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. 2021 Jul 23;16(7):e0255141. doi: 10.1371/journal.pone.0255141

Clinical characteristics of COVID-19 in older adults. A retrospective study in long-term nursing homes in Catalonia

Uxío Meis-Pinheiro 1,#, Francesc Lopez-Segui 2,#, Sandra Walsh 3,#, Anton Ussi 4,‡, Sebastia Santaeugenia 5,6,‡, Jose Augusto Garcia-Navarro 7,‡, Antonio San-Jose 8,‡, Antoni L Andreu 1,4,‡, Magda Campins 9,‡, Benito Almirante 10,‡,*
Editor: Giordano Madeddu11
PMCID: PMC8301631  PMID: 34297774

Abstract

The natural history of COVID-19 and predictors of mortality in older adults need to be investigated to inform clinical operations and healthcare policy planning. A retrospective study took place in 80 long-term nursing homes in Catalonia, Spain collecting data from March 1st to May 31st, 2020. Demographic and clinical data from 2,092 RT-PCR confirmed cases of SARS-CoV-2 infection were registered, including structural characteristics of the facilities. Descriptive statistics to describe the demographic, clinical, and molecular characteristics of our sample were prepared, both overall and by their symptomatology was performed and an analysis of statistically significant bivariate differences and constructions of a logistic regression model were carried out to assess the relationship between variables. The incidence of the infection was 28%. 71% of the residents showed symptoms. Five major symptoms included: fever, dyspnea, dry cough, asthenia and diarrhea. Fever and dyspnea were by far the most frequent (50% and 28%, respectively). The presentation was predominantly acute and symptomatology persisted from days to weeks (mean 9.1 days, SD = 10,9). 16% of residents had confirmed pneumonia and 22% required hospitalization. The accumulated mortality rate was 21.75% (86% concentrated during the first 28 days at onset). A multivariate logistic regression analysis showed a positive predictive value for mortality for some variables such as age, pneumonia, fever, dyspnea, stupor refusal to oral intake and dementia (p<0.01 for all variables). Results suggest that density in the nursing homes did not account for differences in the incidence of the infection within the facilities. This study provides insights into the natural history of the disease in older adults with high dependency living in long-term nursing homes during the first pandemic wave of March-May 2020 in the region of Catalonia, and suggests that some comorbidities and symptoms have a strong predictive value for mortality.

Introduction

COVID-19 presents with a broad spectrum of severity ranging from a completely asymptomatic form to a severe acute respiratory syndrome [1]. The majority of patients presenting with COVID-19 experience a mild illness that can usually be managed in the community but in some patients clinical deterioration occurs and age and the presence of comorbidities are associated with a more severe disease and poor outcome [2]. Major clinical features of the disease include fever, dry cough and dyspnea that can lead to a severe respiratory distress in some patients, but also other signs and symptoms also occur. These include muscle or body aches, anosmia, dysgeusia, headache, gastrointestinal symptoms such as diarrhea and a wide range of skin lesions such as erythematous rashes, urticaria, and chicken pox-like vesicles [2–7]. Although early reports indicated that the main mechanism of transmission was respiratory through respiratory droplets exhaled by an infected person, current knowledge supports the theory that infection is spread through exposure to smaller virus-containing respiratory droplets and particles that can remain suspended in the air over long distances and time, a mechanism known as airborne transmission [8]. Soon after the disease appeared in Wuhan at the end of 2019, the global outbreak of the SARS-CoV2 virus created a public health emergency on a scale unprecedented in recent history. The region of Catalonia in north-eastern Spain has been severely impacted by the pandemic and, as of April 23rd, 2021, remains in the throes of the crisis with more than 590,000 infections. Of note is the high mortality rate notified by the regional health care authorities in long term care homes [9]. More than 8,798 people have died in these facilities, according to official estimates, representing 50% of the total casualties in the region, a percentage similar to other regions in Spain [10, 11]. However, in most cases, COVID-19 was not confirmed during the early stages of the outbreak in March and April 2020, as RT-PCR based diagnostic tests were not fully available. The clinical courses of some casualties in these facilities strongly suggest the presentation of COVID-19, but could not be laboratory confirmed.

The vulnerability of the elderly in long-term care facilities to respiratory disease outbreaks, including influenza and other commonly circulating human corona viruses such as the common cold, is well recognized [12, 13]. These institutions represent a risky setting for COVID-19 transmission due to the characteristics that define the setting i.e. residents who are predominantly at advanced ages and have underlying medical conditions. Although the specific elements of the viral versus host factors that define susceptibility to severe disease are not well understood [14, 15] some specific characteristics of older individuals living in nursing homes such as the high proportion of patients receiving chronic treatment with Anriotensin II receptors blockers increase the risk of acquiring SARS-CoV2 infection [16]. Also the lack of PPEs at the beginning of the pandemic outbreak and the difficulties of wearing masks in aged individuals suffering from cognitive impairment may have accounted for the fast expansion of the virus within these facilities [17]. The high incidence of COVID-19 in long-term care facilities for the elderly has generated a great deal of clinical data that has been recorded in the official data registries of these institutions. Here we report clinical and environmental retrospective data from a multicenter cohort of positive RT-PCR residents living in nursing homes of the region.

Materials and methods

Study population

The study was conducted in long-term nursing homes belonging to ACRA (Associació Catalana de Recursos Assistencials), the largest network of long-term care facilities in the region. These facilities provide full long-term care for older adults that have a high or very high degree of dependency. An open call to participate in the register among the 400 centers of the organization was launched on June 1st 2020, with 160 agreeing to participate. Among them, 80 had confirmed cases of COVID-19 among residents. The sample included facilities located in urban and suburban areas; 2.5% in towns up to 2,000 inhabitants; 20% between 2,001 and 10,000; 28.75% between 10,001 and 100,000 and 48.75% in towns over 100,000. In these facilities, a total of 2,092 COVID-19 cases were confirmed by a RT-PCR test. Additional residents with suspected COVID-19 identified on the basis of serological tests—but without RT-PCR test results—were obtained; however, they were not included in the study due to the high variability of the tests, poor analytical performance and lack of approval by the National Medicinal Products Agency.

Study method/assessment

A detailed questionnaire was distributed to participating centers where information on the characteristics of the facility and pseudonymized clinical information (including when the positive RT-PCR were performed), provided retrospective data over a period of three months, from March 1st to May 31st, the period of the first pandemic wave in Spain. Clinical information was extracted from the Clinical History forms of each resident and reassessed by the medical and nursing services of the nursing home during the period in which data was collected, to define the characteristics of the natural history of the disease in the population studied. The information on the structural characteristics of the nursing-homes included: total number of places, number of beds, single and double rooms, number of bathrooms ensuite or in common areas, as well as the number and size of common areas, including the number of living units cases where in case the nursing-home was organized on the basis of this model [18].

Instead of arbitrary “large” or “small” facilities and, with the aim of differentiating facilities where all residents shared the same spaces from those where daily life is organized in subgroups of residents sharing the same common spaces, we created a synthetic indicator based on the number of “spaces” and “units”. “Spaces” were defined as rooms (excluding bedrooms) where residents spend time during the day (sitting areas, TV rooms, activity rooms, dining areas and so on). “Units” were defined as living units [18], the interconnected group of spaces where independent subgroups of residents do all their daily activities, including bedrooms and common spaces used by a particular subgroup.

Based on these definitions, a synthetic indicator was defined to describe the structural characteristics of the facilities by using 7 variables:

  1. No. of spaces between 10 and 19 m2

  2. No. of spaces between 20 and 49 m2

  3. No. of spaces between 50 and 100 m2

  4. No. of spaces of more than 100 m2

  5. No. units of less than 10 people

  6. No. of units between 10 and 15 people

  7. No. of units of more than 15 people

The first four variables, which refer to the surfaces were transformed by dividing them by the total number of spaces (No. of spaces between…./No. of total spaces). Similarly, the three variables related to the number of people per unit are transformed by dividing them by the total number of units (No. of units between…/No. of total units). This transformation provides and indicator of the proportion of spaces and units of each type. Variables are weighted with values ranging from 1 to 4, being 1 “low density” and 4 “high density” resulting in a coefficient indicative of density per living unit in the entire facility.

The workforce/resident ratio was considered a non-significant variable as it was consistently maintained among these facilities following mandatory regional social care legislation.

Anonymized demographic and clinical data from all positive RT-PCR residents were collected from the institutional records. Demographic variables included age and sex. Clinical variables included the presence or absence of signs and symptoms that have been reported to be associated to COVID-19 [19–22], such as: fever, dyspnea, asthenia, cough, muscular pain, rhinorrhea, sore throat, diarrhea, vomiting, refusal to intake, skin vesicles or eczemas, insomnia, confusion and stupor. Other symptoms associated with COVID-19 such as anosmia or dysgeusia were not recorded as the frailty and high level of dependency of the population studied, including variable levels of cognitive impairment and dementia would had introduced significant bias in the interpretation. The presence or absence of Rx- confirmed pneumonia was also recorded. For each symptom the date of onset and the date of finalization was confirmed. Clinical data also include the presence of frequent chronic underlying health conditions. Clinical follow-up included information on hospitalization and also the resolution of the disease: recovery, ongoing clinical course or exitus at the time data were collected. The date when a positive RT-PCR test was obtained and, in most cases, when it turned to negative was also collected.

Date at onset was defined for each resident as the day the first symptom was present, if this symptom was present within a period of 14 days prior to or after a positive RT-PCR test.

Statistical analysis

We computed descriptive statistics to characterize the demographics and clinical variables of our sample overall and by their symptomatology. Statistically significant bivariate differences were assessed using t-test, Wilcoxon rank sum test or Fisher’s exact test. Additionally, we constructed a logistic regression model to assess the relationship between exitus and a number of variables, including age, symptomatology and underlying health conditions. Microsoft Excel and R-4.0.2. were used for data processing and quantitative analysis.

Ethical issues

The study was approved by the Research Ethics Board of the Hospital Vall d´Hebron in Barcelona, Catalonia, Spain, a reference healthcare institution in the region for COVID-19 patients. A waiver of informed consent was granted because the data were collected for public health surveillance purposes.

Results

The cohort described here included 2,092 patients, residents of long-term nursing homes that were infected by SARS-CoV2 during the first wave of the pandemic in Catalonia (March-April 2020). Mean age of the cohort was 86.7 (SD, 7.06) with a higher proportion of females (73% of total), consistent with the demographic characteristics of this population in nursing homes in Catalonia [9]. Overall, the demographic characteristics of residents and the facilities faithfully represent the general attributes of nursing-homes within the region, and the sample accounts for approximately 10% of the total number of long-term care facilities in Catalonia [23].

Table 1 shows demographic data and clinical symptoms of RT-PCR positive residents. The average incidence of positive RT-PCR in the total population of 80 facilities was 28% (ranging from 1% to 71%) of the total number of residents, and no regional significant differences were identified (data not shown).

Table 1. Demographics, clinical features and underlined health conditions of the cohort.

Total N = 2092 Exitus N = 455 Survivor N = 1637 P-value
Demographic variables
Age (SD) 86.7 (7.06) 87.97 (6.65) 86.3 (7.82) 0.0002
Gender (Female) 1532 (73.23%) 287 (63.08%) 1245 (76.05%) <0.0001
Complex and chronic patient 792 (38%) 158 (34,7%) 634 (38.73%) 0.1262
Pneumonia 331 (16%) 131 (28.8%) 200 (12,22%) <0.0001
Hospitalization 461 (22.04%) 148 (32.5%) 313 (19,12%) <0.0001
Symptomatology
Fever 1055 (50.43%) 344 (75.6%) 711 (43.43%) <0.0001
Dyspnea 601 (28.73%) 268 (58.9%) 333 (20.34%) <0.0001
Asthenia 394 (18.83%) 147 (32.31%) 247 (15.09%) <0.0001
Dry cough 399 (19.07%) 89 (19.56%) 310 (18.94%) 0.787
Muscle pains 181 (8.65%) 54 (11.87%) 127 (7.76%) 0.00808
Nasal congestion 71 (3.39%) 21 (4.62%) 50 (3.05%) 0.108
Excessive nasal discharge 66 (3.15%) 28 (6.15%) 38 (2.32%) 0.000116
Sore throat 47 (2.25%) 11 (2.42%) 36 (2.2%) 0.724
Diarrhea 330 (15.77%) 66 (14.51%) 264 (16.13%) 0.425
Vomiting 184 (8.8%) 47 (10.33%) 137 (8.37%) 0.191
Refusal to oral intake 314 (15.01%) 165 (36.26%) 149 (9.1%) <0.0001
Lip blisters 3 (0.14%) 2 (0.44%) 1 (0.06%) 0.121
Confusion 166 (7.93%) 55 (12.09%) 111 (6.78%) 0.000387
Stupor 121 (5.78%) 103 (22.64%) 18 (1.1%) <0.0001
Insomnia 25 (1.2%) 8 (1.76%) 17 (1.04%) 0.223
Eczema 40 (1.91%) 4 (0.88%) 36 (2.2%) 0.0806
Underlying health conditions
Dementia 1243 (59,41) 326 (71,65%) 917 (56,02%) <0.0001
Heart disease 1007 (48.14%) 204 (44.84%) 803 (49.05%) 0.112
Cerebrovascular disease 483 (23.09%) 117 (25.71%) 366 (22.36%) 0.148
DM without organic involvement 400 (19.12%) 96 (21.1%) 304 (18.57%) 0.226
DM with organic involvement 168 (8.03%) 35 (7.69%) 133 (8.12%) 0.845
COPD 275 (13.15%) 67 (14.73%) 208 (12.71%) 0.272
Hepatopathy 90 (4.3%) 13 (2.86%) 77 (4.7%) 0.0904
Peptic ulcer 89 (4.25%) 27 (5.93%) 62 (3.79%) 0.0492
CKD 501 (23.95%) 114 (25.05%) 387 (23.64%) 0.535
Connective tissue disease 115 (5.5%) 24 (5.27%) 91 (5.56%) 0.908
Tumor without metastases 228 (10.9%) 41 (9.01%) 187 (11.42%) 0.149
Solid Tumor with metastases 14 (0.67%) 4 (0.88%) 10 (0.61%) 0.52
Hematological tumor 16 (0.76%) 1 (0.22%) 15 (0.92%) 0.22
AIDS 5 (0.24%) 0 (0%) 5 (0.31%) 0.592
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Legend: N(%). P-values were calculated by Wilcoxon Rank Sum test and Fisher’s exact test.

DM = Diabetes Mellitus; COPD = Chronic Obstructive Pulmonary Disease; CKD = Chronic Kidney Disease, AIDS = Acquired Immune Deficiency Syndrome.

Fig 1 shows the clinical characteristics of the cohort. 71% of residents showed symptoms and/or signs associated with COVID-19 and 29% were completely asymptomatic. Fever and dyspnea were by far the most frequent symptoms (in 50% and 28% of the cohort, see Fig 1A). When we analyzed the frequency of symptoms in patients that were symptomatic (excluding the 29% of patients that were completely asymptomatic) the frequency of fever and dyspnea was even higher (71% and 40%). Other relatively frequent symptoms or signs included persistent cough, asthenia and diarrhea. The proportion of individuals with three of more symptoms compatible with COVID-19 was 31%. Fig 1B also shows the incidence of clinical phenotypes resulting from the combination of the five most frequent symptoms (fever, dyspnea, dry cough, asthenia and diarrhea). 67.78% patients showed clinical presentations resulting from different combinations of these five major symptoms. Strong correlations for the pairs fever-dyspnea (CC 0.33, p- < 0.001), fever-asthenia (CC 0.22, p < 0.001), dyspnea-asthenia (CC 0.24, p < 0.001) and asthenia-refusal to oral intake (CC 0.39, p-value p < 0.001) were observed. A significant correlation was also identified for the pair refusal to oral intake and stupor (CC 0.33, p < 0.001), in particular in patients with a poor clinical outcome.

Fig 1. Clinical features of the cohort.

Fig 1

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Legend: Panel A- Percentage of patients presenting a symptom. Lights bars indicate percentage of symptoms in all positive PCR individuals. Dark bars indicate percentage of symptoms in positive PCR individuals who show symptoms. Panel B- Most frequent clinical phenotypes among PCR positive patients. Percentage of the most frequent clinical phenotypes in PCR positive patients with symptoms. Panel C- Clinical courses of six of the most frequent symptoms from the onset of the disease. Duration (in days) of the most frequent symptoms (Date at onset is defined for each resident as the day the first symptom was present).

A longitudinal follow-up of the symptoms from onset showed a predominantly acute presentation of the symptomatology which persisted for a few days to a few weeks (see Fig 1C). Fever, diarrhea and vomiting lasted in most cases between 1 and 2 weeks (8, 5.7 and 3.7 mean days respectively), while dyspnea and asthenia tended to last longer (9.6 and 14.3 mean days). 16% of residents had confirmed pneumonia and 22% required hospitalization.

The accumulated mortality rate in this cohort at three months was 22% and there were significant differences between patients who were hospitalized and those who were not (32% vs. 18%, p<0.01). Fig 2A shows the cumulative mortality, which accounted for up to 100% during the 80 days after onset, in particular during the first 28 days, which accounted for 86% of the casualties. The massive and acute outbreak of the disease in the region resulted in a concentration of casualties (see Fig 2B) during a period of 2 months (from mid-March to mid-May), the majority (77%) concentrated in a period of 1 month from end of March to the end of April.

Fig 2. Mortality in the cohort.

Fig 2

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Legend: Panel A- Cumulative mortality rate. The p-value corresponds to the Kolmogorov-Smirnov test between the empirical cumulative distributions of survival days of hospitalized and non-hospitalized patients. Panel B- Date of exitus.

Table 2 presents a logistic regression analysis to identify potential predictive factors for exitus. Age and the presence of pneumonia had a significant predictive value (OR = 1,03 and OR 1,74, respectively). However, the strongest correlations were identified for two symptoms: Fever (OR = 2,39) and dyspnea (OR = 3,13) together with the presence of stupor (OR = 11,38) and refusal to oral intake (OR = 3,21). Most comorbidities did not have a predictive value except dementia and hepatopathy (OR = 1,63 and OR = 0,45, respectively). Interestingly, previous conditions such as cardiovascular disease or COPD were not suggestive of increased probability of mortality.

Table 2. Risk factors associated with exitus.

Variable Univariate OR (95CI) Multivariate OR (95CI)
Age 1.03 (1.02,1.05) 1.03 (1.01, 1.05)
Pneumonia 2.91 (2.26,3.73) 1.74 (1.26, 2.38)
Fever 4.04 (3.19,5.11) 2.39 (1.80, 3.18)
Dyspnea 5.61 (4.49,7.01) 3.13 (2.37, 4.15)
Stupor 26.32 (15.74,44) 11.38 (6.54, 20.74)
Refusal to oral intake 5.68 (4.4,7.33) 3.21 (2.29, 4.51)
Diarrhea 0.88 (0.66,1.18) 0.61 (0.42, 0.88)
Mucous secretion 2.76 (1.67,4.55) 2.09 (1.05, 4.03)
Dry cough 1.04 (0.8,1.35) 0.74 (0.53, 1.04)
Eczema 0.39 (0.14,1.11) 0.36 (0.09, 1.02)
Asthenia 2.69 (2.12,3.41) 0.89 (0.63, 1.24)
Muscle pains 1.6 (1.14,2.24) 1.06 (0.66, 1.70)
Nasal Congestion 1.54 (0.91,2.58) 0.83 (0.38, 1.68)
Sore throat 1.1 (0.56,2.18) 1.14 (0.47, 2.58)
Vomiting 1.26 (0.89,1.79) 1.01 (0.64, 1.55)
Lip blisters 7.22 (0.65,79.84) 4.37 (0.27, 126.90)
Confusion 1.89 (1.34,2.66) 0.78 (0.49, 1.22)
Insomnia 1.71 (0.73,3.98) 0.86 (0.28, 2.43)
Dementia 1.98 (1.58,2.49) 1.63 (1.24, 2.16)
Hepatopathy 0.6 (0.33,1.08) 0.45 (0.20, 0.93)
Cardiovascular disease 0.84 (0.69,1.04) 0.81 (0.62, 1.05)
Cerebrovascular disease 1.2 (0.95,1.53) 1.10 (0.81, 1.48)
DM. without organic involvement 1.17 (0.91,1.52) 1.16 (0.84, 1.60)
DM. with organic involvement 0.94 (0.64,1.39) 0.96 (0.57, 1.57)
COPD 1.19 (0.88,1.6) 1.06 (0.735, 1.52)
Peptic ulcer 1.6 (1.01,2.55) 1.52 (0.85, 2.63)
CKD 1.08 (0.85,1.37) 0.89 (0.65, 1.20)
Connective tissue disease 0.95 (0.6,1.5) 0.74 (0.40, 1.33)
Cancer without metastases 0.77 (0.54,1.1) 0.93 (0.60, 1.40)
Cancer with metastases 1.44 (0.45,4.62) 0.85 (0.16, 3.50)
Hematological tumor 0.24 (0.03,1.81) 0.58 (0.03, 3.06)
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Legend: OR = odds ratio; CI = Confidence interval.

DM = Diabetes Mellitus; COPD = Chronic Obstructive Pulmonary Disease; CKD = Chronic Kidney Disease.

The number of places of the facilities ranged from 15 to 300 (mean = 69,06, SD = 34,32) and did not show a significant correlation with the incidence of COVID-19 in those nursing homes that reported at least one confirmed case of the disease (Fig 3A, R = 0.098, p = 0.33). The density of the institution assessed by a synthetic indicator that weighed the number and size of living units (see methods) showed also no correlation with the incidence of the disease (Fig 3B, R = 0.83, p = 0.47), suggesting that nursing homes organized on a model based on living units were not prone to have a higher incidence of the disease when compared to nursing homes where common spaces where shared by the entire population, once the virus had been introduced in the facility.

Fig 3. Incidence vs density of the institution.

Fig 3

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Legend: Panel A–Correlation between incidence of Covid 19 and number of places of the facility. Panel B–Correlation between incidence of Covid 19 and the nursing home density index.

Discussion

COVID-19 exacted a heavy toll in nursing home facilities in Spain, causing a high number of deaths [10]. Restriction policies and lockdowns were not imposed until the Government declared a state of emergency on March 14, 2020 [24]. In addition to the age and comorbidity profiles of residents, other variables make these institutions particularly fragile when dealing with an infectious disease outbreak. These include lack of access to testing and personal protective equipment, the close quarters of residents, the difficulty of maintaining social distance among mobile patients with cognitive impairment and a workforce that has not been extensively trained for managing infections [25–27]. This combination of factors (intensity of the pandemic outbreak, lack of molecular diagnostic tools and protective equipment, and lack of training of the workforce) created a “perfect storm” that may explain why SARS-CoV-2 spread so rapidly into and within nursing homes in Catalonia in a short period of time, as it also did in other European countries or the US [9, 28] resulting in substantial morbidity and mortality. These findings are strikingly similar to two studies of long-term care facilities where the outbreak was monitored from the very beginning [29, 30]. The findings suggest that asymptomatic transmission from SARS-CoV-2 residents most likely contributed to the rapid and extensive spread of infection to other residents and caregivers.

The proportion of asymptomatic infections reported in different studies varies greatly, ranging from 4% to 41% [31] and these differences may be explained among others by the definition of asymptomatic and paucisymptomatic or the presence of presymptomatic cases. A large nationwide, population-based seroepidemiological study in Spain of 61,000 individuals showed an average seroprevalence (study conducted from April 27th to May 11, 2020) of the infection of 5% in the region of Catalonia, which was slightly higher for nursing home workers (7.9%) [32]. This study also assessed the prevalence of COVID-19 related symptoms and concluded that asymptomatic cases represent between 22% and 36% of all SARS-CoV-2 infections in the general population. Our results showed a similar percentage of asymptomatic individuals (29%), although an earlier study evaluating 69 nursing homes in the metropolitan area of Barcelona suggested that 70% of the positive residents were asymptomatic [33]. This difference could be explained by the way results were reported, as that study did not record the onset of symptomatology after the PCR was conducted.

In a retrospective cross-sectional study of 14238 older people (>65 years) with confirmed COVID-19 in Wuhan during the first outbreak of the pandemic, 31% were diagnosed as severe or critical cases and only 1,4% were asymptomatic [34]. This contrasts with our results and the findings of a study performed in nursing homes in Connecticut where 28% residents tested positive and 22% were symptomatic or paucisymptomatic [35]. In the Wuhan case, the study was conducted during the first months of the pandemic, so most likely only severely affected cases were detected. Our results are consistent with those found in the Connecticut study where the setting (nursing homes) and the diagnostic strategy (active search of cases) were similar.

The range of symptoms in this study show a heterogeneous presentation: fever, dyspnea, cough, asthenia and diarrhea dominate the clinical presentation, and although the pairing fever-dyspnea was frequent. This heterogeneity must be considered when early alert protocols in nursing homes are developed as advanced age and the presence of comorbidities are associated with increased risk of mortality, and asymptomatic or paucisymptomatic patients have the potential for substantial viral shedding [36].

This retrospective cohort identified several risk factors for death in nursing home residents, where age shows a clear predictive value for mortality, an observation that is consistent with previous reports [37], and the typical presentation of fever and dyspnea also show a high predictive value in our model.

Results show that among all comorbidities, dementia had a high predictive value for death, defining a clinical presentation where fever, dyspnea, delirium and refuse to oral intake in a patient suffering from dementia represent a condition with very low probability for survival. Interestingly other comorbidities such as cardiovascular conditions and COPD, which are predictors of mortality in other studies [38] do not seem to have significant weight for poor prognosis. Geriatric syndromes complicate care and indicate a poor prognosis, so systematic assessment is imperative in ensuring adequate management and planning [39, 40]. In all cases, we found geriatric syndromes to be associated with a poorer prognosis in a similar manner to patients admitted in intermediate care facilities [41]. This association was most evident for dementia, delirium and inanition (refusal to oral intake with increased risk of malnutrition) showing that the presence of geriatric syndromes influenced the clinical evolution of patients with SARS-CoV-2 infection.

In a recent study of 351 nursing homes in the US analyzing 5256 residents with confirmed COVID-19, increased age, male gender, fever, shortness of breath, tachycardia, hypoxia, diabetes, chronic kidney disease, and impaired cognitive and physical function, were independently associated with mortality. Our findings also stressed the importance of age, some clinical symptoms, and dementia as risk factors associated with mortality [42].

De Vito et al. recently published a study describing the characteristics of the SARS-CoV-2 infection in an Italian cohort of patients living in nursing homes [43]. The demographic characteristics of their series was similar to our study and both series showed the same mortality rate in infected patients (21.2% in De Vito´s paper versus 21.75% in this study) regardless of the presence or absence of symptoms. Also the analysis of the clinical presentation in both series was similar with fever and dyspnea being the most common symptoms. Both studies highlight the importance of neurological involvement in the risk of developing COVID-19 and they suggest that the vulnerability of patients with dementia may be associated with a more critical presentation of COVID-19 [43]. However, the comparability of the risk factors between both series should be interpreted cautiously as the sample size was not comparable (264 versus 2092) including possible differences related to the demographic and social setting characteristics of both series that may account for different presentation of the disease.

Interestingly, we did not observe a significant effect on viral spreading in relationship to the size of the facility. Our observations suggest that, once the virus was introduced, rapid and widespread transmission occurred and small facilities had a similar incidence of infection to large ones. However, this observation must be interpreted cautiously as the limitation in the number of PCR tests did not rule out the possibility of the presence of additional asymptomatic carriers. Further studies are needed to better understand a potential relationship between widespread transmission and facility size as one of the strategies to impair the spread of the infection could be the implementation of small living units that act as “COVID-19 bubbles”. In this scenario, a potential explanation could be that an efficient shielding effect may have been counteracted by the fact that the workforce performed transversally, providing care to all residents regardless of the living unit they were assigned to, thereby acting as spreaders within the facility [44].

Conclusions

The high mortality rate in nursing homes highlights the vulnerability of this population and cumulative data demonstrates that asymptomatic and paucisymptomatic cases strongly contribute to the dynamics of transmission [45]. We have learned from past experience and also from the continuous outbreaks of COVID-19 in nursing homes that this is a foreseeable consequence of this pandemic. Therefore, we must implement strategies aimed at preventing the introduction of the pathogen into these facilities. To that end, it is imperative that public health authorities provide strategic guidance [46] and working protocols based on the monitoring of infection indicators and performing PCR screenings among residents and staff caring for them. These interventions must be accompanied by training staff in infection control, the use of PPEs and recognition of COVID-19 symptoms. A better understanding of COVID-19 in older adults living in nursing homes is necessary as many national and regional vaccination roll out strategies have put these facilities in the priority groups for vaccine administration and follow-up studies in this population are necessary to assess the efficiency of vaccination plans already in place. The potential emergence of future new variants of SARS-CoV-2 and the length of immune protection in this group of the population requieres a close monitoring of pandemic prepardness and response plans for nursing homes to protect this highly vulnerable population from this and other pathogens that may appear in the future.

Limitations of the study

These limitations include (i) a potential bias in the profile of the nursing homes as their participation was established on a voluntary basis, (ii) the limited extend of the molecular diagnosis, in particular considering that, like in many other European regions, during the first outbreak of the pandemic there was a shortage of PCR tests and (iii) the lack of information on the treatment protocols due to the operational limitations of the data collection, a process directly related to the limited interoperability of the data systems between several health care providers (hospitals and primary care) involved in the implementation of treatment protocols once a patient was diagnosed by PCR in a particular nursing home. However, despite the limitations of the study, the mean incidence of the disease in this cohort does not significantly differ from the estimated global incidence in such facilities in Spain, suggesting that it represents a valid dataset for providing relevant information on the clinical characteristics of the disease in residents of nursing homes.

Supporting information

S1 File

(XLSX)

Click here for additional data file. (86.5KB, xlsx)

Acknowledgments

We acknowledge the participating nursing homes as well as the residents and their families.

Data Availability

All relevant data are within the paper and its S1 File.

Funding Statement

The authors(s) received to specific funding for this work.

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Decision Letter 0

Giordano Madeddu

21 Apr 2021

PONE-D-21-06498

CLINICAL CHARACTERISTICS OF COVID-19 IN OLDER ADULTS. A RETROSPECTIVE STUDY IN LONG-TERM NURSING HOMES IN CATALONIA

PLOS ONE

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Reviewer #1: Meis-Pinheiro et al. conducted an interesting retrospective study about clinical characteristics of COVID-19 in people living in long-term nursing homes. Many issues are present.

General comment

Abbreviations should be written entirely in the first appearance in the text (e.g. yr, CC).

English must be improved.

When the mean is reported, the authors should also write the standard deviation.

Introduction

The authors reported the number of infections and deaths in Spain in August. I suggest doing an update of these data.

The introduction is too short (15 lines). I suggest describing the SARS-CoV-2 and COVID-19, describing the clinical presentation of this disease, adding the major (fever, cough, dyspnea) and minor (anosmia, dysgeusia, headache, gastrointestinal symptoms, skin lesions). You could read and use these articles to improve the introduction: https://doi.org/10.26355/eurrev_202007_22291 https://doi.org/10.1002/hed.26269, https://doi.org/10.1002/hed.26204, https://doi.org/10.1016/S1473-3099(20)30402-3, https://doi.org/10.1097/IPC.0000000000000952 , https://doi.org/10.1111/eci.13427)

Furthermore, I suggest adding more information about the transmission of the disease, explaining why the nursing home is a risky setting and which factors could increase or decrease infection risk. I suggest reading and adding these manuscripts to your introduction: https://doi.org/10.1186/s40779-020-00240-0, https://doi.org/10.1001/jama.2020.12839, https://doi.org/10.26355/eurrev_202101_24424, https:/doi.org/10.1016/j.envpol.2020.115099, https://doi.org/10.1016/j.envpol.2020.11509.

Methods

In methods, the authors wrote "[…]provided retrospective data over a period of three months, from March 1st to May 31st, the period of the most severe impact of the pandemic wave in Spain.". Looking at the spanish data, the pandemic's most severe impact was in October-November 2020 and in January-February 2021. I suggest removing this sentence.

The patient population is not well defined. The entity referred to in the manuscript is retirement nursing homes. It is unclear if this refers to people in sheltered care/ warden controlled accommodation who require very little support, or residential Care home residents (requiring support with some daily living activities) or nursing home residents (requiring nursing care specifically, ie. a high degree of dependency).

How were symptoms ascertained? Were patients who had no symptoms reassessed to see if they were truly asymptomatic, vs pre-symptomatic?

Lines 90-99: this part is not clear. What do the authors mean with "spaces" and "unit"? what do the authors mean with "A", "B", "C", "D"?.

Why have the authors not considered anosmia and dysgeusia between the symptoms?

Result

I suggest not starting with "Table 1 shows demographic data, clinical symptoms of RT-PCR positive residents". It would be better to start with the cohort's description and use this sentence ad the end of the paragraph.

Lines 126-130: I suggest moving these lines in the method section.

I suggest replacing "average" with "mean". Furthermore, the standard deviation of the years is missing.

The sentence "However, the percentage was even higher when we only considered symptomatic individuals with a positive PCR (71% and 40%)", is not clear. Do not all people included in this study had a positive PCR for SARS-COV-2? (lines 78-80).

Lines 156-162. I suggest and the 95%CI after the OR.

It is not clear why the authors described the indicators to describe the facilities' structural characteristics if they have not used them in the results.

Furthermore, the number of deaths could have an impact on the SARS-CoV-2 infection and not on COVID-19.

No data about treatment are present in the manuscript. I suggest adding this information. Otherwise, you should explain the lack of information in the limitation.

Discussion

A recent study about Italian people living in retirement nursing homes has been published: https://doi.org/10.1371/journal.pone.0248009. I suggest reading it and using it to compare your data because there are some common points. In my opinion, this could increase the value of the discussion.

In the multivariate analysis, people with hepatopathy resulted having a lower mortality risk. In my opinion, this result should be discussed.

Table 1

About the p-value, I suggest using four after the comma, making an approximation in those p-values with 5 or 6 numbers after the comma.

It is not clear what "Excessive nasal discharge" means.

The authors sometimes used comma, sometimes dots, to divide the decimal numbers. I suggest always using dots.

I suggest replacing "Tumor without metastases" with "Solid tumor without metastases".

Regarding "AIDS", are you sure that all five people had AIDS and not HIV infection?

Table 2

I suggest switching the column Univariate and Multivariate.

Some words have been abbreviated without any reason (e.g. dis., inv., met.).

Figure 1 b. I suggest specifying that "fever", "dyspnea" means that those people had only that symptoms.

Reviewer #2: Meis-Pinheiro et al. aimed to describe clinical characteristics of COVID-19 in people living in long-term nursing homes. The topic is very interesting, given the subpopulation. However, there are numerous issues to point out:

Introduction

The authors reported the number of infections and deaths in Spain during August. Data are quite old and should be updated. Furthermore, the introduction is quite poor. Describing ways of transmission and clinical features is needed. Follow the example below for the structure and references (please, pay attention to the order):

1. Generalities

In December 2019, a new severe respiratory syndrome was identified in Wuhan, China. On January 2020, a new Coronavirus was detected and called SARS-CoV-2. On March 2021, the World Health Organization (WHO) declared SARS-CoV-2 disease (COVID-19) as a public health emergency.

2. Pathophysiology and transmission. https://doi.org/10.1186/s40779-020-00240-0; https://doi.org/10.1001/jama.2020.12839; https://doi.org/10.26355/eurrev_202101_24424;

3. Clinical features

Most common clinical features are fever, cough, dyspnea, and may also include anosmia, dysgeusia, headache, gastrointestinal symptoms, and skin lesions. https://doi.org/10.26355/eurrev_202007_22291; https://doi.org/10.1002/hed.26269; https://doi.org/10.1016/S1473-3099(20)30402-3

4. Why nursing homes must be evaluated? Explain the importance to provide an insight on this setting.

Methods

There are some not precise information in this section. For example, is reported ‘from March 1st to May 31st, the period of the most severe impact of the pandemic wave in Spain’. Please, delete this sentence. According to your national data, the most severe impact was in the last 5 months.

Readability is quite poor. Please, divide the Methods in subparagraph as follows:

1. Study population

This must be well defined. It is not clear the level of medical/nursing assistance needed in the setting (low, medium, high level of patient’s dependency). Are they sheltered care, residential care home residents, or nursing home residents?

2. Study conduction/assessment

Explain the kind of study (retrospective etc.) and your measures of evaluation. Furthermore, ‘spaces’, ‘units’, ‘A’, ’B’, ‘C’, ‘D’, ‘E’, ‘a’, ‘b’, ‘c’, ‘d’, ‘e’: there is low order in your methodology description. Please, better describe your variables.

3. Statistical analysis

Put before how you measured outcomes, and at the end the software.

4. Ethical issues

Put here your Ethical Committee authorization.

Among symptoms, anosmia and dysgeusia were not considered. Please, explain the reason. Furthermore, this could represent a limitation, with underestimation of symptomatic patients.

Result

Please, search to better present your results. First paragraph should be ‘Overall, xxx patients were included. Of them, xxx were female, and mean age was xxx + SD. Demographics, clinical features and health condition of included patients have been reported in table 1’.

P4L125-130: ‘The sample […] Catalonia’. This is your environment description and should be placed on Methods.

When reporting means (please, don’t use ‘average’), standard deviation must be added.

P4L131: you are starting your clinical features’ description referring to figure. Please, start with general description, then cite the figure.

There is something I still difficult to understand in the text. In Methods, there is a very long description of nursing homes’ structural characteristic. However, there is no mention or relationship studied regarding this parameters, clinical features, viral spread, or something else. This needs to be justified or the paragraph in Methods section should be deleted.

Is it possible to show data on patients’ treatment?

Discussion

A recent study with the same aim was published in PLOS ONE (https://doi.org/10.1371/journal.pone.0248009). Use this paper to enrich your discussion and eventually compare your results.

When looking the multivariate analysis, people with liver disease seemed to have lower mortality risk. Please, add a comment on this.

Tables and figures

Table 1

SD should be capitalized. When reporting p-value, remember to italicize. Furthermore, from the fourth number after the comma, you can approximate. Don’t use commas but points when reporting decimal numbers.

Instead of ‘Excessive nasal discharge’, please use ‘mucous secretion’ or something else. This is not a good description.

‘Tumor without metastases’ should be ‘cancer without metastases".

Table 2

Table 2 is on reverse. Please, report in the first column univariate and in the second multivariate analysis. Furthermore, delete the empty rows.

Figures

Please, when reporting figures delete ‘Title:’ (e.g. ‘Title: Clinical characteristics […]’ should be ‘Clinical features […]’)

Limitations section

Put a separate Limitations section after Conclusions. Beyond those still mentioned, some others should be mentioned:

- underestimation of symptomatic patients, given anosmia and dysgeusia were not considered

- lack of data regarding treatments (if you’ll not have possibility to show data). This is crucial. We don’t know how much people were treated, which were the drugs, and if there was a relationship with survival rates.

Language and typos

Please, carefully revise English language before resubmission. Abbreviations are not full written in the first appearance in the text (e.g. CC, yr, and so on). When reporting ‘p’ value, remember to italicize. Means are reported without standard deviation.

**********

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PLoS One. 2021 Jul 23;16(7):e0255141. doi: 10.1371/journal.pone.0255141.r002

Author response to Decision Letter 0

28 May 2021

RESPONSE TO THE REVIEWERS

Reviewer #1:

General comment

Abbreviations should be written entirely in the first appearance in the text (e.g. yr, CC).

This item has been fixed in the revised version

English must be improved.

This new version has been edited by a native English-speaking coauthor of the manuscript.

When the mean is reported, the authors should also write the standard deviation.

In this update, SDs have been included when means are reported

Introduction

The authors reported the number of infections and deaths in Spain in August. I suggest doing an update of these data.

Data of infections (590.000) and deaths (8.780) have been updated (April 2021) and the text has been edited accordingly

The introduction is too short (15 lines). I suggest describing the SARS-CoV-2 and COVID-19, describing the clinical presentation of this disease, adding the major (fever, cough, dyspnea) and minor (anosmia, dysgeusia, headache, gastrointestinal symptoms, skin lesions). You could read and use these articles to improve the introduction:

A new introduction includes a more detailed description of the clinical characteristics of COVID-19 including major and less frequent presentations. This description of the clinical characteristics of the disease has been referenced to the publications suggested by the reviewer.

Furthermore, I suggest adding more information about the transmission of the disease, explaining why the nursing home is a risky setting and which factors could increase or decrease infection risk. I suggest reading and adding these manuscripts to your introduction:

A new paragraph describing the rationale of the increased risk of transmission in nursing homes has been added to the introduction and further discussed in the discussion section. In this part of the introduction the references suggested by the reviewer have been included and discussed to emphasize the importance of the setting that nursing homes represent for an increased risk of disease transmission.

Methods

In methods, the authors wrote "[…]provided retrospective data over a period of three months, from March 1st to May 31st, the period of the most severe impact of the pandemic wave in Spain.". Looking at the spanish data, the pandemic's most severe impact was in October-November 2020 and in January-February 2021. I suggest removing this sentence.

We agree that this expression is misleading and creates confusion for the reader. The sentence has now been changed to be precise to “the period of the first pandemic wave”

The patient population is not well defined. The entity referred to in the manuscript is retirement nursing homes. It is unclear if this refers to people in sheltered care/ warden controlled accommodation who require very little support, or residential Care home residents (requiring support with some daily living activities) or nursing home residents (requiring nursing care specifically, ie. a high degree of dependency).

Again, we agree with the reviewer that the description of the population studied was poorly defined in the original version, in particular the degree of dependency. In this revised version we have clarified that the facilities analyzed (and, therefore, the population studied) were long-term nursing homes whose main objective is to provide integrate and full care to older adults with a high or very high degree of dependency.

How were symptoms ascertained? Were patients who had no symptoms reassessed to see if they were truly asymptomatic, vs pre-symptomatic?

We agree with the reviewer that we did not clarify which sources of data were used for the study and how symptomatology was assessed and reassessed. The revised version describes now that symptoms were annotated in individual Clinical History Forms and there was a daily reassessment to follow-up the presence or absence of a particular symptom or clinical sign.

Lines 90-99: this part is not clear. What do the authors mean with "spaces" and "unit"? what do the authors mean with "A", "B", "C", "D"?.

Indeed, the concept “space” and “units” were unclear. Instead of arbitrary “large” or “small” facilities and, with the aim of differentiating facilities where all residents shared the same spaces from those where daily life is organized in subgroups of residents sharing the same common spaces we created a synthetic indicator based on the number of “spaces” and “units”. “Spaces” were defined as rooms (excluding bedrooms), where residents spend time during the day (sitting areas, TV rooms, activity rooms, dining areas and so on). “Units” were defined as living units 4, the interconnected group of spaces where independent subgroups of residents do all their daily activities including bedrooms and common spaces used by a particular subgroup.

This is important as this concept is closely related to the level of social interactions within one specific facility. As an example, in a 100 place facility with no living units, all residents share the same common areas. In the same example of one facility of 100 places organized, but where daily life is organized, for example into 5 “units”, there will be 5 individual groups of 20 residents and interactions will tend to occur within these “bubbles” as the use of common spaces will be restricted to each particular bubble.

The concept has been now described into a format that it is easier to understand for the reader.

Why have the authors not considered anosmia and dysgeusia between the symptoms?

We agree with the reviewer that this needs to be clarified and a specific explanation has now been introduced in the novel version. The participants were old adults with a high or very high level of dependency, in most cases, mild to severe cognitive disorders, dementia and/or multiple underlying health conditions. This reality limited the value of subjectively perceived symptoms so to eliminate the possibility of bias we decided not to assess anosmia and dysgeusia in the study.

Results

I suggest not starting with "Table 1 shows demographic data, clinical symptoms of RT-PCR positive residents". It would be better to start with the cohort's description and use this sentence ad the end of the paragraph.

We have now described the characteristics of the cohort and moved the sentence to the end of the paragraph.

Lines 126-130: I suggest moving these lines in the method section.

Number of participant centers in cities with different population sizes has now been moved to the methods section

I suggest replacing "average" with "mean". Furthermore, the standard deviation of the years is missing.

This has now been changed and SD have been added

The sentence "However, the percentage was even higher when we only considered symptomatic individuals with a positive PCR (71% and 40%)", is not clear. Do not all people included in this study had a positive PCR for SARS-COV-2? (lines 78-80).

We agree with the reviewer that the sentence was misleading. Indeed all patients had a positive PCR but not all of them showed symptoms so we think it is relevant to mention the frequency of fever and dyspnea in the whole series of positive PCR individuals, highlighting that when only symptomatic patients were considered, the frequency of these two symptoms increases. We have now reformulated the expression to make it clearer to the reader

Lines 156-162. I suggest and the 95%CI after the OR.

The change has been done

It is not clear why the authors described the indicators to describe the facilities' structural characteristics if they have not used them in the results.

We have clarified this issue in the new version, specifying “places” instead of “beds” referring to Fig 3a and referring to the synthetic indicator that now is precisely described in the amended Methods section.

No data about treatment are present in the manuscript. I suggest adding this information. Otherwise, you should explain the lack of information in the limitation.

We agree that this is a relevant aspect but collecting data on treatment was beyond the scope of this study due to the complex interoperability in the data systems that came about because of the high number of health care providers as patients were followed-up by many different medical teams and hospitals of the region. However, we agree with the reviewer that this consideration is relevant for the reader, so we have restructured the paragraph of limitations of the study in the discussion section to highlight this observation.

Discussion

A recent study about Italian people living in retirement nursing homes has been published: https://doi.org/10.1371/journal.pone.0248009. I suggest reading it and using it to compare your data because there are some common points. In my opinion, this could increase the value of the discussion.

We agree with the reviewer that the study published by De Vito et al. is highly relevant for the discussion of our results and the strategy approach of both studies are similar. Although De Vito´s study was able to collect data on medical treatments and ours was not for the reasons explained above, it is interesting to mention that both series converge of the similar conclusion that the high transmission rate of SARS-CoV2 infection in nursing homes could be related to crowding, sharing of gathering areas, and inadequate infection prevention and control measures. Although the different size of the cohorts (264 patients in De Vito´s paper and 2092 in our study) could explain some differences in the multivariate analysis of the factors that influenced infection occurrence, it is clear that there are strong similarities between both studies such as the mortality rate or the presence of neurological syndromes as a risk factor for developing COVID-19 symptomatic disease. Following the suggestion of the reviewer De Vito´s paper has now been quoted and the similarities between both studies has been discussed in the discussion section.

In the multivariate analysis, people with hepatopathy resulted having a lower mortality risk. In my opinion, this result should be discussed.

Indeed this a striking result considering that several studies have shown that COVID-19 patients with preexisting liver diseases face a higher risk of decompensation and mortality (Mohammed A, Paranji N). However most of these studies have been carried out in adult patients and little data is available on the response of liver function in older adults affected not only by SARS-CoV-2 infection but also other viral pathogens. We have included in this discussion the observation of Kondo et al. (Kondo Y, Tsukada K, Hepatology) who described during an outbreak of acute HBV in nursing home residents, most infected patients were asymptomatic and no patients died or required hospitalization suggesting that more studies

are needed to understand the role of liver function in the elderly in response to viral pathogens.

Table 1

About the p-value, I suggest using four after the comma, making an approximation in those p-values with 5 or 6 numbers after the comma.

It is not clear what "Excessive nasal discharge" means.

The authors sometimes used comma, sometimes dots, to divide the decimal numbers. I suggest always using dots.

I suggest replacing "Tumor without metastases" with "Solid tumor without metastases".

Regarding "AIDS", are you sure that all five people had AIDS and not HIV infection?

The indications suggested by the reviewer have been incorporated. The term “excessive nasal discharge” has been substituted by “rhinorrhea” and for AIDS, we have changed to “HIV infection” as we did not collect precise information of their immune status or the protocol for antiretroviral therapy.

Table 2

I suggest switching the column Univariate and Multivariate.

Some words have been abbreviated without any reason (e.g. dis., inv., met.).

Changes suggested in Table 2 have now been introduced in this version

Figure 1 b. I suggest specifying that "fever", "dyspnea" means that those people had only that symptoms.

This has been clarified in the new version

Reviewer #2:

Meis-Pinheiro et al. aimed to describe clinical characteristics of COVID-19 in people living in long-term nursing homes. The topic is very interesting, given the subpopulation. However, there are numerous issues to point out:

Introduction

The authors reported the number of infections and deaths in Spain during August. Data are quite old and should be updated. Furthermore, the introduction is quite poor. Describing ways of transmission and clinical features is needed. Follow the example below for the structure and references (please, pay attention to the order):

1. Generalities

In December 2019, a new severe respiratory syndrome was identified in Wuhan, China. On January 2020, a new Coronavirus was detected and called SARS-CoV-2. On March 2021, the World Health Organization (WHO) declared SARS-CoV-2 disease (COVID-19) as a public health emergency.

2. Pathophysiology and transmission. https://doi.org/10.1186/s40779-020-00240-0; https://doi.org/10.1001/jama.2020.12839; https://doi.org/10.26355/eurrev_202101_24424;

3. Clinical features

Most common clinical features are fever, cough, dyspnea, and may also include anosmia, dysgeusia, headache, gastrointestinal symptoms, and skin lesions. https://doi.org/10.26355/eurrev_202007_22291; https://doi.org/10.1002/hed.26269; https://doi.org/10.1016/S1473-3099(20)30402-3

4. Why nursing homes must be evaluated? Explain the importance to provide an insight on this setting.

We appreciate the suggestion of restructuring the introduction to present in a coherent way the characteristics of COVID-19 in the particular context of the elderly and, specifically, in the nursing home setting. Following the indications of the reviewer we have created a new introduction based on a narrative that describes the general description of SARS-CoV-2 infection, the clinical characteristics and the particularities of the nursing homes setting for an increased risk of transmission We have included some of the references suggested by the reviewer that will help the reader to contextualize our study.

Methods

There are some not precise information in this section. For example, is reported ‘from March 1st to May 31st, the period of the most severe impact of the pandemic wave in Spain’. Please, delete this sentence. According to your national data, the most severe impact was in the last 5 months.

We have updated the data to April 2021 and corrected the expression “most severe pandemic wave” for “first pandemic wave”. Although in terms of mortality this first wave was by far the most deadly one, we agree that the concept “severity” in the context of our description is confusing and it is more sound to refer to the timeline of the pandemic outbreak.

Readability is quite poor. Please, divide the Methods in subparagraph as follows:

1. Study population

This must be well defined. It is not clear the level of medical/nursing assistance needed in the setting (low, medium, high level of patient’s dependency). Are they sheltered care, residential care home residents, or nursing home residents?

2. Study conduction/assessment

Explain the kind of study (retrospective etc.) and your measures of evaluation. Furthermore, ‘spaces’, ‘units’, ‘A’, ’B’, ‘C’, ‘D’, ‘E’, ‘a’, ‘b’, ‘c’, ‘d’, ‘e’: there is low order in your methodology description. Please, better describe your variables.

3. Statistical analysis

Put before how you measured outcomes, and at the end the software.

4. Ethical issues

Put here your Ethical Committee authorization.

Among symptoms, anosmia and dysgeusia were not considered. Please, explain the reason. Furthermore, this could represent a limitation, with underestimation of symptomatic patients.

We acknowledge the suggestion of the reviewer for structuring the methods section into different subsections. The new version has included this new structure.

Indeed, the concept “space” and “units” were unclear. Instead of arbitrary “large” or “small” facilities and, with the aim of differentiating facilities where all residents shared the same spaces from those where daily life is organized in subgroups of residents sharing the same common spaces we created a synthetic indicator based on the number of “spaces” and “units”. “Spaces” were defined as rooms (excluding bedrooms) where residents spend time during the day (sitting areas, TV rooms, activity rooms, dining areas and so on). “Units” were defined as living units 4, the interconnected group of spaces where independent subgroups of residents do all their daily activities, including bedrooms and common spaces used by a particular subgroup.

This is important as this concept is closely related to the level of social interactions within one specific facility. As an example, in a 100-place facility with no living units, all residents share the same common areas. In the same example of one facility of 100 places where daily life is organized, for example on 5 “units”, there will be 5 individual groups of 20 residents and interactions will tend to occur within these “bubbles” as the use of common spaces will be restricted to each particular bubble.

On the comment of the lack of information on the anosmia/dysgeusia, we agree with the reviewer that this needs to be clarified and a specific explanation has now been introduced. The participants were old adults with a high or very high level of dependency, in most cases, mild to severe cognitive disorders, dementia and/or multiple underlying health conditions. This reality limited the value of subjectively perceived symptoms so to eliminate the possibility of bias we decided not to assess anosmia and dysgeusia in the study.

Results

Please, search to better present your results. First paragraph should be ‘Overall, xxx patients were included. Of them, xxx were female, and mean age was xxx + SD. Demographics, clinical features and health condition of included patients have been reported in table 1’.

P4L125-130: ‘The sample […] Catalonia’. This is your environment description and should be placed on Methods.

When reporting means (please, don’t use ‘average’), standard deviation must be added.

P4L131: you are starting your clinical features’ description referring to figure. Please, start with general description, then cite the figure.

There is something I still difficult to understand in the text. In Methods, there is a very long description of nursing homes’ structural characteristic. However, there is no mention or relationship studied regarding this parameters, clinical features, viral spread, or something else. This needs to be justified or the paragraph in Methods section should be deleted.

Is it possible to show data on patients’ treatment?

We have restructured the results sections clarifying the questions raised by the reviewers. These include:

- We start describing the characteristics of the cohort and the environment descriptions have been moved to the methods sections, including the number of participants in cities with different population sizes.

- “Average” has been replaced by “Mean” and SD have been added.

- The sentence "However, the percentage was even higher when we only considered symptomatic individuals with a positive PCR (71% and 40%)" was misleading. Indeed all patients had a positive PCR but not all of them showed symptoms so we think it is relevant to mention the frequency of fever and dyspnea in the whole series of positive PCR individuals, highlighting that when only symptomatic patients were considered, the frequency of these two symptoms increases. We have now reformulated the expression to make it clearer to the reader.

- We have added 95%CI after the OR.

- We have now explained in detail the bases for the analysis of the structural characteristics of the facilities. In this novel version we use the term “places” instead of “beds” referring to Fig 3a and referring to the synthetic indicator that now is precisely described in the amended Methods section.

- We appreciate the comment about the data on patient treatment. This is a relevant aspect but collecting data on treatment was beyond the scope of this study due to the complex interoperability in the data systems that came about because of the high number of health care providers as patients were followed-up by many different medical teams and hospitals of the region. However, we agree with the reviewer that this consideration is relevant for the reader, so we have restructured the paragraph of limitations of the study in the discussion section to highlight this observation.

Discussion

A recent study with the same aim was published in PLOS ONE (https://doi.org/10.1371/journal.pone.0248009). Use this paper to enrich your discussion and eventually compare your results.

We agree with the reviewer that the study published by De Vito et al. is highly relevant for the discussion of our results and the strategy approach of both studies are similar. Although De Vito´s study was able to collect data on medical treatments and ours was not for the reasons explained above, it is interesting to mention that both series converge of the similar conclusion that the high transmission rate of SARS-CoV2 infection in nursing homes could be related to crowding, sharing of gathering areas, and inadequate infection prevention and control measures. Although the different size of the cohorts (264 patients in De Vito´s paper and 2092 in our study) could explain some differences in the multivariate analysis of the factors that influenced infection occurrence, it is clear that there are strong similarities between both studies such as the mortality rate or the presence of neurological syndromes as a risk factor for developing COVID-19 symptomatic disease.

When looking the multivariate analysis, people with liver disease seemed to have lower mortality risk. Please, add a comment on this.

Indeed this a striking result considering that several studies have shown that COVID-19 patients with preexisting liver diseases face a higher risk of decompensation and mortality (Mohammed A, Paranji N). However most of these studies have been carried out in adult patients and little data is available on the response of liver function in older adults affected not only by SARS-CoV-2 infection but also other viral pathogens. We have included in this discussion the observation of Kondo et al. (Kondo Y, Tsukada K, Hepatology) who described during an outbreak of acute HBV in nursing home residents, that most infected patients were asymptomatic and no patients died or required hospitalization suggesting that more studies are needed to understand the role of liver function in the elderly in response to viral pathogens.

Tables and figures

Table 1

SD should be capitalized. When reporting p-value, remember to italicize. Furthermore, from the fourth number after the comma, you can approximate. Don’t use commas but points when reporting decimal numbers.

Instead of ‘Excessive nasal discharge’, please use ‘mucous secretion’ or something else. This is not a good description.

‘Tumor without metastases’ should be ‘cancer without metastases".

We have included in this revised version the suggestions of the reviewer. The expression “Excessive nasal discharge” has been replaced by “rhinorrhea”.

Table 2

Table 2 is on reverse. Please, report in the first column univariate and in the second multivariate analysis. Furthermore, delete the empty rows.

The structure of table 2 has been modified following the reviewer´s suggestion

Figures

Please, when reporting figures delete ‘Title:’ (e.g. ‘Title: Clinical characteristics […]’ should be ‘Clinical features […]’)

This change has now been introduced in the revised version

Limitations section

Put a separate Limitations section after Conclusions. Beyond those still mentioned, some others should be mentioned:

- underestimation of symptomatic patients, given anosmia and dysgeusia were not considered

- lack of data regarding treatments (if you’ll not have possibility to show data). This is crucial. We don’t know how much people were treated, which were the drugs, and if there was a relationship with survival rates.

Following the reviewer´s suggestion, we have added a section on “limitations on the study”, emphasizing that, in the context of the abrupt outbreak of COVID-19 in long-term nursing homes in Catalonia in April 2020 (interoperability issues, several health care providers involved) it was not possible to collect information of good quality on the treatments received by SARS-CoV-2 patients who develop COVID-19. Also we believe that in the current structure of the manuscript the limitation on the information of the presence of anosmia/dysgeusia fit better in the methods section so this limitation has been mentioned there.

Language and typos

Please, carefully revise English language before resubmission. Abbreviations are not full written in the first appearance in the text (e.g. CC, yr, and so on). When reporting ‘p’ value, remember to italicize. Means are reported without standard deviation.

English has been carefully revised and comments on abbreviations, “p” value and report of means and SD have now been fixed in this revised version

Attachment

Submitted filename: RESPONSE TO REVIEWERS.docx

Click here for additional data file. (65.8KB, docx)

Decision Letter 1

Giordano Madeddu

29 Jun 2021

PONE-D-21-06498R1

CLINICAL CHARACTERISTICS OF COVID-19 IN OLDER ADULTS. A RETROSPECTIVE STUDY IN LONG-TERM NURSING HOMES IN CATALONIA

PLOS ONE

Dear Dr. Almirante,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

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PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

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Reviewer #1: No

Reviewer #2: (No Response)

**********

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Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors provide to assess the manuscript as suggested by my previous revision. Some minor issues are present:

Abbreviations should be written entirely in the first appearance in the text (e.g., COVID-19).

I suggest modifying the first part of the introduction. In my opinion, the authors should start writing a sentence about what is SARS-CoV-2 before explaining the symptoms caused by it.

The figures are missing in this new version of the manuscript. Furthermore, there is no references in the text for the figures. I suggest adding them.

Reviewer #2: The athours thoroughly revised their manuscript and I thank them for addressing my comments. The paper is now ready for publication on PLOS ONE.

**********

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Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

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PLoS One. 2021 Jul 23;16(7):e0255141. doi: 10.1371/journal.pone.0255141.r004

Author response to Decision Letter 1

7 Jul 2021

RESPONSE TO THE REVIEWERS

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors provide to assess the manuscript as suggested by my previous revision. Some minor issues are present:

Abbreviations should be written entirely in the first appearance in the text (e.g., COVID-19).

This item has been fixed in the revised version.

I suggest modifying the first part of the introduction. In my opinion, the authors should start writing a sentence about what is SARS-CoV-2 before explaining the symptoms caused by it.

In this update, this part has been addressed with a new introductory text.

The figures are missing in this new version of the manuscript. Furthermore, there is no references in the text for the figures. I suggest adding them.

This item has been fixed in the revised version and the figures added.

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file. (52.6KB, docx)

Decision Letter 2

Giordano Madeddu

12 Jul 2021

CLINICAL CHARACTERISTICS OF COVID-19 IN OLDER ADULTS. A RETROSPECTIVE STUDY IN LONG-TERM NURSING HOMES IN CATALONIA

PONE-D-21-06498R2

Dear Dr. Almirante,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Giordano Madeddu

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Giordano Madeddu

16 Jul 2021

PONE-D-21-06498R2

CLINICAL CHARACTERISTICS OF COVID-19 IN OLDER ADULTS. A RETROSPECTIVE STUDY IN LONG-TERM NURSING HOMES IN CATALONIA

Dear Dr. Almirante:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Giordano Madeddu

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File

    (XLSX)

    Click here for additional data file. (86.5KB, xlsx)
    Attachment

    Submitted filename: RESPONSE TO REVIEWERS.docx

    Click here for additional data file. (65.8KB, docx)
    Attachment

    Submitted filename: Response to reviewers.docx

    Click here for additional data file. (52.6KB, docx)

    Data Availability Statement

    All relevant data are within the paper and its S1 File.

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