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  1. Article ; Online: De-identifying Spanish medical texts - named entity recognition applied to radiology reports.

    Pérez-Díez, Irene / Pérez-Moraga, Raúl / López-Cerdán, Adolfo / Salinas-Serrano, Jose-Maria / la Iglesia-Vayá, María de

    Journal of biomedical semantics

    2021  Volume 12, Issue 1, Page(s) 6

    Abstract: Background: Medical texts such as radiology reports or electronic health records are a powerful source of data for researchers. Anonymization methods must be developed to de-identify documents containing personal information from both patients and ... ...

    Abstract Background: Medical texts such as radiology reports or electronic health records are a powerful source of data for researchers. Anonymization methods must be developed to de-identify documents containing personal information from both patients and medical staff. Although currently there are several anonymization strategies for the English language, they are also language-dependent. Here, we introduce a named entity recognition strategy for Spanish medical texts, translatable to other languages.
    Results: We tested 4 neural networks on our radiology reports dataset, achieving a recall of 97.18% of the identifying entities. Alongside, we developed a randomization algorithm to substitute the detected entities with new ones from the same category, making it virtually impossible to differentiate real data from synthetic data. The three best architectures were tested with the MEDDOCAN challenge dataset of electronic health records as an external test, achieving a recall of 69.18%.
    Conclusions: The strategy proposed, combining named entity recognition tasks with randomization of entities, is suitable for Spanish radiology reports. It does not require a big training corpus, thus it could be easily extended to other languages and medical texts, such as electronic health records.
    MeSH term(s) Electronic Health Records ; Humans ; Language ; Natural Language Processing ; Neural Networks, Computer ; Radiology
    Language English
    Publishing date 2021-03-29
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2548651-2
    ISSN 2041-1480 ; 2041-1480
    ISSN (online) 2041-1480
    ISSN 2041-1480
    DOI 10.1186/s13326-021-00236-2
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Hospitalization forecast to inform COVID-19 pandemic planning and resource allocation using mathematical models

    Wikman-Jorgensen, Philip Erick / Ruiz, Angel / Giner-Galvañ, Vicente / Llenas-García, Jara / Seguí-Ripoll, José Miguel / Salinas Serrano, Jose María / Borrajo, Emilio / Ibarra Sánchez, José María / García-Sabater, José Pedro / Marín-García, Juan A

    medRxiv

    Abstract: Background The COVID-19 pandemic has put tremendous pressure on hospital resources around the world. Forecasting demand for healthcare services is important generally, but crucial in epidemic contexts, both to facilitate resource planning and to inform ... ...

    Abstract Background The COVID-19 pandemic has put tremendous pressure on hospital resources around the world. Forecasting demand for healthcare services is important generally, but crucial in epidemic contexts, both to facilitate resource planning and to inform situational awareness. There is abundant research on methods for predicting the spread of COVID-19 and even the arrival of COVID-19 patients to hospitals emergency departments. This study builds on that work to propose a hybrid tool, combining a stochastic Markov model and a discrete event simulation model to dynamically predict hospital admissions and total daily occupancy of hospital and ICU beds. Methods The model was developed and validated at San Juan de Alicante University Hospital from 10 July 2020 to 10 January 2022 and externally validated at Hospital Vega Baja. An admissions generator was developed using a stochastic Markov model that feeds a discrete event simulation model in R. Positive microbiological SARS-COV-2 results from the health department’s catchment population were stratified by patient age to calculate the probabilities of hospital admission. Admitted patients follow distinct pathways through the hospital, which are simulated by the discrete event simulation model, allowing administrators to estimate the bed occupancy for the next week. The median absolute difference (MAD) between predicted and actual demand was used as a model performance measure. Results With respect to the San Juan hospital data, the admissions generator yielded a MAD of 6 admissions/week (interquartile range [IQR] 2-11). The MAD between the tool’s predictions and actual bed occupancy was 20 beds/day (IQR  5-43), or 5% of the hospital beds. The MAD between the intensive care unit (ICU)’s predicted and actual occupancy was 4 beds/day (IQR 2-7), or 25% of the beds. When the model was further evaluated with data from Hospital Vega Baja, the admissions generator showed a MAD of 2.42 admissions/week (IQR 1.02-7.41). The MAD between the tools’ predictions and the actual bed occupancy was 18 beds/day (IQR 19.57-38.89), or 5.1% of the hospital beds. For ICU beds, the MAD was 3 beds/day (IQR 1-5), or 21.4% of the ICU beds. Conclusion Predictions of hospital admissions, ward beds, and ICU occupancy for COVID-19 patients were very useful to hospital managers, allowing early planning of hospital resource allocation.
    Keywords covid19
    Language English
    Publishing date 2022-11-05
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2022.11.03.22281898
    Database COVID19

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  3. Article ; Online: Differences in the clinical management of women and men after detection of a solitary pulmonary nodule in clinical practice.

    Chilet-Rosell, Elisa / Parker, Lucy A / Hernández-Aguado, Ildefonso / Pastor-Valero, María / Vilar, José / González-Álvarez, Isabel / Salinas-Serrano, José María / Lorente-Fernández, Fermina / Domingo, M Luisa / Lumbreras, Blanca

    European radiology

    2020  Volume 30, Issue 8, Page(s) 4390–4397

    Abstract: Objectives: To explore differences in the clinical management of men and women in the 5 years after detecting a solitary pulmonary nodule (SPN) by chest radiograph or CT in routine clinical practice.: Methods: We followed up 545 men and 347 women ... ...

    Abstract Objectives: To explore differences in the clinical management of men and women in the 5 years after detecting a solitary pulmonary nodule (SPN) by chest radiograph or CT in routine clinical practice.
    Methods: We followed up 545 men and 347 women with an SPN detected by chest radiograph or CT in a retrospective cohort of 25,422 individuals undergoing routine thoracic imaging in 2010-2011. We compared the frequency of each management strategy (no further test, immediate intervention or follow up) according to sex by means of chi-squared. We estimated the relative risk of women versus men of having been followed up instead of an immediate intervention using multivariate logistic regression. We compared by sex the time between detection of the nodule and lung cancer diagnosis, the time between diagnosis and death by means of Mann-Whitney U test and the cumulative effective dose of radiation in each management strategy by means of t test.
    Results: Women were more likely than men to have follow-up rather than immediate intervention (aRR = 1.8, CI 1.3-2.7, p = 0.002), particularly in those who underwent CT (aRR = 4.2, CI 1.9-9.3, p < 0.001). The median time between SPN detection and lung cancer diagnosis was higher in women (4.2 months, interquartile range (IQR) 5.1) than in men (1.5 months, IQR 16.2). The mean cumulative effective dose was 21.3 mSv, 19.4 mSv in men and 23.9mv in women (p = 0.023).
    Conclusions: Our results could reflect decisions based on a greater suspicion of lung cancer in men. The incidental detection of SPNs is increasing, and it is necessary to establish clear strategies aimed to reduce variability in their management according to patient's sex.
    Key points: • After incidental finding of SPN, women were less likely to receive an immediate intervention. • Accumulative radiation was higher in women than in men. • Our results could reflect decisions based on a greater suspicion of lung cancer in men.
    MeSH term(s) Aged ; Clinical Decision-Making ; Cohort Studies ; Comorbidity ; Delayed Diagnosis/statistics & numerical data ; Female ; Healthcare Disparities ; Humans ; Incidental Findings ; Logistic Models ; Lung ; Lung Neoplasms/diagnosis ; Male ; Men ; Middle Aged ; Mortality ; Multivariate Analysis ; Pulmonary Disease, Chronic Obstructive/epidemiology ; Radiation Dosage ; Radiography, Thoracic ; Retrospective Studies ; Risk ; Sex Factors ; Smoking/epidemiology ; Solitary Pulmonary Nodule/diagnosis ; Spain ; Tomography, X-Ray Computed/methods ; Women
    Language English
    Publishing date 2020-03-19
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 1085366-2
    ISSN 1432-1084 ; 0938-7994 ; 1613-3749
    ISSN (online) 1432-1084
    ISSN 0938-7994 ; 1613-3749
    DOI 10.1007/s00330-020-06791-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: The determinants of lung cancer after detecting a solitary pulmonary nodule are different in men and women, for both chest radiograph and CT.

    Chilet-Rosell, Elisa / Parker, Lucy A / Hernández-Aguado, Ildefonso / Pastor-Valero, María / Vilar, José / González-Álvarez, Isabel / Salinas-Serrano, José María / Lorente-Fernández, Fermina / Domingo, M Luisa / Lumbreras, Blanca

    PloS one

    2019  Volume 14, Issue 9, Page(s) e0221134

    Abstract: Objectives: To determine the factors associated with lung cancer diagnosis and mortality after detecting a solitary pulmonary nodule (SPN) in routine clinical practice, in men and in women for both chest radiograph and CT.: Materials and methods: A 5- ...

    Abstract Objectives: To determine the factors associated with lung cancer diagnosis and mortality after detecting a solitary pulmonary nodule (SPN) in routine clinical practice, in men and in women for both chest radiograph and CT.
    Materials and methods: A 5-year follow-up of a retrospective cohort of of 25,422 (12,594 men, 12,827 women) patients aged ≥35 years referred for chest radiograph or CT in two hospitals in Spain (2010-2011). SPN were detected in 893 (546 men, 347 women) patients. We estimated the cumulative incidence of lung cancer at 5-years, the association of patient and nodule characteristics with SPN malignancy using Poisson logistic regression, stratifying by sex and type of imaging test. We calculated lung cancer specific mortality rate by sex and SPN detection and hazard rates by cox regression.
    Results: 133 (14.9%) out of 893 patients with an SPN and 505 (2.06%) of the 24,529 patients without SPN were diagnosed with lung cancer. Median diameter of SPN in women who developed cancer was larger than in men. Men who had a chest radiograph were more likely to develop a lung cancer if the nodule was in the upper-lobes, which was not the case for women. In patients with an SPN, smoking increased the risk of lung cancer among men (chest radiograph: RR = 11.3, 95%CI 1.5-83.3; CT: RR = 7.5, 95%CI 2.2, 26.0) but smoking was not significantly associated with lung cancer diagnosis or mortality among women with an SPN. The relative risk of lung cancer diagnosis in women with SPN versus those without was much higher compared to men (13.7; 95%CI 9.2, 20.4 versus 6.2; 95%CI 4.9,7.9).
    Conclusion: The factors associated with SPN malignancy and 5-year lung cancer mortality were different among men and women, especially regarding smoking history and SPN characteristics, where we observed a relatively high rate of lung cancer diagnosis among female non-smokers.
    MeSH term(s) Adult ; Aged ; Aged, 80 and over ; Clinical Decision-Making ; Diagnosis, Differential ; Female ; Humans ; Lung Neoplasms/diagnosis ; Lung Neoplasms/mortality ; Lung Neoplasms/therapy ; Male ; Middle Aged ; Radiography, Thoracic/methods ; Retrospective Studies ; Sex Factors ; Solitary Pulmonary Nodule/diagnosis ; Tomography, X-Ray Computed/methods
    Language English
    Publishing date 2019-09-11
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1932-6203
    ISSN (online) 1932-6203
    DOI 10.1371/journal.pone.0221134
    Database MEDical Literature Analysis and Retrieval System OnLINE

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