Predictive role of lung ultrasound score for mortality risk of patients with severe pneumonia: a systematic review and meta-analysis

Introduction

Severe pneumonia remains a major cause of critical illness and death worldwide. Global estimates show that lower respiratory infections continue to cause a large number of deaths each year, with particularly high mortality among older adults and patients requiring intensive care; reported in-hospital and intensive care unit (ICU) mortality for severe pneumonia and acute respiratory distress syndrome (ARDS) may reach upward of 20–40% depending on pathogen and comorbidity profiles (1,2). Clinical prognosis and treatment decisions in severe pneumonia currently rely on a combination of physiologic severity scores (e.g., APACHE II, SOFA, CURB-65), gas-exchange indices (PaO₂/FiO₂ or SpO₂/FiO₂), radiologic assessment, and laboratory biomarkers such as procalcitonin and C-reactive protein; these tools provide useful risk stratification but have only moderate discriminatory power and—particularly for bedside, repeatable risk assessment—practical limitations in critically ill or resource-limited settings (3-5).

Lung ultrasound score (LUS) is a semi-quantitative bedside tool that assesses global lung aeration by scanning standardized lung zones and summing region scores reflecting A-lines, B-lines, consolidations and pleural abnormalities; it is increasingly used for diagnosis, monitoring and ventilatory management in acute respiratory failure and pneumonia because it is radiation-free, repeatable, and can be performed at the point of care (6,7). Evidence accumulated in recent years indicates that LUS often outperforms chest X-ray for detecting consolidation/effusion and has prognostic value in various acute lung diseases [including coronavirus disease 2019 (COVID-19) and ARDS], while offering particular advantage when computed tomography (CT) is impractical or unsafe in unstable patients (8-10). However, although several single-center cohorts and small observational studies have reported associations between higher LUS and worse outcomes, the prognostic accuracy of LUS specifically for predicting mortality in patients with severe pneumonia—its pooled sensitivity, specificity, and overall discriminatory performance—remains incompletely defined.

Thus, we performed the present meta-analysis to quantitatively synthesize available evidence and clarify the value of LUS for mortality risk stratification in severe pneumonia. We present this article in accordance with the PRISMA reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0112/rc) (11).

Methods

Literature search

PubMed, Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases were searched up to November 13, 2025 with following terms: lung ultrasound score, LUS, severe pneumonia, mortality and death. Detailed search strategies in above databases were shown in Appendix 1. MeSH terms and free texts were applied during the searching process.

Study selection

Studies meeting following criteria were included: (I) patients were diagnosed with severe pneumonia according to established clinical guidelines adopted in the original studies, including national or international criteria incorporating clinical severity, respiratory failure, or need for intensive care support (12-14); (II) the LUS was evaluated based on previously published formula after the diagnosis of severe pneumonia (15,16); (III) studies investigating the association between LUS and mortality risk or diagnosis role of LUS for mortality risk among patients with severe pneumonia; (IV) relevant data were reported and available; (V) available full texts; (VI) studies were published in English or Chinese.

Studies meeting following criteria were excluded: (I) letters, editorials, case reports, animal trials or meeting abstract; (II) insufficient, overlapped or duplicated data.

Data collection

We extracted the following information from included studies: first author, country, year, study design (retrospective vs. prospective), sample size, number of deaths, age, pathogen classification, combined disease and cutoff value of LUS. For studies investigating the relationship between LUS and risk of mortality in severe pneumonia, odds ratios (ORs) with 95% confidence intervals (CIs) were collected. For diagnostic studies, the number of patients who were true positive (TP), false positive (FP), false negative (FN) and true negative (TN) was extracted, as well as the area under the curve (AUC), sensitivity and specificity.

Quality evaluation

For cohort studies, methodological quality was evaluated by the Newcastle-Ottawa Scale (NOS), and studies with NOS scores ≥6 were defined as high-quality studies (17). For diagnostic studies, we assessed the methodological quality of the included studies using the QUADAS-2 tool, which evaluates four domains: patient selection, index test, reference standard, and flow and timing. Each domain was judged for risk of bias, and the first three domains were additionally assessed for applicability concerns. All evaluations were performed using Review Manager 5.4 (18).

Literature screening, study selection, data extraction, and quality assessment were independently performed by two reviewers, and any disagreements were resolved through discussion until consensus was reached.

Statistical analysis

For the association between LUS and mortality risk of severe pneumonia patients, all analyses were performed by STATA version 17.0 software. Heterogeneity between studies was calculated by the Q test and I² statistic. When significant heterogeneity was detected, represented as I²>50% and/or P<0.1, the random effects model was used; otherwise, the fixed effects model was applied (19). ORs with 95% CIs were combined to assess the relationship between LUS and the risk of mortality. Subgroup analyses were predefined based on clinically and methodologically relevant factors, including study design, country, age group, and pathogen type, which are known to influence disease severity, ultrasound practice, and outcome assessment. These analyses were conducted to explore potential sources of heterogeneity rather than to generate post-hoc hypotheses.

Then we explored the diagnostic role of LUS for risk of mortality among patients with severe pneumonia. Evidence from eligible studies was synthesized through both qualitative description and quantitative pooling. For each study, we extracted or reconstructed the corresponding 2×2 contingency data based on the reported diagnostic parameters to calculate unified effect estimates. Study characteristics were summarized narratively to facilitate methodological comparison and identify potential sources of variability. A formal diagnostic meta-analysis was then conducted to obtain pooled sensitivity, pooled specificity, and the summary receiver operating characteristic (SROC) curve. Forest plots were generated, and a random-effects model was applied to account for between-study heterogeneity. The diagnostic OR (DOR) for each study was calculated using the extracted contingency values, and overall diagnostic performance was assessed through SROC modeling. All statistical analyses were performed using Meta-DiSc 2.0, a freely accessible web-based platform for diagnostic test meta-analysis (20,21).

In this meta-analysis, our primary aim was to evaluate the prognostic utility of LUS as a single score rather than to synthesize multivariable prognostic models. Because most included studies did not report comparable AUC or c-statistic data, effect ORs and diagnostic accuracy measures (sensitivity, specificity, and DOR) were used for quantitative synthesis.

Results

Literature selection

A total of 358 records were searched from databases and 32 duplicated publications were excluded. Then we reviewed the titles, abstracts and full articles, 13 available studies were eventually included (22-34) (Figure 1).

Figure 1 PRISMA flow diagram of this meta-analysis.

Basic characteristics

Among 13 included studies, 962 patients were included and 337 patients died with the mortality rate of 35.03%. Eleven studies and six studies explored the diagnostic performance of LUS for mortality risk and association of LUS with mortality risk among severe pneumonia patients, respectively. Besides, most studies were retrospective (10/13), focused on adults (12/13) and from China. Mortality outcomes were defined as reported in the original studies, most commonly including in-hospital or short-term mortality. The quality of six cohort studies identifying the association of LUS with mortality risk was evaluated by NOS tool and all the six studies were with high-quality. Then the risk of bias and applicability concerns of 11 diagnostic studies were assessed by the QUADAS-2 tool and the specific information is presented in Figure 2 (Table 1).

Figure 2 Risk of bias and applicability concerns summary of diagnostic accuracy of studies using the QUADAS-2 tool.

Association between LUS and mortality risk of patients with severe pneumonia

Six studies explored the relationship of LUS with risk of mortality among severe pneumonia patients. Pooled results demonstrated that elevated LUS was significantly associated with increased risk of mortality (OR =1.79, 95% CI: 1.23–2.61, P=0.003; I²=86.0%, P<0.001) (Figure 3).

Figure 3 The association between lung ultrasound score and mortality risk of patients with severe pneumonia. CI, confidence interval; OR, odds ratio.

Then we performed the subgroup analyses by the country (non-China: OR =12.07, 95% CI: 1.97–74.08, P=0.007; China: OR =1.59, 95% CI: 1.12–2.24, P=0.009) (Figure S1A), study design (prospective: OR =4.07, 95% CI: 0.49–34.18, P=0.20; retrospective: OR =1.93, 95% CI: 1.15–3.24, P=0.01) (Figure S1B) and pathogen classification (COVID-19: OR =12.07, 95% CI: 1.97–74.08, P=0.007; mixed: OR =1.59, 95% CI: 1.12–2.24, P=0.009) (Figure S1C), which further manifested the significant association between LUS and mortality risk of patients with severe pneumonia (Table 2).

Diagnostic accuracy of LUS for mortality risk of patients with severe pneumonia

Eleven studies explored the diagnostic role of LUS for risk of mortality among severe pneumonia patients. After combining all diagnostic studies, the pooled sensitivity and specificity was 84% (95% CI: 0.77–0.89) and 78% (95% CI: 0.72–0.83), with the positive likelihood ratio (LR+), negative likelihood ratio (LR–) and false positive rate (FPR) of 3.78 (95% CI: 3.04–4.72), 0.21 (95% CI: 0.15–0.29) and 0.22 (95% CI: 0.17–0.28). Detailed data for the sensitivity and specificity of each study and SROC curve is shown in Figure 4. Meanwhile, the DOR was detected to be 18.28 (95% CI: 12.24–27.3). Information of heterogeneity analysis was presented in Table 3.

Figure 4 Forest plots of sensitivity (A) and specificity (B) and summary receiver operating curve (C) of all included diagnostic studies. CI, confidence interval; FN, false negative; FP, false positive; ROC, receiver operating curve; SROC, summary receiver operating curve; TN, true negative; TP, true positive.

Then we conducted subgroup analysis. For retrospective studies, the pooled sensitivity, specificity, DOR, LR+, LR− and FPR were 82% (95% CI: 0.75–0.87), 79% (95% CI: 0.73–0.84), 16.28 (95% CI: 10.88–24.36), 3.83 (95% CI: 3–4.89), 0.24 (95% CI: 0.18–0.32) and 0.21 (95% CI: 0.16–0.27), with detailed information in the Figure S2. After combining Chinese studies, the pooled sensitivity, specificity, DOR, LR+, LR− and FPR were 82% (95% CI: 0.74–0.87), 78% (95% CI: 0.72–0.84), 16.18 (95% CI: 10.6–24.71), 3.78 (95% CI: 2.94–4.86), 0.23 (95% CI: 0.17–0.32) and 0.22 (95% CI: 0.16–0.28) and specific information was shown in Figure S3. Besides, for studies focusing on adults, the pooled sensitivity, specificity, DOR, LR+, LR− and FPR were 85% (95% CI: 0.77–0.9), 77% (95% CI: 0.7–0.82), 17.96 (95% CI: 11.57–27.88), 3.6 (95% CI: 2.89–4.48), 0.2 (95% CI: 0.14–0.29) and 0.24 (95% CI: 0.18–0.3) (Figure S4).

Therefore, according to above results, it was demonstrated that LUS had a high diagnostic accuracy for mortality risk of patients with severe pneumonia.

Discussion

In this meta-analysis of 13 studies including 962 patients with severe pneumonia, we found that elevated LUS were significantly associated with an increased risk of mortality, with a pooled OR of 1.79. Furthermore, the pooled diagnostic analysis of 11 studies demonstrated that LUS has high accuracy for predicting mortality, with a sensitivity of 84%, specificity of 78%, and a DOR of 18.28. Subgroup analyses by country, study design, patient age, and pathogen type consistently supported these findings, indicating the robustness and generalizability of LUS as a prognostic tool. Collectively, these results suggest that LUS is not only significantly correlated with adverse outcomes in severe pneumonia but also provides reliable diagnostic performance for early risk stratification, reinforcing its potential clinical utility in guiding bedside decision-making for critically ill patients. Notably, the direction and magnitude of the association between higher LUS and mortality remained consistent across multiple subgroup analyses and random-effects modeling, supporting the robustness of the main findings despite underlying heterogeneity.

Severe pneumonia is associated with high morbidity and mortality, and early identification of patients at high risk of death is critical for timely interventions and allocation of intensive care resources. Traditional prognostic tools, such as APACHE II, SOFA, and laboratory biomarkers, provide some guidance but often lack real-time, bedside applicability, and may not reflect rapid changes in lung pathology (35,36). Clarifying the predictive value of LUS for mortality allows clinicians to stratify patients more accurately, prioritize high-risk patients for advanced monitoring or therapy, and potentially improve clinical outcomes through earlier interventions (6,7).

The ability of LUS to predict mortality in severe pneumonia likely stems from its direct assessment of lung aeration and detection of pathophysiological changes associated with disease severity. LUS quantifies loss of aeration due to alveolar consolidation, interstitial edema, and pleural effusion, which are closely linked to impaired gas exchange, hypoxemia, and progression to respiratory failure (37,38). Studies have shown that higher LUS correlates with lower PaO₂/FiO₂ ratios, increased need for mechanical ventilation, and higher inflammatory burden, all of which are established predictors of poor outcomes in severe pneumonia (37,38). Additionally, LUS can detect early subclinical changes in lung morphology that are not always apparent on chest radiography, providing a sensitive indicator of disease progression (38).

From a clinical perspective, LUS and its dynamic changes can be used for bedside monitoring and guiding treatment strategies in severe pneumonia. Serial LUS assessments allow for timely evaluation of therapeutic responses, such as improvement in aeration following antibiotics, diuretics, or ventilatory support (39,40). For instance, an increasing LUS may prompt escalation of care, including intensified oxygen therapy or early ICU transfer, while decreasing scores may support de-escalation and facilitate safe weaning from mechanical ventilation (41). Furthermore, integration of LUS with other bedside parameters, such as hemodynamics and inflammatory markers, can provide a comprehensive, non-invasive approach for continuous risk assessment and personalized management (42,43). Overall, these applications underscore the potential of LUS to improve clinical decision-making and optimize outcomes in patients with severe pneumonia.

Compared with conventional prognostic tools such as APACHE II, SOFA, and laboratory markers (e.g., PaO₂/FiO₂, C-reactive protein, procalcitonin), LUS offers several distinct advantages in the management of severe pneumonia. Traditional scoring systems provide valuable risk stratification but are often limited by their reliance on static measurements, complex calculations, or laboratory availability, and they may not reflect rapid changes in pulmonary status (35,36). In contrast, LUS provides real-time, bedside assessment of lung aeration and consolidation, allowing clinicians to capture dynamic changes in pulmonary pathology that precede alterations in physiological or laboratory parameters (6). Moreover, integrating LUS with conventional scores can enhance prognostic accuracy, as combined evaluation incorporates both systemic severity and direct pulmonary assessment, potentially improving the identification of high-risk patients and guiding individualized interventions (38,44). Therefore, LUS should be considered a complementary tool rather than a replacement for traditional indices, offering an immediate, non-invasive, and radiation-free method to monitor disease progression, evaluate treatment response, and optimize clinical decision-making in critically ill patients with severe pneumonia.

It should be noted that heterogeneity existed among included studies in terms of LUS scoring protocols, including the number of lung zones examined, scoring ranges, cutoff values, and timing of assessment, which may have contributed to between-study heterogeneity. However, despite these methodological differences, higher LUS consistently reflected greater loss of lung aeration and was significantly associated with increased mortality risk across studies and subgroup analyses. These findings suggest that the prognostic value of LUS is robust across different scoring schemes, although future studies with standardized protocols are warranted.

There were some limitations in this meta-analysis. First, the overall sample size was relatively small and most studies were from China, which would cause some bias. Second, the heterogeneity was significant. However, the potential sources of heterogeneity were not well identified by the subgroup analysis. Third, due to lack of original data, it was unable to conducted more specific subgroup analyses by other important parameters such as the sex and treatment strategy. Four, the cutoff values of LUS used to predict mortality varied considerably across the included studies. This variability likely reflects differences in LUS scoring systems, patient populations, disease severity, and timing of ultrasound assessment, which may limit the direct comparability of diagnostic accuracy estimates and preclude identification of an optimal universal cutoff. Therefore, although LUS demonstrated stable prognostic performance across studies, future large-scale prospective studies are needed to establish standardized cutoff values for clinical risk stratification. In addition, mortality outcomes were defined using different time horizons (e.g., in-hospital or short-term mortality), which may have further contributed to between-study heterogeneity.

Conclusions

This meta-analysis demonstrates that higher LUS are significantly associated with an increased risk of mortality among patients with severe pneumonia. The pooled diagnostic performance indicates that LUS provides acceptable sensitivity, specificity, and overall discriminatory ability for predicting adverse outcomes. These findings confirm that LUS is a valuable noninvasive tool for early risk stratification in severe pneumonia. Beyond these results, the study highlights the clinical value of incorporating LUS into routine bedside assessment, as it may facilitate timely clinical decision-making and optimize resource allocation, particularly in critically ill patients.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the PRISMA reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0112/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0112/prf

Funding: This research was funded by the National Major Science and Technology Project (No. 2023ZD0501804).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0112/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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