A local risk prediction model for prolonged ventilation after adult heart valve surgery in a Chinese single center

Background: Two consistent overall cell protective preconditioning treatments should provide more protection. We hypothesized that limb remote ischemic preconditioning (RIPC, second preconditioning stimulus) applied during sevoflurane inhalation (first preconditioning stimulus) would provide more protection to the lungs of patients undergoing adult heart valve surgery. Methods: In this randomized, placebo-controlled, double-blind trial, 50 patients were assigned to the RIPC group or the placebo group (1:1). Patients in the RIPC group received three 5-min cycles of 300 mmHg cuff inflation/deflation of the left-side lower limb before aortic cross-clamping. Anesthesia consisted of opioids and propofol for induction and sevoflurane for maintenance. The primary end point was comparison of the postoperative arterial–alveolar oxygen tension ratio (a/A ratio) between groups. Secondary end points included comparisons of pulmonary variables, postoperative morbidity and mortality and regional and systemic inflammatory cytokines between groups. Results: In the RIPC group, the a/A ratio and other pulmonary variables exhibited no significant differences throughout the study period compared with the placebo group. No significant differences in either plasma or bronchoalveolar lavage levels of TNF- α were noted between the groups at 10 min after anesthetic induction and 1 h after cross-clamp release. The percentage of neutrophils at 12 h postoperation was significantly increased in the RIPC group compared with the placebo group (91.34±0.00 vs. 89.42±0.10, P = 0.023). Conclusions: Limb RIPC applied during sevoflurane anesthesia did not provide additional significant pulmonary protection following adult valvular cardiac surgery.

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A risk prediction model for dysphagia in older patients: a single-center prospective study

Geriatric Nursing ◽

10.1016/j.gerinurse.2021.12.013 ◽

2022 ◽

Vol 44 ◽

pp. 24-29

Author(s):

Lili Yu ◽

Yingqiang Li ◽

Dongyun Zhang ◽

Wanyun Huang ◽

Runping Li ◽

...

Keyword(s):

Prediction Model ◽

Prospective Study ◽

Risk Prediction ◽

Older Patients ◽

Risk Prediction Model ◽

Single Center

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Can one risk prediction model be used for both aortic and mitral valve surgery?

Nature Clinical Practice Cardiovascular Medicine ◽

10.1038/ncpcardio0412 ◽

2006 ◽

Vol 3 (1) ◽

pp. 22-23

Author(s):

Ruyun Jin ◽

Gary L Grunkemeier

Keyword(s):

Mitral Valve ◽

Prediction Model ◽

Risk Prediction ◽

Mitral Valve Surgery ◽

Valve Surgery ◽

Risk Prediction Model

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A Nomogram To Predict The Cumulative Live Birth Rate for Patients with Low Prognosis According To The POSEIDON Criteria: A Retrospective Observational Cohort Study of 4,395 Patients in Chinese Population

10.21203/rs.3.rs-390210/v1 ◽

2021 ◽

Author(s):

Lijuan Chen ◽

Pengfei Qu ◽

Jinfang Wu ◽

Jinlin Xie ◽

Hui Wang ◽

...

Keyword(s):

Prediction Model ◽

Risk Prediction ◽

Live Birth ◽

Chinese Population ◽

Birth Rate ◽

Live Birth Rate ◽

Risk Prediction Model ◽

Single Center ◽

Cumulative Live Birth Rate ◽

Cumulative Live Birth

Abstract Purpose A small number of risk prediction model have been previously reported to predict the infertility treatment success. While the studies of the risk prediction model for the patients with low prognosis are limited. This study aimed to construct and validate a nomogram for the prediction of cumulative live birth rate (CLBR) in patients with low prognosis from a single center database in Chinese population. Methods Clinical data of 4,395 patients with low prognosis, who received in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) therapy between 2014 and 2018, were retrieved and randomly divided into training (70%) and the external validation (30%) sets. Multivariate analysis with logistic regression model was conducted. Results Multivariate analyses showed that maternal age, body mass index (BMI), basal serum follicle-stimulating hormone (FSH) level, type of infertility, male factors, uterine factors, and usable embryos number at day 3 were risk factors for CLBR in patients with low prognosis. The area under the receiver operating characteristic curve (AUC) of the prediction model was 0.769 (95% confident interval (CI): 0.751, 0.787) in training set. The validation set presented good performance with an AUC of 0.749 (95% CI: 0.720, 0.778). In addition, Hosmer-Lemeshow chi-square value was 10.194 (P = 0.252). Conclusion We constructed and validated a nomogram for the prediction of CLBR in low prognosis patients with a single center database in Chinese population. The validated nomogram for the prediction of CLBR could be potentially applied in clinic for IVF counselling in patients with low prognosis.

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