| 1. |
- Dave, Nishi, et al.
(author)
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Nosocomial SARS-CoV-2 infections and mortality during unique COVID-19 epidemic waves
- 2023
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In: JAMA Network Open. - : American Medical Association (AMA). - 2574-3805. ; 6:11
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Journal article (peer-reviewed)abstract
- Importance: Quantifying the burden of nosocomial SARS-CoV-2 infections and associated mortality is necessary to assess the need for infection prevention and control measures.Objective: To investigate the occurrence of nosocomial SARS-CoV-2 infections and associated 30-day mortality among patients admitted to hospitals in Region Stockholm, Sweden.Design, Setting, and Participants: A retrospective, matched cohort study divided the period from March 1, 2020, until September 15, 2022, into a prevaccination period, early vaccination and pre-Omicron (period 1), and late vaccination and Omicron (period 2). From among 303 898 patients 18 years or older living in Region Stockholm, 538 951 hospital admissions across all hospitals were included. Hospitalized admissions with nosocomial SARS-CoV-2 infections were matched to as many as 5 hospitalized admissions without nosocomial SARS-CoV-2 by age, sex, length of stay, admission time, and hospital unit.Exposure: Nosocomial SARS-CoV-2 infection defined as the first positive polymerase chain reaction test result at least 8 days after hospital admission or within 2 days after discharge.Main Outcomes and Measures: Primary outcome of 30-day mortality was analyzed using time-to-event analyses with a Cox proportional hazards regression model adjusted for age, sex, educational level, and comorbidities.Results: Among 2193 patients with SARS-CoV-2 infections or reinfections (1107 women [50.5%]; median age, 80 [IQR, 71-87] years), 2203 nosocomial SARS-CoV-2 infections were identified. The incidence rate of nosocomial SARS-CoV-2 infections was 1.57 (95% CI, 1.51-1.64) per 1000 patient-days. In the matched cohort, 1487 hospital admissions with nosocomial SARS-CoV-2 infections were matched to 5044 hospital admissions without nosocomial SARS-CoV-2 infections. Thirty-day mortality was higher in the prevaccination period (adjusted hazard ratio [AHR], 2.97 [95% CI, 2.50-3.53]) compared with period 1 (AHR, 2.08 [95% CI, 1.50-2.88]) or period 2 (AHR, 1.22 [95% CI, 0.92-1.60]). Among patients with nosocomial SARS-CoV-2 infections, 30-day AHR comparing those with 2 or more doses of SARS-CoV-2 vaccination and those with less than 2 doses was 0.64 (95% CI, 0.46-0.88).Conclusions and Relevance: In this matched cohort study, nosocomial SARS-CoV-2 infections were associated with higher 30-day mortality during the early phases of the pandemic and lower mortality during the Omicron variant wave and after the introduction of vaccinations. Mitigation of excess mortality risk from nosocomial transmission should be a strong focus when population immunity is low through implementation of adequate infection prevention and control measures.
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| 2. |
- Henriksson, Aron, 1985-, et al.
(author)
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Multimodal fine-tuning of clinical language models for predicting COVID-19 outcomes
- 2023
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In: Artificial Intelligence in Medicine. - 0933-3657 .- 1873-2860. ; 146
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Journal article (peer-reviewed)abstract
- Clinical prediction models tend only to incorporate structured healthcare data, ignoring information recorded in other data modalities, including free-text clinical notes. Here, we demonstrate how multimodal models that effectively leverage both structured and unstructured data can be developed for predicting COVID-19 outcomes. The models are trained end-to-end using a technique we refer to as multimodal fine-tuning, whereby a pre -trained language model is updated based on both structured and unstructured data. The multimodal models are trained and evaluated using a multicenter cohort of COVID-19 patients encompassing all encounters at the emergency department of six hospitals. Experimental results show that multimodal models, leveraging the notion of multimodal fine-tuning and trained to predict (i) 30-day mortality, (ii) safe discharge and (iii) readmission, outperform unimodal models trained using only structured or unstructured healthcare data on all three outcomes. Sensitivity analyses are performed to better understand how well the multimodal models perform on different patient groups, while an ablation study is conducted to investigate the impact of different types of clinical notes on model performance. We argue that multimodal models that make effective use of routinely collected healthcare data to predict COVID-19 outcomes may facilitate patient management and contribute to the effective use of limited healthcare resources.
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| 3. |
- Pawar, Yash, et al.
(author)
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Leveraging Clinical BERT in Multimodal Mortality Prediction Models for COVID-19
- 2022
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In: In Proceedings of IEEE International Symposium on Computer-Based Medical Systems (CMBS 2022). - : IEEE. - 9781665467704 ; , s. 199-204
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Conference paper (peer-reviewed)abstract
- Clinical prediction models are often based solely on the use of structured data in electronic health records, e.g. vital parameters and laboratory results, effectively ignoring potentially valuable information recorded in other modalities, such as free-text clinical notes. Here, we report on the development of a multimodal model that combines structured and unstructured data. In particular, we study how best to make use of a clinical language model in a multimodal setup for predicting 30-day all-cause mortality upon hospital admission in patients with COVID-19. We evaluate three strategies for incorporating a domain-specific clinical BERT model in multimodal prediction systems: (i) without fine-tuning, (ii) with unimodal fine-tuning, and (iii) with multimodal fine-tuning. The best-performing model leverages multimodal fine-tuning, in which the clinical BERT model is updated based also on the structured data. This multimodal mortality prediction model is shown to outperform unimodal models that are based on using either only structured data or only unstructured data. The experimental results indicate that clinical prediction models can be improved by including data in other modalities and that multimodal fine-tuning of a clinical language model is an effective strategy for incorporating information from clinical notes in multimodal prediction systems.
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| 4. |
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| 5. |
- Cronholm, Pontus, et al.
(author)
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Intracellular Uptake and Toxicity of Ag and CuO Nanoparticles : A Comparison Between Nanoparticles and their Corresponding Metal Ions
- 2013
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In: Small. - : Wiley. - 1613-6810 .- 1613-6829. ; 9:7, s. 970-982
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Journal article (peer-reviewed)abstract
- An increased understanding of nanoparticle toxicity and its impact on human health is essential to enable a safe use of nanoparticles in our society. The aim of this study is to investigate the role of a Trojan horse type mechanism for the toxicity of Ag-nano and CuO-nano particles and their corresponding metal ionic species (using CuCl2 and AgNO3), i.e., the importance of the solid particle to mediate cellular uptake and subsequent release of toxic species inside the cell. The human lung cell lines A549 and BEAS-2B are used and cell death/membrane integrity and DNA damage are investigated by means of trypan blue staining and the comet assay, respectively. Chemical analysis of the cellular dose of copper and silver is performed using atomic absorption spectroscopy. Furthermore, transmission electron microscopy, laser scanning confocal microscopy, and confocal Raman microscopy are employed to study cellular uptake and particle-cell interactions. The results confirm a high uptake of CuO-nano and Ag-nano compared to no, or low, uptake of the soluble salts. CuO-nano induces both cell death and DNA damage whereas CuCl2 induces no toxicity. The opposite is observed for silver, where Ag-nano does not cause any toxicity, whereas AgNO3 induces a high level of cell death. In conclusion: CuO-nano toxicity is predominantly mediated by intracellular uptake and subsequent release of copper ions, whereas no toxicity is observed for Ag-nano due to low release of silver ions within short time periods.
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| 6. |
- Gyllencreutz, Lina, et al.
(author)
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Preparedness for chemical, radiologic and nuclear incidents among a sample of emergency physicians' and general practitioners' : a qualitative study
- 2023
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In: International Journal of Emergency Services. - : Emerald Group Publishing Limited. - 2047-0894 .- 2047-0908. ; 12:2, s. 161-170
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Journal article (peer-reviewed)abstract
- Purpose: This study describes preparedness of emergency physicians and general practitioners following chemical, radiological and nuclear incidents.Design/methodology/approach: Five emergency physicians and six general practitioners were interviewed individually, and data was analysed using qualitative content analysis.Findings: The study results showed that physicians' preparedness for chemical, radiological and nuclear incidents is linked to one main category: to be an expert and to seek expertise and two categories: preparations before receiving CRN patients, and physical examination and treatment of CRN patients with subcategories.Research limitations/implications: The results have implications for further research on the complexity of generalist vs specialist competence and knowledge when responding to chemical, radiological and nuclear incidents.Originality/value: This study provides insights regarding chemical, radiological and nuclear preparedness among physicians at emergency departments and primary healthcare centres.
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| 7. |
- Hedberg, Pontus
(author)
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Clinical presentation and outcomes of COVID-19 compared with other respiratory virus infections and hospital populations
- 2022
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Doctoral thesis (other academic/artistic)abstract
- As of September 2022, more than 600 million cases of coronavirus disease 2019 (COVID-19) and 6.5 million deaths have been officially reported to the World Health Organization (WHO). The unfolding pandemic has exerted enormous strains on healthcare systems worldwide yet to be fully understood. The overarching aim of this thesis was to characterize clinical presentation and outcomes in adult patients hospitalized with COVID-19 and compare these with patients hospitalized with other respiratory virus infections as well as other hospital populations. Six retrospective cohort studies were conducted, all set in Stockholm Region in Sweden. In study I, baseline characteristics, clinical presentation, and outcomes in patients hospitalized with COVID-19 were compared with patients hospitalized with influenza, respiratory syncytial virus (RSV) infection, and other respiratory virus infections. Despite being younger and having an overall better health status, adult patients hospitalized with COVID-19 had an increased risk of severe outcomes, in particular mortality, compared with the other infections. These risks were greater among the elderly and during the first months of the pandemic. In study II, the prevalence of bacterial co-infections in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive community-acquired pneumonia (CAP) upon hospital admission was compared with patients hospitalized with influenza virus positive CAP and RSV positive CAP. The occurrence of detected bacterial co-infection upon hospital admission was substantially lower in the SARS-CoV-2 cohort compared with both the influenza and the RSV cohort. In study III, we compared the occurrence of ventilator-associated lower respiratory tract infection (VA-LRTI) in patients mechanically ventilated with versus without COVID-19. The incidence rate was increased in the COVID-19 cohort when compared with influenza and other infectious diseases but decreased when compared with most of the non-infectious diseases. Further, the incidence rate was in the COVID-19 cohort increased during the second wave when compared with the first wave of the pandemic. In study IV, the incidence rate and 30-day mortality rate of hospital-onset bacteraemia (HOB) were compared among patients hospitalized with COVID-19 and patients hospitalized without COVID-19 both before and during the pandemic. The incidence as well as mortality of HOB was increased for both COVID-19 and non-COVID-19 patients during the pandemic when compared with patients hospitalized before the pandemic. In study V, we investigated one-year mortality among patients admitted to the intensive care unit (ICU) with versus without COVID-19. Furthermore, we compared the number of days alive and free from hospitalization during one year in those patients who were discharged alive from the ICU-associated hospitalization. An increased risk of acute mortality was observed in patients treated in the ICU with versus without COVID-19, primarily among the elderly. On the contrary, survivors of COVID-19 critical illness had compared with other critical illness survivors more days alive and free from further hospitalizations during the next year. In study VI, we investigated the occurrence and characteristics of post COVID-19 condition (PCC) diagnosis across different severities of the acute COVID-19 episode. The occurrence of PCC diagnosis was substantially higher in individuals hospitalized versus not hospitalized during the acute COVID-19 episode. Associations between health status factors and PCC diagnosis differed by severity of the acute COVID-19 episode, with more and stronger associations among those not hospitalized during the acute infection. Increases in outpatient healthcare utilization up to one year after the acute infection indicated an incomplete recovery in individuals diagnosed with PCC. Taken together, these studies contribute to our understanding of the clinical epidemiology of COVID-19, highlighting severe acute clinical outcomes in hospitalized patients as well as a different occurrence and trajectory of PCC across different severities of the acute infection. Given the life-saving rollout of COVID-19 vaccines and the evolving nature of the virus, the generalizability of these findings over time needs to be carefully considered. Further investigations of the acute and in particular long-term effects of COVID-19 are warranted. An improved understanding of how the pandemic has caused disruptions and backlogs in healthcare delivery is also necessary.
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| 8. |
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| 9. |
- Piscator, Eva, et al.
(author)
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Survival after in-hospital cardiac arrest is highly associated with the Age-combined Charlson Co-morbidity Index in a cohort study from a two-site Swedish University hospital
- 2015
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In: Resuscitation. - : Elsevier Ireland Ltd. - 0300-9572 .- 1873-1570. ; 99, s. 79-83
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Journal article (peer-reviewed)abstract
- Abstract Background In-hospital cardiac arrest (IHCA) has a poor prognosis and clinicians often write “Do-Not-Attempt-Resuscitation” (DNAR) orders based on co-morbidities. Aim To assess the impact of the Age-combined Charlson Co-morbidity Index (ACCI) on 30-days survival after IHCA. Material and methods All patients suffering IHCA at Karolinska University Hospital between 1st January and 31st December 2014 were included. Data regarding patient characteristics, co-morbidities and survival were drawn from the electronic patient records. Co-morbidities were assessed prior to the IHCA as ICD-10 codes according to the ACCI. Differences in survival were assessed with adjusted logistic regression models and presented as Odds Ratios with 95% Confidence Intervals (OR, 95% CI) between patients with an ACCI of 0–4 points versus those with 5–7 points, as well as those with ≥8 points. Adjustments included hospital site, heart rhythm, ECG surveillance, witnessed status and place of IHCA. Results In all, 174 patients suffered IHCA, of whom 41 (24%) survived at least 30 days. Patients with an ACCI of 5–7 points had a minor chance and those with an ACCI of ≥8 points had a minimal chance of surviving IHCA compared to those with an ACCI of 0–4 points (adjusted OR 0.10, 95% CI 0.04–0.26 and OR 0.04, 95% CI 0.03–0.42, respectively). Conclusion Patients with a moderate or severe burden of ACCI have a minor chance of surviving an IHCA. This information could be used as part of the decision tools during ongoing CPR, and could be an aid for clinicians in planning care and discussing DNAR orders.
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