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      Respiratory Prehabilitation for the Prevention of Postoperative Pulmonary Complications after Major Surgery

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      Current Anesthesiology Reports
      Springer Science and Business Media LLC

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          Determinants of long-term survival after major surgery and the adverse effect of postoperative complications.

          The objective of this study was to identify the determinants of 30-day postoperative mortality and long-term survival after major surgery as exemplified by 8 common operations. The National Surgical Quality Improvement Program (NSQIP) database contains pre-, intra-, and 30-day postoperative data, prospectively collected in a standardized fashion by a dedicated nurse reviewer, on major surgery in the Veterans Administration (VA). The Beneficiary Identification and Records Locator Subsystem (BIRLS) is a VA file that depicts the vital status of U.S. veterans with 87% to 95% accuracy. NSQIP data were merged with BIRLS to determine the vital status of 105,951 patients who underwent 8 types of operations performed between 1991 and 1999, providing an average follow up of 8 years. Logistic and Cox regression analyses were performed to identify the predictors of 30-day mortality and long-term survival, respectively. The most important determinant of decreased postoperative survival was the occurrence, within 30 days postoperatively, of any one of 22 types of complications collected in the NSQIP. Independent of preoperative patient risk, the occurrence of a 30-day complication in the total patient group reduced median patient survival by 69%. The adverse effect of a complication on patient survival was also influenced by the operation type and was sustained even when patients who did not survive for 30 days were excluded from the analyses. The occurrence of a 30-day postoperative complication is more important than preoperative patient risk and intraoperative factors in determining the survival after major surgery in the VA. Quality and process improvement in surgery should be directed toward the prevention of postoperative complications.
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            Prediction of postoperative pulmonary complications in a population-based surgical cohort.

            Current knowledge of the risk for postoperative pulmonary complications (PPCs) rests on studies that narrowly selected patients and procedures. Hypothesizing that PPC occurrence could be predicted from a reduced set of perioperative variables, we aimed to develop a predictive index for a broad surgical population. Patients undergoing surgical procedures given general, neuraxial, or regional anesthesia in 59 hospitals were randomly selected for this prospective, multicenter study. The main outcome was the development of at least one of the following: respiratory infection, respiratory failure, bronchospasm, atelectasis, pleural effusion, pneumothorax, or aspiration pneumonitis. The cohort was randomly divided into a development subsample to construct a logistic regression model and a validation subsample. A PPC predictive index was constructed. Of 2,464 patients studied, 252 events were observed in 123 (5%). Thirty-day mortality was higher in patients with a PPC (19.5%; 95% [CI], 12.5-26.5%) than in those without a PPC (0.5%; 95% CI, 0.2-0.8%). Regression modeling identified seven independent risk factors: low preoperative arterial oxygen saturation, acute respiratory infection during the previous month, age, preoperative anemia, upper abdominal or intrathoracic surgery, surgical duration of at least 2 h, and emergency surgery. The area under the receiver operating characteristic curve was 90% (95% CI, 85-94%) for the development subsample and 88% (95% CI, 84-93%) for the validation subsample. The risk index based on seven objective, easily assessed factors has excellent discriminative ability. The index can be used to assess individual risk of PPC and focus further research on measures to improve patient care.
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              Postoperative pulmonary complications.

              Postoperative pulmonary complications (PPCs) are common, costly, and increase patient mortality. Changes to the respiratory system occur immediately on induction of general anaesthesia: respiratory drive and muscle function are altered, lung volumes reduced, and atelectasis develops in > 75% of patients receiving a neuromuscular blocking drug. The respiratory system may take 6 weeks to return to its preoperative state after general anaesthesia for major surgery. Risk factors for PPC development are numerous, and clinicians should be aware of non-modifiable and modifiable factors in order to recognize those at risk and optimize their care. Many validated risk prediction models are described. These have been useful for improving our understanding of PPC development, but there remains inadequate consensus for them to be useful clinically. Preventative measures include preoperative optimization of co-morbidities, smoking cessation, and correction of anaemia, in addition to intraoperative protective ventilation strategies and appropriate management of neuromuscular blocking drugs. Protective ventilation includes low tidal volumes, which must be calculated according to the patient's ideal body weight. Further evidence for the most beneficial level of PEEP is required, and on-going randomized trials will hopefully provide more information. When PEEP is used, it may be useful to precede this with a recruitment manoeuvre if atelectasis is suspected. For high-risk patients, surgical time should be minimized. After surgery, nasogastric tubes should be avoided and analgesia optimized. A postoperative mobilization, chest physiotherapy, and oral hygiene bundle reduces PPCs.
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                Author and article information

                Contributors
                Journal
                Current Anesthesiology Reports
                Curr Anesthesiol Rep
                Springer Science and Business Media LLC
                2167-6275
                March 2022
                December 01 2021
                March 2022
                : 12
                : 1
                : 44-58
                Article
                10.1007/s40140-021-00495-w
                daa7fd36-9d34-464f-8b40-2fb34be95a2e
                © 2022

                https://www.springer.com/tdm

                https://www.springer.com/tdm

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