Thrombocytopenia and platelet transfusions in ICU patients: an international inception cohort study (PLOT-ICU)

Purpose Thrombocytopenia (platelet count < 150 × 109/L) is common in intensive care unit (ICU) patients and is likely associated with worse outcomes. In this study we present international contemporary data on thrombocytopenia in ICU patients. Methods We conducted a prospective cohort study in adult ICU patients in 52 ICUs across 10 countries. We assessed frequencies of thrombocytopenia, use of platelet transfusions and clinical outcomes including mortality. We evaluated pre-selected potential risk factors for the development of thrombocytopenia during ICU stay and associations between thrombocytopenia at ICU admission and 90-day mortality using pre-specified logistic regression analyses. Results We analysed 1166 ICU patients; the median age was 63 years and 39.5% were female. Overall, 43.2% (95% confidence interval (CI) 40.4–46.1) had thrombocytopenia; 23.4% (20–26) had thrombocytopenia at ICU admission, and 19.8% (17.6–22.2) developed thrombocytopenia during their ICU stay. Non-AIDS-, non-cancer-related immune deficiency, liver failure, male sex, septic shock, and bleeding at ICU admission were associated with the development of thrombocytopenia during ICU stay. Among patients with thrombocytopenia, 22.6% received platelet transfusion(s), and 64.3% of in-ICU transfusions were prophylactic. Patients with thrombocytopenia had higher occurrences of bleeding and death, fewer days alive without the use of life-support, and fewer days alive and out of hospital. Thrombocytopenia at ICU admission was associated with 90-day mortality (adjusted odds ratio 1.7; 95% CI 1.19–2.42). Conclusion Thrombocytopenia occurred in 43% of critically ill patients and was associated with worse outcomes including increased mortality. Platelet transfusions were given to 23% of patients with thrombocytopenia and most were prophylactic.publishedVersio

Association of respiratory symptoms and lung function with occupation in the multinational Burden of Obstructive Lung Disease (BOLD) study

Background Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. Methods We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1)/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Results Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV1/FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. Conclusion At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.publishedVersio

Cohort Profile: Burden of Obstructive Lung Disease (BOLD) study

The Burden of Obstructive Lung Disease (BOLD) study was established to assess the prevalence of chronic airflow obstruction, a key characteristic of chronic obstructive pulmonary disease, and its risk factors in adults (≥40 years) from general populations across the world. The baseline study was conducted between 2003 and 2016, in 41 sites across Africa, Asia, Europe, North America, the Caribbean and Oceania, and collected high-quality pre- and post-bronchodilator spirometry from 28 828 participants. The follow-up study was conducted between 2019 and 2021, in 18 sites across Africa, Asia, Europe and the Caribbean. At baseline, there were in these sites 12 502 participants with high-quality spirometry. A total of 6452 were followed up, with 5936 completing the study core questionnaire. Of these, 4044 also provided high-quality pre- and post-bronchodilator spirometry. On both occasions, the core questionnaire covered information on respiratory symptoms, doctor diagnoses, health care use, medication use and ealth status, as well as potential risk factors. Information on occupation, environmental exposures and diet was also collected

Early life body size and puberty markers as predictors of breast cancer risk later in life: A neural network analysis.

BackgroundThe early life factors of birthweight, child weight, height, body mass index (BMI) and pubertal timing are associated with risks of breast cancer. However, the predictive value of these factors in relation to breast cancer is largely unknown. Therefore, using a machine learning approach, we examined whether birthweight, childhood weights, heights, BMIs, and pubertal timing individually and in combination were predictive of breast cancer.MethodsWe used information on birthweight, childhood height and weight, and pubertal timing assessed by the onset of the growth spurt (OGS) from 164,216 girls born 1930-1996 from the Copenhagen School Health Records Register. Of these, 10,002 women were diagnosed with breast cancer during 1977-2019 according to a nationwide breast cancer database. We developed a feed-forward neural network, which was trained and tested on early life body size measures individually and in various combinations. Evaluation metrics were examined to identify the best performing model.ResultsThe highest area under the receiver operating curve (AUC) was achieved in a model that included birthweight, childhood heights, weights and age at OGS (AUC = 0.600). A model based on childhood heights and weights had a comparable AUC value (AUC = 0.598), whereas a model including only childhood heights had the lowest AUC value (AUC = 0.572). The sensitivity of the models ranged from 0.698 to 0.760 while the precision ranged from 0.071 to 0.076.ConclusionWe found that the best performing network was based on birthweight, childhood weights, heights and age at OGS as the input features. Nonetheless, this performance was only slightly better than the model including childhood heights and weights. Further, although the performance of our networks was relatively low, it was similar to those from previous studies including well-established risk factors. As such, our results suggest that childhood body size may add additional value to breast cancer prediction models

Performance metrics for the neural networks predicting breast cancer^b'*'^,^b'**'.

Performance metrics for the neural networks predicting breast cancerb'*',b'**'.</p

ROC curves for the neural networks with early life body measures predicting breast cancer.

Abbreviations: AUC, area under the curve; BMI, body mass index; OGS, onset of the growth spurt; ROC, Reciever operating characteristics.</p