Monocytosis in the Acute Phase of SARS-CoV-2 Infection Predicts the Presence of Anosognosia for Cognitive Deficits in the Chronic Phase

Monocytosis in the Acute Phase of SARS-CoV-2 Infection Predicts the Presence of Anosognosia for Cognitive Deficits in the Chronic Phase | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Monocytosis in the Acute Phase of SARS-CoV-2 Infection Predicts the Presence of Anosognosia for Cognitive Deficits in the Chronic Phase Anthony Nuber-Champier, Philippe Voruz, Isabele Jacot de Alcântara, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1361211/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Sep, 2022 Read the published version in Brain, Behavior, & Immunity - Health → Version 1 posted You are reading this latest preprint version Abstract Altered awareness of neuropsychological disorders (i.e., anosognosia) is a striking symptom of post-COVID-19 syndrome. Some leukocytes markers in the acute phase might predict the presence of anosognosia in the chronic phase, but they have not been identified yet. This study aims to determine whether patients with anosognosia for their memory deficits in the chronic phase present specific leukocytes distribution in the acute phase, and if so, whether these leukocytes parameters could predict this anosognosia. First, we compare the acute immunological data of the leukocytes distribution of 20 patients infected with SARS-Cov-2 who displayed anosognosia 69 months after SARS-Cov-2 infection (230.25 ± 46.65 days) versus 41 patients infected with SARS-Cov-2 without developing anosognosia. Second, we performed a ROC analysis to evaluate the predictive value of the leukocytes markers that emerged from this comparison. Blood circulating monocytes (%) at the acute phase of SARS-CoV2 infection is associated with long term post-COVID-19 anosognosia. Finally, serology on admission showing a percentage rate of monocytes of 7.35% of the total number of leukocytes, seems to predict the presence of chronic anosognosia for 6–9 months after infection. anosognosia immunology monocytes cognition neuropsychology SARS-CoV-2 post-COVID-19 syndrome Figures Figure 1 Figure 2 1 Introduction The persistence of cognitive symptoms following SARS-CoV-2 infection is highlighted by the presence of memory deficits and impaired executive, instrumental and attentional functioning several weeks and even months post-discharge 1 – 3 . These impairments can be severe, even in individuals with no previous neurological conditions 2 . Initial observations point to fairly heterogeneous neuropsychological profiles, one striking clinical feature being the presence of impaired awareness of neuropsychological deficits, referred to as anosognosia 3 , 4 . Some patients complain of extremely severe cognitive problems but have no objective disorders, whereas others have no subjective complaints but exhibit severe cognitive disorders 2 , 3 . In this regard, interesting information can be derived from other types of human coronavirus (HCoV). In the past, neuroinvasive types of HCoV have been reported to induce acute and chronic complications for cognition and consciousness 5 .HCoV-OC43 may even contribute to the development of neurodegenerative cascades 6 , with brain regions injured by HCoV viral attack 7 overlapping with those responsible for self-consciousness, as observed in SARS-CoV-2 4 . Interestingly, in patients with human immunodeficiency virus (HIV) 8 , 9 , Alzheimer's disease 10 or multiple sclerosis 11 , anosognosia 12 is predictive of the presence and intensity of neuropsychological symptoms; more anosognosic patients ,having the more severe their neuropsychological deficits 10 . Currently, we observed that SARS-CoV-2 cause cognitive and neurological damage in the same line as the pathologies mentioned. Indeed, Voruz et al., 3 have recently demonstrated that anosognosic patients 6 to 9 months after SARS-CoV-2 infection have significantly greater memory deficits than nosognosic patients. In addition, anosognosic patients had fewer self-reported psychiatric symptoms and a better self-reported quality of life. These post-SARS-CoV-2 cognitive findings in anosognosic patients are mainly supported by hypoconnectivity between frontal and dorsolateral prefrontal regions, somatosensory networks and some cerebellar lobules 3 . This post-SARS-CoV-2 neurocognitive phenotype would therefore be congruent with the neurodegenerative, viral, and autoimmune pathologies mentioned previously. Another striking observation regarding post-COVID-19 syndrome is that the severity of the respiratory form in the acute phase does not seem to be the best predictor of cognitive impairment in the chronic phase 3 , 13 . Indeed, in a recent literature review, intrinsic risk factors such as genetics, lifestyle, and immunological profile were better predictors of the pathophysiological consequences of SARS-CoV-2 infection (e.g., neuroinflammation, cytokine cascade, hypercoagulability, direct brain injury, astrocyte infection) that ultimately lead to the development of cognitive impairment 14 . In this context, we wondered whether acute-phase biological markers other than respiratory distress might predict the presence of cognitive deficits, particularly anosognosia, which is known to be correlated with severe neuropsychological syndromes 3 , 10 . Identifying these predictors might allow for the development of individualized and targeted management for patients most likely to exhibit severe cognitive impairments. This is, nevertheless, no easy task, as the pathways associated with the neurotropism of SARS-CoV-2 infection are not yet well established (for reviews, see 13 , 14 ). In order to investigate the neurotropism of SARS-CoV-2 we focus here on the hypothesis of an indirect effect of leukocyte variation on cognition 15 , 16 . Patterns of dysregulation of the complex immune system during SARS-CoV-2 infection have been associated with the severity and final outcome of the infection 17 , 18 . One review suggested that monocyte-derived macrophages are a characteristic target of SARS-CoV-2 19 , while studies have pointed to the persistence of pro-inflammatory immune dysregulation after SARS-CoV-2 infection 14 , 19 , 20 . Interestingly, these phenomena seem to be linked to cognitive deficits and psychiatric symptoms up to 3 months post-infection 20 , 21 , but results remain limited, and no study has so far comprehensively evaluated the association between overall cognitive function and acute immunological profiles. Associations between immunological aspects and cognitive deficits have been observed in several neurocognitive pathologies following an infection, including HIV 22 and sepsis-associated encephalopathy (SAE) 23 – 26 , as well as in neurodegenerative diseases 27 . Taken together, these observations suggest that the interaction between dysregulation of the immune system in the acute phase of SARS-CoV-2 infection and long-term cognitive deficits particularly anosognosia is an interesting lead to follow. Therefore, in this study we further investigate the etiological understanding of the neurocognitive long COVID syndrome in an immune-related way.The objective of the present study was to determine whether patients who go on to exhibit anosognosia in the chronic phase differ significantly on leucocytes distribution in the acute phase from those who do not, and whether any such significant differences are predictive of this chronic lack of awareness. In line with the results of Cervia, et al. 28 showing on general post-acute long-COVID syndrome symptomatology that the immunoglobulin signature predicts the risk of long-COVID syndrome. As well as addressing the need to identify physiological markers that can predict long-term cognitive impairment after SARS-CoV-2 13 , and based on the hypothesis of immune damage to the central nervous system (CNS) in the context of SARS-CoV-2 3,19 and other viral or neurodegenerative diseases (e.g., HIV, Alzheimer's disease) 29 , 30 . We hypothesized that innate immunity biomarkers measured at the time of SARS-CoV2 infection (acute phase) can be used to distinguish anosognosic from nosognosic patients 69 months post-infection (chronic phase). More specifically, based on research showing that anosognosic patients with Alzheimer's disease or post- Covid-19 syndrome 3 have more marked cognitive deficits than nosognosic patients 1 0 , with elevated inflammatory markers 3 1 , we hypothesized that anosognosic patients with post SARS-CoV-2 infection have higher levels of various leukocyte biomarkers than nosognosic patients. Finally, we hypothesized that these markers are predictive of anosognosia 69 months after SARS-CoV-2 infection. 2 Results 2.1 Symptom validity and presence of noncredible symptoms The measurement of symptom validity, congruence, and presence of noncredible symptoms using the BRIEF-A yielded good to excellent results for all participants. 2.2 Sociodemographic and clinical variables as a function of anosognosia for memory disorders in the chronic phase ( Table 1 ) No significant differences were observed between the two groups on either sociodemographic characteristics, namely age, handedness, sex, sociocultural level, or other clinical variables (see Table 1 ), with the exception of chronic renal failure (χ 2 = 4.24, p = .040). Table 1 Sociodemographic and clinical measures of patients with SARS-CoV-2 divided into two groups according to presence/absence of anosognosia 69 months post-infection Anosognosic patients n = 20 Nosognosic patients n = 41 p < .050 Mean age in years (± SD ) 58.40 (± 13.57) 58.10 (± 10.17) .604 Education level (Levels 1/2/3) 2/6/12 1/14/26 .446 Sex (F/M) 5/15 15/26 .333 Number of patients who required conventional hospitalization/ICU in the acute phase 12/8 26/15 .851 Mean days of hospitalization (± SD ) 24.60 (± 24.35) 22.00 (± 26.82) .963 Mean days between positive RT-PCR test and collection of immunological data (± SD ) 1.35 (± 3.41) 2.05 (± 3.50) Diabetes (Yes/No) 4/16 5/36 .328 History of respiratory disorders (Yes/No) 2/18 7/34 .465 History of cardiovascular disorders (Yes/No) 6/14 6/35 .156 History of neurological disorders (Yes/No) 0/20 0/41 1 History of psychiatric disorders (Yes/No) 0/20 1/40 .309 History of cancer (Yes/No) 0/20 0/41 1 History of severe immunosuppression (Yes/No) 0/20 0/41 1 History of developmental disorders (Yes/No) 0/20 0/41 1 Chronic renal failure (Yes/No) 2/18 0/41 .040* Sleep apnea syndrome (Yes/No) 1/19 9/32 .093 Note. Education level: 1 = compulsory schooling, 2 = post-compulsory schooling, and 3 = university degree or equivalent. ICU: intensive care unit; RT-PCR: reverse transcription polymerase chain reaction allowing RNA to be quantified to determine SARS-CoV-2 infection. The nosognosic/anosognosic groups were formed according to awareness or lack of awareness of memory impairment 69 months after SARS-CoV-2 infection. 2.3 Percentage of monocytes to total leukocytes in acute phase as a function of anosognosia for chronic phase memory impairment (6–9 months post infection) ( Table 2 ) After FDR correction, the only surviving comparison concerned the percentage of monocytes in the total number of leukocytes. Anosognosic patients had a significantly higher monocyte percentage than nosognosic patients ( z = -2.87, p = .004, r = − .387). Consistent with these results, more anosognosic patients had a monocyte percentage above the threshold defined as normal than nosognosic patients did (χ 2 = 5.80, p = .016). The distribution of nosognosic and anosognosic patients according to the different immunological parameters is available in Supplementary Material (2). Table 2 Immunological measures (White blood cell count) for patients with SARS-CoV-2 on admission to hospital according to presence/absence of anosognosia 6–9 months post infection White blood cell count/repartition at Day 1 of hospitalization Anosognosic patients Mean (± SD ) Nosognosic patients Mean (± SD ) M-W or chi 2 FDR-corrected Leucocytes (G/l) 5.46 (± 1.98) 7.31 (± 2.88) .020* Lymphocytes (G/l) 0.87 (± 0.37) 1.13 (± 0.98) .731 Neutrophils (G/l) 3.91 (± 1.56) 5.77 (± 2.71) .019* Eosinophils (G/l) 0.01 (± 0.04) 0.02 (± 0.04) .195 Basophils (G/l) 0.01 (± 0.01) 0.02 (± 0.02) .868 Monocytes (G/l) 0.44 (± 0.18) 0.37 (± 0.23) .510 Lymphocytes % 17.84 (± 8.68) 16.38 (± 10.82) .481 Neutrophils % 71.16 (± 11.93) 75.84 (± 12.38) .188 Eosinophils % 0.19 (± 0.62) 0.27 (± 0.48) .220 Basophils % 0.20 (± 0.17) 0.20 (± 0.24) .622 Monocytes % 8.29 (± 2.71) 5.56 (± 3.59) .004** Lymphocytes (below/normal/above threshold) 7/9/0 20/19/0 .612 Neutrophils (normal/above threshold) 14/2 23/16 .041* Eosinophils (normal/above threshold) 15/0 39/0 1 Basophils (below/above threshold) 15/0 39/0 1 Monocytes (below/above threshold) 08/07 33/6 .016* Lymphocyte/Monocyte ratio 2.11 (± 1.03) 4.37 (± 7.55) .018* Lymphocyte/Neutrophil ratio 5.55 (± 4.37) 10.68 (± 15.74) .359 Neutrophil/Monocyte ratio 10.62 (± 6.89) 28.12 (± 41.65) .009* CRP 73.42 (± 48.34) 99.79 (± 95.37) .678 Note. Immunological parameters were measured in two different units: giga per liter (G/l) and percentage of blood serum. Calculating the ratio between two immunological parameters allowed us to know the ratio of overactivation of one parameter to that of another. 2.4 Immunological variables in acute phase as predictors of anosgnosia 69 months post- SARS-CoV-2 infection ( Fig. 2 ) An ROC curve analysis was performed on 52 of the 61 patients (anosognosic: n = 15; nosognosic: n = 37), as we analyzed one measure of each immunological parameter, and nine patients who did not have all the immunological measures were therefore excluded. This analysis revealed that monocyte percentage in the total number of leukocytes ( p = .004) in the acute phase significantly predicted anosognosia 69 months post-infection. On the basis of the area under the curve for each of these variables, an area equivalent to .70 was considered good, such that only the percentage of monocytes was considered good (.755) with an estimated 95% confidence interval of [.614, .895] and a standard error of .072 (see Fig. 2 ). The best cut-off for monocyte percentage was deemed to be the nearest score to .80 for sensitivity and the nearest score to .20 for 1-specificity, such that the best threshold for maximizing the avoidance of false positive and false negative errors was a monocyte percentage of 7.35%. The Youden test revealed that with 7.35% of monocytes, the ROC curve model (AUC = .755) was able to predict at best 74.3% of cases of anosognosia 69 months after Sars-CoV-2 infection. Interestingly, neither CRP nor basophil percentage predicted anosognosia and associated cognitive impairment. 3 Discussion In the present study, we found that the percentage of monocytes in the total number of leukocytes obtained in the acute phase of the disease (at hospital admission), discriminates and predicts anosognosic patients from their memory deficits in the chronic phase compared to nosognosic patients (6–9 months after SARS-CoV-2 infection) (Fig. 1 and Table 2 ). ROC analyses revealed that SARS-CoV-2 infected patients with a mean proportion of blood circulating monocytes above 7.35% of leucocytes measured in the acute phase predicted the presence of anosognosia in the chronic phase with high sensitivity (80%) and specificity (80%) (Fig. 2 ). Finally, our results showed that CRP differentiated patients according to the severity of the disease, but the cognitive disorders marked by anosognosia in the long term were not associated with this inflammatory marker (SI A-B). The observation of different immunological profiles at the time of hospitalization among patients who exhibited anosognosia of memory functions 69 months after infection supports the hypothesis of indirect CNS damage mediated by immune phenomena 1 9 , which then fosters the development of long-term cognitive deficits 4 4, 4 5 . SARS-CoV-2 infection may have induced a different immunological response balance in the group of post-COVID-19 long-term anosognosic patients. Our study suggests that post-COVID-19 long-term anosognosia may be the result of an immune imbalance in the acute phase of SARS-CoV-2 infection, particularly in terms of leukocyte distribution. Among the parameters found, in addition to the percentage of monocytes among all leukocytes, we found that both the neutrophil/monocyte ratio and the neutrophil count (G/l) tend to be lower in the acute phase of SARS-CoV-2 infection in patients who will develop chronic anosognosia compared to nosognosic patients. Changes in blood neutrophil levels in association with neurocognitive semiology are currently discussed in neurodegenerative diseases (e.g. Alzhemeir) 46 and more recently in SARS-CoV-2 47,48 . The pro-NETotic effect of neutrophils would generate an innate immune response capable of containing different infectious agents such as SARS-CoV-2 49 . Anosognosic patients have fewer neutrophils (G/L) and a lower neutrophil to monocyte ratio during the acute phase of SARS-CoV-2 infection compared to nosognosic patients. Different immunological mechanisms may be involved in the fight against a viral agent like SARS-CoV2, both innate and adaptive immunity. Regarding innate immunity, patients who develop anosognosia would have a higher propensity to involve the monocyte/macrophage lineage while those who remain nosognosic would have a preponderance of their neutrophilic response. We can therefore hypothesise a different susceptibility of certain brain networks and cognitive processes according to the type of systemic inflammatory mechanism generated in a parainfectious context. Congruent with our observations, studies focusing on the immunological phenomena induced by SARS-CoV-2 in the acute phase have shown distinct immune cascades in relation to premorbid factors intrinsic to the individual 50 . Taken together with the present results, these distinct immuno-physiological combinations may help to explain the development of different trajectories in relation to post-COVID syndrome. An interesting and promising element in the understanding of the pathology is the phenomenon of hyperinflammation resulting from excessive production of pro-inflammatory factors 51 . Thus, cellular immunity and the production of inflammatory cytokines appear to persist in the subacute period (3 months post-infection), while inflammatory phenomena and cellular responses seem to persist 6 months post-infection. Conversely, the mechanisms of humoral immunity seem to decrease over time 52 . In line with these inflammatory hypotheses, we showed that CRP and basophils can be used to distinguish between patients who end up in intensive care and those who remain in intermediate care in the acute phase, but do not predict or distinguish long-term cognitive impairment such as anosognosia. In relation with our findings Rhally, et al. 53 show that increased CRP is associated with vascular inflammation and altered microstructural changes in the white matter. Therefore, the hypothesis of cognitive effects originating from systemic inflammation measurable by different inflammatory markers remains a central line of research in infectious contexts such as SARS-CoV-2. This interesting variation illustrates the observation that the severity of acute respiratory impairment is not a good predictor of long-term post-COVID-19 syndrome at least not its cognitive aspects 13 . We therefore showed here that specific acute immunological parameters can be used to understand long-term cognitive phenomena, in particular leukocytes variations marked by the percentage of monocytes as a predictor of anosognosia. Abnormally high levels of monocytes have already been observed in SARS-CoV-2 45,54 and have been associated with more severe disease outcomes (e.g., inflammatory amplification, impaired type I IFN production), but to our knowledge, they have never been associated with the development of cognitive impairment. Interestingly, previous studies in other pathologies have highlighted relationships between monocytic processes and cognition 30 , 55 , 56 . Studies in HIV have highlighted relationships between increased CD14 and poorer cognitive performance, including on a composite score on learning, memory, mental flexibility, verbal fluency and praxis tasks 29 . Studies in multiple sclerosis 55 and other neurodegenerative diseases (e.g., Alzheimer's disease or Parkinson's disease) have also shown an association between the overexpression of pro-inflammatory monocytes and decreased global cognitive performance 30 , 56 . Interestingly, encephalopathy has been observed in the acute phase of SARS-CoV-2 infection 57 , and the persistence of cognitive deficits could partly be explained by this acute-phase episode, bearing in mind that some patients may not have had a specific diagnosis of SARS-CoV-2 encephalopathy. Previous research 23 , 25 , 58 has revealed immunopathological mechanisms roughly similar to the SARS-CoV-2 pattern in pneumonia-induced SAE. One of the key pathophysiological hypotheses concerning SAE is that the pro-inflammatory expression of monocytes can engender cognitive impairment in the long term 23 – 26 . Potentially relevant to SARS-CoV-2 infections, recent studies have shown that early intervention to limit pro-inflammatory monocyte proliferation in SAE can modulate long-term cognitive deficits 23 , 25 . SARS-CoV-2-related immune responses 54 and the resulting cognitive deficits may therefore lie on the same continuum as the immune responses seen in pneumonia-induced SAE 23 . Reasonably, one of the targets of current research is aimed at a better understanding of the phenomenon of the long COVID syndrome. In an original way, we support the hypothesis that acute immunological variations have repercussions on cognition 6 to 9 months later. Several reflections related to the long COVID syndrome can be drawn from our results; on the one hand different immune variations could generate different cognitive deficits, here we show that the percentage of monocytes does predict the phenomenon of anosognosia of memory deficits but other leukocyte parameters (e.g. neutrophils) could also have effects on other cognitive processes than anosognosia 47 , 48 . On the other hand, at a time when the number of people suffering from long COVID syndrome is increasing 59 , 60 , our results suggest that it would be possible to plan neuropsychological follow-ups based on acute leukocyte markers as soon as patients infected by SARS-CoV-2 are hospitalised. The provision of these follow-ups would allow a better organisation of hospital structures and a more specialised support for patients. Finally, as a predictive approach, recent studies have shown that SARS-CoV-2 infection may be a trigger for neurodegenerative pathologies (e.g., Alzheimer's disease), as well as a catalyst for neurodegenerative processes, just like other HCoVs 6 , 61 . In our study, as well as in Voruz et al. 3 , we argue that the cognitive profiles of the anosognosic patients were very similar to those observed in Alzheimer's disease 10 , suggesting from a cognitive perspective a potential development of precursor to a neurodegenerative pathology. The mechanisms that trigger neurodegenerative pathologies are not yet well understood. However, one hypothesis suggests that neurodegenerative pathologies may be triggered by infiltration of the nervous system by microglia 27 following inflammatory responses. This hypothesis could be applied to SARS-CoV-2 44,62 . Thus, the high level of monocytes observed both in our study and in previous studies of patients with SARS-CoV-2 54 , could be a risk factor for the development of neurodegenerative processes. Future studies are needed to look for markers of neurodegenerative pathologies in patients infected with SARS-CoV-2. It should be noted that our study had several limitations. First, although no other study has yet attempted to link cognitive and immunological variables in SARS-CoV-2, and although we performed a power analysis to calculate the number of participants to include (see Section 2 “Method”), our sample of 61 patients could be considered small. However, as we illustrated in section 2 "Method", our power analysis on two conditions (i.e. Sepsis and HIV) that attempted to establish a link between cognition and immunology, revealed that we had sufficient participants in this cohort of SARS-CoV-2 infected patients. Second, our measure of anosognosia could be subject to debate 10 . Anosognosia is difficult to measure, despite important advances in its understanding in mild cognitive impairment and Alzheimer's disease 10 , 63 . It can be measured (i) by the clinician, using a clinical assessment, (ii) as the discrepancy between the patient's subjective complaints and objective neuropsychological scores, or (iii) as the difference between the patient's complaints and the caregiver's assessment in terms of activities of daily living 10 . In our study, we used two measures of anosognosia (clinical assessment and calculation of self-appraisal discrepancy score SAD). Third, while we included patients free of relevant medical history before the infection and while we retrospectively extracted their physiological variables on admission to hospital, to avoid the effect of any treatment for SARS-CoV-2, their immunological characteristics may have be modulated by treatments taken beforehand. 4 Conclusion We conducted the first retrospective analysis to establish a relationship between immunological responses in the acute phase of SARS-CoV-2 infection and long-term cognitive deficits, 69 months after SARS-CoV-2 infection, including anosognosia for memory impairment. Our results could be of great importance in the future management of patients and for understanding the emergence of post-COVID-19 syndrome phenomenon. A high blood circulating monocyte proportion of leucocytes could be a predictor of post-COVID-19 neuropsychological syndrome, whereas disease severity in the acute phase is not predictive of long-term cognitive effects. These results open the door to new research on potential acute-phase treatments that could reduce the emergence of post-COVID neurocognitive syndrome. 5 Method 5.1 Participants (Table 1 ) The sample comprised 61 patients with SARS-CoV-2 infection drawn from the COVID-COG cohort of Geneva University Hospitals (HUG), who were assessed 69 months after being admitted to hospital. We selected patients with no previous history of cognitive deficits or neuropsychiatric disease. Blood samples were collected from DATE-to DATE and no one single patient received anti-SARS-COV-2mAbs. Of these, 38 had had moderate symptoms (conventional hospitalization) in the acute phase, and 23 had had severe symptoms requiring a stay in intensive care unit (ICU) and intubation. SARS-CoV-2 infection was detected using a reverse transcription polymerase chain reaction (RT-PCR) test. This technique allows the N and E genes to be detected with the LightCycler 480 system (Roche, Switzerland). In rare cases, where PCR testing is not available for clinical reasons, intrathecal IgG synthesis has been used for diagnostic purposes and to confirm SARS-CoV-2 infection. For the purpose of the COVID-COG study, all patients completed a battery of neurological, neuropsychological and psychiatric tests and questionnaires 230.25 ± 46.65 days following SARS-CoV-2 infection. For the present study, only sociodemographic data, clinical history, objective memory tests and self-reported cognitive complaints related to memory disorders were extracted. 5.1.1 Subdivision of patients according to their anosognosia score. Patients were divided into two groups, according to their anosognosia for memory disturbances, measured 69 months after SARS-CoV-2 infection: 1) anosognosic for memory dysfunctions ( n = 20), versus 2) nosognosic for memory functions/dysfunctions ( n = 41). This was therefore done independently of the severity of their respiratory symptoms in the acute phase of the disease (anosognosic: n = 12 moderate and n = 8 severe vs. nosognosic: n = 26 moderate and n = 15 severe). Anosognosia was measured as follows: scores on the self-report Cognitive Complaints Questionnaire (QPC) 3 2 were first standardized and divided into four categories: 0 = normal behavior, 1 = limited influence on daily life, 2 = noticeable influence on daily life, and 3 = substantial influence on daily life. Each standardized score on this subjective measure was then subtracted from the standardized scores on objective measures of memory. Short-term memory was assessed with forward digit spans 3 3 and the Corsi test 3 4 , and episodic memory with the 16-item free/cued recall (RL/RI 16) paradigm 3 5 and the delayed recall of the Rey-Osterrieth Complex Figure test 3 6 . The resulting self-appraisal discrepancy scores (SAD) could therefore range from − 3 to 3, with any score below 0 indicating anosognosia. For example, if a patient reported no memory disorders (QPC score = 3) but performed very poorly on verbal episodic memory (RL/RI 16 delayed free recall test score = 0), he or she was deemed to exhibit anosognosia for memory dysfunction (0–3 = -3). Of note, the Behavior Rating Inventory of Executive Function - Adult Version (BRIEF-A) 3 7 was used to measure the validity of the patients' responses, as well as the presence of any noncredible symptoms. The method of subdivision of anosognosic versus nosognosic patients in this study follows the same procedure validated in Voruz et al., 3 . 5.1.2 Power analysis We performed a power analysis of the number of participants required using the following equation: This calculation was based on previous studies that had examined the relationship between immunity and cognition in patients with HIV+) or SAE 38 , 39 . Relying on previous power analyses for HIV+, 20 participants, with 10 per group (alpha = 0.05, beta = 0.2, and power = 0.8) was the total number of participants required for the study. As we intended to use nonparametric statistical tests, we added 15% more participants to the initial number needed 40 . We thus determined that the total number of participants required was 23 (i.e., 12 per group). Power calculations previously used for SAE yielded a total number of 34 persons. After adding the 15% owing to the use of nonparametric tests, we arrived at 39 persons (i.e., 19 persons per group; alpha = 0.05, beta = 0.2, and power = 0.8). 5.1.3 Ethics After being given a full description of the study, participants provided their written informed consent. The study was conducted in accordance with the Declaration of Helsinki, and the study protocol was approved by the cantonal ethics committee of Geneva (CER-02186). 5.2 Retrospective extraction of acute-phase physiological parameters Immunological parameters were retrospectively extracted from HUG’s internal database. We only selected physiological parameters measured on admission to hospital (1.35 ± 3.41 days after a positive RT-PCR test for anosognosic patients versus 2.05 ± 3.50 days for nosognosic patients), to avoid any effect of subsequent medication and oxygen therapy. We also extracted hematological, and metabolic and cardiac parameters, as we knew that these variables might have an impact on cognition. can contribute significantly to the development of cognitive deficits in dementia 41 , 42 . Parameters were measured by the diagnostic department of HUG’s Gas Testing, Hematology and Virology Laboratory. All laboratory samples were taken with Piccolo Xpress (Sysmex, Switzerland) tools and an ABL blood gas analyzer (Radiometer RSCH GmbH, Switzerland) at HUG. The following leukocytes distribution parameters (venous blood) were extracted: percentage (%) and mass concentration (G/l) of lymphocytes, monocytes, basophils, eosinophils, and neutrophils. Only mass concentration (G/l) was extracted for leukocytes. Subsequently, based on previous studies in SARS-CoV-2 43 , the following ratios were calculated: lymphocyte/monocyte ratio [lymphocyte (G/l) divided by monocyte (G/l)], lymphocyte/neutrophil ratio [lymphocyte (G/l) divided by neutrophil (G/l)], neutrophil/monocyte ratio [neutrophil (G/l) divided by monocyte (G/l)]. Inflammation was also measured as C-reactive protein (CRP) (mg/l). Finally, we classified the patients according to the normal thresholds for each percentage of each immunological variable (we considered the normal range to be 33%80% for neutrophils, 0%5% for eosinophils, 0%2% for basophils, 0%9% for monocytes, and 15%60% for lymphocytes. 5.3 Other clinical variables (69 months post-infection) 5.3.1 Sociodemographic and clinical data In addition to age, collected during the inclusion interview, we recorded patients’ sex, handedness, and education level. To complement information about previous neurological, psychiatric, and developmental conditions and cancer collected during the inclusion interview, we asked patients about previous cardiovascular disease, respiratory disorders, immunosuppression status, sleep apnea syndrome, diabetes, and smoking. Participants were asked to describe the symptoms they had experienced, both during the acute phase of the infection and currently (69 months post-infection), and the number of days they had spent in hospital, where relevant. 5.4 Statistical analysis Given the nonparametric distribution of our dataset, intergroup (anosognosic vs. nosognosic) analyses on sociodemographic and immunological variables were performed with nonparametric MannWhitney U tests for continuous data and chi-square tests for categorical variables, with a significance threshold of p = .05 false discovery rate (FDR) corrected. Moreover, a receiver operating characteristic (ROC) analysis was performed to identify the acute immunological variable(s) predictive of anosognosia 69 months after infection. For significant variables, a Youden test was performed to determine the best cut-off. Finally, to explore intergroup (intermediate vs. intensive care) differences, we also performed nonparametric MannWhitney U tests for continuous data and chi-square tests for binary categorical variables, with a significance level of p < 0.05 FDR corrected. All analyses were performed with SPSS statistical version 28.0.1. These analyses and their results are provided in Supplementary Information (Table 1. 1 and Table 1. 2 ) Abbreviations central nervous system (CNS), human immunodeficiency virus (HIV), human coronavirus (HCoV), intensive care unit (ICU), Cognitive Complaints Questionnaire (QPC), Behavior Rating Inventory of Executive Function - Adult Version (BRIEF-A), receiver operating characteristic (ROC), C-reactive protein (CRP), sepsis-associated encephalopathy (SAE), reverse transcription polymerase chain reaction (RT-PCR), false discovery rate (FDR), Area under the curve (AUC) Declarations Acknowledgements The present research was supported by Swiss National Science Foundation (SNSF) funding to JAP (PI) and FA (Co-PI) within the framework of the COVID-19 National Research Program (NRP 78; grant no. 407840_198438, RNP 78). Conflict of interest The authors report no conflicts of interest. 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Akinwumi, J. A., Edem, F. V. & Arinola, G. O. Cellular Inflammatory Indices in Hospitalized Nigerian COVID-19 Patients. Journal of Health Science Research, 19–26 (2021). Sun, B. et al. Characterization and biomarker analyses of post-COVID-19 complications and neurological manifestations. Cells 10 , 386 (2021). Visvabharathy, L. et al. Neuro-COVID long-haulers exhibit broad dysfunction in T cell memory generation and responses to vaccination. medRxiv (2021). Soehnlein, O., Steffens, S., Hidalgo, A. & Weber, C. Neutrophils as protagonists and targets in chronic inflammation. Nature Reviews Immunology 17 , 248–261 (2017). Sarubbo, F., El Haji, K., Vidal-Balle, A. & Lleonart, J. B. Neurological consequences of COVID-19 and brain related pathogenic mechanisms: A new challenge for neuroscience. Brain, Behavior, & Immunity-Health 19 , 100399 (2022). García-Grimshaw, M. et al. Critical role of acute hypoxemia on the cognitive impairment after severe COVID-19 pneumonia: a multivariate causality model analysis. Neurological Sciences, 1–13 (2022). Zuo, Y. et al. Neutrophil extracellular traps in COVID-19. JCI insight 5 (2020). Brodin, P. Immune determinants of COVID-19 disease presentation and severity. Nature Medicine 27 , 28–33 (2021). Widjaja, G. et al. Humoral immune mechanisms involved in protective and pathological immunity during COVID-19. Human Immunology 82 , 733–745 (2021). Bilich, T. et al. T cell and antibody kinetics delineate SARS-CoV-2 peptides mediating long-term immune responses in COVID-19 convalescent individuals. Science translational medicine 13 (2021). Rhally, A. et al. C-reactive protein and white matter microstructural changes in COVID-19 patients with encephalopathy. Journal of Neural Transmission 128 , 1899–1906 (2021). Bedin, A.-S. et al. Monocyte CD169 expression as a biomarker in the early diagnosis of coronavirus disease 2019. The Journal of infectious diseases 223 , 562–567 (2021). Di Filippo, M., Portaccio, E., Mancini, A. & Calabresi, P. Multiple sclerosis and cognition: synaptic failure and network dysfunction. Nature Reviews Neuroscience 19 , 599–609 (2018). Nissen, S. K. et al. Soluble CD163 changes indicate monocyte association with cognitive deficits in Parkinson's disease. Movement Disorders 36 , 963–976 (2021). Uginet, M. et al. COVID-19 encephalopathy: Clinical and neurobiological features. Journal of Medical Virology (2021). Li, H. et al. SARS-CoV-2 and viral sepsis: observations and hypotheses. The Lancet 395 , 1517–1520 (2020). Gorna, R. et al. Long COVID guidelines need to reflect lived experience. The Lancet 397 , 455–457, doi: 10.1016/s0140-6736(20)32705-7 (2021). Sudre, C. H. et al. Attributes and predictors of long COVID. Nature Medicine 27 , 626–631, doi: 10.1038/s41591-021-01292-y (2021). Dolatshahi, M., Sabahi, M. & Aarabi, M. H. Pathophysiological Clues to How the Emergent SARS-CoV-2 Can Potentially Increase the Susceptibility to Neurodegeneration. Molecular Neurobiology 58 , 2379–2394, doi: 10.1007/s12035-020-02236-2 (2021). Li, L., Acioglu, C., Heary, R. F. & Elkabes, S. Role of astroglial toll-like receptors (TLRs) in central nervous system infections, injury and neurodegenerative diseases. Brain, Behavior, and Immunity 91 , 740–755, doi: 10.1016/j.bbi.2020.10.007 (2021). Tondelli, M. et al. Neural Correlates of Anosognosia in Alzheimer's Disease and Mild Cognitive Impairment: A Multi-Method Assessment. Frontiers in Behavioral Neuroscience 12 , doi: 10.3389/fnbeh.2018.00100 (2018). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1361211","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":86962936,"identity":"ff319c0c-60ca-42b4-86da-1465e846c14c","order_by":0,"name":"Anthony Nuber-Champier","email":"","orcid":"","institution":"University of Geneva","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Anthony","middleName":"","lastName":"Nuber-Champier","suffix":""},{"id":86962937,"identity":"5b3b81f1-df90-4449-9973-2aecdaef6157","order_by":1,"name":"Philippe Voruz","email":"","orcid":"","institution":"University of Geneva","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Philippe","middleName":"","lastName":"Voruz","suffix":""},{"id":86962938,"identity":"5ae2f817-330a-4fab-acc5-3cc7b52b1221","order_by":2,"name":"Isabele Jacot de Alcântara","email":"","orcid":"","institution":"University of Geneva","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Isabele","middleName":"Jacot","lastName":"de Alcântara","suffix":""},{"id":86962939,"identity":"20d5b328-87d9-4014-92e7-656832b29f1b","order_by":3,"name":"Gautier Breville","email":"","orcid":"","institution":"Geneva University Hospitals","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gautier","middleName":"","lastName":"Breville","suffix":""},{"id":86962940,"identity":"f2d1a232-08ef-4f94-a139-1e3cf94e53ea","order_by":4,"name":"Gilles Allali","email":"","orcid":"","institution":"Lausanne University Hospital and University of Lausanne","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gilles","middleName":"","lastName":"Allali","suffix":""},{"id":86962941,"identity":"88043c3e-540b-43ec-a8f1-91ca9313f02d","order_by":5,"name":"Patrice. 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These impairments can be severe, even in individuals with no previous neurological conditions\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Initial observations point to fairly heterogeneous neuropsychological profiles, one striking clinical feature being the presence of impaired awareness of neuropsychological deficits, referred to as \u003cem\u003eanosognosia\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Some patients complain of extremely severe cognitive problems but have no objective disorders, whereas others have no subjective complaints but exhibit severe cognitive disorders\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In this regard, interesting information can be derived from other types of human coronavirus (HCoV). In the past, neuroinvasive types of HCoV have been reported to induce acute and chronic complications for cognition and consciousness\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e .HCoV-OC43 may even contribute to the development of neurodegenerative cascades\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, with brain regions injured by HCoV viral attack\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e overlapping with those responsible for self-consciousness, as observed in SARS-CoV-2\u003csup\u003e4\u003c/sup\u003e. Interestingly, in patients with human immunodeficiency virus (HIV)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, Alzheimer's disease\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e or multiple sclerosis\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, anosognosia\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e is predictive of the presence and intensity of neuropsychological symptoms; more anosognosic patients ,having the more severe their neuropsychological deficits\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Currently, we observed that SARS-CoV-2 cause cognitive and neurological damage in the same line as the pathologies mentioned. Indeed, Voruz et al.,\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e have recently demonstrated that anosognosic patients 6 to 9 months after SARS-CoV-2 infection have significantly greater memory deficits than nosognosic patients. In addition, anosognosic patients had fewer self-reported psychiatric symptoms and a better self-reported quality of life. These post-SARS-CoV-2 cognitive findings in anosognosic patients are mainly supported by hypoconnectivity between frontal and dorsolateral prefrontal regions, somatosensory networks and some cerebellar lobules\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis post-SARS-CoV-2 neurocognitive phenotype would therefore be congruent with the neurodegenerative, viral, and autoimmune pathologies mentioned previously.\u003c/p\u003e \u003cp\u003eAnother striking observation regarding post-COVID-19 syndrome is that the severity of the respiratory form in the acute phase does not seem to be the best predictor of cognitive impairment in the chronic phase\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Indeed, in a recent literature review, intrinsic risk factors such as genetics, lifestyle, and immunological profile were better predictors of the pathophysiological consequences of SARS-CoV-2 infection (e.g., neuroinflammation, cytokine cascade, hypercoagulability, direct brain injury, astrocyte infection) that ultimately lead to the development of cognitive impairment\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. In this context, we wondered whether acute-phase biological markers other than respiratory distress might predict the presence of cognitive deficits, particularly anosognosia, which is known to be correlated with severe neuropsychological syndromes\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Identifying these predictors might allow for the development of individualized and targeted management for patients most likely to exhibit severe cognitive impairments. This is, nevertheless, no easy task, as the pathways associated with the neurotropism of SARS-CoV-2 infection are not yet well established (for reviews, see\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eIn order to investigate the neurotropism of SARS-CoV-2 we focus here on the hypothesis of an indirect effect of leukocyte variation on cognition\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Patterns of dysregulation of the complex immune system during SARS-CoV-2 infection have been associated with the severity and final outcome of the infection\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. One review suggested that monocyte-derived macrophages are a characteristic target of SARS-CoV-2\u003csup\u003e19\u003c/sup\u003e, while studies have pointed to the persistence of pro-inflammatory immune dysregulation after SARS-CoV-2 infection\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Interestingly, these phenomena seem to be linked to cognitive deficits and psychiatric symptoms up to 3 months post-infection\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, but results remain limited, and no study has so far comprehensively evaluated the association between overall cognitive function and acute immunological profiles. Associations between immunological aspects and cognitive deficits have been observed in several neurocognitive pathologies following an infection, including HIV\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and sepsis-associated encephalopathy (SAE)\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, as well as in neurodegenerative diseases\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Taken together, these observations suggest that the interaction between dysregulation of the immune system in the acute phase of SARS-CoV-2 infection and long-term cognitive deficits particularly anosognosia is an interesting lead to follow.\u003c/p\u003e \u003cp\u003eTherefore, in this study we further investigate the etiological understanding of the neurocognitive long COVID syndrome in an immune-related way.The objective of the present study was to determine whether patients who go on to exhibit anosognosia in the chronic phase differ significantly on leucocytes distribution in the acute phase from those who do not, and whether any such significant differences are predictive of this chronic lack of awareness. In line with the results of Cervia, et al. \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e showing on general post-acute long-COVID syndrome symptomatology that the immunoglobulin signature predicts the risk of long-COVID syndrome. As well as addressing the need to identify physiological markers that can predict long-term cognitive impairment after SARS-CoV-2\u003csup\u003e13\u003c/sup\u003e, and based on the hypothesis of immune damage to the central nervous system (CNS) in the context of SARS-CoV-2\u003csup\u003e3,19\u003c/sup\u003eand other viral or neurodegenerative diseases (e.g., HIV, Alzheimer's disease)\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. We hypothesized that innate immunity biomarkers measured at the time of SARS-CoV2 infection (acute phase) can be used to distinguish anosognosic from nosognosic patients 69 months post-infection (chronic phase). More specifically, based on research showing that anosognosic patients with Alzheimer's disease or post- Covid-19 syndrome\u003csup\u003e3\u003c/sup\u003ehave more marked cognitive deficits than nosognosic patients\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e0\u003c/sup\u003e, with elevated inflammatory markers\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e1\u003c/sup\u003e, we hypothesized that anosognosic patients with post SARS-CoV-2 infection have higher levels of various leukocyte biomarkers than nosognosic patients. Finally, we hypothesized that these markers are predictive of anosognosia 69 months after SARS-CoV-2 infection.\u003c/p\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Symptom validity and presence of noncredible symptoms\u003c/h2\u003e \u003cp\u003eThe measurement of symptom validity, congruence, and presence of noncredible symptoms using the BRIEF-A yielded good to excellent results for all participants.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.2 Sociodemographic and clinical variables as a function of anosognosia for memory disorders in the chronic phase (\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNo significant differences were observed between the two groups on either sociodemographic characteristics, namely age, handedness, sex, sociocultural level, or other clinical variables (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with the exception of chronic renal failure (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;4.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.040).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic and clinical measures of patients with SARS-CoV-2 divided into two groups according to presence/absence of anosognosia 69 months post-infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnosognosic patients \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNosognosic patients\u003c/p\u003e \u003cp\u003e\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;41\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.050\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean age in years (\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.40 (\u0026plusmn;\u0026thinsp;13.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.10 (\u0026plusmn;\u0026thinsp;10.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.604\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level (Levels 1/2/3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2/6/12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/14/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.446\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (F/M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5/15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15/26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.333\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients who required conventional hospitalization/ICU in the acute phase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26/15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean days of hospitalization (\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.60 (\u0026plusmn;\u0026thinsp;24.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.00 (\u0026plusmn;\u0026thinsp;26.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean days between positive RT-PCR test and collection of immunological data (\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (\u0026plusmn;\u0026thinsp;3.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.05 (\u0026plusmn;\u0026thinsp;3.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5/36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of respiratory disorders (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2/18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7/34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.465\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of cardiovascular disorders (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6/35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of neurological disorders (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of psychiatric disorders (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1/40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.309\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of cancer (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of severe immunosuppression (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of developmental disorders (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0/20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic renal failure (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2/18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0/41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.040*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSleep apnea syndrome (Yes/No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1/19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9/32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.093\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eNote.\u003c/em\u003e Education level: 1\u0026thinsp;=\u0026thinsp;compulsory schooling, 2\u0026thinsp;=\u0026thinsp;post-compulsory schooling, and 3\u0026thinsp;=\u0026thinsp;university degree or equivalent. ICU: intensive care unit; RT-PCR: reverse transcription polymerase chain reaction allowing RNA to be quantified to determine SARS-CoV-2 infection. The nosognosic/anosognosic groups were formed according to awareness or lack of awareness of memory impairment 69 months after SARS-CoV-2 infection.\u003c/p\u003e \u003cp\u003e \u003cb\u003e2.3 Percentage of monocytes to total leukocytes in acute phase as a function of anosognosia for chronic phase memory impairment (6\u0026ndash;9 months post infection) (\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAfter FDR correction, the only surviving comparison concerned the percentage of monocytes in the total number of leukocytes. Anosognosic patients had a significantly higher monocyte percentage than nosognosic patients (\u003cem\u003ez\u003c/em\u003e = -2.87, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.004, \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.387). Consistent with these results, more anosognosic patients had a monocyte percentage above the threshold defined as normal than nosognosic patients did (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.80, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.016). The distribution of nosognosic and anosognosic patients according to the different immunological parameters is available in Supplementary Material (2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImmunological measures (White blood cell count) for patients with SARS-CoV-2 on admission to hospital according to presence/absence of anosognosia 6\u0026ndash;9 months post infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell count/repartition at Day 1 of hospitalization\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnosognosic patients\u003c/p\u003e \u003cp\u003eMean (\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNosognosic patients\u003c/p\u003e \u003cp\u003eMean (\u0026plusmn;\u0026thinsp;\u003cem\u003eSD\u003c/em\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM-W or chi\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFDR-corrected\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeucocytes (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.46 (\u0026plusmn;\u0026thinsp;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.31 (\u0026plusmn;\u0026thinsp;2.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.020*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocytes (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.87 (\u0026plusmn;\u0026thinsp;0.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (\u0026plusmn;\u0026thinsp;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophils (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.91 (\u0026plusmn;\u0026thinsp;1.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.77 (\u0026plusmn;\u0026thinsp;2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.019*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEosinophils (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01 (\u0026plusmn;\u0026thinsp;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02 (\u0026plusmn;\u0026thinsp;0.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.195\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBasophils (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01 (\u0026plusmn;\u0026thinsp;0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02 (\u0026plusmn;\u0026thinsp;0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonocytes (G/l)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.44 (\u0026plusmn;\u0026thinsp;0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37 (\u0026plusmn;\u0026thinsp;0.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.510\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocytes %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.84 (\u0026plusmn;\u0026thinsp;8.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.38 (\u0026plusmn;\u0026thinsp;10.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophils %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71.16 (\u0026plusmn;\u0026thinsp;11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.84 (\u0026plusmn;\u0026thinsp;12.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.188\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEosinophils %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.19 (\u0026plusmn;\u0026thinsp;0.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.27 (\u0026plusmn;\u0026thinsp;0.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.220\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBasophils %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.20 (\u0026plusmn;\u0026thinsp;0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.20 (\u0026plusmn;\u0026thinsp;0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonocytes %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.29 (\u0026plusmn;\u0026thinsp;2.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.56 (\u0026plusmn;\u0026thinsp;3.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.004**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocytes (below/normal/above threshold)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7/9/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20/19/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.612\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophils (normal/above threshold)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23/16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.041*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEosinophils (normal/above threshold)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBasophils (below/above threshold)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonocytes (below/above threshold)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e08/07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33/6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.016*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocyte/Monocyte ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.11 (\u0026plusmn;\u0026thinsp;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.37 (\u0026plusmn;\u0026thinsp;7.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.018*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocyte/Neutrophil ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.55 (\u0026plusmn;\u0026thinsp;4.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.68 (\u0026plusmn;\u0026thinsp;15.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.359\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophil/Monocyte ratio\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.62 (\u0026plusmn;\u0026thinsp;6.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.12 (\u0026plusmn;\u0026thinsp;41.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.009*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.42 (\u0026plusmn;\u0026thinsp;48.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99.79 (\u0026plusmn;\u0026thinsp;95.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.678\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eNote.\u003c/em\u003e Immunological parameters were measured in two different units: giga per liter (G/l) and percentage of blood serum. Calculating the ratio between two immunological parameters allowed us to know the ratio of overactivation of one parameter to that of another.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2.4 Immunological variables in acute phase as predictors of anosgnosia 69 months post- SARS-CoV-2 infection (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAn ROC curve analysis was performed on 52 of the 61 patients (anosognosic: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15; nosognosic: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;37), as we analyzed one measure of each immunological parameter, and nine patients who did not have all the immunological measures were therefore excluded. This analysis revealed that monocyte percentage in the total number of leukocytes (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.004) in the acute phase significantly predicted anosognosia 69 months post-infection. On the basis of the area under the curve for each of these variables, an area equivalent to .70 was considered good, such that only the percentage of monocytes was considered good (.755) with an estimated 95% confidence interval of [.614, .895] and a standard error of .072 (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The best cut-off for monocyte percentage was deemed to be the nearest score to .80 for sensitivity and the nearest score to .20 for 1-specificity, such that the best threshold for maximizing the avoidance of false positive and false negative errors was a monocyte percentage of 7.35%. The Youden test revealed that with 7.35% of monocytes, the ROC curve model (AUC\u0026thinsp;=\u0026thinsp;.755) was able to predict at best 74.3% of cases of anosognosia 69 months after Sars-CoV-2 infection. Interestingly, neither CRP nor basophil percentage predicted anosognosia and associated cognitive impairment.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eIn the present study, we found that the percentage of monocytes in the total number of leukocytes obtained in the acute phase of the disease (at hospital admission), discriminates and predicts anosognosic patients from their memory deficits in the chronic phase compared to nosognosic patients (6\u0026ndash;9 months after SARS-CoV-2 infection) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). ROC analyses revealed that SARS-CoV-2 infected patients with a mean proportion of blood circulating monocytes above 7.35% of leucocytes measured in the acute phase predicted the presence of anosognosia in the chronic phase with high sensitivity (80%) and specificity (80%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Finally, our results showed that CRP differentiated patients according to the severity of the disease, but the cognitive disorders marked by anosognosia in the long term were not associated with this inflammatory marker (SI A-B).\u003c/p\u003e \u003cp\u003eThe observation of different immunological profiles at the time of hospitalization among patients who exhibited anosognosia of memory functions 69 months after infection supports the hypothesis of indirect CNS damage mediated by immune phenomena\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e9\u003c/sup\u003e, which then fosters the development of long-term cognitive deficits\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e4, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e5\u003c/sup\u003e. SARS-CoV-2 infection may have induced a different immunological response balance in the group of post-COVID-19 long-term anosognosic patients.\u003c/p\u003e \u003cp\u003eOur study suggests that post-COVID-19 long-term anosognosia may be the result of an immune imbalance in the acute phase of SARS-CoV-2 infection, particularly in terms of leukocyte distribution. Among the parameters found, in addition to the percentage of monocytes among all leukocytes, we found that both the neutrophil/monocyte ratio and the neutrophil count (G/l) tend to be lower in the acute phase of SARS-CoV-2 infection in patients who will develop chronic anosognosia compared to nosognosic patients. Changes in blood neutrophil levels in association with neurocognitive semiology are currently discussed in neurodegenerative diseases (e.g. Alzhemeir)\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e and more recently in SARS-CoV-2\u003csup\u003e47,48\u003c/sup\u003e. The pro-NETotic effect of neutrophils would generate an innate immune response capable of containing different infectious agents such as SARS-CoV-2\u003csup\u003e49\u003c/sup\u003e. Anosognosic patients have fewer neutrophils (G/L) and a lower neutrophil to monocyte ratio during the acute phase of SARS-CoV-2 infection compared to nosognosic patients. Different immunological mechanisms may be involved in the fight against a viral agent like SARS-CoV2, both innate and adaptive immunity. Regarding innate immunity, patients who develop anosognosia would have a higher propensity to involve the monocyte/macrophage lineage while those who remain nosognosic would have a preponderance of their neutrophilic response. We can therefore hypothesise a different susceptibility of certain brain networks and cognitive processes according to the type of systemic inflammatory mechanism generated in a parainfectious context.\u003c/p\u003e \u003cp\u003eCongruent with our observations, studies focusing on the immunological phenomena induced by SARS-CoV-2 in the acute phase have shown distinct immune cascades in relation to premorbid factors intrinsic to the individual\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. Taken together with the present results, these distinct immuno-physiological combinations may help to explain the development of different trajectories in relation to post-COVID syndrome. An interesting and promising element in the understanding of the pathology is the phenomenon of hyperinflammation resulting from excessive production of pro-inflammatory factors\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Thus, cellular immunity and the production of inflammatory cytokines appear to persist in the subacute period (3 months post-infection), while inflammatory phenomena and cellular responses seem to persist 6 months post-infection. Conversely, the mechanisms of humoral immunity seem to decrease over time\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. In line with these inflammatory hypotheses, we showed that CRP and basophils can be used to distinguish between patients who end up in intensive care and those who remain in intermediate care in the acute phase, but do not predict or distinguish long-term cognitive impairment such as anosognosia. In relation with our findings Rhally, et al. \u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e show that increased CRP is associated with vascular inflammation and altered microstructural changes in the white matter. Therefore, the hypothesis of cognitive effects originating from systemic inflammation measurable by different inflammatory markers remains a central line of research in infectious contexts such as SARS-CoV-2. This interesting variation illustrates the observation that the severity of acute respiratory impairment is not a good predictor of long-term post-COVID-19 syndrome at least not its cognitive aspects\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eWe therefore showed here that specific acute immunological parameters can be used to understand long-term cognitive phenomena, in particular leukocytes variations marked by the percentage of monocytes as a predictor of anosognosia. Abnormally high levels of monocytes have already been observed in SARS-CoV-2\u003csup\u003e45,54\u003c/sup\u003e and have been associated with more severe disease outcomes (e.g., inflammatory amplification, impaired type I IFN production), but to our knowledge, they have never been associated with the development of cognitive impairment. Interestingly, previous studies in other pathologies have highlighted relationships between monocytic processes and cognition\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Studies in HIV have highlighted relationships between increased CD14 and poorer cognitive performance, including on a composite score on learning, memory, mental flexibility, verbal fluency and praxis tasks\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Studies in multiple sclerosis\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e and other neurodegenerative diseases (e.g., Alzheimer's disease or Parkinson's disease) have also shown an association between the overexpression of pro-inflammatory monocytes and decreased global cognitive performance\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Interestingly, encephalopathy has been observed in the acute phase of SARS-CoV-2 infection\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, and the persistence of cognitive deficits could partly be explained by this acute-phase episode, bearing in mind that some patients may not have had a specific diagnosis of SARS-CoV-2 encephalopathy. Previous research\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e has revealed immunopathological mechanisms roughly similar to the SARS-CoV-2 pattern in pneumonia-induced SAE. One of the key pathophysiological hypotheses concerning SAE is that the pro-inflammatory expression of monocytes can engender cognitive impairment in the long term\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Potentially relevant to SARS-CoV-2 infections, recent studies have shown that early intervention to limit pro-inflammatory monocyte proliferation in SAE can modulate long-term cognitive deficits\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. SARS-CoV-2-related immune responses\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e and the resulting cognitive deficits may therefore lie on the same continuum as the immune responses seen in pneumonia-induced SAE\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eReasonably, one of the targets of current research is aimed at a better understanding of the phenomenon of the long COVID syndrome. In an original way, we support the hypothesis that acute immunological variations have repercussions on cognition 6 to 9 months later. Several reflections related to the long COVID syndrome can be drawn from our results; on the one hand different immune variations could generate different cognitive deficits, here we show that the percentage of monocytes does predict the phenomenon of anosognosia of memory deficits but other leukocyte parameters (e.g. neutrophils) could also have effects on other cognitive processes than anosognosia\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. On the other hand, at a time when the number of people suffering from long COVID syndrome is increasing\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e,\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, our results suggest that it would be possible to plan neuropsychological follow-ups based on acute leukocyte markers as soon as patients infected by SARS-CoV-2 are hospitalised. The provision of these follow-ups would allow a better organisation of hospital structures and a more specialised support for patients.\u003c/p\u003e \u003cp\u003eFinally, as a predictive approach, recent studies have shown that SARS-CoV-2 infection may be a trigger for neurodegenerative pathologies (e.g., Alzheimer's disease), as well as a catalyst for neurodegenerative processes, just like other HCoVs\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. In our study, as well as in Voruz et al.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, we argue that the cognitive profiles of the anosognosic patients were very similar to those observed in Alzheimer's disease\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e, suggesting from a cognitive perspective a potential development of precursor to a neurodegenerative pathology. The mechanisms that trigger neurodegenerative pathologies are not yet well understood. However, one hypothesis suggests that neurodegenerative pathologies may be triggered by infiltration of the nervous system by microglia\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e following inflammatory responses. This hypothesis could be applied to SARS-CoV-2\u003csup\u003e44,62\u003c/sup\u003e. Thus, the high level of monocytes observed both in our study and in previous studies of patients with SARS-CoV-2\u003csup\u003e54\u003c/sup\u003e, could be a risk factor for the development of neurodegenerative processes. Future studies are needed to look for markers of neurodegenerative pathologies in patients infected with SARS-CoV-2.\u003c/p\u003e \u003cp\u003eIt should be noted that our study had several limitations. First, although no other study has yet attempted to link cognitive and immunological variables in SARS-CoV-2, and although we performed a power analysis to calculate the number of participants to include (see Section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026ldquo;Method\u0026rdquo;), our sample of 61 patients could be considered small. However, as we illustrated in section \u003cspan refid=\"Sec2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \"Method\", our power analysis on two conditions (i.e. Sepsis and HIV) that attempted to establish a link between cognition and immunology, revealed that we had sufficient participants in this cohort of SARS-CoV-2 infected patients. Second, our measure of anosognosia could be subject to debate\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Anosognosia is difficult to measure, despite important advances in its understanding in mild cognitive impairment and Alzheimer's disease\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. It can be measured (i) by the clinician, using a clinical assessment, (ii) as the discrepancy between the patient's subjective complaints and objective neuropsychological scores, or (iii) as the difference between the patient's complaints and the caregiver's assessment in terms of activities of daily living\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In our study, we used two measures of anosognosia (clinical assessment and calculation of self-appraisal discrepancy score SAD). Third, while we included patients free of relevant medical history before the infection and while we retrospectively extracted their physiological variables on admission to hospital, to avoid the effect of any treatment for SARS-CoV-2, their immunological characteristics may have be modulated by treatments taken beforehand.\u003c/p\u003e"},{"header":"4 Conclusion","content":"\u003cp\u003eWe conducted the first retrospective analysis to establish a relationship between immunological responses in the acute phase of SARS-CoV-2 infection and long-term cognitive deficits, 69 months after SARS-CoV-2 infection, including anosognosia for memory impairment. Our results could be of great importance in the future management of patients and for understanding the emergence of post-COVID-19 syndrome phenomenon. A high blood circulating monocyte proportion of leucocytes could be a predictor of post-COVID-19 neuropsychological syndrome, whereas disease severity in the acute phase is not predictive of long-term cognitive effects. These results open the door to new research on potential acute-phase treatments that could reduce the emergence of post-COVID neurocognitive syndrome.\u003c/p\u003e"},{"header":"5 Method","content":"\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e5.1 Participants (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/h2\u003e\n \u003cp\u003eThe sample comprised 61 patients with SARS-CoV-2 infection drawn from the COVID-COG cohort of Geneva University Hospitals (HUG), who were assessed 69 months after being admitted to hospital. We selected patients with no previous history of cognitive deficits or neuropsychiatric disease. Blood samples were collected from DATE-to DATE and no one single patient received anti-SARS-COV-2mAbs. Of these, 38 had had moderate symptoms (conventional hospitalization) in the acute phase, and 23 had had severe symptoms requiring a stay in intensive care unit (ICU) and intubation. SARS-CoV-2 infection was detected using a reverse transcription polymerase chain reaction (RT-PCR) test. This technique allows the N and E genes to be detected with the LightCycler 480 system (Roche, Switzerland). In rare cases, where PCR testing is not available for clinical reasons, intrathecal IgG synthesis has been used for diagnostic purposes and to confirm SARS-CoV-2 infection. For the purpose of the COVID-COG study, all patients completed a battery of neurological, neuropsychological and psychiatric tests and questionnaires 230.25\u0026thinsp;\u0026plusmn;\u0026thinsp;46.65 days following SARS-CoV-2 infection. For the present study, only sociodemographic data, clinical history, objective memory tests and self-reported cognitive complaints related to memory disorders were extracted.\u003c/p\u003e\n \u003cdiv class=\"Section3\" id=\"Sec8\"\u003e\n \u003ch2\u003e5.1.1 Subdivision of patients according to their anosognosia score.\u003c/h2\u003e\n \u003cp\u003ePatients were divided into two groups, according to their anosognosia for memory disturbances, measured 69 months after SARS-CoV-2 infection: 1) anosognosic for memory dysfunctions (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20), versus 2) nosognosic for memory functions/dysfunctions (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;41). This was therefore done independently of the severity of their respiratory symptoms in the acute phase of the disease (anosognosic: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;12 moderate and \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8 severe vs. nosognosic: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;26 moderate and \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;15 severe). Anosognosia was measured as follows: scores on the self-report Cognitive Complaints Questionnaire (QPC)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e2\u003c/sup\u003e were first standardized and divided into four categories: 0\u0026thinsp;=\u0026thinsp;normal behavior, 1\u0026thinsp;=\u0026thinsp;limited influence on daily life, 2\u0026thinsp;=\u0026thinsp;noticeable influence on daily life, and 3\u0026thinsp;=\u0026thinsp;substantial influence on daily life. Each standardized score on this subjective measure was then subtracted from the standardized scores on objective measures of memory. Short-term memory was assessed with forward digit spans\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e3\u003c/sup\u003e and the Corsi test\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e4\u003c/sup\u003e, and episodic memory with the 16-item free/cued recall (RL/RI 16) paradigm\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e5\u003c/sup\u003e and the delayed recall of the Rey-Osterrieth Complex Figure test\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e6\u003c/sup\u003e. The resulting self-appraisal discrepancy scores (SAD) could therefore range from \u0026minus;\u0026thinsp;3 to 3, with any score below 0 indicating anosognosia. For example, if a patient reported no memory disorders (QPC score\u0026thinsp;=\u0026thinsp;3) but performed very poorly on verbal episodic memory (RL/RI 16 delayed free recall test score\u0026thinsp;=\u0026thinsp;0), he or she was deemed to exhibit anosognosia for memory dysfunction (0\u0026ndash;3 = -3). Of note, the Behavior Rating Inventory of Executive Function - Adult Version (BRIEF-A)\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e7\u003c/sup\u003e was used to measure the validity of the patients\u0026apos; responses, as well as the presence of any noncredible symptoms. The method of subdivision of anosognosic versus nosognosic patients in this study follows the same procedure validated in Voruz et al.,\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section3\" id=\"Sec9\"\u003e\n \u003ch2\u003e5.1.2 Power analysis\u003c/h2\u003e\n \u003cp\u003eWe performed a power analysis of the number of participants required using the following equation: \u003cimg 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This calculation was based on previous studies that had examined the relationship between immunity and cognition in patients with HIV+) or SAE\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. Relying on previous power analyses for HIV+, 20 participants, with 10 per group (alpha\u0026thinsp;=\u0026thinsp;0.05, beta\u0026thinsp;=\u0026thinsp;0.2, and power\u0026thinsp;=\u0026thinsp;0.8) was the total number of participants required for the study. As we intended to use nonparametric statistical tests, we added 15% more participants to the initial number needed\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. We thus determined that the total number of participants required was 23 (i.e., 12 per group). Power calculations previously used for SAE yielded a total number of 34 persons. After adding the 15% owing to the use of nonparametric tests, we arrived at 39 persons (i.e., 19 persons per group; alpha\u0026thinsp;=\u0026thinsp;0.05, beta\u0026thinsp;=\u0026thinsp;0.2, and power\u0026thinsp;=\u0026thinsp;0.8).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"Section3\" id=\"Sec10\"\u003e\n \u003ch2\u003e5.1.3 Ethics\u003c/h2\u003e\n \u003cp\u003eAfter being given a full description of the study, participants provided their written informed consent. The study was conducted in accordance with the Declaration of Helsinki, and the study protocol was approved by the cantonal ethics committee of Geneva (CER-02186).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003e5.2 Retrospective extraction of acute-phase physiological parameters\u003c/h2\u003e\n \u003cp\u003eImmunological parameters were retrospectively extracted from HUG\u0026rsquo;s internal database. We only selected physiological parameters measured on admission to hospital (1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;3.41 days after a positive RT-PCR test for anosognosic patients versus 2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;3.50 days for nosognosic patients), to avoid any effect of subsequent medication and oxygen therapy. We also extracted hematological, and metabolic and cardiac parameters, as we knew that these variables might have an impact on cognition. can contribute significantly to the development of cognitive deficits in dementia\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e,\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Parameters were measured by the diagnostic department of HUG\u0026rsquo;s Gas Testing, Hematology and Virology Laboratory. All laboratory samples were taken with Piccolo Xpress (Sysmex, Switzerland) tools and an ABL blood gas analyzer (Radiometer RSCH GmbH, Switzerland) at HUG. The following leukocytes distribution parameters (venous blood) were extracted: percentage (%) and mass concentration (G/l) of lymphocytes, monocytes, basophils, eosinophils, and neutrophils. Only mass concentration (G/l) was extracted for leukocytes. Subsequently, based on previous studies in SARS-CoV-2\u003csup\u003e43\u003c/sup\u003e, the following ratios were calculated: lymphocyte/monocyte ratio [lymphocyte (G/l) divided by monocyte (G/l)], lymphocyte/neutrophil ratio [lymphocyte (G/l) divided by neutrophil (G/l)], neutrophil/monocyte ratio [neutrophil (G/l) divided by monocyte (G/l)]. Inflammation was also measured as C-reactive protein (CRP) (mg/l). Finally, we classified the patients according to the normal thresholds for each percentage of each immunological variable (we considered the normal range to be 33%80% for neutrophils, 0%5% for eosinophils, 0%2% for basophils, 0%9% for monocytes, and 15%60% for lymphocytes.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003e5.3 Other clinical variables (69 months post-infection)\u003c/h2\u003e\n \u003cdiv class=\"Section3\" id=\"Sec13\"\u003e\n \u003ch2\u003e5.3.1 Sociodemographic and clinical data\u003c/h2\u003e\n \u003cp\u003eIn addition to age, collected during the inclusion interview, we recorded patients\u0026rsquo; sex, handedness, and education level. To complement information about previous neurological, psychiatric, and developmental conditions and cancer collected during the inclusion interview, we asked patients about previous cardiovascular disease, respiratory disorders, immunosuppression status, sleep apnea syndrome, diabetes, and smoking. Participants were asked to describe the symptoms they had experienced, both during the acute phase of the infection and currently (69 months post-infection), and the number of days they had spent in hospital, where relevant.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec14\"\u003e\n \u003ch2\u003e5.4 Statistical analysis\u003c/h2\u003e\n \u003cp\u003eGiven the nonparametric distribution of our dataset, intergroup (anosognosic vs. nosognosic) analyses on sociodemographic and immunological variables were performed with nonparametric MannWhitney \u003cem\u003eU\u003c/em\u003e tests for continuous data and chi-square tests for categorical variables, with a significance threshold of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.05 false discovery rate (FDR) corrected. Moreover, a receiver operating characteristic (ROC) analysis was performed to identify the acute immunological variable(s) predictive of anosognosia 69 months after infection. For significant variables, a Youden test was performed to determine the best cut-off. Finally, to explore intergroup (intermediate vs. intensive care) differences, we also performed nonparametric MannWhitney \u003cem\u003eU\u003c/em\u003e tests for continuous data and chi-square tests for binary categorical variables, with a significance level of \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 FDR corrected. All analyses were performed with SPSS statistical version 28.0.1. These analyses and their results are provided in Supplementary Information (Table\u0026nbsp;1.\u003csub\u003e1\u003c/sub\u003e and Table 1.\u003csub\u003e2\u003c/sub\u003e)\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ecentral nervous system (CNS), human immunodeficiency virus (HIV), human coronavirus (HCoV), intensive care unit (ICU), Cognitive Complaints Questionnaire (QPC), Behavior Rating Inventory of Executive Function - Adult Version (BRIEF-A), receiver operating characteristic (ROC), C-reactive protein (CRP), sepsis-associated encephalopathy (SAE), reverse transcription polymerase chain reaction (RT-PCR), false discovery rate (FDR), Area under the curve (AUC)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present research was supported by Swiss National Science Foundation (SNSF) funding to JAP (PI) and FA (Co-PI) within the framework of the COVID-19 National Research Program (NRP 78; grant no. 407840_198438, RNP 78).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors report no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNonsensitive COVID-COG data will be made available at the end of the project in open access on a dedicated platform.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlemanno, F. \u003cem\u003eet al.\u003c/em\u003e COVID-19 cognitive deficits after respiratory assistance in the subacute phase: A COVID-rehabilitation unit experience. 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Frontiers in Behavioral Neuroscience \u003cb\u003e12\u003c/b\u003e, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fnbeh.2018.00100\u003c/span\u003e\u003c/span\u003e (2018).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"anosognosia, immunology, monocytes, cognition, neuropsychology, SARS-CoV-2, post-COVID-19 syndrome","lastPublishedDoi":"10.21203/rs.3.rs-1361211/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1361211/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAltered awareness of neuropsychological disorders (i.e., anosognosia) is a striking symptom of post-COVID-19 syndrome. Some leukocytes markers in the acute phase might predict the presence of anosognosia in the chronic phase, but they have not been identified yet. This study aims to determine whether patients with anosognosia for their memory deficits in the chronic phase present specific leukocytes distribution in the acute phase, and if so, whether these leukocytes parameters could predict this anosognosia.\u003c/p\u003e \u003cp\u003eFirst, we compare the acute immunological data of the leukocytes distribution of 20 patients infected with SARS-Cov-2 who displayed anosognosia 69 months after SARS-Cov-2 infection (230.25\u0026thinsp;\u0026plusmn;\u0026thinsp;46.65 days) versus 41 patients infected with SARS-Cov-2 without developing anosognosia. Second, we performed a ROC analysis to evaluate the predictive value of the leukocytes markers that emerged from this comparison.\u003c/p\u003e \u003cp\u003eBlood circulating monocytes (%) at the acute phase of SARS-CoV2 infection is associated with long term post-COVID-19 anosognosia. Finally, serology on admission showing a percentage rate of monocytes of 7.35% of the total number of leukocytes, seems to predict the presence of chronic anosognosia for 6\u0026ndash;9 months after infection.\u003c/p\u003e","manuscriptTitle":"Monocytosis in the Acute Phase of SARS-CoV-2 Infection Predicts the Presence of Anosognosia for Cognitive Deficits in the Chronic Phase","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-02 20:39:21","doi":"10.21203/rs.3.rs-1361211/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"14e1400c-19e0-4b41-bcb2-5bda97bb4368","owner":[],"postedDate":"March 2nd, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-01-13T15:04:06+00:00","versionOfRecord":{"articleIdentity":"rs-1361211","link":"https://doi.org/10.1016/j.bbih.2022.100511","journal":{"identity":"brain-behavior-and-immunity-health","isVorOnly":true,"title":"Brain, Behavior, \u0026 Immunity - Health"},"publishedOn":"2022-09-26 00:00:00","publishedOnDateReadable":"September 26th, 2022"},"versionCreatedAt":"2022-03-02 20:39:21","video":"","vorDoi":"10.1016/j.bbih.2022.100511","vorDoiUrl":"https://doi.org/10.1016/j.bbih.2022.100511","workflowStages":[]},"version":"v1","identity":"rs-1361211","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1361211","identity":"rs-1361211","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}