project aims to develop a machine learning model, which serves as a cost-effective tool for VO2max estimation in individuals with obesity, improving accessibility to this important health marker. This is the first known attempt in Norway to estimate VO2max in an obese population using machine learning, based on a unique clinical database. The project holds significant societal value with potential national and international relevance for healthcare and patient outcomes. CLINICALTRIAL ClinicalTrials.gov (Identifier: NCT07011108)

• Bratland-Sanda, Solfrid; Støa, Eva Maria; Sanda, Åsmund; Reinboth, Michael Sæther & Gjevestad, Espen Svendsen (2023). Fit for beredskap? En litteraturstudie om helse og livsstil blant innsatsledere i politiet. In Dille, Therese; Kristiansen, Elsa & Boe, Ole (Ed.), Eventer i en beredskapskontekst. Universitetsforlaget. ISSN 9788215054636. p. 136–159. doi: 10.18261/9788215054599-23-09. Full text in Research Archive Show summary

  Politiets innsatsledere er en mannsdominert ansattgruppe utsatt for mange stressfaktorer som kan påvirke både helse og sikkerhet i yrkesrollen. Dette kapitlet fokuserer på hvordan innsatsledernes helse og livsstil er av betydning for beredskap og tjenesteutførelse i daglig beredskap og i beredskap på planlagte eventer. Vår kunnskapsoppsummering identifiserer behov for empiri og for at tjenestepersoner og forskere sammen fremskaffer kunnskap på feltet.

• Berk, Kirsten A.; Borgeraas, Heidi; Narverud, Ingunn; Mulder, Monique T.; Øyri, Linn Kristin Lie & Verhoeven, Adrie J M [Show all 14 contributors for this article] (2022). Differential effects of bariatric surgery and lifestyle interventions on plasma levels of Lp(a) and fatty acids. Lipids in Health and Disease. 21(145), p. 1–14. doi: 10.1186/s12944-022-01756-1. Full text in Research Archive Show summary

  Limited evidence suggests that surgical and non-surgical obesity treatment differentially influence plasma Lipoprotein (a) [Lp(a)] levels. Further, a novel association between plasma arachidonic acid and Lp(a) has recently been shown, suggesting that fatty acids are a possible target to influence Lp(a). Here, the effects of bariatric surgery and lifestyle interventions on plasma levels of Lp(a) were compared, and it was examined whether the effects were mediated by changes in plasma fatty acid (FA) levels. Methods The study includes two independent trials of patients with overweight or obesity. Trial 1: Two-armed intervention study including 82 patients who underwent a 7-week low energy diet (LED), followed by Roux-en-Y gastric bypass and 52-week follow-up (surgery-group), and 77 patients who underwent a 59-week energy restricted diet- and exercise-program (lifestyle-group). Trial 2: A clinical study including 134 patients who underwent a 20-week very-LED/LED (lifestyle-cohort). Results In the surgery-group, Lp(a) levels [median (interquartile range)] tended to increase in the pre-surgical LED-phase [17(7–68)-21(7–81)nmol/L, P = 0.05], but decreased by 48% after surgery [21(7–81)—11(7–56)nmol/L, P < 0.001]. In the lifestyle-group and lifestyle-cohort, Lp(a) increased by 36%[14(7–77)—19(7–94)nmol/L, P < 0.001] and 14%[50(14–160)—57(19–208)nmol/L, P < 0.001], respectively. Changes in Lp(a) were independent of weight loss. Plasma levels of total saturated FAs remained unchanged after surgery, but decreased after lifestyle interventions. Arachidonic acid and total n-3 FAs decreased after surgery, but increased after lifestyle interventions. Plasma FAs did not mediate the effects on Lp(a). Conclusion Bariatric surgery reduced, whereas lifestyle interventions increased plasma Lp(a), independent of weight loss. The interventions differentially influenced changes in plasma FAs, but these changes did not mediate changes in Lp(a).

• Berge, Jarle; Hjelmesæth, Jøran Sture; Kolotkin, Ronette Loganzo; Støren, Øyvind; Bratland-Sanda, Solfrid & Hertel, Jens Kristoffer [Show all 10 contributors for this article] (2022). Effect of aerobic exercise intensity on health-related quality of life in severe obesity: a randomized controlled trial. Health and Quality of Life Outcomes. 20. doi: 10.1186/s12955-022-01940-y. Full text in Research Archive Show summary

  Background Aerobic exercise is an important part of obesity treatment and may improve health-related quality of life (HRQOL). The objective of this study was to compare the effect of two different exercise programs on health-related quality of life in patients with severe obesity. Methods This was a single-center, open-label, randomized, parallel-group study comparing the effects of a 24-week moderate-intensity continuous training (MICT) program and a combined high-intensity interval training program with MICT (HIIT/MICT). The primary objective (specified secondary outcome) was to assess HRQOL by using the general health dimension of the Short Form Health Survey (SF-36). The secondary objectives were to assess other dimensional SF-36 scores, the impact of weight on the physical and psychosocial aspects of quality of life (IWQOL-Lite), and the burden of obesity-specific weight symptoms (WRSM). Results 73 patients were enrolled and reported patient reported outcome measures, with 71 patients (55% females) allocated to either MICT (n = 34) or HIIT/MICT (n = 37). In the intention-to-treat analysis, general health scores increased between baseline and 24-week follow-up in both the HIIT/MICT group and the MICT group, with a mean change of 13 (95% CI 6–21) points and 11 (95% CI 5–17) points, respectively, with no difference between the groups. The effect sizes of these changes were moderate. The vitality and social functioning scores of SF-36, and the physical function and self-esteem scores of IWQOL-Lite increased moderately in both groups, with no difference between groups. The tiredness, back pain, and physical stamina scores based on WRSM showed moderate to strong changes in both the groups. Conclusions Patients who had completed a combined HIIT/MICT program did not experience larger improvements in general health compared with those completing a clean 24-week MICT program. Exercise may confer general health benefits independent of intensity.

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• Grindaker, Eirik; Gjevestad, Espen Svendsen; Valnes, Thomas Andre & Lognseth, Stig (2026). Fra opptak til beredskap – hvordan utvikler vi robuste operative politifolk? doi: https:/share.transistor.fm/s/70c64248. Full text in Research Archive Show summary

  I denne episoden utforsker vi hvordan politiet utvikler og vedlikeholder fysisk kapasitet for å møte reelle operative krav. Vi diskuterer hva som skal til for å utvikle robust personell som tåler høy belastning over tid, hvordan trening, kultur, ledelse og organisatorisk tilrettelegging påvirker dette, samt balansen mellom individuelt ansvar og organisatorisk tilrettelegging når kapasitet skal utvikles og opprettholdes over tid. Vi belyser også hvordan samfunnstrekk som økt inaktivitet og stillesitting kan påvirke rekruttering, fysisk kapasitet og beredskap i operative virksomheter som politiet og Forsvaret.

• Grindaker, Eirik; Gjevestad, Espen Svendsen; Valnes, Thomas Andre & Lognseth, Stig (2026). Fysiske krav i politiet – hva krever jobben i praksis? doi: https:/share.transistor.fm/s/a8fe6a00. Full text in Research Archive Show summary

  I denne episoden utforsker vi hvilke fysiske krav som stilles til operativt politiarbeid, og hva tilstrekkelig fysisk yteevne innebærer i praksis. Vi diskuterer hvilke oppdrag og situasjoner som stiller de høyeste kravene, hvordan fysisk kapasitet påvirker prestasjon under stress, og hvordan fysiske, mentale og taktiske krav virker sammen i operativ tjeneste. Videre ser vi nærmere på forholdet mellom opptakskrav og de reelle kravene i yrket, hva som kan defineres som “godt nok”, og forskjellen mellom å bestå tester og å prestere robust over tid. Vi diskuterer også variasjoner mellom ulike operative funksjoner, kjønnsforskjeller i fysisk kapasitet, samt belastning, skader og bærekraft i tjenesten. I tillegg belyser vi hva politiet og Forsvaret kan lære av hverandre.

• Berge, Jarle; Nunavath, Vimala; Asbjørnsen, Rikke Aune; Borgeraas, Heidi; Hertel, Jens Kristoffer & Linge, Anita Dyb [Show all 15 contributors for this article] (2026). Machine Learning for Estimating Cardiorespiratory Fitness in Patients With Obesity: Protocol for a Retrospective and Prospective Multicenter Cohort Study. doi: 10.2196/85069. Full text in Research Archive Show summary

  Abstract Background Cardiorespiratory fitness (CRF) is a key predictor of cardiovascular and other health-related diseases in individuals with obesity. CRF is most accurately assessed through maximal exercise testing with advanced gas-analysis equipment (maximum volume of oxygen [VO 2max ]); however, this approach is time-consuming, costly, and requires specialized expertise. Therefore, submaximal tests and self-reported physical activity levels have been used to develop predictive algorithms to estimate CRF, yet they often performed poorly in individuals with low CRF levels, such as patients with obesity, because they are predominantly developed using data from healthy populations. Studies using machine learning (ML) models based on VO 2max data from patients with obesity appear to be lacking in the literature. ML models based on routinely collected clinical measures may offer a more practical and potentially accurate way to estimate CRF, reducing time, costs, and clinical burden. Objective The primary aim of this study is to use multicenter, longitudinal, real-world clinical data from a uniquely characterized population with obesity to develop and validate a clinically relevant ML model for estimating CRF and to compare its performance with the gold standard of VO 2max testing. Methods A retrospective data set combining assessments of VO 2max tests and clinical parameters from adult patients with severe obesity BMI (≥40.0 kg/m 2 or 35.0‐39.9 kg/m 2 with at least 1 obesity-related comorbidity) from Vestfold Hospital Trust, Muritunet Rehabilitation Institution, and Norwegian School of Sport Sciences will be the foundation for developing the ML model. The clinically relevant ML model for estimating CRF will be presented as a web application, allowing easy access and interaction. The model’s estimations will be compared against direct VO 2max measurements obtained from medical equipment across institutions as part of a prospective validation. Ethical approval has been obtained for the use of 2 databases in the initial model development; approval for the remaining data and prospective phase is pending. Results Vestfold Hospital Trust, the Norwegian School of Sport Medicine, and Muritunet Rehabilitation Institution conducted more than 2623 VO ₂max tests and collected clinical parameters from 1279 adults with severe obesity during 2013-2025, both before, during, and after lifestyle interventions. The first scientific publication of the clinically relevant ML model is expected to be published in 2026. The results of the overall project are expected to be completed in 2028. The project was awarded salary funding in two rounds from Vestfold Hospital (October and December 2023) and salary funding from the Research Council of Norway (October 2024). In addition, the project received allocated supervision hours from InnoMed Norway (April 2024). Conclusions This project aims to develop a clinically relevant ML model, which serves as a cost-effective tool for CRF estimation in individuals with obesity, improving accessibility to this important health marker. To our knowledge, this is the first initiative in Norway to estimate CRF in individuals with obesity using ML, based on a unique clinical database. The project carries substantial societal value and holds national and international relevance for health care practice and patient outcomes.

• Bratland-Sanda, Solfrid; Støa, Eva Maria; Sanda, Åsmund; Reinboth, Michael Sæther; Ringheim, Henriette Kaasa & Berge, Jarle [Show all 7 contributors for this article] (2023). Fit for beredskap! Helse og livsstil som sikkerhetsfaktor blant funksjonsrettede ledere i politiet. Full text in Research Archive
• Jenssen, Ole Ragnar N. & Gjevestad, Espen Svendsen (2023). Fysisk form, trening og ernæring: forberedelse til oppdraget. In Bergsjø, Per; Sandvik, Asle Makoto & Meland, Sigurd (Ed.), Politipatruljen: en lærebok i patruljetjeneste. Fagbokforlaget. ISSN 9788245039924. p. 41–58. Full text in Research Archive
• Henneseid, Linn; Jenssen, Ole Ragnar N. & Gjevestad, Espen Svendsen (2023). Førstehjelp. In Bergsjø, Per; Sandvik, Asle Makoto & Meland, Sigurd (Ed.), Politipatruljen: en lærebok i patruljetjeneste. Fagbokforlaget. ISSN 9788245039924. p. 219–232. Full text in Research Archive

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