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Pneumonia is one of the most common complications following a stroke, affecting around 1 in 8 patients and is associated with poorer recovery and survival. This guideline aims to support healthcare professionals in diagnosing, preventing and treating stroke-associated pneumonia. As robust scientific evidence remains limited, many recommendations are based on expert consensus. The guideline recommends the use of standardised diagnostic criteria and the prompt initiation of antibiotic treatment when pneumonia is suspected, while preventive antibiotic use is not advised. Preventive care should focus on simple measures such as appropriate patient positioning, safe nutrition and early mobilisation where suitable. Additional treatments may be considered in selected patients. Overall, these recommendations are intended to support stroke teams in everyday clinical practice and highlight the need for further research to improve care and outcomes for patients after stroke.

Composition and approval of the module working group 4 Development and approval of clinical questions 4 Evaluation of the quality of evidence and formulation of recommendations 5 Drafting of the document, revision and approval 5

Infections are among the most common medical complications in the acute phase after stroke, with pneumonia and urinary tract infections representing the 2 most frequent entities. Stroke-associated pneumonia (SAP) is reported in approximately 5%–30% of acute stroke patients with the incidence depending on diagnostic criteria, timing, methods of assessment, stroke severity, as well as on patient- and care-related factors. In a recent meta-analysis including more than 32 million stroke patients, SAP remained the most frequent infectious complication (12.1%) and was associated with substantial in-patient mortality (rate 21.6%). Despite an overall decline in post-stroke infection rates over the past decade, SAP continues to constitute the leading infectious burden and a major clinical hazard in acute stroke care.

SAP results from a multifactorial disruption of protective airway and immune mechanisms. Major contributing factors are aspiration due to post-stroke dysphagia, a reduced level of consciousness, diminished cough and airway clearance reflexes, as well as stroke-induced immunodepression, which compromises antibacterial defence and increases vulnerability to respiratory infections. , , SAP usually becomes clinically apparent between the second and fifth day after stroke onset, providing an important window of opportunity for early risk stratification and the timely implementation of targeted preventive measures. This temporal pattern has stimulated the development of both non-pharmacological and pharmacological strategies aimed at reducing SAP occurrence, alongside considerable efforts to establish biomarkers and clinical prediction scores for identifying patients at highest risk. ,

SAP has a profound impact on both short- and long-term outcomes after stroke. It is strongly associated with respiratory failure, prolonged hospital and intensive care stays, poorer functional recovery, increased rates of institutionalisation, stroke recurrence and mortality. , Emerging evidence further suggests that stroke-associated infections (SAI), including SAP, may contribute to subsequent vascular cognitive impairment and dementia. , Beyond its direct physical complications, SAP therefore imposes a substantial burden on patients, reduces independence and increases healthcare costs. Given its high epidemiological relevance and its role as a major determinant of post-stroke morbidity and mortality, SAP represents a key target for improved prevention and management in contemporary stroke care.

Despite its clinical importance, there is currently no dedicated evidence-based guideline specifically addressing the diagnosis, prediction, prevention and treatment of SAP. Although SAP management and preventive measures and treatment are embedded within broader acute stroke care guidelines, such as those issued by the American Heart Association/American Stroke Association AHA/ASA and within the ESO dysphagia guideline, detailed evidence-based guidance specifically addressing SAP management remains lacking. , The Pneumonia In Stroke ConsEnsuS (PISCES) group has provided important proposals on diagnostic criteria, microbiological aetiologies and potential preventive and therapeutic strategies. However, these were largely based on limited evidence, highlighting the need for updated, structured and evidence-based guidance. Dysphagia is a key risk factor for SAP, and dysphagia screening and swallowing management are established components of post-stroke care with proven relevance for SAP prevention. These topics were intentionally excluded from the current PICO (Population, Intervention, Comparator and Outcome) framework, as they have been comprehensively addressed in the 2021 ESO guideline on Post-Stroke Dysphagia, to which readers are referred for detailed recommendations.

Given these unmet needs, the European Stroke Organisation (ESO), in collaboration with relevant multidisciplinary partners, has decided to compile guidelines on the management of SAP. These recommendations are based on the systematic evaluation of evidence from randomised controlled trials (RCTs), observational studies and expert consensus where evidence is limited. They were developed according to the ESO standard operating procedure (SOP) for guideline development and were agreed through consensus among the involved authors using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. The guideline document has received approval from the ESO Executive Committee. The aim of this guideline is to provide practical recommendations for physicians, stroke nurses, speech-and-language therapists and all members of the multidisciplinary stroke care team on how to diagnose SAP, identify patients at risk, implement evidence-based preventive interventions and optimise treatment strategies in order to reduce SAP-related complications and improve outcomes after stroke.

These guidelines were initiated by the ESO. One chairperson (AM) was selected to assemble and coordinate the Guideline Module Working Group (MWG). The expert panel comprised a multidisciplinary group of 9 specialists from 6 European countries, primarily from the fields of neurology and stroke medicine, complemented by expertise in neurorehabilitation, cardiovascular and clinical neuroscience, stroke epidemiology and guideline methodology within the ESO. The ESO Guideline Board and Executive Committee reviewed the intellectual and financial disclosures of all MWG members and approved the composition of the group. The full details of all MWG members and their disclosures is included in .

This guideline was prepared according to the ESO SOPs, which are based on the GRADE framework. The MWG developed a list of topics and corresponding questions of greatest clinical interest. Questions were formatted using the PICO approach and reviewed by 2 external reviewers as well as members of the ESO Guideline Board and Executive Committee. The outcomes were rated by members of the MWG as: critical, important or of limited importance according to GRADE criteria. Final decision on outcomes used a Delphi approach. Results of the outcomes rating for each PICO question are included in the .

For the literature search, the MWG defined the search criteria with regard to (1) general eligibility criteria for the populations of interest (see ), (2) the intervention and comparator (see ) and (3) the outcomes. To determine the outcome-related search terms for the individual PICO questions, we first compiled a comprehensive list of clinically relevant outcomes, complications and healthcare-related measures from a clinical practice perspective. Critical clinical outcomes included functional status (modified Rankin Scale, analysed as dichotomised outcome and/or shift analysis), activities of daily living (Barthel Index), survival and quality of life. Relevant complications comprised recurrent vascular events (stroke, transient ischaemic attack, myocardial infarction, intracerebral haemorrhage [ICH]), seizures, sepsis, recurrent infections, venous thromboembolism (deep vein thrombosis and pulmonary embolism) and antibiotic-related adverse events such as antibiotic-associated diarrhoea, Clostridioides difficile infection and antimicrobial resistance. Healthcare-related outcomes included length of hospital stay, hospital readmission, discharge destination and antibiotic use. All candidate outcomes were then rated anonymously by members of the MWG on a 9-point rating scale according to their importance for decision-making. Outcomes rated as critical for decision-making (mean score 7–9) were included in the literature search. The general outcomes and complication-related outcomes of further interest are summarised in and . These outcomes were subsequently incorporated into the search strategy for the respective PICO questions.

For each PICO question, search terms were developed by the MWG and ESO methodologist (SH). Where a validated search strategy was available, this was used or adapted. Where there was a recent relevant systematic review on the question of interest, the corresponding search strategy and results were used and updated as necessary. Search strategies are described in . The search was performed by the ESO Guideline methodologist (SH). The following databases were searched: Medline and EMBASE from 1946 to February 2023. Reference lists of review articles, the authors’ personal reference libraries and updated non-structured searches were also done up to March 2026. Search results were loaded into the web-based Covidence platform (Health Innovation, Melbourne, Australia) for assessment by the MWG. Two or more MWG members were assigned to independently screen the titles and abstracts of publications registered in Covidence and then assess the full text of studies determined to be potentially relevant. All disagreements were resolved by discussion between the 2 reviewers or by a third MWG member. We prioritised fully published RCTs; where data were limited, we also considered health registry analyses, large observational studies and systematic reviews or meta-analyses. Only studies in humans were included, while conference abstracts without full publication and animal studies were excluded.

Data extraction and analysis was performed by the MWG members and ESO methodologist (AP). Where appropriate, random-effects meta-analyses (Mantel–Haenszel method) were conducted using Review Manager (RevMan) online or MedCalc software. Results were presented as estimates of effect with associated 95% CIs (Wald method). Statistical heterogeneity across studies was assessed using the tau 2 statistics (DerSimonian and Laird method) and I 2 statistic, and classified as moderate (≥30%), substantial (≥50%) or considerable (≥75%). Funnel plot or Eggers test were used for the assessment of publication bias. , Where appropriate, subgroup analyses based on medication group were performed (PICO 7).

The risk of bias of each included randomised trial was assessed with the Cochrane Rob2 tool, observational studies by ROBINS-I and diagnostic accuracy with the PROBAST tool. The robvis tool was used for visualisation. As recommended, the evidence synthesis did not use a quality “score” threshold but classified overall risk of bias at study level and then in aggregate. The results of data analysis were imported into the GRADEpro Guideline Development Tool (McMaster University, 2015; developed by Evidence Prime, Inc.) For each PICO question, and each outcome, the following were considered: risk of bias based on the type of available evidence (randomised or observational studies); considerations on inconsistency of results; indirectness of evidence, imprecision of results and other possible bias. GRADE evidence profiles/summary of findings tables were generated and used to prepare recommendations. “Evidence-based Recommendations” were based on the GRADE methodology. The direction, strength and formulation of the recommendations were determined according to the GRADE evidence profiles and the ESO-SOP. ,

Finally, Expert Consensus Statements were added whenever the PICO group considered that there was insufficient evidence available to provide Evidence-based Recommendations and where practical guidance is needed for routine clinical practice. The Expert Consensus Statements were based on voting by all expert MWG members. Importantly, these Expert Consensus Statements should not be regarded as evidence-based recommendations, since they only reflect the opinion of the writing group.

Each PICO question was addressed in distinct sections, in line with the updated ESO SOP. First, “Analysis of current evidence” summarised current pathophysiological considerations followed by a summary and discussion of the results of the identified RCTs and other studies. Second, “Additional information” was added when more details on the studies referred to in the first section were needed to provide information on key subgroup analyses of the included studies, on ongoing or future RCTs, and on other studies which can provide important clinical guidance on the topic. Third, an “Expert consensus statement” paragraph was added whenever the MWG considered that insufficient evidence was available to provide evidence-based recommendations for situations in which practical guidance is needed for everyday clinical practice. The Guideline document was reviewed several times by all MWG members and modified using a Delphi approach until consensus was reached.

In hospitalised adults with acute ischaemic or haemorrhagic stroke (non-ventilated) within 7 days of stroke symptom onset, does use of any standardised diagnostic criteria for SAP, compared to non-standardised clinician-based diagnosis, improve clinical outcomes?

In hospitalised adult patients with acute ischaemic or haemorrhagic stroke (non-ventilated) there is continued uncertainty over the most accurate approach for diagnosing SAP, because of the lack of a validated gold standard.

The PISCES group proposed a pragmatic approach recommending the use of adapted Centers for Disease Control and Prevention (CDC) criteria for the diagnosis of SAP. Probable SAP is defined as fulfilment of the CDC criteria without typical chest X-ray findings despite repeated imaging, whereas confirmed SAP requires fulfilment of the CDC criteria including typical chest X-ray changes.

In a secondary analysis of the multicentre STROKE-INF randomised trial, the diagnostic utility of an algorithm-defined approach to pneumonia, compared to physician-diagnosed pneumonia, was evaluated in 1088 patients within 14 days of stroke onset. The algorithm-defined diagnosis was based on CDC criteria and performed by the study statistician independent of treating physicians at trial centres. Adjudicated diagnosis of pneumonia by 2 independent experts was used as the reference standard when there was discrepancy between the physician and algorithm-defined diagnosis. Physician-diagnosed pneumonia occurred in 176 of 1088 (16%) and algorithm-defined pneumonia in 123 of 1088 (11.3%) patients. Diagnosis was concordant in 885 of 1088 (81.3%) patients (κ 0.22, 95% CI, 0.14–0.29). On a blinded review, 129 of 1088 (11.8%) patients were adjudicated as having pneumonia. The algorithm (97%, 95% CI, 96–98) and the physician diagnosis (90%, 95% CI, 88–92) both had high specificity, but only moderate sensitivity ((72%, 95% CI, 64–80) and (65%, 95% CI, 56–73), respectively) in diagnosing pneumonia. The algorithm-defined approach had better positive predictive value (PPV; (76%, 95% CI, 67–83) vs (48%, 95% CI, 40–55)), diagnostic OR ((80, 95% CI, 42–136) vs (18, 95% CI, 12–27)) and agreement ((κ 0.70, 95% CI, 0.63–0.78) vs (0.48, 95% CI, 0.41–0.54)) than physician diagnosis with adjudicated pneumonia. These findings illustrate that physician diagnosis, and algorithm-based approaches are very good at excluding patients who do not have post-stroke pneumonia (<5% false-negative rate). Both the physician diagnosis and algorithm-defined approach over-diagnosed pneumonia, although the algorithm-defined approach had greater diagnostic utility. However, these different diagnostic approaches were not related to clinical outcomes.

In hospitalised adults with acute ischaemic or haemorrhagic stroke (non-ventilated) within 7 days of stroke symptom onset, does use of chest ultrasound or computed tomography to diagnose SAP, compared to chest X-ray alone, increase diagnostic accuracy and improve clinical outcomes?

An observational study aimed to evaluate the diagnostic accuracy of chest X-ray (CXR) in the setting of SAP and the use of pulmonary computed tomography (CT) as a reference standard for final diagnosis. The study found that CXR had limited diagnostic value in clinically suspected SAP when using pulmonary CT as a diagnostic reference standard. Only 13 out of 40 CXRs (32.5%) were reported as suggestive of pneumonia by the independent thoracic radiologist, while pulmonary CT confirmed pneumonia in only 12 out of 35 patients (34%). Compared to the pulmonary CT reported by the independent thoracic radiologist as the reference standard for diagnosis of SAP, CXR had a sensitivity of 58.3%, a specificity of 73.9%, a PPV of 53.8%, a negative predictive value (NPV) of 77.2%. The inter-rater reliability of reported CXR interpretation of pneumonia between the local radiologists and independent thoracic radiologist was moderate ( k = 0.42), while the inter-rater reliability for CXR diagnosis of pneumonia between the 4 stroke physicians (independent thoracic radiologist as standard) was weak ( k = 0.35). The utility of CXR or CT was not related to outcome, and the interpretation was limited by relatively small numbers and lack of external validation.

Another observational study aimed to evaluate lung ultrasound (US) in 70 patients with clinically suspected pneumonia occurring after stroke. This study is discussed here rather than under the analysis of current evidence, as no performance metrics were reported to assess the diagnostic accuracy of CXR compared with lung US. Pneumonia was adjudicated using standardised CDC-based criteria, although the interval of pneumonia following stroke onset was not defined. Lung US and CXR were both undertaken within 24 hours of onset of the clinical manifestation of pneumonia, and a non-contrast pulmonary CT was planned only if the CXR or lung US were inconclusive. CXR was negative for signs of pneumonia in 44 (63%). Lung US and CXR were concordant in 42 out of 63 cases, 66.7 % ( P = .001). Pulmonary CT was only performed in 9 of 21 patients where there was disagreement between lung US and CXR, but in this situation always confirmed lung US results. However, the reference standard was unclear and diagnostic accuracy for CXR or lung US was not reported (). Accordingly, there are currently no specific recommendation supporting its use in acutely unwell stroke patients.

In hospitalised adults with acute ischaemic or haemorrhagic stroke (non-ventilated) within 7 days of stroke symptom onset, does incorporation of any diagnostic (blood) biomarker, compared to not making use of diagnostic (blood) biomarkers, increase diagnostic accuracy and improve clinical outcomes? Improved diagnostic accuracy may influence clinical decision-making, particularly with regard to the timely initiation of antibiotic therapy, and may thereby impact downstream outcomes such as infection control. Importantly, as SAP is associated with increased mortality and morbidity after stroke, more accurate and timely diagnosis may also contribute to improved survival and functional recovery. In this context, the incorporation of biomarkers into diagnostic algorithms may be helpful in enhancing diagnostic performance.

In the study “Ex vivo synthesized cytokines as a biomarker of stroke-associated pneumonia,” 20 out of 279 patients (7%) prospectively recruited patients with ischemic stroke had a diagnosis of SAP. Patients with SAP exhibited lower ex vivo release of blood TNFα, IL-1β, IL-12, IP-10, and higher levels of circulating IL-6 compared to those without pneumonia. Specifically, the odds ratios for pneumonia were 0.27 (95% CI, 0.11–0.65) for TNFα, 0.31 (95% CI, 0.14–0.67) for IL-1β, 0.06 (95% CI, 0.01–0.33) for IL-12, 0.11 (95% CI, 0.03–0.47) for IP-10 and 2.02 (95% CI, 1.45–2.79) for plasma IL-6 in univariate logistic regression. In multivariate analysis, cytokines with P -values below 0.1 included ex vivo IL-12 (OR 0.09, 95%CI, 0.01–0.75), IP-10 (OR 0.32, 95% CI, 0.09–1.13) and plasma IL-6 (OR 1.70, 95% CI, 1.18–2.45). The multimarker score comprising IL-12, IP-10 and IL-6 showed good sensitivity (0.89) and specificity (0.88) for SAP, outperforming individual cytokines (). These findings suggest the potential of cytokines as biomarkers for early detection of SAP, emphasising the importance of a multimarker approach for improved diagnostic accuracy and patient care. However, these cytokines were not related to clinical outcomes and the clinical value of assessment of ex vivo cytokine production from blood samples remains unclear.

In a secondary analysis of the single centre MAPS (metoclopramide to prevent pneumonia in stroke patients fed via nasogastric tubes) randomised trial, plasma C-reactive protein (CRP) was evaluated as a diagnostic biomarker for development of pneumonia up to 21 days after stroke onset in 60 dysphagic patients with acute ischaemic or haemorrhagic stroke. Post-stroke pneumonia was diagnosed in 33 patients (44 episodes) using modified British Thoracic Society criteria, with a median (IQR) interval from stroke onset to the first pneumonia of 3.5 days (3.0–5.0 days). For patients with no incident pneumonia, the mean of all available CRP values over the first week was used, whereas the CRP value on the day of, or the closest to the day of, the diagnosis of pneumonia was used in patients with confirmed pneumonia. The area under the ROC curve for CRP was 0.83 (95% CI, 0.72–0.93). The diagnostic cut-off for CRP with an acceptable sensitivity (>0.8) was 25.6 mg/L (Youden index (J) 0.52; sensitivity 0.85; specificity 0.67). A cut-off of 64.7 mg/L had the highest diagnostic accuracy (J 0.56; sensitivity 0.64; specificity 0.93). A CRP cut of ≥40 had an acceptable sensitivity of 0.69 and a specificity of 0.75. In summary, CRP could be a useful biomarker in diagnosing SAP with different cut-off values offering trade-offs between sensitivity and specificity but needs further evaluation of utility and external validation.