6
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Changing COVID-19 outcomes in patients with rheumatic disease—are we really getting better at this?

      discussion
      a , b
      The Lancet. Rheumatology
      Elsevier Ltd.

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The COVID-19 pandemic has continued to impact the world, and we are now on track to exceed two million deaths worldwide. Patients with rheumatic disease were an immediate concern, but research to date has not convincingly suggested that having a rheumatic disease per se increases the risk of poor outcomes. Instead, poor outcomes seem to be driven by comorbidities and certain medications, such as chronic glucocorticoids and rituximab.1, 2 An important question to ask is whether we are getting better at treating COVID-19. In The Lancet Rheumatology, April Jorge and colleagues 3 address this by exploring temporal trends in patients with rheumatic disease, comparing an early cohort (Jan 20 to April 19, 2020) with a late cohort (April 20 to July 19, 2020). They used a large network of hospitals and health systems across the USA from the TriNetX database with over 8500 patients with rheumatic disease, and completed both an unmatched and matched analysis to try to reduce confounding factors. They found that the risk of hospitalisation for COVID-19 decreased in the late cohort compared with the early cohort (874 [32·4%] of 2701 patients vs 1227 [45·4%] of 2701 patients; relative risk [RR] 0·71, 95% CI 0·67–0·76). Outcomes such as intensive care unit admission, mechanical ventilation, kidney injury, and death were also reduced in the late cohort compared with the early cohort. Among those patients that were hospitalised for COVID-19, the risks of intensive care unit admission, mechanical ventilation, and death were lower in the later part of the pandemic compared with the earlier part of the pandemic (334 [30·7%] of 1089 patients vs 450 [41·3%] of 1089 patients; RR 0·74, 95% CI 0·67–0·83). These improvements mirror recent findings within the general population, with reductions in COVID-19 mortality during the later months of the pandemic compared with the first few months. 4 The strengths of this study include its large sample size and detailed patient information, including comorbidities. 3 The authors also did appropriate sensitivity analyses, such as restricting analyses to hospitalised patients and accounting for a washout period. What are some of the potential explanations for these findings? First, artefacts should be considered, such as expanded testing capacity detecting milder cases in the later months of the pandemic. There is also the potential for factors that were not captured in the analysis, such as background glucocorticoid dose and rheumatic disease severity and activity being unbalanced between the early period and the later period, to bias the outcomes. Additionally, it has been shown that those infected in the later part of the pandemic had a different risk profile, leading to differing background risks of poor outcomes. 5 Insufficient information about outcomes across facilities and geographies, which were not included in propensity score matching, raises the issue of health-care facility differences driven by resource availability or hospital overload. For example, hospitals that were overwhelmed at the start of the pandemic in April might have lowered their threshold for hospitalisation in June as a result of increased bed capacity. By not adjusting for such features, the findings might be explained by these epidemiological and health-care system factors. 6 Therapeutics have also changed over the course of the COVID-19 pandemic, with treatments being used in the later cohort that were not routinely used in the earlier cohort. Agents such as remdesivir and glucocorticoids have become the standard of care in many health-care settings and, as Jorge and colleagues 3 have pointed out, non-pharmacological treatment has also changed, including avoidance of mechanical ventilation in favour of non-invasive ventilation, 7 altering ventilation strategies, 8 prone positioning, 9 and anti-coagulation treatment. 10 It is unlikely that our acquired knowledge of specific risks in patients with rheumatic disease affected results, as comorbidities and therapies such as glucocorticoids and rituximab are difficult to alter in the short term, and in the absence of active infection the recommendations have been to not alter therapy. Therefore, clinical improvements in the treatment of COVID-19 might explain the differences in outcomes over time. It is difficult to determine how much of the improvement seen in Jorge and colleagues’ study is due to clinical factors, such as therapies and practices, versus a selection bias of patients in earlier cohorts compared with later cohorts. A key finding of this study is that use of historical controls might overestimate the effect of treatments. As the pandemic evolves and we continue to measure patient outcomes, it will be important to appropriately account for changes over time and place in longitudinal studies. So, on one hand we must remain vigilant to consider the limitations of outcome studies published during the pandemic, but on the other hand, be hopeful that we are making progress. © 2021 Shutterstock 2021 Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

          Related collections

          Most cited references8

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          COVID-19 pneumonia: different respiratory treatments for different phenotypes?

          The Surviving Sepsis Campaign panel recently recommended that “mechanically ventilated patients with COVID-19 should be managed similarly to other patients with acute respiratory failure in the ICU [1].” Yet, COVID-19 pneumonia [2], despite falling in most of the circumstances under the Berlin definition of ARDS [3], is a specific disease, whose distinctive features are severe hypoxemia often associated with near normal respiratory system compliance (more than 50% of the 150 patients measured by the authors and further confirmed by several colleagues in Northern Italy). This remarkable combination is almost never seen in severe ARDS. These severely hypoxemic patients despite sharing a single etiology (SARS-CoV-2) may present quite differently from one another: normally breathing (“silent” hypoxemia) or remarkably dyspneic; quite responsive to nitric oxide or not; deeply hypocapnic or normo/hypercapnic; and either responsive to prone position or not. Therefore, the same disease actually presents itself with impressive non-uniformity. Based on detailed observation of several cases and discussions with colleagues treating these patients, we hypothesize that the different COVID-19 patterns found at presentation in the emergency department depend on the interaction between three factors: (1) the severity of the infection, the host response, physiological reserve and comorbidities; (2) the ventilatory responsiveness of the patient to hypoxemia; (3) the time elapsed between the onset of the disease and the observation in the hospital. The interaction between these factors leads to the development of a time-related disease spectrum within two primary “phenotypes”: Type L, characterized by Low elastance (i.e., high compliance), Low ventilation-to-perfusion ratio, Low lung weight and Low recruitability and Type H, characterized by High elastance, High right-to-left shunt, High lung weight and High recruitability. COVID-19 pneumonia, Type L At the beginning, COVID-19 pneumonia presents with the following characteristics: Low elastance. The nearly normal compliance indicates that the amount of gas in the lung is nearly normal [4]. Low ventilation-to-perfusion (VA/Q) ratio. Since the gas volume is nearly normal, hypoxemia may be best explained by the loss of regulation of perfusion and by loss of hypoxic vasoconstriction. Accordingly, at this stage, the pulmonary artery pressure should be near normal. Low lung weight. Only ground-glass densities are present on CT scan, primarily located subpleurally and along the lung fissures. Consequently, lung weight is only moderately increased. Low lung recruitability. The amount of non-aerated tissue is very low; consequently, the recruitability is low [5]. To conceptualize these phenomena, we hypothesize the following sequence of events: the viral infection leads to a modest local subpleural interstitial edema (ground-glass lesions) particularly located at the interfaces between lung structures with different elastic properties, where stress and strain are concentrated [6]. Vasoplegia accounts for severe hypoxemia. The normal response to hypoxemia is to increase minute ventilation, primarily by increasing the tidal volume [7] (up to 15–20 ml/kg), which is associated with a more negative intrathoracic inspiratory pressure. Undetermined factors other than hypoxemia markedly stimulate, in these patients, the respiratory drive. The near normal compliance, however, explains why some of the patients present without dyspnea as the patient inhales the volume he expects. This increase in minute ventilation leads to a decrease in PaCO2. The evolution of the disease: transitioning between phenotypes The Type L patients may remain unchanging for a period and then improve or worsen. The possible key feature which determines the evolution of the disease, other than the severity of the disease itself, is the depth of the negative intrathoracic pressure associated with the increased tidal volume in spontaneous breathing. Indeed, the combination of a negative inspiratory intrathoracic pressure and increased lung permeability due to inflammation results in interstitial lung edema. This phenomenon, initially described by Barach in [8] and Mascheroni in [9] both in an experimental setting, has been recently recognized as the leading cause of patient self-inflicted lung injury (P-SILI) [10]. Over time, the increased edema increases lung weight, superimposed pressure and dependent atelectasis. When lung edema reaches a certain magnitude, the gas volume in the lung decreases, and the tidal volumes generated for a given inspiratory pressure decrease [11]. At this stage, dyspnea develops, which in turn leads to worsening P-SILI. The transition from Type L to Type H may be due to the evolution of the COVID-19 pneumonia on one hand and the injury attributable to high-stress ventilation on the other. COVID-19 pneumonia, Type H The Type H patient: High elastance. The decrease in gas volume due to increased edema accounts for the increased lung elastance. High right-to-left shunt. This is due to the fraction of cardiac output perfusing the non-aerated tissue which develops in the dependent lung regions due to the increased edema and superimposed pressure. High lung weight. Quantitative analysis of the CT scan shows a remarkable increase in lung weight (> 1.5 kg), on the order of magnitude of severe ARDS [12]. High lung recruitability. The increased amount of non-aerated tissue is associated, as in severe ARDS, with increased recruitability [5]. The Type H pattern, 20–30% of patients in our series, fully fits the severe ARDS criteria: hypoxemia, bilateral infiltrates, decreased the respiratory system compliance, increased lung weight and potential for recruitment. Figure 1 summarizes the time course we described. In panel a, we show the CT in spontaneous breathing of a Type L patient at admission, and in panel b, its transition in Type H after 7 days of noninvasive support. As shown, a similar degree of hypoxemia was associated with different patterns in lung imaging. Fig. 1 a CT scan acquired during spontaneous breathing. The cumulative distribution of the CT number is shifted to the left (well-aerated compartments), being the 0 to − 100 HU compartment, the non-aerated tissue virtually 0. Indeed, the total lung tissue weight was 1108 g, 7.8% of which was not aerated and the gas volume was 4228 ml. Patient receiving oxygen with venturi mask inspired oxygen fraction of 0.8. b CT acquired during mechanical ventilation at end-expiratory pressure at 5 cmH2O of PEEP. The cumulative distribution of the CT scan is shifted to the right (non-aerated compartments), while the left compartments are greatly reduced. Indeed, the total lung tissue weight was 2744 g, 54% of which was not aerated and the gas volume was 1360 ml. The patient was ventilated in volume controlled mode, 7.8 ml/kg of tidal volume, respiratory rate of 20 breaths per minute, inspired oxygen fraction of 0.7 Respiratory treatment Given this conceptual model, it follows that the respiratory treatment offered to Type L and Type H patients must be different. The proposed treatment is consistent with what observed in COVID-19, even though the overwhelming number of patients seen in this pandemic may limit its wide applicability. The first step to reverse hypoxemia is through an increase in FiO2 to which the Type L patient responds well, particularly if not yet breathless. In Type L patients with dyspnea, several noninvasive options are available: high-flow nasal cannula (HFNC), continuous positive airway pressure (CPAP) or noninvasive ventilation (NIV). At this stage, the measurement (or the estimation) of the inspiratory esophageal pressure swings is crucial [13]. In the absence of the esophageal manometry, surrogate measures of work of breathing, such as the swings of central venous pressure [14] or clinical detection of excessive inspiratory effort, should be assessed. In intubated patients, the P0.1 and P occlusion should also be determined. High PEEP, in some patients, may decrease the pleural pressure swings and stop the vicious cycle that exacerbates lung injury. However, high PEEP in patients with normal compliance may have detrimental effects on hemodynamics. In any case, noninvasive options are questionable, as they may be associated with high failure rates and delayed intubation, in a disease which typically lasts several weeks. The magnitude of inspiratory pleural pressures swings may determine the transition from the Type L to the Type H phenotype. As esophageal pressure swings increase from 5 to 10 cmH2O—which are generally well tolerated—to above 15 cmH2O, the risk of lung injury increases and therefore intubation should be performed as soon as possible. Once intubated and deeply sedated, the Type L patients, if hypercapnic, can be ventilated with volumes greater than 6 ml/kg (up to 8–9 ml/kg), as the high compliance results in tolerable strain without the risk of VILI. Prone positioning should be used only as a rescue maneuver, as the lung conditions are “too good” for the prone position effectiveness, which is based on improved stress and strain redistribution. The PEEP should be reduced to 8–10 cmH2O, given that the recruitability is low and the risk of hemodynamic failure increases at higher levels. An early intubation may avert the transition to Type H phenotype. Type H patients should be treated as severe ARDS, including higher PEEP, if compatible with hemodynamics, prone positioning and extracorporeal support. In conclusion, Type L and Type H patients are best identified by CT scan and are affected by different pathophysiological mechanisms. If not available, signs which are implicit in Type L and Type H definition could be used as surrogates: respiratory system elastance and recruitability. Understanding the correct pathophysiology is crucial to establishing the basis for appropriate treatment.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found

            Characteristics associated with hospitalisation for COVID-19 in people with rheumatic disease: data from the COVID-19 Global Rheumatology Alliance physician-reported registry

            Objectives COVID-19 outcomes in people with rheumatic diseases remain poorly understood. The aim was to examine demographic and clinical factors associated with COVID-19 hospitalisation status in people with rheumatic disease. Methods Case series of individuals with rheumatic disease and COVID-19 from the COVID-19 Global Rheumatology Alliance registry: 24 March 2020 to 20 April 2020. Multivariable logistic regression was used to estimate ORs and 95% CIs of hospitalisation. Age, sex, smoking status, rheumatic disease diagnosis, comorbidities and rheumatic disease medications taken immediately prior to infection were analysed. Results A total of 600 cases from 40 countries were included. Nearly half of the cases were hospitalised (277, 46%) and 55 (9%) died. In multivariable-adjusted models, prednisone dose ≥10 mg/day was associated with higher odds of hospitalisation (OR 2.05, 95% CI 1.06 to 3.96). Use of conventional disease-modifying antirheumatic drug (DMARD) alone or in combination with biologics/Janus Kinase inhibitors was not associated with hospitalisation (OR 1.23, 95% CI 0.70 to 2.17 and OR 0.74, 95% CI 0.37 to 1.46, respectively). Non-steroidal anti-inflammatory drug (NSAID) use was not associated with hospitalisation status (OR 0.64, 95% CI 0.39 to 1.06). Tumour necrosis factor inhibitor (anti-TNF) use was associated with a reduced odds of hospitalisation (OR 0.40, 95% CI 0.19 to 0.81), while no association with antimalarial use (OR 0.94, 95% CI 0.57 to 1.57) was observed. Conclusions We found that glucocorticoid exposure of ≥10 mg/day is associated with a higher odds of hospitalisation and anti-TNF with a decreased odds of hospitalisation in patients with rheumatic disease. Neither exposure to DMARDs nor NSAIDs were associated with increased odds of hospitalisation.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Feasibility and physiological effects of prone positioning in non-intubated patients with acute respiratory failure due to COVID-19 (PRON-COVID): a prospective cohort study

              Summary Background The COVID-19 pandemic is challenging advanced health systems, which are dealing with an overwhelming number of patients in need of intensive care for respiratory failure, often requiring intubation. Prone positioning in intubated patients is known to reduce mortality in moderate-to-severe acute respiratory distress syndrome. We aimed to investigate feasibility and effect on gas exchange of prone positioning in awake, non-intubated patients with COVID-19-related pneumonia. Methods In this prospective, feasibility, cohort study, patients aged 18–75 years with a confirmed diagnosis of COVID-19-related pneumonia receiving supplemental oxygen or non-invasive continuous positive airway pressure were recruited from San Gerardo Hospital, Monza, Italy. We collected baseline data on demographics, anthropometrics, arterial blood gas, and ventilation parameters. After baseline data collection, patients were helped into the prone position, which was maintained for a minimum duration of 3 h. Clinical data were re-collected 10 min after prone positioning and 1 h after returning to the supine position. The main study outcome was the variation in oxygenation (partial pressure of oxygen [PaO2]/fractional concentration of oxygen in inspired air [FiO2]) between baseline and resupination, as an index of pulmonary recruitment. This study is registered on ClinicalTrials.gov, NCT04365959, and is now complete. Findings Between March 20 and April 9, 2020, we enrolled 56 patients, of whom 44 (79%) were male; the mean age was 57·4 years (SD 7·4) and the mean BMI was 27·5 kg/m2 (3·7). Prone positioning was feasible (ie, maintained for at least 3 h) in 47 patients (83·9% [95% CI 71·7 to 92·4]). Oxygenation substantially improved from supine to prone positioning (PaO2/FiO2 ratio 180·5 mm Hg [SD 76·6] in supine position vs 285·5 mm Hg [112·9] in prone position; p<0·0001). After resupination, improved oxygenation was maintained in 23 patients (50·0% [95% CI 34·9–65·1]; ie, responders); however, this improvement was on average not significant compared with before prone positioning (PaO2/FiO2 ratio 192·9 mm Hg [100·9] 1 h after resupination; p=0·29). Patients who maintained increased oxygenation had increased levels of inflammatory markers (C-reactive protein: 12·7 mg/L [SD 6·9] in responders vs 8·4 mg/L [6·2] in non-responders; and platelets: 241·1 × 103/μL [101·9] vs 319·8 × 103/μL [120·6]) and shorter time between admission to hospital and prone positioning (2·7 days [SD 2·1] in responders vs 4·6 days [3·7] in non-responders) than did those for whom improved oxygenation was not maintained. 13 (28%) of 46 patients were eventually intubated, seven (30%) of 23 responders and six (26%) of 23 non-responders (p=0·74). Five patients died during follow-up due to underlying disease, unrelated to study procedure. Interpretation Prone positioning was feasible and effective in rapidly ameliorating blood oxygenation in awake patients with COVID-19-related pneumonia requiring oxygen supplementation. The effect was maintained after resupination in half of the patients. Further studies are warranted to ascertain the potential benefit of this technique in improving final respiratory and global outcomes. Funding University of Milan-Bicocca.
                Bookmark

                Author and article information

                Journal
                Lancet Rheumatol
                Lancet Rheumatol
                The Lancet. Rheumatology
                Elsevier Ltd.
                2665-9913
                28 January 2021
                February 2021
                28 January 2021
                : 3
                : 2
                : e88-e90
                Affiliations
                [a ]Division of Rheumatology, School of Medicine, University of California San Francisco, San Francisco, CA 94110, USA
                [b ]University of Queensland Faculty of Medicine, Herston, Australia
                Article
                S2665-9913(21)00008-4
                10.1016/S2665-9913(21)00008-4
                7906652
                4f5eafd8-ffed-491c-88b2-6775ce899699
                © 2021 Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Categories
                Comment

                Comments

                Comment on this article