Pulmonary Function Tests for the Prediction of Postoperative Pulmonary Complications

A Systematic Review

Background: Pulmonary function tests (PFTs) such as spirometry and blood gas analysis have been claimed to improve preoperative risk assessment. This systematic review summarizes the available scientific literature regarding the ability of PFTs to predict postoperative pulmonary complications (PPC) in non-thoracic surgery.

Methods: We systematically searched MEDLINE, CINAHL, and the Cochrane Library for pertinent original research articles (PROSPERO CRD42020215502), framed by the PIT-criteria (PIT, participants, index test, target conditions), respecting the PRISMA-DTA recommendations (DTA, diagnostic test accuracy).

Results: 46 original research studies were identified that used PFT-findings as index tests and PPC as target condition. QUADAS-2 quality assessment revealed a high risk of bias regarding patient selection, blinding, and outcome definitions. Qualitative synthesis of prospective studies revealed inconclusive study findings: 65% argue for and 35% against preoperative spirometry, and 43% argue for blood gas analysis. A (post-hoc) subgroup analysis in prospective studies with low-risk of selection bias identified a possible benefit in upper abdominal surgery (three studies with 959 participants argued for and one study with 60 participants against spirometry).

Conclusion: As the existing literature is inconclusive it is currently unknown if PFTs improve risk assessment before non-thoracic surgery. Spirometry should be considered in individuals with key indicators for chronic obstructive pulmonary disease (COPD) scheduling for upper abdominal surgery

More than 310 million people undergo surgery each year worldwide (1); the estimated postoperative mortality is 1–4% (2). The incidence of postoperative complications that affect the respiratory tract ranges between 9% and 40% (2), and postoperative pulmonary complications (PPC) are associated with elevated mortality (3).

Worldwide, the estimated mean prevalence of chronic obstructive pulmonary disease (COPD) is 13.1% (4). Spirometry is the gold standard method for the detection of airflow limitations and is recommended in patients with typical clinical signs of COPD (GOLD key indicators: dyspnea, chronic cough, chronic sputum production, recurrent lower respiratory tract infection, and exposure to risk factors [5]) (GOLD, Global Initiative for Chronic Obstructive Lung Disease).

Due to the growing prevalence, increased life expectancy and the rising demand for operative interventions, surgery is increasingly being carried out in patients with undiagnosed COPD. Although COPD is a major risk factor for PPC (6), it is still underdiagnosed (7). Both anesthesia and surgery itself affect the respiratory system and may aggravate pre-existing airway obstructions.

Preoperative pulmonary function tests (PFT) are recommended in patients scheduled for lung resection (8) or cardiac surgery (9). Moreover, it has frequently been postulated that PFT improve preoperative pulmonary risk assessment in non-thoracic surgery.

The aims of this systematic review of the literature were the following:

• Identification of eligible studies
• A qualitative and quantitative synthesis of the extracted data
• A structured quality rating of the studies identified.

The intention was to provide an overview of the existing evidence on whether PPC in patients undergoing non-thoracic surgery can be predicted on the basis of preoperative PFT.

Methods

The systematic literature search was conducted in accordance with the recommendations of the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) (10, 11, 12).

To avoid redundancy, we searched PROSPERO and the Cochrane Database of Systematic Reviews for related systematic reviews. The systematic review protocol was registered with PROSPERO (#CRD42020215502; 23 November 2020) (13). For the planning and internal audit of the systematic review, the Revised Assessment of Multiple Systematic Reviews (R-AMSTAR) criteria (14, 15) and the Scottish Intercollegiate Guidelines Network (SIGN) (16) checklist for systematic reviews and meta-analyses were used. PIT criteria (participants, index test, target conditions) (10) were applied for framing of the research question (Box 1).

Box 1

The PIT criteria (participants, index test, target conditions) for a priori framing of the research question in a systematic review of the literature

Eligibility criteria

Original research studies in adult cohorts, published in peer-reviewed journals, were considered for inclusion (Box 2). Although we had originally intended to search without language restrictions, on grounds of practicability we decided to include only studies in English or German.

Box 2

Eligibility criteria for the systematic review of the literature

Search algorithm

The systematic search algorithm was developed in collaboration with a medical librarian (KDP). We systematically searched MEDLINE, CINAHL, and the Cochrane Library for original research articles published between 1 January 1968 and 1 December 2020 (eBox 1).

eBox

Final search algorithm and filters for the PubMed search

Study selection

The studies identified were uploaded into EndNote X9 (Clarivate Analytics, London, UK) to facilitate a structured review. Duplicates were removed. Structured screening of the title, abstract, and full text was performed by two independent reviewers (AD, MP). The selection process was documented in a PRISMA flowchart (Figure 1) (12). Discrepancies were discussed, and where no consensus could be reached a third reviewer (TD) was consulted. Additional sources such as systematic reviews, guidelines, and review articles, as well as the reference lists from the identified original articles, were checked for further eligible studies (non-systematic search).

Figure 1

PRISMA-DTA flowchart

Quality assessment

Quality was assessed in accordance with PRISMA-DTA (10). The risk of bias and concerns regarding applicability were rated for each study using the revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool (17) and the SIGN methodology checklists (16). QUADAS-2 evaluates the risk of bias and the applicability in four domains: patient selection, index test, reference standard, and flow and timing. The risk of bias in each domain is assessed using signaling questions. Selection and spectrum bias was assumed in the event of irregular exclusions (exclusion of pulmonary high-risk or low-risk patients) irregular inclusion criteria (inclusion of non-pulmonary comorbidities/cofactors or non-systematic referral patterns, e.g., personal preferences of the assigning physician) (18). The risk of bias in randomized controlled trials was further checked using the updated Cochrane Collaboration risk-of-bias tool (19). Quality assessment was performed by two raters (AD, MP) independently. In the event of disagreement a third rater (TD) was consulted.

Data extraction, analysis, and synthesis

A specific data collection form was created, piloted with five randomly selected papers, and refined. Extracted data were, if possible, summarized and relevant facts were cumulatively pooled in a narrative, qualitative synthesis. A structured quantitative data synthesis was planned, depending on the degree of heterogeneity across the identified primary studies. Only prospective studies were included in the final qualitative synthesis.

We further performed a subgroup analysis (post hoc) that focused specifically on upper abdominal surgery and included only prospective studies with a low risk of selection bias (associated with low applicability concerns) in the QUADAS-2 analysis.

Results

The systematic search algorithm identified 2330 studies; a further 48 potentially eligible studies were identified by means of an additional non-systematic search. After title and abstract screening, 161 articles underwent full-text review. Forty-six original articles (e1, e2, e3, e4, e5, e6, e7, e8, e9, e10, e11, e12, e13, e14, e15, e16, e17, e18, e19, e20, e21, e22, e23, e24, e25, e26, e27, e28, e29, e30, e31, e32, e33, e34, e35, e36, e37, e38, e39, e40, e41, e42, e43, e44, e45, e46) fulfilled all eligibility criteria; all 46 of them investigated preoperative spirometry (eTable 1, Table 1) and eight investigated preoperative blood gas analysis (e10, e13, e17, e20, e22, e23, e24, e27) (eTable 2).

eTable 1

Qualitative synthesis of identified retrospective studies dealing with spirometry

eTable 2

Qualitative synthesis of identified studies that investigated the association between blood gas analysis and postoperative pulmonary complications

Quality assessment

Assessment of the quality of these 46 studies identified a substantial cumulative risk of bias and clinical applicability concerns (Figure 2, eTable 3), particularly regarding patient selection (QUADAS-2 rating: high risk of bias in 59%, high applicability concerns in 57%) and the reference standard (high risk of bias in 87%, high applicability concerns in 87%). There were major concerns regarding the outcome definition (PPC), blinding of the results of the index test (diagnostic review bias), preselection of study cohorts, referral pattern (spectrum bias) and unclear prior clinical tests. Fewer concerns arose regarding the index test, flow, and timing.

Figure 2

Quality assessment of the studies by means of QUADAS- 2, cumulative results

eTable 3

QUADAS-2 risk of bias and applicability concerns: overview of all included studies

Study methods

We identified 26 prospective studies (Table 1), and 20 retrospective studies (eTable 1). In retrospective cohort studies physicians were mostly not blinded to the index tests (PFT); rather, the findings were used for clinical decision making and thus impacted the patients’ outcome (diagnostic review bias). For this reason, retrospective studies were not included in the final qualitative analysis.

Five studies were secondary analyses from randomized controlled trials with interventions other than PFT. Twenty studies used only descriptive or univariate analysis. Twenty-six of the identified studies applied multivariable regression analysis but employed a wide variety of different covariables for adjustment; hence, the results of these multivariable models are difficult to compare and to synthesize.

Qualitative synthesis of prospective studies

Qualitative synthesis of the identified prospective studies revealed conflicting, inconclusive results. Seventeen studies (65%) argued for and nine (35%) against the ability of spirometry to predict PPC. Three prospective studies argued for (43%) and four (57%) against the ability of blood gas analysis to predict PPC (eTable 2). As the high level of methodological heterogeneity and the variety of PFT parameters tested, referral patterns, and outcome definitions precluded quantitative synthesis of the extracted data, we performed a qualitative synthesis instead (Table 1).

Table 1

Qualitative synthesis of identified prospective studies that investigated the association between spirometry and postoperative pulmonary complications

Index parameters

In the reviewed studies various index parameters were tested and diverse PFT parameters were found to be suitable (Table 1, right column). Few studies clearly defined the standard procedures, cut-off values and reference cohorts for spirometry.

Outcome definition

AS outlined in the PIT criteria (10), the 2015 European Perioperative Clinical Outcome (EPCO) definitions (20) and the 2018 Standardised Endpoints in Perioperative Medicine (StEP) (2) were regarded as the current clinical standard outcome definitions for PPC; however, only a small number of study outcomes conformed with either of these definitions; moreover, the two definitions differ substantially from each other.

Patient selection

As the selection criteria of the reviewed studies were extremely inhomogeneous, generalization of cumulative findings is precluded. In particular, irregular preselection on the basis of comorbidity/cofactors other than pulmonary preconditions or systematic exclusion of pulmonary high-risk patients gave rise to concerns regarding selection/spectrum bias and applicability (eMethods).

Type of surgery

To do justice to the research question of this systematic review, the study populations of the reviewed studies must correspond as closely as possible with the target population defined by the PIT criteria (10, 18). The identified studies came from a broad surgical spectrum: abdominal, bariatric, vascular, non-thoracic procedures, head and neck operations, esophagectomy, or mixed cohorts. Some study cohorts included a significant proportion of lung resections or cardiac surgery (not a formal exclusion criterion for this review, but a potential source of bias).

As upper abdominal surgery is associated with a high risk of PPC (e27), we decided to perform an additional (post-hoc) subgroup analysis. This analysis focused on prospective studies in patients undergoing upper abdominal surgery but included only studies with low risk of selection bias and low applicability concerns in the QUADAS-2 analysis (Table 2). Three studies (with a total of 959 patients) concluded that spirometry can predict PPC; one study (60 patients) reported that it cannot.

Table 2

Quantitative analysis of prospective studies investigating the association between spirometry prior to upper abdominal surgery and postoperative pulmonary complications

Discussion

Our systematic review of the literature shows that due to a lack of robust evidence and methodological flaws it is remains unclear whether preoperative PFT sufficiently predict PPC prior to non-thoracic surgery. The existing literature is inconclusive: 65% of the prospective studies argue for and 35% against the ability of preoperative spirometry to predict PPC, while 43% argue for the ability of blood gas analysis to predict PPC. In the absence of randomized controlled trials, the existing evidence is based on inhomogeneous studies with divergent basic assumptions.

Quality assessment of the studies by means of QUADAS-2 gave rise to substantial concerns regarding patient selection, referral patterns, outcome definition, blinding of the results of the index test, and unclear prior clinical testing, associated with a cumulative high risk of bias and concerns regarding clinical applicability.

Because a wide variety of index parameters were chosen in the studies analyzed, it remains unclear on which parameters of spirometry the prediction of PPC should be based. The studies employed various analysis methods: univariate or descriptive analysis in 43%, multivariable regression analysis in 57%. However, an association between an index parameter and PPC on univariate analysis does not rule out the possibility that simple clinical findings (e.g., dyspnea, cough, or wheezing) or a risk factor (e.g., smoking) would predict PPC equally well.

Almost half of the identified trials were retrospective. However, retrospective cohort studies seem inadequate to answer our research question, as PFT findings were often used for clinical decision making, thus changing the clinical course and possibly the patient’s outcome, with a resultant effect on the endpoint of the diagnostic study. Many prospective studies were also afflicted by this problem, because inadequate blinding of the index test meant that the treating physicians were aware of the PFT findings (diagnostic review bias).

All of the trials analyzed were affected by the major problem of inconsistent outcome definitions, hampering the interpretation of pooled data. The 2018 StEP consensus definition of PPC (2) represents an important step towards standardized endpoint definition, which will allow synthesis of data from different trials in the future; however, this does not help us to evaluate historical data.

Our systematic analysis features a very broad spectrum of different types of surgery making general conclusions and recommendations difficult. Upper abdominal surgery is associated with a strikingly high risk of PPC (e27). In a (post-hoc) subgroup analysis we identified a significant number of prospective studies with lower risk of selection and spectrum bias that concerned themselves with spirometry prior to upper abdominal surgery. In these studies we found some evidence of an additional diagnostic benefit of preoperative spirometry. We therefore believe it is reasonable to test for relevant airflow obstruction before upper abdominal surgery in persons with a reasonable pretest probability, especially those with typical symptoms of COPD as defined by the GOLD key indicators (5).

However, based on our literature research we hold that PFT cannot currently be recommended in advance of other kinds of non-thoracic surgery. It is important to note that this conclusion rests on the lack of evidence, and especially in this field the absence of evidence of efficacy does not constitute evidence of inefficacy.

The studies included in this review focus especially on answering the question of whether PFT can predict PPC. Other important applications of preoperative PFT should not be forgotten. Spirometry is mandatory to verify the diagnosis of COPD (5), which in turn goes along with perioperative therapeutic or preventive measures and may also have implications for the long-term outcome and quality of life (21). Moreover, spirometry enables determination of the baseline pulmonary function status for personalized grading of postoperative pulmonary dysfunction and thus the setting of individual treatment goals.

PFT can be beneficial for the planning of preoperative pulmonary rehabilitation measures, antiobstructive treatment, personalized ventilation strategies, and the choice of drugs or monitoring methods (21). Lee et al. propose five fundamental factors for preoperative optimization: smoking cessation, pulmonary rehabilitation, vaccination, self-management, and the identification and optimization of comorbidities (21). Beyond the intended improvement of patient outcome, this also allows efficient use of healthcare resources.

This systemic review of the literature has some limitations. Studies were collected from a period of several decades, in the course of which the diagnostic and clinical standards have changed. Our literature research makes no claim to be complete; we assume that some studies that used PFT as a baseline measure per protocol will have been missed.

Conclusion

Our systematic review shows the lack of robust evidence from large high-quality studies and concludes that it remains unproven whether preoperative PFT predict PPC prior to non-thoracic surgery. On the other hand, our (post-hoc) subgroup analysis suggests that there might be a benefit or incremental diagnostic value of spirometry in patients scheduled for upper abdominal surgery. This question has not yet been explored in randomized controlled trials. Nevertheless, a broad, quasi-unchallenged consensus exists that preoperative spirometry is not recommended in patients who show no clinical abnormality (22, 23, 24, 25, 26), while it may be considered in selected high-risk patients scheduled for intermediate- or high-risk procedures (24, 26). In our opinion, further high-quality studies are required to conclusively answer these research questions.

The existing prospective studies come to conflicting conclusions: 17 of 26 studies (65%) argue for and nine (35%) against preoperative spirometry, and three of seven (43%) argue in favor of blood gas analysis. Due to methodological flaws and inconsistent study designs it is currently unknown whether PFT are able to predict PPC prior to non-thoracic surgery. Based on the studies included in this review, spirometry prior to upper abdominal surgery should be considered in individuals with typical symptoms of COPD (GOLD key indicators), but no benefit of PFT before other kinds of non-thoracic surgery has yet been demonstrated.

Acknowledgment

The authors would like to thank Mr. Klaus-Dieter Papke from the Central Medical Library of the University Medical Center Hamburg-Eppendorf for his support in the development of an enhanced search algorithm for a comprehensive database search.

Conflict of interest statement
PD Dr. Petzoldt has received consultancy honoraria from Radiometer Medical, Copenhagen.

The remaining authors declare that no conflict of interest exists.

Manuscript submitted on 12 August 2021, revised version accepted on 29 November 2021

Corresponding author
PD Dr. med. Martin Petzoldt
Klinik für Anästhesiologie
Zentrum für Anästhesiologie und Intensivmedizin
Universitätsklinikum Hamburg-Eppendorf
Martinistr. 52, 20246 Hamburg, Germany

Cite this as:
Dankert A, Dohrmann T, Löser, B, Zapf A, Zöllner C, Petzoldt M: Pulmonary function tests for the prediction of postoperative pulmonary complications—a systematic review. Dtsch Arztebl Int 2022; 119: 99–106. DOI: 10.3238/arztebl.m2022.0074

►Supplementary material

eReferences, eMethods, eTable, eBox:
www.aerzteblatt-international.de/m2022.0074

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