COVID-19 infection and 2-year mortality in nursing home residents who survived the first wave of the pandemic

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Residents who survived the COVID-19 infection may have become frailer. This study aimed to determine the predictive value of having a COVID-19 infection during the 1st CoPW for 2-year mortality in NH residents. Methods This was a retrospective study conducted in three NHs. Residents who had survived the 1st CoPW (March to May 2020) were included. The diagnosis of COVID-19 was based on the results of a positive reverse transcriptase-polymerase chain reaction test. The collected data also included age, sex, length of residence in the NH, disability status, legal guardianship status, nutritional status, need for texture-modified food and hospitalization during lockdown. Nonadjusted and adjusted Cox models were used to analyse factors associated with 2-year post-1st CoPW mortality. Results Among the 315 CoPW1 survivors (72% female, mean age 88 years, 48% with severe disability), 35% presented with COVID-19. Having a history of COVID-19 was not associated with 2-year mortality: hazard ratio (HR) [95% confidence interval] = 0.96 [0.81–1.13], p = 0.62. The factors independently associated with 2-year mortality were older age (for each additional year, HR = 1.05 [1.03–1.08], p < 0.01), severe disability vs moderate or no disability (HR = 1.35 [1.12–1.63], p < 0.01) and severe malnutrition vs no malnutrition (HR = 1.29 [1.04–1.60], p = 0.02). Conclusions Having survived a COVID-19 infection during the 1st CoPW did not affect subsequent 2-year survival in older adults living in NHs, suggesting that most of these residents recovered from the infection without COVID-19-related life-threatening sequelae. COVID-19 Long-term mortality Nursing Homes Older Adults Figures Figure 1 Figure 2 Background Nursing home (NH) residents were seriously affected by the first wave of the COVID-19 pandemic (1st CoPW) ( 1 – 3 ). The older population is at risk for severe clinical forms of COVID-19 and increased mortality ( 4 ), and survivors are likely to experience a decline in their health status. Among NH survivors of the 1st CoPW, COVID-19-positive residents had a 4-fold greater chance of developing frailty than noninfected residents did ( 5 ). COVID-19 was also identified as an independent risk factor for weight loss during the 1st CoPW ( 6 ). Similarly, in older patients admitted to acute geriatric wards for COVID-19, 3 months of follow-up showed functional decline and worsening frailty status compared to their preadmission status ( 7 ). Similar findings were reported in COVID-19 patients in intensive care wards ( 8 , 9 ). Post-COVID-19 functional decline, frailty and malnutrition can be expected to impact subsequent mortality. However, in NHs, long-term mortality in COVID-19 survivors has received little attention. A better understanding of the prognostic value of a history of COVID-19 would allow for the adoption of care in this specific population. To the best of our knowledge, in NHs, only one study compared mortality between COVID-19-positive and COVID-19-negative survivors of COVID-19 in the 1st CoPW: the 6-month mortality risk did not differ between groups ( 10 ). The main objective of this study was to determine the impact of having survived a COVID-19 infection during the 1st CoPW in NH, as opposed to having survived the 1st CoPW without contracting a COVID-19 infection, on 2-year mortality. The secondary objective was to determine whether other characteristics of the residents were associated with 2-year mortality. Methods Study design and ethics This retrospective study was conducted in three NHs in the Paris area (France). Residents who survived the 1st CoPW (March to May 2020) were included. The diagnosis of COVID-19 was based on the results of a positive reverse transcriptase-polymerase chain reaction test. The collected data also included age, sex, disability status, legal guardianship status, need for texture-modified food, nutritional status, and hospitalization during lockdown. Nonadjusted and adjusted Cox models were used to analyse factors associated with 2-year post-1st CoPW mortality. We conducted a retrospective multicentre observational study with a 2-year survival analysis. This ancillary study included the participants of our previously published study that aimed to assess the impact of COVID-19 and lockdown sanitary restrictions on weight loss in NH residents ( 6 ). Residents from 3 NHs were included at the end of the 1st CoPW in May 2020 after receiving written information and expressing any opposition. Residents under guardianship were included on the condition that their guardian was informed and did not express opposition. The inclusion criteria were (I) being a resident of one of the three NHs during the first pandemic wave (from March 11th to May 11 th, 2020); (II) having survived to the 1st CoPW having contracted the COVID-19 or not; and (III) having information on nutritional status before and after the pandemic wave. Supplementary Table 1 shows the main characteristics of the three nursing homes at the time of the study. The study protocol was reviewed and approved by the Gérontopôle d’Ile-de-France Ethics Committee (approval number: 22021). Data collection The investigator collected the characteristics of the participants from the computerized database of each NH. Due to the retrospective design of the study, the number of variables that could be collected, and thus, the assessment of potential confounding factors such as comorbidities or the severity of COVID-19 was limited. COVID-19 status was determined using reverse transcription‒polymerase chain reaction (RT‒PCR). We also recorded age, sex, length of residence in the NH, being under legal guardianship (considered a proxy for severe cognitive or psychiatric disorders), malnutrition according to the Global Leadership Initiative on Malnutrition (GLIM) criteria ( 11 ), based on weight loss during the 1st CoPW and BMI at the end of the lockdown, texture-modified food (minced or pureed food, considered as a proxy of dysphagia) and impairment in activities of daily living using the Groupe Iso Ressource (GIR) score ( 12 ). The GIR is a French administrative score system that assesses basic activities of daily living (walking, feeding, dressing, washing, and urinary and faecal continence) and more complex activities (perception of time and place, managing medication, shopping and finances and using a telephone). The GIR can vary from 1 (bed-ridden or major physical and mental limitations requiring assistance in all daily living activities) to 6 (no disability). We categorized participants who scored GIR 1 and 2 as severely disabled and participants who scored GIR ≥ 3 as moderately disabled or having no disability. Participants’ ability to self-feed was rated as follows: no assistance, the need for close supervision (stimulation and verbal encouragement at mealtimes) and full assistance (direct physical assistance from caregivers at mealtimes). Disability status was not reassessed after the 1st CoPW. Participants’ medical records were unavailable because residents were cared for by their community general practitioners, and the medical records were not saved in the NH databases. Thus, some clinical data were missing, including the specific listing of comorbidities, medications or COVID-19 infection severity. However, hospital admissions for any reason were collected by cross-referencing the NH database with the admission database of the referral hospitals. The 2-year mortality data collection started after the end of the 1st CoPW, from May 11th, 2020, to July 15th, 2022, when the NH database, the referral hospital records and the civil register were collected. The maximum follow-up time was 26 months. Statistical analyses Resident characteristics at the end of the lockdown were described by numbers (percentages, %) for categorical variables and means (standard deviations, SDs) for quantitative variables. The baseline characteristics were compared according to survival during the 2-year follow-up. After visual verification, because the sample size was greater than 30 individuals per group, we assumed that the distribution of continuous variables followed a normal distribution pattern. Continuous variables were compared using Student’s t test. Categorical variables were compared using the chi-square test, Yates continuity correction test, or Fisher’s exact test. Kaplan Meier curves were generated to analyse survival during the 2-year follow-up stratified by COVID-19 status at the time of the 1st CoPW. The curves were compared by the log-rank or Wilcoxon test as appropriate. A Cox model was used to analyse the associations between variables and survival before and after adjustment. The adjusted model included the variables associated with 2-year mortality in the unadjusted analysis (p < 0.20) and less than 10% of the data were missing. The centre was added to the model. The results are presented as hazard ratios (HRs) with 95% confidence intervals (95% CIs). The level of statistical significance was defined as p < 0.05. Analyses were performed using JMP 9.0.3 (SAS Software®). Results Three hundred and fifteen residents who were alive at the end of the first PW were included in the study (flow chart in Fig. 1 ). Among them, 111 (35%) contracted COVID-19 during the first wave of the pandemic. The median (Q1; Q3) follow-up was 24 (12; 25) months after the end of the lockdown. During this period, 145 (46%) residents died (mortality rate of 26 per 100 residents per year). The characteristics of the total population and the survival data collected during the follow-up are summarized in Table 1 . Compared to those who survived afterwards, the residents who died during the follow-up were significantly older, had greater disability according to the GIR, required more frequently texture-modified food, had a lower BMI and experienced significantly greater weight loss during the first PW, resulting in more prevalent severe malnutrition according to the GLIM criteria. Table 1 Characteristics of first COVID-19 pandemic wave surviving residents and 2-year mortality MD Total Population N = 315 2-year mortality Yes N = 145 No N = 170 P Before 1stCoPW Female sex 226 (72) 102 (70) 124 (73) 0.61 Age (years) 88 ± 8 90 ± 8 86 ± 8 < 0.01 Length of stay in the NH (months) 55 ± 32 54 ± 32 56 ± 31 0.50 Disability 2 Moderate-none 164 (52) 55 (38) 109 (65) < 0.01 severe 149 (48) 89 (62) 60 (35) Legal guardianship 12 115 (38) 56 (42) 59 (35) 0.22 Texture-modified food 59 114 (45) 66 (60) 48 (33) < 0.01 End of the 1stCoPW COVID-positive 111 (35) 48 (33) 63 (37) 0.46 Malnutrition 5 no 147 (47) 54 (38) 93 (56) < 0.01 moderate 75 (25) 32 ( 22 ) 43 (26) severe 88 (28) 57 (40) 31 ( 18 ) Hospitalization for any cause 34 17 ( 6 ) 6 ( 5 ) 11 ( 7 ) 0.35 1stCoPW: first COVID-19 pandemic wave; MD: Missing data; NH: Nursing home. The results are expressed as the means ± SDs or counts (%). Student’s t test and the chi-square test were used to compare the characteristics of the participants according to 2-year mortality. Figure 2 presents Kaplan‒Meier curves for 2-year survival as a function of having a history of COVID-19 during the 1st CoPW1 or not. The associations with 2-year survival according to the nonadjusted and adjusted Cox models are presented in Table 2 . A history of COVID-19 infection and survival during Co1stPW were not associated with excess 2-year mortality (HR [95% CI] 0.96 [0.80–1.13], p = 0.62). Factors associated with 2-year mortality in the unadjusted Cox model were older age, severe disability, requiring texture-modified food and severe malnutrition after the lockdown. According to the adjusted Cox model (including age, disability, legal guardianship, malnutrition and centre), older age (1.05 [1.03–1.08], p < 0.01), severe disability (1.35 [1.12–1.63], p < 0.01) and severe malnutrition (1.29 [1.04–1.60], p = 0.02) were independently associated with poorer survival. A trend toward higher mortality was observed in the case of legal guardianship (1.19 [0.99–1.43], p = 0.06). Table 2 Associations between the characteristics of residents and 2-year mortality 2-year mortality Unadjusted HR (95% CI) P Adjusted HR (95% CI) P Female sex 0.93 (0.78–1.12) 0.46 - Age (years) 1.06 (1.03–1.08) < 0.01 1.05 (1.03–1.08) < 0.01 Length of stay in the nursing home (months) 1.00 (0.99–1.00) 0.37 - Severe disability (vs moderate or no disability) 1.43 (1.21–1.70) < 0.01 1.35 (1.12–1.63) < 0.01 Legal guardianship 1.15 (0.96–1.36) 0.13 1.19 (0.99–1.43) 0.06 Texture-modified food (vs normal) 1.48 (1.23–1.80) < 0.01 - COVID-positive 0.96 (0.81–1.13) 0.62 Malnutrition (vs no malnutrition) moderate malnutrition 1.09 (0.87–1.36) 0.43 - severe malnutrition 1.59 (1.32–1.91) < 0.01 1.29 (1.04–1.60) 0.02 Hospitalization for any causes during lockdown 0.87 (0.55–1.26) 0.50 - Associations between the characteristics of residents and 2-year mortality were tested using Cox models. The adjusted Cox model included age, disability, legal guardianship, severe malnutrition and centre. The results are expressed as hazard ratios (HRs) and 95% confidence intervals (95% CIs). For the variables age and length of stay in the nursing home, the HR was calculated for a one-unit increase. Discussion This study revealed that in NH residents who had survived the 1st CoPW, having a history of COVID-19 during the 1st CoPW did not affect 2-year mortality. Independent risk factors for 2-year mortality were increasing age, severe disability and severe malnutrition. Increasing age, disability and malnutrition have consistently been associated with increased mortality in older adults, in the community, in the hospital and in NHs ( 13 – 15 ). The finding that having a history of COVID-19 had no impact on 2-year mortality in NH 1st CoPW survivors is intriguing. The 1st CoPW COVID-19-positive survivors were older and more often severely disabled before the 1st CoPW and were more often severely malnourished at the end of the 1st CoPW than were the noninfected survivors (Table 1 ). Only age, severe disability and severe malnutrition were risk factors for 2-year mortality according to both univariate and multivariate analyses. Both groups would have suffered equally from the consequences of the lockdown, leading to social isolation, disorganization of the facilities and poorer healthcare. This suggests that once the COVID-19 infection is resolved and the patient has survived, it has no further impact on subsequent survival. Our results are in line with a previously published study on NHs ( 10 ) and extend data on follow-up to two years. Interestingly, the survival curves were superposable and linear in both groups, suggesting that the four subsequent COVID-19 pandemic waves (observed in France as follows: the 2nd wave between August 1st, 2020, and December 31st, 2020; the 3rd wave between January 1st, 2021, and June 30th, 2021; the 4th wave between July 1st, 2021, and December 31st, 2021; and the 5th Omic wave between January 1st and 31st, 2022) and the vaccination program (starting on December 27th, 2020, in the French NH) had no impact on the mortality rate in either group over the 2-year follow-up. In our study, the mortality rate could not be compared to that of the previous 1st CoPW years. However, in the United Kingdom (UK), for people aged ≥ 75 years living in care homes, mortality rates were not compared between COVID-19-positive and COVID-19-negative residents but doubled from March 2020 to June 2020 when compared to the five-year average (excluding 2020) and then returned to average, with no meaningful variation, from June 2020 to December 2022 ( 16 ). This is very different from the overall UK mortality rate, where as in many countries, excess mortality persisted after the 1st CoPW up to 2023 ( 17 ). Likewise, in the United States of America, large increases in mortality due to Alzheimer’s disease and related dementias, which are underlying or contributing causes of death, occurred in COVID-19 pandemic year 1 but were largely mitigated in pandemic year 2 ( 18 ). The most pronounced declines were observed for deaths in nursing home/long-term care settings; conversely, excess deaths at home and in medical facilities remained high in year 2 ( 18 ). Thus, the observed stability of the mortality rate after the 1st CoPW was reached is in accordance with other data. The lack of impact of COVID-19 infection on subsequent mortality in NHs remains difficult to explain. The first hypothesis would be that surviving COVID-19 infection in the 1st CoPW conferred some COVID-19 immunity for a few months before the first vaccination campaign; this could have resulted in a lower mortality (as compared to not previously infected residents) during the second pandemic wave (August 2020 – late December 2021). However, in an unvaccinated population in Denmark, two rounds of nationwide PCR testing separated by 6 months showed that protection against a new COVID-19 infection was 80.5% in the general population but 47.1% in people aged 65 and older ( 19 ). The immunity from a first COVID-19 infection may be even lower in older institutionalized adults ( 20 ). The second hypothesis was that the survivors of COVID-19 were less severely burdened with comorbidities (data that could not be collected in our study) than were those who died and those who survived the 1st CoPW without COVID-19. The deleterious effect of COVID-19 on nutritional and frailty status ( 5 – 7 ) could be somewhat counterbalanced by a lower disease burden in survivors. In hospitalized all-age COVID-19 patients, the risk of mortality is strongly influenced by chronic diseases, which are also common in NH residents ( 21 ). However, in geriatric acute care wards for older patients with COVID-19, the Charlson comorbidity index was not associated with in-hospital mortality, while disability was the only preexisting condition that was associated with in-hospital mortality ( 22 ). Furthermore, in NHs, comorbidities have been extensively described but were not associated with 30-day or 6-month COVID-19 mortality or with mortality risk after COVID-19 infection ( 10 ). The reason why comorbidities were not associated with mortality in older COVID-19 patients remains to be explained. It may be that the severity of the disease and the impact of the disease on disability are much stronger risk factors for mortality than the etiology of the disease itself. The third hypothesis is that COVID-19 may have selected for survival in a population that was initially more physically/psychologically resilient, as defined by the ability to recover in the face of disease, a concept that goes beyond the concept of physical frailty ( 23 ). The results of our study must be interpreted with regard to methodological limitations. First, this was an observational study that did not allow any conclusions to be drawn on the causal relationships between the assumed risk factors and mortality. Second, its retrospective design limited the number of variables that could be collected, and thus, the assessment of potential confounding factors such as comorbidities or the severity of COVID-19 could not be performed. In particular, disability status was not assessed after the 1st CoPW, and we used the pre1st CoPW as a potential confounding factor for post-1st CoPW mortality. Third, we were not able to document the cause of death during the 2-year follow-up. Conclusions Our study revealed that having a history of COVID-19 during the first CoPW and surviving were not associated with subsequent 2-year excess mortality in NH residents. Our data suggest that high levels of frailty and comorbidities, such as severe disability, cognitive disorders, dysphagia or severe malnutrition, are independently associated with reduced life expectancy in the context of the pandemic. Healthcare professionals should still consider these factors to be strong predictors of the risk of death to propose specific and individualized interventions for NH residents. Abbreviations 1st CoPW: first COVID-19 pandemic wave BMI: body mass index GIR: groupe iso ressource GLIM: global leadership initiative on malnutrition HR: hazard ratio NH: nursing home RT-PCR: reverse-transcription polymerase chain reaction SD: standard deviation Declarations Ethics approval and consent to participate The study protocol was reviewed and approved by the Gérontopôle d’Ile-de-France Ethics Committee (approval number: 22021). In accordance with French ethical requirements for retrospective studies, each participant or legal guardian was informed of the study by mail and asked to consent to the use of the data within one month. In case of refusal to participate expressed by a phone call or a return mail, the participants were excluded from the study. Consent for publication Not applicable Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests Funding No funding Authors' contributions MS, PCA, VH and ARS designed the study. VH, HA and CC collected data in nursing homes. MS and PCA performed statistical analysis. MS, PCA, and ARS contributed in writing the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable References Team EPHE, Danis K, Fonteneau L, Georges S, Daniau C, Bernard-Stoecklin S, et al. High impact of COVID-19 in long-term care facilities, suggestion for monitoring in the EU/EEA, May 2020. Euro June. 2020;25(22):2000956. Graham NSN, Junghans C, Downes R, Sendall C, Lai H, McKirdy A, et al. SARS-CoV-2 infection, clinical features and outcome of COVID-19 in United Kingdom nursing homes. 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Cite Share Download PDF Status: Published Journal Publication published 01 Aug, 2024 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Revision requested 30 May, 2024 Reviews received at journal 11 Apr, 2024 Reviews received at journal 08 Apr, 2024 Reviewers agreed at journal 29 Mar, 2024 Reviewers agreed at journal 29 Mar, 2024 Reviewers invited by journal 29 Mar, 2024 Editor assigned by journal 25 Mar, 2024 Editor invited by journal 21 Mar, 2024 Submission checks completed at journal 21 Mar, 2024 First submitted to journal 16 Mar, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Sanchez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIie3PLQvCQBjA8UeEpYH15EA/gXBDmAjTfZWNwdIUo91gmX2gH0KTCIYTwTRdPdBgWjIsGha8qfgSvGkz3B/upfzuBUAm+9t611nhwwBAfOnnEvIg7o2EP5B1PqkNtxuUEDBL40F8TNKo2sAjCqvlZ6KHXbccELCDw6ahBepeW0x2FtBYQKinY5WABcxTsIr2hSnzSDGhAhKddJzyh1UzkpKdmRGgIsL4Lfz72eEKBovaX5BTvekTZM+Yq5d96jiLoGtRIYk8jZ37hllhTozOabs1R53VUUTuoeeWgAr54K2MyGQymey1Cy4aVMvOQW7HAAAAAElFTkSuQmCC","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":true,"prefix":"","firstName":"Manuel","middleName":"","lastName":"Sanchez","suffix":""},{"id":283678595,"identity":"0f3eb038-93b9-44d8-9f1a-8e2d0930054d","order_by":1,"name":"Pauline Courtois-Amiot","email":"","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Pauline","middleName":"","lastName":"Courtois-Amiot","suffix":""},{"id":283678596,"identity":"f51f679f-d0cd-4905-899b-162d447eafa7","order_by":2,"name":"Vincent Herrault","email":"","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Vincent","middleName":"","lastName":"Herrault","suffix":""},{"id":283678597,"identity":"d71fef55-176d-4f88-850f-29a8fc13e0be","order_by":3,"name":"Hélène Allart","email":"","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Hélène","middleName":"","lastName":"Allart","suffix":""},{"id":283678598,"identity":"18451446-7816-4eb6-bfa3-b49785da8cf5","order_by":4,"name":"Philippe Eischen","email":"","orcid":"","institution":"Fondation Roguet Nursing Home","correspondingAuthor":false,"prefix":"","firstName":"Philippe","middleName":"","lastName":"Eischen","suffix":""},{"id":283678599,"identity":"64180671-0982-4888-a847-774455a2cd23","order_by":5,"name":"Fabienne Chetaille","email":"","orcid":"","institution":"Les Artistes de Batignolles Nursing Home","correspondingAuthor":false,"prefix":"","firstName":"Fabienne","middleName":"","lastName":"Chetaille","suffix":""},{"id":283678600,"identity":"1a452267-a58e-4e28-9f75-54771c3f1464","order_by":6,"name":"Denise Lepineux","email":"","orcid":"","institution":"Fondation COS Jacques Barrot Nursing Home","correspondingAuthor":false,"prefix":"","firstName":"Denise","middleName":"","lastName":"Lepineux","suffix":""},{"id":283678601,"identity":"ff801ac1-3c45-44e3-9ea4-39f54cde8674","order_by":7,"name":"Castille Cathelineau","email":"","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Castille","middleName":"","lastName":"Cathelineau","suffix":""},{"id":283678602,"identity":"d81ee0fb-2e1a-40c5-967f-f80994052c39","order_by":8,"name":"Agathe Raynaud-Simon","email":"","orcid":"","institution":"AP-HP, Bichat and Beaujon University Hospitals","correspondingAuthor":false,"prefix":"","firstName":"Agathe","middleName":"","lastName":"Raynaud-Simon","suffix":""}],"badges":[],"createdAt":"2024-03-16 10:14:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4112561/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4112561/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-024-05220-w","type":"published","date":"2024-08-01T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53469768,"identity":"e9fc5697-2ec2-43e2-b41b-9b1d830b5ba7","added_by":"auto","created_at":"2024-03-26 11:17:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":108447,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow-chart\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"sanchezetalfigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4112561/v1/302748a0f5a6ca24eb407cfd.png"},{"id":53469767,"identity":"feba388f-a7bb-4c16-a884-665fe8614a2c","added_by":"auto","created_at":"2024-03-26 11:17:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":151055,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan‒Meier curves for survival during follow-up stratified by COVID‒19 status during the first wave of the pandemic\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Sanchezetal.Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4112561/v1/bc012bdb152f761eb195cba6.png"},{"id":61793529,"identity":"a5ddecc3-aba8-4450-8e69-d233368b8350","added_by":"auto","created_at":"2024-08-05 16:13:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":789851,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4112561/v1/590ba600-d3c5-40e9-b701-4ce7be44c04e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"COVID-19 infection and 2-year mortality in nursing home residents who survived the first wave of the pandemic","fulltext":[{"header":"Background","content":"\u003cp\u003eNursing home (NH) residents were seriously affected by the first wave of the COVID-19 pandemic (1st CoPW) (\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). The older population is at risk for severe clinical forms of COVID-19 and increased mortality (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), and survivors are likely to experience a decline in their health status. Among NH survivors of the 1st CoPW, COVID-19-positive residents had a 4-fold greater chance of developing frailty than noninfected residents did (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). COVID-19 was also identified as an independent risk factor for weight loss during the 1st CoPW (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Similarly, in older patients admitted to acute geriatric wards for COVID-19, 3 months of follow-up showed functional decline and worsening frailty status compared to their preadmission status (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Similar findings were reported in COVID-19 patients in intensive care wards (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePost-COVID-19 functional decline, frailty and malnutrition can be expected to impact subsequent mortality. However, in NHs, long-term mortality in COVID-19 survivors has received little attention. A better understanding of the prognostic value of a history of COVID-19 would allow for the adoption of care in this specific population. To the best of our knowledge, in NHs, only one study compared mortality between COVID-19-positive and COVID-19-negative survivors of COVID-19 in the 1st CoPW: the 6-month mortality risk did not differ between groups (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main objective of this study was to determine the impact of having survived a COVID-19 infection during the 1st CoPW in NH, as opposed to having survived the 1st CoPW without contracting a COVID-19 infection, on 2-year mortality. The secondary objective was to determine whether other characteristics of the residents were associated with 2-year mortality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and ethics\u003c/h2\u003e \u003cp\u003eThis retrospective study was conducted in three NHs in the Paris area (France). Residents who survived the 1st CoPW (March to May 2020) were included. The diagnosis of COVID-19 was based on the results of a positive reverse transcriptase-polymerase chain reaction test. The collected data also included age, sex, disability status, legal guardianship status, need for texture-modified food, nutritional status, and hospitalization during lockdown. Nonadjusted and adjusted Cox models were used to analyse factors associated with 2-year post-1st CoPW mortality.\u003c/p\u003e \u003cp\u003eWe conducted a retrospective multicentre observational study with a 2-year survival analysis. This ancillary study included the participants of our previously published study that aimed to assess the impact of COVID-19 and lockdown sanitary restrictions on weight loss in NH residents (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Residents from 3 NHs were included at the end of the 1st CoPW in May 2020 after receiving written information and expressing any opposition. Residents under guardianship were included on the condition that their guardian was informed and did not express opposition. The inclusion criteria were (I) being a resident of one of the three NHs during the first pandemic wave (from March 11th to May 11\u003csup\u003eth,\u003c/sup\u003e 2020); (II) having survived to the 1st CoPW having contracted the COVID-19 or not; and (III) having information on nutritional status before and after the pandemic wave. Supplementary Table\u0026nbsp;1 shows the main characteristics of the three nursing homes at the time of the study. The study protocol was reviewed and approved by the \u003cem\u003eG\u0026eacute;rontop\u0026ocirc;le d\u0026rsquo;Ile-de-France\u003c/em\u003e Ethics Committee (approval number: 22021).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eThe investigator collected the characteristics of the participants from the computerized database of each NH. Due to the retrospective design of the study, the number of variables that could be collected, and thus, the assessment of potential confounding factors such as comorbidities or the severity of COVID-19 was limited. COVID-19 status was determined using reverse transcription‒polymerase chain reaction (RT‒PCR). We also recorded age, sex, length of residence in the NH, being under legal guardianship (considered a proxy for severe cognitive or psychiatric disorders), malnutrition according to the Global Leadership Initiative on Malnutrition (GLIM) criteria (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), based on weight loss during the 1st CoPW and BMI at the end of the lockdown, texture-modified food (minced or pureed food, considered as a proxy of dysphagia) and impairment in activities of daily living using the \u003cem\u003eGroupe Iso Ressource\u003c/em\u003e (GIR) score (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The GIR is a French administrative score system that assesses basic activities of daily living (walking, feeding, dressing, washing, and urinary and faecal continence) and more complex activities (perception of time and place, managing medication, shopping and finances and using a telephone). The GIR can vary from 1 (bed-ridden or major physical and mental limitations requiring assistance in all daily living activities) to 6 (no disability). We categorized participants who scored GIR 1 and 2 as severely disabled and participants who scored GIR\u0026thinsp;\u0026ge;\u0026thinsp;3 as moderately disabled or having no disability. Participants\u0026rsquo; ability to self-feed was rated as follows: no assistance, the need for close supervision (stimulation and verbal encouragement at mealtimes) and full assistance (direct physical assistance from caregivers at mealtimes). Disability status was not reassessed after the 1st CoPW. Participants\u0026rsquo; medical records were unavailable because residents were cared for by their community general practitioners, and the medical records were not saved in the NH databases. Thus, some clinical data were missing, including the specific listing of comorbidities, medications or COVID-19 infection severity. However, hospital admissions for any reason were collected by cross-referencing the NH database with the admission database of the referral hospitals.\u003c/p\u003e \u003cp\u003eThe 2-year mortality data collection started after the end of the 1st CoPW, from May 11th, 2020, to July 15th, 2022, when the NH database, the referral hospital records and the civil register were collected. The maximum follow-up time was 26 months.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eResident characteristics at the end of the lockdown were described by numbers (percentages, %) for categorical variables and means (standard deviations, SDs) for quantitative variables. The baseline characteristics were compared according to survival during the 2-year follow-up. After visual verification, because the sample size was greater than 30 individuals per group, we assumed that the distribution of continuous variables followed a normal distribution pattern. Continuous variables were compared using Student\u0026rsquo;s t test. Categorical variables were compared using the chi-square test, Yates continuity correction test, or Fisher\u0026rsquo;s exact test.\u003c/p\u003e \u003cp\u003eKaplan Meier curves were generated to analyse survival during the 2-year follow-up stratified by COVID-19 status at the time of the 1st CoPW. The curves were compared by the log-rank or Wilcoxon test as appropriate. A Cox model was used to analyse the associations between variables and survival before and after adjustment. The adjusted model included the variables associated with 2-year mortality in the unadjusted analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.20) and less than 10% of the data were missing. The centre was added to the model. The results are presented as hazard ratios (HRs) with 95% confidence intervals (95% CIs). The level of statistical significance was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Analyses were performed using JMP 9.0.3 (SAS Software\u0026reg;).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThree hundred and fifteen residents who were alive at the end of the first PW were included in the study (flow chart in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among them, 111 (35%) contracted COVID-19 during the first wave of the pandemic. The median (Q1; Q3) follow-up was 24 (12; 25) months after the end of the lockdown. During this period, 145 (46%) residents died (mortality rate of 26 per 100 residents per year). The characteristics of the total population and the survival data collected during the follow-up are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Compared to those who survived afterwards, the residents who died during the follow-up were significantly older, had greater disability according to the GIR, required more frequently texture-modified food, had a lower BMI and experienced significantly greater weight loss during the first PW, resulting in more prevalent severe malnutrition according to the GLIM criteria.\u003c/p\u003e \u003cp\u003e \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\u003eCharacteristics of first COVID-19 pandemic wave surviving residents and 2-year mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal Population\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;315\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003e2-year mortality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;145\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;170\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore 1stCoPW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e226 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e124 (73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e86\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay in the NH (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerate-none\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e109 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89 (62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60 (35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegal guardianship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e115 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56 (42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTexture-modified food\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnd of the 1stCoPW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63 (37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eno\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emoderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization for any cause\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e1stCoPW: first COVID-19 pandemic wave; MD: Missing data; NH: Nursing home. The results are expressed as the means\u0026thinsp;\u0026plusmn;\u0026thinsp;SDs or counts (%). Student\u0026rsquo;s t test and the chi-square test were used to compare the characteristics of the participants according to 2-year mortality.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents Kaplan‒Meier curves for 2-year survival as a function of having a history of COVID-19 during the 1st CoPW1 or not. The associations with 2-year survival according to the nonadjusted and adjusted Cox models are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. A history of COVID-19 infection and survival during Co1stPW were not associated with excess 2-year mortality (HR [95% CI] 0.96 [0.80\u0026ndash;1.13], p\u0026thinsp;=\u0026thinsp;0.62). Factors associated with 2-year mortality in the unadjusted Cox model were older age, severe disability, requiring texture-modified food and severe malnutrition after the lockdown. According to the adjusted Cox model (including age, disability, legal guardianship, malnutrition and centre), older age (1.05 [1.03\u0026ndash;1.08], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), severe disability (1.35 [1.12\u0026ndash;1.63], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and severe malnutrition (1.29 [1.04\u0026ndash;1.60], p\u0026thinsp;=\u0026thinsp;0.02) were independently associated with poorer survival. A trend toward higher mortality was observed in the case of legal guardianship (1.19 [0.99\u0026ndash;1.43], p\u0026thinsp;=\u0026thinsp;0.06).\u003c/p\u003e \u003cp\u003e \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\u003eAssociations between the characteristics of residents and 2-year mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e2-year mortality\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted\u003c/p\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.78\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.06 (1.03\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (1.03\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay in the nursing home (months)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.99\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere disability (vs moderate or no disability)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.43 (1.21\u0026ndash;1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35 (1.12\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLegal guardianship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.15 (0.96\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.19 (0.99\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTexture-modified food (vs normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.48 (1.23\u0026ndash;1.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOVID-positive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.81\u0026ndash;1.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMalnutrition (vs no malnutrition)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emoderate malnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09 (0.87\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003esevere malnutrition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.59 (1.32\u0026ndash;1.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.29 (1.04\u0026ndash;1.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization for any causes during lockdown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.87 (0.55\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eAssociations between the characteristics of residents and 2-year mortality were tested using Cox models. The adjusted Cox model included age, disability, legal guardianship, severe malnutrition and centre. The results are expressed as hazard ratios (HRs) and 95% confidence intervals (95% CIs). For the variables age and length of stay in the nursing home, the HR was calculated for a one-unit increase.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study revealed that in NH residents who had survived the 1st CoPW, having a history of COVID-19 during the 1st CoPW did not affect 2-year mortality. Independent risk factors for 2-year mortality were increasing age, severe disability and severe malnutrition.\u003c/p\u003e \u003cp\u003eIncreasing age, disability and malnutrition have consistently been associated with increased mortality in older adults, in the community, in the hospital and in NHs (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The finding that having a history of COVID-19 had no impact on 2-year mortality in NH 1st CoPW survivors is intriguing. The 1st CoPW COVID-19-positive survivors were older and more often severely disabled before the 1st CoPW and were more often severely malnourished at the end of the 1st CoPW than were the noninfected survivors (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Only age, severe disability and severe malnutrition were risk factors for 2-year mortality according to both univariate and multivariate analyses. Both groups would have suffered equally from the consequences of the lockdown, leading to social isolation, disorganization of the facilities and poorer healthcare. This suggests that once the COVID-19 infection is resolved and the patient has survived, it has no further impact on subsequent survival. Our results are in line with a previously published study on NHs (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) and extend data on follow-up to two years.\u003c/p\u003e \u003cp\u003eInterestingly, the survival curves were superposable and linear in both groups, suggesting that the four subsequent COVID-19 pandemic waves (observed in France as follows: the 2nd wave between August 1st, 2020, and December 31st, 2020; the 3rd wave between January 1st, 2021, and June 30th, 2021; the 4th wave between July 1st, 2021, and December 31st, 2021; and the 5th Omic wave between January 1st and 31st, 2022) and the vaccination program (starting on December 27th, 2020, in the French NH) had no impact on the mortality rate in either group over the 2-year follow-up. In our study, the mortality rate could not be compared to that of the previous 1st CoPW years. However, in the United Kingdom (UK), for people aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years living in care homes, mortality rates were not compared between COVID-19-positive and COVID-19-negative residents but doubled from March 2020 to June 2020 when compared to the five-year average (excluding 2020) and then returned to average, with no meaningful variation, from June 2020 to December 2022 (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This is very different from the overall UK mortality rate, where as in many countries, excess mortality persisted after the 1st CoPW up to 2023 (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Likewise, in the United States of America, large increases in mortality due to Alzheimer\u0026rsquo;s disease and related dementias, which are underlying or contributing causes of death, occurred in COVID-19 pandemic year 1 but were largely mitigated in pandemic year 2 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The most pronounced declines were observed for deaths in nursing home/long-term care settings; conversely, excess deaths at home and in medical facilities remained high in year 2 (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Thus, the observed stability of the mortality rate after the 1st CoPW was reached is in accordance with other data.\u003c/p\u003e \u003cp\u003eThe lack of impact of COVID-19 infection on subsequent mortality in NHs remains difficult to explain. The first hypothesis would be that surviving COVID-19 infection in the 1st CoPW conferred some COVID-19 immunity for a few months before the first vaccination campaign; this could have resulted in a lower mortality (as compared to not previously infected residents) during the second pandemic wave (August 2020 \u0026ndash; late December 2021). However, in an unvaccinated population in Denmark, two rounds of nationwide PCR testing separated by 6 months showed that protection against a new COVID-19 infection was 80.5% in the general population but 47.1% in people aged 65 and older (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The immunity from a first COVID-19 infection may be even lower in older institutionalized adults (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The second hypothesis was that the survivors of COVID-19 were less severely burdened with comorbidities (data that could not be collected in our study) than were those who died and those who survived the 1st CoPW without COVID-19. The deleterious effect of COVID-19 on nutritional and frailty status (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) could be somewhat counterbalanced by a lower disease burden in survivors. In hospitalized all-age COVID-19 patients, the risk of mortality is strongly influenced by chronic diseases, which are also common in NH residents (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). However, in geriatric acute care wards for older patients with COVID-19, the Charlson comorbidity index was not associated with in-hospital mortality, while disability was the only preexisting condition that was associated with in-hospital mortality (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Furthermore, in NHs, comorbidities have been extensively described but were not associated with 30-day or 6-month COVID-19 mortality or with mortality risk after COVID-19 infection (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The reason why comorbidities were not associated with mortality in older COVID-19 patients remains to be explained. It may be that the severity of the disease and the impact of the disease on disability are much stronger risk factors for mortality than the etiology of the disease itself. The third hypothesis is that COVID-19 may have selected for survival in a population that was initially more physically/psychologically resilient, as defined by the ability to recover in the face of disease, a concept that goes beyond the concept of physical frailty (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe results of our study must be interpreted with regard to methodological limitations. First, this was an observational study that did not allow any conclusions to be drawn on the causal relationships between the assumed risk factors and mortality. Second, its retrospective design limited the number of variables that could be collected, and thus, the assessment of potential confounding factors such as comorbidities or the severity of COVID-19 could not be performed. In particular, disability status was not assessed after the 1st CoPW, and we used the pre1st CoPW as a potential confounding factor for post-1st CoPW mortality. Third, we were not able to document the cause of death during the 2-year follow-up.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study revealed that having a history of COVID-19 during the first CoPW and surviving were not associated with subsequent 2-year excess mortality in NH residents. Our data suggest that high levels of frailty and comorbidities, such as severe disability, cognitive disorders, dysphagia or severe malnutrition, are independently associated with reduced life expectancy in the context of the pandemic. Healthcare professionals should still consider these factors to be strong predictors of the risk of death to propose specific and individualized interventions for NH residents.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e1st CoPW: first COVID-19 pandemic wave\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eGIR: \u003cem\u003egroupe iso ressource\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGLIM: global leadership initiative on malnutrition\u003c/p\u003e\n\u003cp\u003eHR: hazard ratio\u003c/p\u003e\n\u003cp\u003eNH: nursing home\u003c/p\u003e\n\u003cp\u003eRT-PCR: reverse-transcription polymerase chain reaction\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the \u003cem\u003eG\u0026eacute;rontop\u0026ocirc;le d\u0026rsquo;Ile-de-France\u003c/em\u003e Ethics Committee (approval number: 22021). In accordance with French ethical requirements for\u003c/p\u003e\n\u003cp\u003eretrospective studies, each participant or legal guardian was informed of the study by mail and asked to consent to the use of the data within one month. In case of refusal to participate expressed by a phone call or a return mail, the participants were excluded from the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMS, PCA, VH and ARS designed the study. VH, HA and CC collected data in nursing homes. MS and PCA performed statistical analysis. MS, PCA, and ARS contributed in writing the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTeam EPHE, Danis K, Fonteneau L, Georges S, Daniau C, Bernard-Stoecklin S, et al. High impact of COVID-19 in long-term care facilities, suggestion for monitoring in the EU/EEA, May 2020. Euro June. 2020;25(22):2000956.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraham NSN, Junghans C, Downes R, Sendall C, Lai H, McKirdy A, et al. SARS-CoV-2 infection, clinical features and outcome of COVID-19 in United Kingdom nursing homes. J Infect Sept. 2020;81(3):411\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCangiano B, Fatti LM, Danesi L, Gazzano G, Croci M, Vitale G, et al. Mortality in an Italian nursing home during COVID-19 pandemic: correlation with gender, age, ADL, vitamin D supplementation, and limitations of the diagnostic tests. Aging (Albany NY) Dec. 2020;12(24):24522\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnder G, Rezza G, Brusaferro S. Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA May. 2020;323(18):1775\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreco GI, Noale M, Trevisan C, Zatti G, Dalla Pozza M, Lazzarin M, et al. Increase in Frailty in Nursing Home Survivors of Coronavirus Disease 2019: Comparison With Noninfected Residents. J Am Med Dir Assoc May. 2021;22(5):943\u0026ndash;e9473.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCourtois-Amiot P, Allart H, de Cathelineau C, Legu\u0026eacute; C, Eischen P, Chetaille F et al. Covid-19 as an Independent Risk Factor for Weight Loss in Older Adults living in Nursing Homes. Gerontol Febr 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrampart S, Le Gentil S, Bureau ML, Macchi C, Leroux C, Chapelet G, et al. Functional decline, long term symptoms and course of frailty at 3-months follow-up in COVID-19 older survivors, a prospective observational cohort study. BMC Geriatr June. 2022;22(1):542.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaniguchi LU, Avelino-Silva TJ, Dias MB, Jacob-Filho W, Aliberti MJR, COVID-19 and Frailty (CO-FRAIL) Study Group and EPIdemiology of Critical COVID-19 (EPICCoV). Study Group, for COVID Hospital das Clinicas, University of Sao Paulo Medical School (HCFMUSP) Study Group. Patient-Centered Outcomes Following COVID-19: Frailty and Disability Transitions in Critical Care Survivors. Crit Care Med June. 2022;50(6):955\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaniguchi LU, Aliberti MJR, Dias MB, Jacob-Filho W, Avelino-Silva TJ. Twelve Months and Counting: Following Clinical Outcomes in Critical COVID-19 Survivors. Ann Am Thorac Soc Feb. 2023;20(2):289\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBooij JA, van de Haterd JCHQ, Huttjes SN, van Deijck RHPD, Koopmans RTCM. Short- and Long-Term Mortality and Mortality Risk Factors among Nursing Home Patients after COVID-19 Infection. J Am Med Dir Assoc Aug. 2022;23(8):1274\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCederholm T, Jensen GL, Correia MITD, Gonzalez MC, Fukushima R, Higashiguchi T, et al. GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community. Clin Nutr. 2019;38(1):1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAguilova L, Sauz\u0026eacute;on H, Balland \u0026Eacute;, Consel C, N\u0026rsquo;Kaoua B. Grille AGGIR et aide \u0026agrave; la sp\u0026eacute;cification des besoins des personnes \u0026acirc;g\u0026eacute;es en perte d\u0026rsquo;autonomie. Revue Neurologique March. 2014;170(3):216\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eS\u0026aacute;nchez-Rodr\u0026iacute;guez D, De Meester D, Minon L, Claessens M, G\u0026uuml;m\u0026uuml;s N, Lieten S, et al. Association between Malnutrition Assessed by the Global Leadership Initiative on Malnutrition Criteria and Mortality in Older People: A Scoping Review. IJERPH March. 2023;20(7):5320.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRothera IC, Jones R, Harwood R, Avery AJ, Waite J. Survival in a cohort of social services placements in nursing and residential homes: factors associated with life expectancy and mortality. Public Health May. 2002;116(3):160\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIncalzi RA, Capparella O, Gemma A, Landi F, Bruno E, Di Meo F, et al. The interaction between age and comorbidity contributes to predicting the mortality of geriatric patients in the acute-care hospital. J Intern Med Oct. 1997;242(4):291\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGOV.UK [Internet]. 2023 [accessed 5 Feb 2024]. Excess mortality: bespoke analyses. Available on: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gov.uk/government/statistics/excess-mortality-bespoke-analyses\u003c/span\u003e\u003cspan address=\"https://www.gov.uk/government/statistics/excess-mortality-bespoke-analyses\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePearson-Stuttard J, Caul S, McDonald S, Whamond E, Newton JN. Excess mortality in England post COVID-19 pandemic: implications for secondary prevention. Lancet Reg Health Eur Jan. 2024;36:100802.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen R, Charpignon ML, Raquib RV, Wang J, Meza E, Aschmann HE, et al. Excess Mortality With Alzheimer Disease and Related Dementias as an Underlying or Contributing Cause During the COVID-19 Pandemic in the US. JAMA Neurol Sept. 2023;80(9):919\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHansen CH, Michlmayr D, Gubbels SM, M\u0026oslash;lbak K, Ethelberg S. Assessment of protection against reinfection with SARS-CoV-2 among 4 million PCR-tested individuals in Denmark in 2020: a population-level observational study. Lancet. 2021;397(10280):1204\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFulop T, Pawelec G, Castle S, Loeb M. Immunosenescence and vaccination in nursing home residents. Clin Infect Dis Feb. 2009;48(4):443\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDessie ZG, Zewotir T. Mortality-related risk factors for COVID-19: a systematic review and meta-analysis of 42 studies and 423,117 patients. BMC Infect Dis Aug. 2021;21(1):855.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZerah L, Baudouin \u0026Eacute;, P\u0026eacute;pin M, Mary M, Krypciak S, Bianco C, Roux S, Gross A, Tom\u0026eacute;o C, Lemari\u0026eacute; N, Dureau A, Bastiani S, Ketz F, Boully C, de Villelongue C, Romdhani M, Desoutter MA, Duron E, David JP, Thomas C, Paillaud E, de Malglaive P, Bouvard E, Lacrampe M, Mercadier E, Monti A, Hanon O, Fossey-Diaz V, Bourdonnec L, Riou B, Vallet H, Boddaert J. Clinical Characteristics and Outcomes of 821 Older Patients With SARS-Cov-2 Infection Admitted to Acute Care Geriatric Wards. J Gerontol Biol Sci Med Sci. 2021;76(3):e4\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitson HE, Duan-Porter W, Schmader KE, Morey MC, Cohen HJ, Col\u0026oacute;n-Emeric CS. Physical Resilience in Older Adults: Systematic Review and Development of an Emerging Construct. J Gerontol Biol Sci Med Sci Apr. 2016;71(4):489\u0026ndash;95.\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":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Long-term mortality , Nursing Homes, Older Adults","lastPublishedDoi":"10.21203/rs.3.rs-4112561/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4112561/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDuring the first COVID-19 pandemic wave (1stCoPW), nursing homes (NHs) experienced a high rate of COVID-19 infection and death. Residents who survived the COVID-19 infection may have become frailer. This study aimed to determine the predictive value of having a COVID-19 infection during the 1st CoPW for 2-year mortality in NH residents.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis was a retrospective study conducted in three NHs. Residents who had survived the 1st CoPW (March to May 2020) were included. The diagnosis of COVID-19 was based on the results of a positive reverse transcriptase-polymerase chain reaction test. The collected data also included age, sex, length of residence in the NH, disability status, legal guardianship status, nutritional status, need for texture-modified food and hospitalization during lockdown. Nonadjusted and adjusted Cox models were used to analyse factors associated with 2-year post-1st CoPW mortality.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAmong the 315 CoPW1 survivors (72% female, mean age 88 years, 48% with severe disability), 35% presented with COVID-19. Having a history of COVID-19 was not associated with 2-year mortality: hazard ratio (HR) [95% confidence interval]\u0026thinsp;=\u0026thinsp;0.96 [0.81\u0026ndash;1.13], p\u0026thinsp;=\u0026thinsp;0.62. The factors independently associated with 2-year mortality were older age (for each additional year, HR\u0026thinsp;=\u0026thinsp;1.05 [1.03\u0026ndash;1.08], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), severe disability vs moderate or no disability (HR\u0026thinsp;=\u0026thinsp;1.35 [1.12\u0026ndash;1.63], p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and severe malnutrition vs no malnutrition (HR\u0026thinsp;=\u0026thinsp;1.29 [1.04\u0026ndash;1.60], p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eHaving survived a COVID-19 infection during the 1st CoPW did not affect subsequent 2-year survival in older adults living in NHs, suggesting that most of these residents recovered from the infection without COVID-19-related life-threatening sequelae.\u003c/p\u003e","manuscriptTitle":"COVID-19 infection and 2-year mortality in nursing home residents who survived the first wave of the pandemic","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-26 11:17:44","doi":"10.21203/rs.3.rs-4112561/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-30T07:45:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-11T13:39:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-08T13:06:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6622e1e3-8332-413f-a251-0f7e0eac74f3","date":"2024-03-29T13:43:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78f92588-2444-4640-a8c7-73b39446eecd","date":"2024-03-29T11:29:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-29T09:12:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-25T06:29:09+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-03-22T03:59:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-22T03:54:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2024-03-16T10:10:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"741c4526-28aa-4d14-a540-a795a90a9703","owner":[],"postedDate":"March 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T16:04:15+00:00","versionOfRecord":{"articleIdentity":"rs-4112561","link":"https://doi.org/10.1186/s12877-024-05220-w","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2024-08-01 15:57:46","publishedOnDateReadable":"August 1st, 2024"},"versionCreatedAt":"2024-03-26 11:17:44","video":"","vorDoi":"10.1186/s12877-024-05220-w","vorDoiUrl":"https://doi.org/10.1186/s12877-024-05220-w","workflowStages":[]},"version":"v1","identity":"rs-4112561","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4112561","identity":"rs-4112561","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}