A noninvasive postoperative clinical score to identify patients at risk for postoperative pulmonary complications: the Air-Test Score

Abstract Background Postoperative pulmonary complications (PPCs) are important contributors to mortality and morbidity after surgery. The available predicting models are useful in preoperative risk assessment, but there is a need for validated tools for the early postoperative period as well. Lung ultrasound is becoming popular in intensive and perioperative care and there is a growing interest to evaluate its role in the detection of postoperative pulmonary pathologies. Objectives We aimed to identify characteristics with the potential of recognizing patients at risk by comparing the lung ultrasound scores (LUS) of patients with/without PPC in a 24-h postoperative timeframe. Methods Observational study at a university clinic. We recruited ASA 2–3 patients undergoing elective major abdominal surgery under general anaesthesia. LUS was assessed preoperatively, and also 1 and 24 h after surgery. Baseline and operative characteristics were also collected. A one-week follow up identified PPC+ and PPC- patients. Significantly differing LUS values underwent ROC analysis. A multi-variate logistic regression analysis with forward stepwise model building was performed to find independent predictors of PPCs. Results Out of the 77 recruited patients, 67 were included in the study. We evaluated 18 patients in the PPC+ and 49 in the PPC- group. Mean ages were 68.4 ± 10.2 and 66.4 ± 9.6 years, respectively (p = 0.4829). Patients conforming to ASA 3 class were significantly more represented in the PPC+ group (66.7 and 26.5%; p = 0.0026). LUS at baseline and in the postoperative hour were similar in both populations. The median LUS at 0 h was 1.5 (IQR 1–2) and 1 (IQR 0–2; p = 0.4625) in the PPC+ and PPC- groups, respectively. In the first postoperative hour, both groups had a marked increase, resulting in scores of 6.5 (IQR 3–9) and 5 (IQR 3–7; p = 0.1925). However, in the 24th hour, median LUS were significantly higher in the PPC+ group (6; IQR 6–10 vs 3; IQR 2–4; p < 0.0001) and it was an independent risk factor (OR = 2.6448 CI95% 1.5555–4.4971; p = 0.0003). ROC analysis identified the optimal cut-off at 5 points with high sensitivity (0.9444) and good specificity (0.7755). Conclusion Postoperative LUS at 24 h can identify patients at risk of or in an early phase of PPCs.

Download Full-text

Preoperative evaluation of patients at risk for postoperative pulmonary complications

Seminars in Anesthesia Perioperative Medicine and Pain ◽

10.1016/s0277-0326(96)80048-1 ◽

1996 ◽

Vol 15 (4) ◽

pp. 353-362

Author(s):

Stewart J. Lustik ◽

Lindsey C. Henson

Keyword(s):

At Risk ◽

Preoperative Evaluation ◽

Pulmonary Complications ◽

Postoperative Pulmonary Complications ◽

Patients At Risk

Download Full-text

Perioperative redistribution of regional ventilation and pulmonary function: a prospective observational study in two cohorts of patients at risk for postoperative pulmonary complications

BMC Anesthesiology ◽

10.1186/s12871-019-0805-8 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 2

Author(s):

Maria Bauer ◽

Anne Opitz ◽

Jörg Filser ◽

Hendrik Jansen ◽

Rainer H. Meffert ◽

...

Keyword(s):

At Risk ◽

Observational Study ◽

Pulmonary Function ◽

Prospective Observational Study ◽

Pulmonary Complications ◽

Postoperative Pulmonary Complications ◽

Regional Ventilation ◽

Patients At Risk

Download Full-text

Pulmonary complications after open heart surgery: A retrospective study

International Journal of Emerging Trends in Health Sciences ◽

10.18844/ijeths.v5i1.5300 ◽

2021 ◽

Vol 5 (1) ◽

pp. 01-12

Author(s):

Abdul-Monim Mohammad Batiha ◽

Ibtisam Al-Zaru ◽

Majdee Saiah AL-Shaarani ◽

Fadwa N Alhalaiqa

Keyword(s):

Risk Factors ◽

At Risk ◽

Heart Surgery ◽

Open Heart Surgery ◽

Pulmonary Complications ◽

University Hospital ◽

Open Heart ◽

Assessment Sheet ◽

Patients At Risk ◽

Prolonged Hospital

Despite significant advances in open heart surgery over the last two decades, postoperative pulmonary complications (PPCs) are considered the most important causes that contribute to patient morbidity, mortality and prolonged hospital stay. The ultimate goal of this paper was to investigate the risk factors which increasing the incidence rate of pulmonary complications after open heart surgery of Jordanian patients. A retrospective design using an existing coronary artery surgery database of adults (n = 200) who had undergone open heart surgery between August 2014 and July 2015 at a University Hospital in Jordan. A structured PPCs instrument was used to assess ‘PPCs risk factors assessment sheet’. According to the results, the proposed model provides a preliminary indication of risk factors placing open heart surgical patients at risk of PPCs. Determining patients who are at risk of developing PPC’s after cardiac surgeries are the first step towards its prevention. This reduces its burden in term of morbidity, mortality and cost. Keywords: Jordan, open heart surgery, predictors, pulmonary complications, risk factors.

Download Full-text

Prediction of COVID-19 deterioration in high-risk patients at diagnosis: an early warning score for advanced COVID-19 developed by machine learning

Infection ◽

10.1007/s15010-021-01656-z ◽

2021 ◽

Author(s):

Carolin E. M. Jakob ◽

Ujjwal Mukund Mahajan ◽

Marcus Oswald ◽

Melanie Stecher ◽

Maximilian Schons ◽

...

Keyword(s):

Machine Learning ◽

At Risk ◽

Smoking Habit ◽

Clinical Score ◽

Early Warning Score ◽

Predictive Score ◽

Good Prediction ◽

Validation Data ◽

Patients At Risk ◽

Predictor Model

Abstract Purpose While more advanced COVID-19 necessitates medical interventions and hospitalization, patients with mild COVID-19 do not require this. Identifying patients at risk of progressing to advanced COVID-19 might guide treatment decisions, particularly for better prioritizing patients in need for hospitalization. Methods We developed a machine learning-based predictor for deriving a clinical score identifying patients with asymptomatic/mild COVID-19 at risk of progressing to advanced COVID-19. Clinical data from SARS-CoV-2 positive patients from the multicenter Lean European Open Survey on SARS-CoV-2 Infected Patients (LEOSS) were used for discovery (2020-03-16 to 2020-07-14) and validation (data from 2020-07-15 to 2021-02-16). Results The LEOSS dataset contains 473 baseline patient parameters measured at the first patient contact. After training the predictor model on a training dataset comprising 1233 patients, 20 of the 473 parameters were selected for the predictor model. From the predictor model, we delineated a composite predictive score (SACOV-19, Score for the prediction of an Advanced stage of COVID-19) with eleven variables. In the validation cohort (n = 2264 patients), we observed good prediction performance with an area under the curve (AUC) of 0.73 ± 0.01. Besides temperature, age, body mass index and smoking habit, variables indicating pulmonary involvement (respiration rate, oxygen saturation, dyspnea), inflammation (CRP, LDH, lymphocyte counts), and acute kidney injury at diagnosis were identified. For better interpretability, the predictor was translated into a web interface. Conclusion We present a machine learning-based predictor model and a clinical score for identifying patients at risk of developing advanced COVID-19.

Download Full-text

Postoperative atelectasis and pneumonia: risk factors

American Journal of Critical Care ◽

10.4037/ajcc1995.4.5.340 ◽

1995 ◽

Vol 4 (5) ◽

pp. 340-349 ◽

Cited By ~ 44

Author(s):

JA Brooks-Brunn

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Pulmonary Function ◽

Infectious Complications ◽

Hospital Length ◽

Pulmonary Complications ◽

Hospital Length Of Stay ◽

Postoperative Pulmonary Complications ◽

Patients At Risk ◽

Factor Evaluation

Postoperative pulmonary complications frequently lead to increased patient morbidity and mortality, hospital length of stay, and resource utilization. Atelectasis and infectious complications account for the majority of reported pulmonary complications. Risk factors are thought to exaggerate pulmonary function deterioration, which occurs both during and after surgical procedures. This article reviews the literature and describes risk factors frequently identified in relation to pre-, intra-, and postoperative settings, impact of each risk factor on pulmonary function, and issues related to risk factor evaluation. Eighteen risk factors are reviewed regarding their pathophysiologic impact on pre-, intra-, and postoperative pulmonary function. Key issues related to risk factor evaluation are also discussed. Identification of risk factors and prediction of postoperative pulmonary complications are important. Early identification of patients at risk for postoperative pulmonary complications can guide our respiratory care to prevent or minimize these complications.

Download Full-text