Lung histopathologic clusters in severe COVID-19: a link between clinical picture and tissue damage

SARS-CoV-2 infection causes a systemic disease, namely coronavirus 2019 disease (COVID-19), with multiple organ involvement [1‐3]. However, the respiratory system is undoubtedly the main viral target, hence the name “severe acute respiratory syndrome,” and lung injury is the leading cause of death.

From the onset of the pandemic, some studies have described the postmortem findings, aiming at unveiling the characteristics and evolution of pulmonary alterations and their role in the pathogenesis of this complex condition. Autoptic findings usually reveal variable degrees of diffuse alveolar damage (DAD): Acute-phase DAD (during the first week after the pulmonary injury) usually shows exudative features with interstitial widening, formation of intra-alveolar edema, thickened alveolar septa, and perivascular lymphoplasmacytic infiltration, while in late-phase (one to several weeks) DAD proliferative features prevail with pneumocyte hyperplasia inducing interstitial thickening and collapsed alveoli, which may finally develop into organizing patterns (weeks to months), with marked fibroblastic proliferation and fibrosis, sometimes even leading to squamous metaplasia [4‐8]. Even though the DAD pattern is not found exclusively in COVID-19, exudative or proliferative DAD development is a key pathophysiological mechanism in lung injury induced by SARS-CoV-2.

The characteristics of DAD evolve during the disease course. However, there may be high spatial and temporal heterogeneity, since features which can be usually found in the acute phase may coexist with features of the late phase and the relative extension of each pattern may be highly variable [4‐8].

Besides damage of epithelial cells, SARS-CoV-2 has been proved to cause vascular alterations, with virions identified in the endothelial cells and hyperpermeability due to disruption of inter-endothelial junctions [4]. Endothelialitis, due to direct damage by SARS-CoV-2 and to multiple factors such as local/systemic inflammatory response and hypoxia, also leads to switching to a procoagulant phenotype of injured endothelial cells. Hence, it promotes the so-called immunothrombosis, leading to macrothrombosis (e.g., pulmonary embolism) and microthrombosis, often detected in autoptic samples [9‐13]. These mechanisms are crucial in the immunopathogenesis of respiratory failure, which characterizes severe COVID-19.

Although autoptic pulmonary findings have already been described [8], there is still a significant dearth of knowledge on the correlation between clinical data and histopathologic pulmonary damage in patients who died from severe COVID-19.

This study aims to investigate the relationship between clinical–biochemical–radiological characteristics and histopathologic features in patients hospitalized for severe SARS-CoV-2 infection.

This was a retrospective cohort observational study on consecutive patients who died from COVID-19 between February 29 and June 30, 2020, whose autopsies were conducted by the Pathology Unit at Luigi Sacco Hospital in Milan, the referral center for highly transmissible diseases in northern Italy.

In the study period, 92 complete autopsies (24 females and 68 males) were conducted at our center. They represent all the autopsies carried out at the Pathology Unit of L. Sacco Hospital from February 29 to June 30, 2020. The flowchart of the studied population is summarized in Additional file 1: Fig. S1.

The full pulmonary examination was available only in 75 patients; in the remaining 17 cases, it was not possible to carry out a complete macroscopic examination of the lungs due to sampling problems. These cases were removed from the study. Forty-eight patients (64%), 44 from ICU (91.7%) and four (8.3%) from the medical ward, had complete clinical records. Among the patients without complete clinical data (n = 27), three (11.1%) died at home, six (22.2%) died in the emergency department, and 18 (66.7%) died in other hospitals (nine in ICU, eight in medical wards, one missing data). The prevalence of patients admitted to ICU was different between groups with and without clinical data (91.7% vs. 33.3%, p < 0.0001).

Clinical characteristics, main laboratory, and radiological findings are shown in Table 1 and Additional file 1: Table S1.

Macroscopically, the lungs showed a spectrum of alterations ranging from complete consolidation to near-normal parenchyma; most frequently, a given pulmonary lobe presented areas with different degrees of consolidation. Main histopathologic findings are shown in Figs. 1 and 2 and are summarized in Additional file 1: Table S2.

The extent and coexistence of patterns in each studied subject of the whole cohort are shown in Fig. 3.

The correlation analysis between clinical characteristics and histopathologic findings was conducted on 48 patients with available complete clinical records.

Exudative DAD had a weak correlation with length of stay (LOS) in hospital (r = − 0.399, p = 0.005), MV days (r = –0.304, p = 0.048), and PPVdays (r = − 0.35, p = 0.015). AFOP was revealed to have a weak correlation with LOS in ICU (r = 0.363, p = 0.015), MVdays (r = 0.353, p = 0.02), procalcitonin (r = 0.404, p = 0.005), worst serum albumin (r = − 0.335, p = 0.021), ferritin (r = 0.36, p = 0.034), total SOFA (r = 0.345, p = 0.016), and cPEEP_MV (r = 0.365, p = 0.017). Late proliferative DAD showed a correlation with LOS in hospital (r = 0.5, p < 0.001), LOS in ICU (r = 0.39, p = 0.009), PPVdays (r = 0.48, p = 0.001), MVdays (r = 0.48, p = 0.001), WBC count (r = 0.33, p = 0.022), cPEEP_PPV (r = 0.42, p = 0.004), and cPEEP_MV (r = 0.426, p = 0.004).

No significant correlation was found between clinical–biochemical–radiological parameters and early proliferative DAD or bronchopneumonia.

Thrombi had a positive correlation with CXR score (r = 0.409, p = 0.004) and IL-6 (r = 0.362, p = 0.049). Areas of normal lung were correlated with LOS in hospital (r = − 0.3, p = 0.038), PPVdays (r = − 0.369, p = 0.01), baseline serum albumin (r = 0.312, p = 0.031), worst serum albumin (r = 0.43, p = 0.008), cPEEP_PPV (r = − 0.373, p = 0.011), and cPEEP_MV (r = − 0.373, p = 0.015).

There was no correlation between histopathologic findings and intervals from (1) symptoms onset to hospitalization, (2) first non-respiratory symptoms to dyspnea onset, (3) CPAP to mechanical ventilation start, and (4) symptoms onset to mechanical ventilation start (Additional file 1: Fig. S2).

Five clusters were identified in the whole cohort of 75 autoptic examinations, and four clusters were also represented in the cohort of 48 patients with complete clinical data (Fig. 4a). The optimal number of clusters is shown in Additional file 1: Fig. S3. Cluster 4 consisted mainly of patients without clinical data in whom areas of normal lung were predominant. The main histopathologic features of different clusters are summarized in Table 2. As shown in Fig. 4b, cluster 3 was characterized by a high prevalence of both early DAD and late proliferative DAD compared to the other clusters.

LOS in hospital (p < 0.0001), LOS in ICU (p < 0.0001), PPVdays (p < 0.0001), mPEEP_TOT (p = 0.007), MVdays (p < 0.0001), cPEEP_PPV (p = 0.003), cPEEP_MV (p = 0.003), worst serum albumin (p = 0.017), IL-6 (p = 0.047), and Kidney SOFA (p = 0.001) were different among clusters (Fig. 5). The major differences were detected in the duration of hospitalization and positive-pressure ventilation (PPV or MV) between cluster 3 and the others. Intervals from (1) symptoms onset to hospitalization, (2) first non-respiratory symptoms to dyspnea onset, (3) CPAP to mechanical ventilation start, (4) symptoms onset to mechanical ventilation start did not differ between clusters (Additional file 1: Fig. S4). An overview of histopathologic and clinical characteristics of clusters is shown in Fig. 6.

Among the pharmacological treatments shown in Table 1, only steroid use was associated with cluster 3 (p = 0.04). Moreover, a history of cardiovascular disease was also associated with cluster 3 (p = 0.023). At the multiple variable analysis, age, worst serum albumin, mPEEP_TOT, and PPVdays were fitted into the generalized linear model as continuous covariates, steroid treatment as binomial covariate, and cluster 3 (yes/no) as dependent variable. As a result, only mPEEP_TOT and PPVdays, with interaction effect, were significant (Table 3).

Survival curves were different between cluster 3 and the other clusters (LOS in hospital 33 [25.5–41.7] vs. 15 [10.2–20] days, p < 0.0001) (Fig. 7). Kaplan–Meier curves of clusters are shown in detail in Additional file 1: Figs. S5 and S6.

Finally, five patients on 75 autopsies also had invasive aspergillosis (Additional file 1: Fig. S7).

The contribution of postmortem studies to our knowledge of the pathology underlying the clinical picture in COVID-19 is undeniable, and the topic is still under investigation. We found that some clinical parameters and, of particular interest, the long-lasting application of positive pressure to the patients’ airways are correlated with specific clustered histopathologic findings. Interestingly, the intensity and the duration of positive-pressure ventilation were associated both with exudative DAD and late proliferative DAD; consistently, a negative correlation of the same parameters with areas of normal lung has been found.

Since the first case series, efforts have been made to gather available studies and try to elaborate hypotheses on potential unifying pathophysiological mechanisms [22]. However, most of these studies focus on pathology and suffer from the lack of data on clinical-laboratory and imaging findings, so that they do not allow to get insights or at least valuable inputs on their possible links.

Indeed, confounding factors may be several in such a complex clinical scenario, and detecting straightforward causal relationships, discriminating the net impact of each player, seems impossible. Although different histopathologic findings are known to vary according to the time course of COVID-19 progression, our results suggest that temporality is not the only (and possibly not even the main) factor that shows a correlation with the development of lung injury. In fact, our results highlight that it is possible to discriminate different clinical courses (thus including treatments applied), which are associated with a variable mix of histopathologic findings, probably due to the impact of a variable mix of complex underlying pathophysiological mechanisms, often acting simultaneously, with a changing degree and duration.

In particular, the development of late proliferative DAD, which is characterized by collagen deposition, prevails in cluster 3, and it is correlated with prolonged treatment with positive-pressure ventilation.

It has been demonstrated that SARS-CoV-2 directly damages both endothelial and epithelial cells in lung tissue [23]. Our group also described damage of both type II pneumocytes and endothelial cells, with intracytoplasmic virions and disruption of adherens junctions, in patients who died for COVID-19 [24]. Our study suggests that even the length of exposure to physical stressors, such as prolonged use of positive pressure, correlates with advanced DAD stages with fibroproliferative features and markedly reduced normal areas.

Interestingly, the significant correlation between serum albumin and both AFOP and areas of normal lung corroborates the likely link between hypoalbuminemia and alterations of endothelial permeability [24].

The correlation between thrombi and chest X-ray score as well as IL-6 values reveals that patients with more compromised interstitial patterns and more pronounced inflammatory response are at higher risk of developing thrombotic complications, in line with the "immunothrombosis" hypothesis [11, 25].

Severe COVID-19 is characterized by a marked hyperinflammatory response resulting in a cytokine storm, with dysregulated production of proinflammatory cytokines (e.g., IL-1β and IL-6), resulting in significant lymphopenia, C-reactive protein increase, and a profound vascular dysfunction. Both direct and immune-mediated endothelial injury may act as procoagulant triggers, resulting in hypercoagulability and thromboinflammation, which lead to intra-alveolar activation of coagulation and thrombin generation [26]. The extensive endothelial damage is marked by increased D-dimer levels and increased incidence of venous thrombosis and pulmonary thromboembolism [27]. In fact, postmortem findings of COVID-19 patients revealed diffuse alveolar damage with severe capillary congestion, thrombosis of pulmonary capillaries, small arteries < 1 mm, midsized arteries, and pulmonary thromboembolism suggesting systemic endothelial dysfunction [4, 28]. These features may explain the peculiar mechanoelastic properties of the respiratory system in COVID-19 ARDS, which at presentation is characterized by higher compliance than other kinds of ARDS [29]. Interestingly, we did not find any significant correlation between peak airway pressure or elevated D-dimer and C-reactive protein levels and specific histopathologic findings in our series. However, cumulative PEEP during the hospital stay was positively correlated with late proliferative DAD and it was higher in cluster 3, which was characterized by prevailing early and late proliferative DAD.

These findings could be explained by the relevance not only of the inflammatory (and procoagulant) macro- and microenvironment per se at baseline, but also of the prolonged interplay of such inflammatory factors with protracted exposure to positive pressures and mechanical ventilation (the latter carrying benefits but also potentially harmful effects on lung tissues).

It is intriguing that patients who died soon after the onset of respiratory failure showed a trend to more diffuse areas of normal lung, probably due to less prolonged exposure to the cytokine storm and therapeutic interventions such as positive-pressure and mechanical ventilation. The significantly lower representation of proliferative DAD in these rapidly worsening patients is consistent with results obtained from antemortem lung biopsies [30]. Furthermore, we found a positive correlation between steroid use and cluster 3 at the univariate analysis. This result is unexpected and elicits several considerations and hypotheses: A selection bias cannot be excluded. During the first pandemic wave, this treatment did not still represent the “standard of care” and was often administered as rescue therapy in very compromised patients. Moreover, the low fraction of patients who received steroids (29.2%) and a non-standardized use of such therapy (as regards timing and dose) during the first COVID-19 outbreak should be taken into consideration when interpreting these correlations. Therefore, these results require further confirmation.

Clustering allowed us to highlight the correlation between clinical variables and complex histological pictures deriving from a variable mix of each pattern (e.g., overlap between exudative DAD and features of AFOP), which contributes to the severe distortion of lung architecture characterizing COVID-19.

This study has some limitations. Our findings derive from autopsies conducted during the first pandemic wave in Italy, when steroid use was inconstant and probably delayed in the course of the disease. However, the proportion of patients undergoing such a treatment strategy is not-negligible, and some patients (25%) who were not administered steroid treatment received tocilizumab, a therapeutic strategy that has been a matter of debate in severe COVID-19 and whose impact on lung tissues is still only partially understood. Nonetheless, we believe that we actually had the rare and precious opportunity to observe the clinical course of a new condition, with only a few confounding factors, which might have limited or blunted the complex inflammatory mechanisms which lead to initiation and development of the clinical–biochemical–radiological and histopathologic picture.

The choice of the optimal number of clusters is usually a difficult task. This is a crucial issue which has been matter of debate in the literature, and it is undeniable that the process of clustering may carry a certain degree of arbitrariness. However, when used with awareness of the source of data to be analyzed and their clinical meaning and value, clustering can be a powerful statistical tool, which allows to interpret the complexity of the clinical picture. In our study clustering resulted to be informative: The association between clusters and clinical features was strong and explained by plausible pathophysiological mechanisms.

Finally, our findings are based on postmortem findings: The histopathologic patterns of survivors (and possibly their correlation to the clinical picture) may show some dissimilarities from those of non-survivors.

Our results provide novel insights into the correlations between the clinical–biochemical–radiological picture and the histopathologic findings in patients with severe COVID-19. Therefore, they may prove helpful in deepening our awareness of the disease course, suggesting clues to the complexity of the underlying pathophysiological mechanisms.