Prophylactic Penehyclidine Inhalation for Prevention of Postoperative Pulmonary Complications in High-risk Patients: A Double-blind Randomized Trial.

BACKGROUND: Postoperative pulmonary complications are common. Aging and respiratory disease provoke airway hyperresponsiveness, high-risk surgery induces diaphragmatic dysfunction, and general anesthesia contributes to atelectasis and peripheral airway injury. This study therefore tested the hypothesis that inhalation of penehyclidine, a long-acting muscarinic antagonist, reduces the incidence of pulmonary complications in high-risk patients over the initial 30 postoperative days. METHODS: This single-center double-blind trial enrolled 864 patients age over 50 yr who were scheduled for major upper-abdominal or noncardiac thoracic surgery lasting 2 h or more and who had an Assess Respiratory Risk in Surgical Patients in Catalonia score of 45 or higher. The patients were randomly assigned to placebo or prophylactic penehyclidine inhalation from the night before surgery through postoperative day 2 at 12-h intervals. The primary outcome was the incidence of a composite of pulmonary complications within 30 postoperative days, including respiratory infection, respiratory failure, pleural effusion, atelectasis, pneumothorax, bronchospasm, and aspiration pneumonitis. RESULTS: A total of 826 patients (mean age, 64 yr; 63% male) were included in the intention-to-treat analysis. A composite of pulmonary complications was less common in patients assigned to penehyclidine (18.9% [79 of 417]) than those receiving the placebo (26.4% [108 of 409]; relative risk, 0.72; 95% CI, 0.56 to 0.93; P = 0.010; number needed to treat, 13). Bronchospasm was less common in penehyclidine than placebo patients: 1.4% (6 of 417) versus 4.4% (18 of 409; relative risk, 0.327; 95% CI, 0.131 to 0.82; P = 0.011). None of the other individual pulmonary complications differed significantly. Peak airway pressures greater than 40 cm H2O were also less common in patients given penehyclidine: 1.9% (8 of 432) versus 4.9% (21 of 432; relative risk, 0.381; 95% CI, 0.171 to 0.85; P = 0.014). The incidence of other adverse events, including dry mouth and delirium, that were potentially related to penehyclidine inhalation did not differ between the groups. CONCLUSIONS: In high-risk patients having major upper-abdominal or noncardiac thoracic surgery, prophylactic penehyclidine inhalation reduced the incidence of pulmonary complications without provoking complications.

Prophylactic penehyclidine inhalation for prevention of postoperative pulmonary complications in high-risk patients: study protocol of a randomized controlled trial.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major causes of morbidity, mortality, and prolonged hospital stay in patients after surgery. Using effective strategies to prevent its occurrence is essential to improve outcome. However, despite various efforts, the incidence of PPCs remains elevated in high-risk patients. Anticholinergic inhalation is used to reduce high airway resistance and improve pulmonary function; it may be helpful to decrease the risk of PPCs. Penehyclidine is a long-acting anticholinergic agent which selectively blocks M1 and M3 receptors. We hypothesize that, in high-risk patients, prophylactic penehyclidine inhalation may decrease the incidence of PPCs. METHODS: This is a randomized, double-blind, placebo-controlled trial with two parallel arms. A total of 864 patients at high risk of PPCs will be enrolled and randomized to receive prophylactic inhalation of either penehyclidine or placebo (water for injection). Study drug inhalation will be administered from the night (7 pm) before surgery until the second day after surgery, in an interval of every 12 hours. The primary outcome is the incidence of PPCs within 30 days after surgery. Secondary outcomes include the time to onset of PPCs (from end of surgery to first diagnosis of PPCs), the number of PPCs (indicates the number of diagnosed individual PPCs), the incidence of postoperative extrapulmonary complications, the length of stay in hospital after surgery, and the 30-day all-cause mortality. DISCUSSION: Results of the present study will provide evidence to guide clinical practice in using prophylactic inhalation of an anticholinergic to prevent PPCs in high-risk patients. TRIAL REGISTRATION: The study was registered prospectively in Chinese Clinical Trial Registry ( www.chictr.org.cn , ChiCTR-IPC-15006603 ) on 14 May 2015 and retrospectively in ClinicalTrials.gov ( NCT02644876 ) on 30 December 2015.

Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

BACKGROUND: Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. RESULTS: We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. CONCLUSIONS: The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.