/pdf/comparison-of-haematological-indices-and-transfusion-1nxhd3ka.pdf

Comparison of haematological indices and transfusion management in severe and massive postpartum haemorrhage: analysis of a two-year national prospective observational study.

To the best of our knowledge, no previous study has quantitatively estimated the dynamics and cumulative susceptibility to influenza infections after the widespread lifting of COVID-19 public health measures. We constructed an imitated stochastic susceptible-infected-removed model using particle-filtered Markov Chain Monte Carlo sampling to estimate the time-dependent reproduction number of influenza based on influenza surveillance data in southern China, northern China, and the United States during the 2022-2023 season. We compared these estimates to those from 2011 to 2019 seasons without strong social distancing interventions to determine cumulative susceptibility during COVID-19 restrictions. Compared to the 2011-2019 seasons without a strong intervention with social measures, the 2022-2023 influenza season length was 45.0%, 47.1%, and 57.1% shorter in southern China, northern China, and the United States, respectively, corresponding to an 140.1%, 74.8%, and 50.9% increase in scale of influenza infections, and a 60.3%, 72.9%, and 45.1% increase in population susceptibility to influenza. Large and high-intensity influenza epidemics occurred in China and the United States in 2022-2023. Population susceptibility increased in 2019-2022, especially in China. We recommend promoting influenza vaccination, taking personal prevention actions on at-risk populations, and monitoring changes in the dynamic levels of influenza and other respiratory infections to prevent potential outbreaks in the coming influenza season.

Increased population susceptibility to seasonal influenza during the COVID-19 pandemic in China and the United States.

To clarify whether "low-risk total PP" patients bleed more than partial/marginal PP patients.The retrospective cohort study was performed involving patients with PP between April 2006 and December 2018. The placental position was determined by ultrasound. From medical charts, the backgrounds as well as obstetric and neonatal outcomes of PP patients were retrieved.This study included 349 patients with PP, which was classified into three types according to the distance between the placenta and internal ostium: total (n = 174), partial (n = 52), and marginal (n = 123) PP. In total PP patients, three factors (prior CS, anterior placenta, and placental lacunae on ultrasound) significantly increased blood loss at CS, the need for hysterectomy, homologous transfusion (≥10 U), and ICU admission. No significant difference was observed in bleeding-related poor outcomes (rate of blood loss ≥2000 mL, amount of homologous transfusion, need for hysterectomy, and ICU admission) between total PP patients without all three factors: "low-risk total PP patients" and partial/marginal PP patients (19.8 vs. 17.1%; p = 0.604, 3.7 vs. 1.1%; p = 0.330, 1.2 vs. 1.1%; p = 1.000, and 1.2 vs. 1.1%; p = 1.000, respectively).Prior CS, anterior placenta, and placental lacunae on ultrasound were risk factors for a bleeding-related poor outcome in total PP patients. Total PP patients without these three factors showed the same bleeding-related poor outcome as partial/marginal PP patients. 

Bleeding-related outcomes of low-risk total placenta previa are equivalent to those of partial/marginal placenta previa.

Background To develop and compare different AutoML frameworks and machine learning models to predict premature birth. Methods The study used a large electronic medical record database to include 715,962 participants who had the principal diagnosis code of childbirth. Three Automatic Machine Learning (AutoML) were used to construct machine learning models including tree-based models, ensembled models, and deep neural networks on the training sample (N = 536,971). The area under the curve (AUC) and training times were used to assess the performance of the prediction models, and feature importance was computed via permutation-shuffling. Results The H2O AutoML framework had the highest median AUC of 0.846, followed by AutoGluon (median AUC: 0.840) and Auto-sklearn (median AUC: 0.820), and the median training time was the lowest for H2O AutoML (0.14 min), followed by AutoGluon (0.16 min) and Auto-sklearn (4.33 min). Among different types of machine learning models, the Gradient Boosting Machines (GBM) or Extreme Gradient Boosting (XGBoost), stacked ensemble, and random forrest models had better predictive performance, with median AUC scores being 0.846, 0.846, and 0.842, respectively. Important features related to preterm birth included premature rupture of membrane (PROM), incompetent cervix, occupation, and preeclampsia. Conclusions Our study highlights the potential of machine learning models in predicting the risk of preterm birth using readily available electronic medical record data, which have significant implications for improving prenatal care and outcomes.

Predicting preterm birth using auto-ML frameworks: a large observational study using electronic inpatient discharge data

A hemorragia pós-parto constitui a complicação obstétrica com maior morbimortalidade materna em todo o mundo. É um problema de saúde importante e pode ser causada por atonia uterina, retenção de tecido placentário, trauma ou distúrbios de coagulação. Este estudo objetivou descrever os cuidados de enfermagem na hemorragia pós-parto através de uma pesquisa bibliográfica do tipo revisão integrativa da literatura com abordagem qualitativa dos estudos, consultou-se as bases de dados da National Library of Medicine e Biblioteca Virtual em Saúde utilizando-se de estudos disponíveis em sua totalidade, publicados nos anos de 2018 até 2021 nos idiomas Português, Espanhol e inglês. Os onze estudos apresentam as principais causas, fatores de risco da hemorragia pós-parto e discorrem acerca das atribuições da enfermagem obstétrica e das práticas realizadas nas complicações à puérpera, além de medidas de prevenção da hemorragia pós-parto. Conclui-se que o enfermeiro obstetra é fundamental nos cuidados de enfermagem dentro da obstetrícia, cabe a ele, prestar assistência adequada, afim de intervir para a prevenção e recuperação dessa complicação obstétrica. 

/pdf/cuidados-de-enfermagem-na-hemorragia-pos-parto-nursing-care-3gdcr8ic.pdf

Cuidados de enfermagem na hemorragia pós-parto / Nursing care in postpartum hemorrhage

Delivery methods are associated with postpartum hemorrhage (PPH) both in nulliparous and multiparous women. However, few studies have examined the difference in this association between nulliparous and multiparous women. This study aimed to explore the difference of maternal and neonatal characteristics and delivery methods between Chinese nulliparous and multiparous women, and then examine the differential effects of different delivery methods on PPH between these two-type women. Totally 151,333 medical records of women who gave birth between April 2013 to May 2016 were obtained from the electronic health records (EHR) in a northern province, China. The severity of PPH was estimated and classified into blood loss at the level of  2100 ml. Neonatal and maternal characteristics related to PPH were derived from the same database. Multiple ordinal logistic regression was used to estimate associations. Medical comorbidities, placenta previa and accreta were higher in the nulliparous group and the episiotomy rate was higher in the multiparous group. Compared with spontaneous vaginal delivery (SVD), the adjusted odds (aOR) for progression to severe PPH due to the forceps-assisted delivery was much higher in multiparous women (aOR: 9.32; 95% CI: 3.66–23.71) than in nulliparous women (aOR: 1.70; 95% CI: 0.91–3.18). The (aOR) for progression to severe PPH due to cesarean section (CS) compared to SVD was twice as high in the multiparous women (aOR: 4.32; 95% CI: 3.03–6.14) as in the nulliparous women (aOR: 2.04; 95% CI: 1.40–2.97). However, the (aOR) for progression to severe PPH due to episiotomy compared to SVD between multiparous (aOR: 1.24; 95% CI: 0.96–1.62) and nulliparous women (aOR: 1.55; 95% CI: 0.92–2.60) was not significantly different. The (aOR) for progression to severe PPH due to vacuum-assisted delivery compared to SVD in multiparous women (aOR: 2.41; 95% CI: 0.36–16.29) was not significantly different from the nulliparous women (aOR: 1.05; 95% CI: 0.40–2.73). Forceps-assisted delivery and CS methods were found to increase the risk of severity of the PPH. The adverse effects were even greater for multiparous women. Episiotomy and the vacuum-assisted delivery, and SVD were similar to the risk of progression to severe PPH in either nulliparous or multiparous women. Our findings have implications for the obstetric decision on the choice of delivery methods, maternal and neonatal health care, and obstetric quality control.

/pdf/differential-effects-of-different-delivery-methods-on-2agasf1g8i.pdf

Differential effects of different delivery methods on progression to severe postpartum hemorrhage between Chinese nulliparous and multiparous women: a retrospective cohort study

Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: A multi-central study based on 30 provinces in mainland China from 2013 to 2018

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Differential effects of different delivery methods on progression to severe postpartum hemorrhage between Chinese nulliparous and multiparous women: a retrospective cohort study

Effects and interaction of temperature and relative humidity on the trend of influenza prevalence: A multi-central study based on 30 provinces in mainland China from 2013 to 2018