Next Article in Journal
Epitope Profiling of Diphtheria Toxoid Provides Enhanced Monitoring for Consistency Testing during Manufacturing Process Changes
Next Article in Special Issue
Potential Immunologic and Integrative Methods to Enhance Vaccine Safety
Previous Article in Journal
The Effects of COVID-19 Vaccine Mandates in Hawaii
Previous Article in Special Issue
Ocular Manifestations after Receiving COVID-19 Vaccine: A Systematic Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Spread of COVID-19 Infection in Long-Term Care Facilities of Trieste (Italy) during the Pre-Vaccination Era, Integrating Findings of 41 Forensic Autopsies with Geriatric Comorbidity Index as a Valid Option for the Assessment of Strength of Causation

1
Department of Medical Surgical and Health Sciences, University of Trieste, 34149 Trieste, Italy
2
Department of Medicine, Forensic Medicine University of Udine, 33100 Udine, Italy
3
Department of Pathology, Santa Maria della Misericordia University Hospital, 33100 Udine, Italy
*
Author to whom correspondence should be addressed.
Vaccines 2022, 10(5), 774; https://doi.org/10.3390/vaccines10050774
Submission received: 11 April 2022 / Revised: 2 May 2022 / Accepted: 11 May 2022 / Published: 13 May 2022

Abstract

:
Background: in 2020, a new form of coronavirus spread around the world starting from China. The older people were the population most affected by the virus worldwide, in particular in Italy where more than 90% of deaths were people over 65 years. In these people, the definition of the cause of death is tricky due to the presence of numerous comorbidities. Objective: to determine whether COVID-19 was the cause of death in a series of older adults residents of nursing care homes. Methods: 41 autopsies were performed from May to June 2020. External examination, swabs, and macroscopic and microscopic examination were performed. Results: the case series consisted of nursing home guests; 15 men and 26 women, with a mean age of 87 years. The average number of comorbidities was 4. Based only on the autopsy results, the defined cause of death was acute respiratory failure due to diffuse alveolar damage (8%) or (31%) bronchopneumonia with one or more positive swabs for SARS-CoV-2. Acute cardiac failure with one or more positive swabs for SARS-CoV-2 was indicated as the cause of death in in symptomatic (37%) and asymptomatic (10%) patients. Few patients died for septic shock (three cases), malignant neoplastic diseases (two cases), and massive digestive bleeding (one case). Conclusions: Data from post-mortem investigation were integrated with previously generated Geriatric Index of Comorbidity (GIC), resulting in four different degrees of probabilities: high (12%), intermediate (10%), low (59%), and none (19%), which define the level of strength of causation and the role of COVID-19 disease in determining death.

1. Introduction

In the first 5 months of the SARS-CoV-2 pandemic in Italy, 32,981 cases of COVID-19-related deaths were reported, with a mean age of 81 years and only 1% occurring in people under 50 years [1,2]. A similar trend was observed in USA, China, and northern Europe, thus providing important information regarding the increased risk of mortality in the higher age groups [3,4,5,6]. It was observed that individuals >59 years of age are five times more likely to die following the onset of COVID-19 symptoms as compared to those between the ages of 30–59 [7,8]. Long-term care facilities were dramatically hit by the COVID-19 outbreak, where a death percentage of 25–85% was recorded worldwide [9,10,11,12]. It has been observed that long-term care facilities consisted of a high-risk population in a high risk setting (Gardner) [13,14,15,16]. Many authors described an over 50 times higher death rate in residents of long-term care facilities than community-dwelling older people [17,18,19,20,21]. It was observed that characteristics of the residents in long-term care facilities (age, higher body mass index, male sex, and renal impairment) had a different impact on the death rate as well as the quality level of healthcare and the adequacy of safety measures adopted to face the spread of the infection and its deadly consequences (specific training of the staff, good staff/resident ratio) [21,22,23,24,25]. In Italy, the territorial distribution of long-term care facilities (or residential care homes) exhibits a gradient moving from the North to the South of the country and has been considered significant in the distribution of death during the COVID-19 pandemic [26]. Concerns about the possibility that personnel represented the source of COVID-19 introduction and promoted the spread of the infection among the residents favored the onset of claims and triggered efforts to ensure equal access to high-quality healthcare across long-term care facilities as well as to provide the extensive vaccination of residents and personnel [27,28,29]. The Italian health authorities, for example, promoted COVID-19 vaccination of the residents of long-term care facilities, their relatives, and healthcare personnel as a priority in the vaccination plan, with the aim to reduce the risk of severe COVID-19 disease in older people and the risk of hospitalization, to guarantee the continuity of care [30,31]. In May 2021, the Italian health authorities published a survey of the spread of COVID-19 infection in about 41% of all Italian long-term care facilities; of the 9154 patients who died, 680 had a positive nasopharyngeal swab and 3092 had flu-like symptoms, and a death rate of 0.7 per 100 residents was estimated, 7.4% of which involved residents with SARS-CoV-2 infection [32]. A 3:1 ratio of mortality was estimated when comparing the long-term care facilities’ residents and people aged over 70 living in the community. There can be no doubt that comorbidities in older people affected by COVID-19 infection played a determinant role in their death [33]. Mehra MR et al. showed that underlying cardiovascular disease and chronic obstructive pulmonary disease were associated with a higher mortality rate amongst hospitalized COVID-19 patients [34]. Also, Lippi G et al. observed a five and half times higher risk of developing a severe infection due to SARS-CoV-2 in older people affected by COPD [35]. The distinction between “died from” and “died with” COVID-19 remains a topic of debate especially in older people where the role of comorbidities needs to be accurately assessed [36,37]. The international guidelines for certification and classification of COVID-19 as the cause of death defined a COVID-19-related death on the basis of a clinically compatible illness, in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death that cannot be related to COVID-19 disease [38]. The Italian health authorities updated the definition of death due to COVID-19 infection based on objective criteria, although in the same period they discouraged autopsies in suspected or confirmed cases of COVID-19 (Table 1) [39,40,41,42,43,44,45,46].
Some authors proposed different standardized models to better define the cause of death in older people with COVID-19 infection on the basis of clinical data or autopsy findings, respectively [47,48,49,50,51].
The purpose of this study is to validate a methodological approach in the assessment of the strength of causation between COVID-19 infection and death, by integrating data collected from 41 consecutive autopsies of older people residents in long-term care facilities who died in the period May–June 2021 with Geriatric Index of Comorbidity (GIC), commonly used in clinical practice as a measure of frailty.

2. Materials and Methods

Between the beginning of May and the beginning of June 2020, a total of 41 consecutive deaths occurred in five different long-term care facilities where the spread of COVID-19 infection was reported. A complete post-mortem examination was performed in each case according to existing safety measures and protocols in clinical and forensic autopsies [43,52,53,54,55]. Before and during autopsies, multiple swabs were collected at identical sites from rhynopharinx, oropharynx, trachea, right and left bronchus, and rectum, which were examined by Real Time Polymerase Chain Reaction (RT-PCR). Positive results were reported as semi-quantitative Cycle Threshold (Ct) values [56]. The Ct values, collected and grouped into three categories, were defined as follows: <25 strongly positive, 25–35 moderately positive, and >35 weakly positive [57]. Gross examination of the head, thoracic, and abdominal organs was performed in each case, followed by extended sampling of organs for histological examinations with routine hematoxylin and eosin staining. Histological examination was integrated with immunohistochemistry by means of anti-core and anti-spike proteins and anti-CD4-8 panel antibodies in cases of interstitial lymphocytic infiltration. Data regarding age, sex, comorbidities, onset of symptoms before death, and the results of swabs when performed before the death were extracted from medical records and collected in an extended database. The level of frailty was estimated for each resident according to the Geriatric Index of Comorbidity (class I to IV) on the grounds of the number of reported diseases and the severity of the diseases measured by the Greenfield’s Individual Disease Severity (IDS) by grading each condition on a 0–4 scale on the basis of the following general framework: 0 = absence of disease, 1 = asymptomatic disease, 2 =symptomatic disease requiring medication but under satisfactory control, 3 = symptomatic disease uncontrolled by therapy, and 4 = life-threatening disease or greatest severity of the disease [58]. Class I includes residents with one or more conditions with IDS = 1, class II included patients with one or more conditions with IDS = 2, class III includes patients with one condition with IDS = 3, and class IV included residents with two or more conditions with IDS = 3 or one or more conditions with IDS = 4 [59].
Data from post-mortem investigation were integrated with the Geriatric Index of Comorbidity (GIC), resulting in four different strengths of causation (high, intermediate, low, and none), which define the level of strength of causation and the role of COVID-19 disease in determining death.

3. Results

Description of the population. Forty one consecutive deaths occurred among the residents of five different long term care facilities from May to June 2020. The mean age was 87 (range 57–99) with a prevalence of female sex (63%). Sixty one percent of residents were symptomatic within 10 days before the death, suffering from fever (44%), dyspnea or respiratory failure in therapy with oxygen (39%), drowsiness (12%), hypotension (12%), and acute renal failure (7%). In 45% of cases, death occurred unexpectedly. In 80% of symptomatic residents, an oropharyngeal swab was performed before death, 72% of which showed a positive result for COVID-19.
Geriatric Index of Comorbidity. The number of comorbidities varied from 0 to more than 7, with an average number of 4. The most frequent was severe walking impairment/bed rest syndrome (73%) followed by severe cognitive impairment (61%), hypertension (41%), ischemic heart disease (34%), COPD (29%), chronic kidney failure (29%), arrhythmogenic heart disease (24%), neoplastic disease with dissemination (17%), congestive heart failure/valvulopathy (17%), and diabetes mellitus (12%). The severity of frailty was measured for each resident based on the Geriatric Index of Comorbidity (GIC). None of the deceased belonged to class I, 2% of the cases belonged to class II, 20% of the cases belonged to class III, and 78% of the cases belonged to class IV (Table 2).
Post mortem swabs. The mean time between death and swab collection was 36 days (range 12–60). Swabs were analyzed by real time PCR and in 34 cases (83%) one or more of these resulted positive for COVID-19. The range of cycle threshold for the nasopharyngeal swabs was 15.47–37.11 cycles, for the oropharyngeal swabs 17.64–36.35 cycles, for the tracheal swabs 18.08–35.45 cycles, for the right bronchus swabs 19.69–36.7 cycles, for the left bronchus swabs 16.65–36.56 cycles, and for the rectal swabs 32.62–35–72 cycles. Based on Ct values, 19% of the swabs resulted highly positive (Ct < 24), 27% moderately positive (Ct 24–33,99), and 7% weakly positive (Ct < 35) (Table 3).
Autopsy findings. The mean time between death and autopsy was 36 days (range 12–60). All cadavers were preserved in cold or refrigerated rooms before autopsy. Heavy, congested, and edematous lungs were reported in all autopsies. Lung cancer with liver metastasis was observed in only one case. Pleural fluid was reported in only two cases as well as pleural adhesions. The mean weight of the right and left lung was 621 gr (range 260–1000) and 559 gr (range 180–940), respectively. The mean weight of the brain was 1256 gr (range 880–1700), that of the heart was 407 gr (range 240–700), that of the liver was 912 gr (range 560–1440), that of the spleen was 125 gr (range 40–360), and that of the right and left kidney was 112 gr (range 40–350) and 112 gr (range 40–350), respectively. A massive pulmonary embolism was recorded in only one case as well as purulent peritonitis and gastrointestinal hemorrhage due to gastric ulcer. Microscopic examination was heavily influenced by the advancing of putrefactive changes. Vascular changes associated with proliferative and exudative diffuse alveolar damage with hyaline membrane deposition, necrosis of alveolar lining cells, type II pneumocyte hyperplasia with nucleomegaly associated with the accumulation of macrophages, and multinucleated giant cells were observed in 24% of cases. Mild interstitial focal infiltration with peribronchiolar and perivascular CD-3 positive T cells with a predominance of CD4-positive T cells over CD8-positive T cells was also described in 48% of cases. Fibrin thrombi in pre-capillary and post-capillary vessels were observed in lung specimens in 15% of residents. Findings of chronic obstructive pulmonary disease were observed in 73% of cases. In 66% of cases, features of bacterial pneumonia were described.
In 73% of cases, pathologic cardiac features were generally related to chronic cardiovascular comorbidities (ischemic dilated cardiomyopathy and myocardial scarring), and in 54% of cases severe coronary artery disease was recorded. Advanced putrefactive changes limited histopathological observation of renal samples so that acute kidney injury (AKI) could not be excluded at all. In 73% of cases, arterionephrosclerosis and pre-existing pathological features of hypertension and diabetes were observed as well as focal and sparse chronic inflammatory infiltrates. On the basis of autopsy findings, acute respiratory failure due to bacterial bronchopneumonia was indicated as the cause of death in 31% of residents. Eight percent of residents with one or more positive swabs for SARS-CoV-2 died as a result of the diffuse alveolar damage. Acute cardiac failure in residents affected with chronic ischemic cardiomyopathy was indicated as the cause of death in 37% of residents with one or more positive swabs for COVID-19. Acute cardiac failure in residents affected with chronic ischemic cardiomyopathy without signs of COVID-19 was indicated as the cause of death in 10% of residents. In 8% of residents, death was related to septic shock and multiple organ failure syndrome. Four percent of the deceased died from advanced malignant disease (stage IV) complicated by bacterial bronchopneumonia. In one case, the death was related to acute hemorrhagic shock due to massive digestive bleeding.
Degree of strength of causation. Data from post-mortem investigation were integrated with previously generated Geriatric Index of Comorbidity (GIC), resulting in four different degrees of probabilities: high (12%), intermediate (10%), low (59%), and none (19%), which define the level of strength of causation and the role of COVID-19 disease in determining death (Table 4).

4. Discussion

Deaths related to COVID-19 as a direct or indirect result of SARS-CoV-2 infection and correct attribution to the pandemic may be a challenge, especially in older people. In this population, heavily affected during the first wave of the pandemic, the higher vulnerability and the presence of multiple comorbidities contributed significantly to an overestimation of the phenomenon, also because of the lack of a systematic post-mortem examination. Dying from COVID-19 or with COVID-19 represented an unsolved dilemma in residents of long-term care facilities, where clinical manifestations of COVID-19 may be difficult to recognize because typical symptoms such as fever, cough, and dyspnea may already be present due to other comorbidities like several pulmonary diseases or may also have specific or atypical presentations like anorexia, diarrhea, fatigue, headache, and dizziness, and clinical data from medical records are scarce, when available [2,60,61,62]. In this scenario of uncertainty, Italian long-term care facilities are going through a judicial pandemic because of the spread of deadly COVID-19 infections among residents.
In our study, a methodological approach is proposed for the study of COVID-19-related death in a selected population of 41 older residents who died in the bimester May–June 2020 in five different long-term care facilities with suspected or confirmed COVID-19 infection. The data provided by complete autopsies were integrated with the severity of frailty measured by the Geriatric Index of Comorbidity for the purpose of assessing the role of comorbidities in the mechanism of death and to provide an affordable definition of the causes of death based on objective criteria.
The small sample size is unlikely to be fully representative of older people, however, it provides an estimate of the true number of mortalities directly related to the pandemic in older people affected by multiple comorbidities in community contexts.
The characteristics of the population observed differ, in fact, from other studies, because of the peculiarity of the context (long-term care facilities) with a prevalence for the female sex (63%) and mean age of 87 years, higher than that of hospitalized patients. In the biggest autopsy studies in the literature, mean age was between 69 and 79 years, with a prevalence of male patients (58–87%) [48,50,63,64,65,66,67]. Only two case series of elder patients or patients who died in community settings had a prevalence of female patients (55–59%), with a mean age of 88 and 72 years [49,68].
The number of comorbidities varied from one to more than seven, with 85% of the subjects affected by more than three comorbidities. Hypertension, complications of diabetes mellitus, and chronic obstructive pulmonary disease were most frequently reported as expected in consideration of the data observed in other studies, where diabetes was seen in 8–44% of the cases, hypertension in 22–100% of the deceased, and chronic obstructive pulmonary disease in 6–55% of the patients who underwent an autopsy [43,48,63,64,65,66,67,68,69]. The severe walking impairment/bed rest syndrome and the severe cognitive impairment observed in most cases characterized our population and can be considered as an independent prognostic factor for death, highly impacting on the severity of frailty [44,70]; in fact, walking impairment was not identified in any of the previous studies, and chronic neurological conditions were seen in 10–41% of the cases [43,48,63,64,65,66,68,69]. As observed by other authors, fever, dyspnea, and respiratory failure were described in the days prior to death in 55–68%% of cases [49,65,68]. In our case series, the presence of fewer symptomatic patients could probably be influenced by the scarcity of data reported in the medical records of the residents of long-term care facilities.
Autopsy macroscopic findings were compatible with what is reported in other studies, with a mainly pulmonary engagement with increased weight, congestion, and oedema, which were found in 78–100% of the cases [49,63,66,69], and histological features of exudative and proliferative diffuse alveolar damage found in 67–100% of the deceased [48,49,63,66,67,69]. Unlike data from literature where pulmonary thromboembolism was found in 6–25% of patients [43,50,66,67,69], only a small number of patients of our case series showed microthrombi in alveolar capillaries or in small vessels, probably due to the limited time between infection and death as Youd and Moore pointed out [50]. Advanced putrefactive phenomena limited the recording of acute kidney injury.
Significant results were provided by the analysis of cycle threshold of multiple swabs performed before and during autopsy. The Ct value is defined as the number of cycles of amplification required for the fluorescent signal to cross the threshold, which is above the background signal. Therefore, Ct values are inversely proportional to the amount of target nuclei acid present in the tested sample. Recent studies demonstrated that qRT-PCR Ct values correlate strongly with the cultivable virus, providing a valuable surrogate for infectious virus detection in biological samples [71,72].
In our study, the mean time between death and swab collection was 36 days (range 12–60) more than in other studies in which the persistence of viral RNA was observed in post-mortem collected swabs up to 128 h after death or in buried and exhumed corpses [73,74,75,76]. Swabs were analyzed by real time PCR, 42% of which were from moderate (27%) to highly positive (15%).
The parameters of vulnerability were chosen among the several scoring systems available in clinical practice [77]. We decided to integrate data deriving from autopsies with the GIC considered to be the most accurate predictor of death to evaluate the impact and burden of the diseases on the mechanism of death [78]. It enabled the grouping of residents into four categories characterized by a different strength of causation, and in 78% of cases the role of COVID-19 in determining death was excluded.

5. Conclusions

The current classification of COVID-19-related deaths may be ineffective, and the risk of an overestimation of mortality rate is realistic in this selected population, especially if a complete autopsy is not performed systematically. The integration of autopsy findings and the assessment of severity of comorbidities by means of frailty scores used in clinical practice has proved to be a valid option for assessing the strength of causation. The use of this index currently represents a diagnostic proposal to identify whether SARS-CoV-2 infection represents the cause of death in subjects with multiple comorbidities. However, this methodology should be used on larger case studies to validate its use in assessing the cause of death.

Author Contributions

Conceptualization, S.D. and M.Z.; methodology, S.D.; software, M.Z.; validation, D.R., M.C. and M.P.; formal analysis, C.M.; investigation, S.P.; writing—original draft preparation, S.D.; writing—review and editing, M.Z.; visualization, M.C.; supervision, D.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The described procedures were authorized by the competing authorities and in accordance with the 1964 Helsinki Declaration and its later amendments.

Informed Consent Statement

Consent to participate was not required because the described procedures were authorized by the competing authorities. Consent for publication was not required because applicable law (EU GDPR) does not require consent for publication in scientific research when—as in this case—the manuscript does not contain data that refer to identifiable specific individuals.

Data Availability Statement

All the data are in the hands of the authors and can be shown if requested.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Dai, S.P.; Zhao, X.; Wu, J.H. Effects of comorbidities on the elderly patients with COVID-19: Clinical characteristics of elderly infected with COVID-19 from Sichuan, China. J. Nutr. Health Aging 2021, 25, 18–24. [Google Scholar] [CrossRef] [PubMed]
  2. Neumann-Podczaska, A.; Al-Saad, S.R.; Karbowski, L.M.; Chojnicki, M.; Tobis, S.; Wieczorowska-Tobis, K. COVID-19—Clinical picture in the elderly population: A qualitative systematic review. Aging Dis. 2020, 11, 988–1008. [Google Scholar] [CrossRef] [PubMed]
  3. Liu, K.; Chen, Y.; Lin, R.; Han, K. Clinical features of COVID-19 in elderly patients: A comparison with young and middle-aged patients. J. Infect. 2020, 80, 14–18. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. ISS. Istat. Report Epidemia COVID-2019 28 April 2021. Available online: https://www.epicentro.iss.it/coronavirus/bollettino/Bollettino-sorveglianza-integrata-COVID-19_28-aprile-2021.pdf (accessed on 5 November 2021).
  5. Iritani, O.; Okuno, T.; Hama, D.; Kane, A.; Kodera, K.; Morigaki, K.; Terai, T.; Maeno, N.; Morimoto, S. Clusters of COVID-19 in long-term care hospitals and facilities in Japan from 16 January to 9 May 2020. Geriatr. Gerontol. Int. 2020, 20, 715–719. [Google Scholar] [CrossRef]
  6. Amore, S.; Puppo, E.; Melara, J.; Terracciano, E.; Gentili, S.; Liotta, G. Impact of COVID-19 on older adults and role of long-term care facilities during early stages of epidemic in Italy. Sci. Rep. 2021, 11, 12530. [Google Scholar] [CrossRef]
  7. Wu, J.T.; Leung, K.; Bushman, M.; Kishore, N.; Niehus, R.; de Salazar, P.M.; Cowling, B.J.; Lipsitch, M.; Leung, G.M. Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nat. Med. 2020, 26, 506–510. [Google Scholar] [CrossRef] [Green Version]
  8. Dorrucci, M.; Minelli, G.; Boros, S.; Manno, V.; Prati, S.; Battaglini, M.; Corsetti, G.; Andrianou, X.; Riccardo, F.; Fabiani, M.; et al. Excess on Mortality in Italy during the COVID-19 pandemic: Assessing the differences between the first and the second wave, year 2020. Front. Publ. Health 2021, 16, 669209. [Google Scholar] [CrossRef]
  9. McMichael, T.M.; Currie, D.W.; Clark, S.; Pogosjans, S.; Kay, M.; Schwartz, N.G.; Lewis, J.; Baer, A.; Kawakami, V.; Lukoff, M.D.; et al. Epidemiology of COVID-19 in a long term care facility in king county, Washington. N. Engl. J. Med. 2020, 382, 2005–2011. [Google Scholar] [CrossRef]
  10. Etard, J.F.; Vanhems, P.; Atlani-Duault, L.; Eochard, R. Potential lethal outbreak of coronavirus disease (COVID-19) among the elderly in retirement homes and long term facilities, France, March 2020. Eurosurveillance 2020, 25, 2000448. [Google Scholar] [CrossRef]
  11. Comas-Herrera, A.; Zalakaín, J.; Lemmon, E.; Henderson, D.; Litwin, C.; Hsu, A.T.; Schmidt, A.E.; Arling, G.; Kruse, F.; Fernández, J.L. Mortality Associated with COVID-19 Outbreaks in Care Homes: Early International Evidence. International Long Term Care Policy Network. Available online: https://ltccovid.org/2020/04/12/mortality-associated-with-covid-19-outbreaks-in-care-homes-early-international-evidence/ (accessed on 30 November 2021).
  12. Pesaresi, F. COVID-19. La Mortalità nelle Strutture Residenziali per Anziani. Available online: https://francopesaresi.blogspot/2020/07/covid-19-la-mortalitanelle-strutture.htmal (accessed on 30 November 2021).
  13. Gardner, W.; States, D.; Bagley, B. The coronavirus and the risk to the elderly in long-term care. J. Aging Soc. Policy 2020, 32, 310–315. [Google Scholar] [CrossRef] [Green Version]
  14. Heudorf, U.; Müller, M.; Schmehl, C.; Gasteyer, S.; Steul, K. COVID-19 in long-term care facilities in Frankfurt am Main, Germany: Incidence, case reports, and lessons learned. GMS Hyg. Infect. Control 2020, 15, Doc26. [Google Scholar] [CrossRef] [PubMed]
  15. Thompson, D.C.; Barbu, M.G.; Beiu, C.; Popa, L.G.; Mihai, M.M.; Berteanu, M.; Popescu, M.N. The Impact of COVID-19 Pandemic on Long-Term Care Facilities Worldwide: An Overview on International Issues. BioMed Res. Int. 2020, 2020, 8870249. [Google Scholar] [CrossRef] [PubMed]
  16. Ballotari, P.; Guarda, L.; Giacomazzi, E.; Ceruti, A.; Gatti, L.; Ricci, P. Excess mortality risk in nursing care homes before and during the COVID-19 outbreak in Mantua and Cremona provinces (Lombardy Region, Northern Italy). Epidemiol. Prev. 2020, 44, 282–287. [Google Scholar] [CrossRef] [PubMed]
  17. Izurieta, H.S.; Graham, D.J.; Jiao, Y.; Hu, M.; Lu, Y.; Wu, Y.; Chillarige, Y.; Wernecke, M.; Menis, M.; Pratt, D.; et al. Natural history of coronavirus disease 2019: Risk factors for hospitalizations and death among >26 million US Medicare beneficiaries. J. Infect. Dis. 2021, 223, 945–956. [Google Scholar] [CrossRef] [PubMed]
  18. Gorges, R.J.; Konetzka, R.T. Factors associated with racial differences in deaths among nursing home residents with COVID-19 infection in the US. JAMA Newt. Open 2021, 4, e2037431. [Google Scholar] [CrossRef] [PubMed]
  19. Li, Y.; Cen, X.; Cai, X.; Temkin-Greener, H. Racial and ethnic disparities in COVID-19 infections and death across U.S. nursing homes. J. Am. Geriatr. Soc. 2020, 68, 2454–2461. [Google Scholar] [CrossRef]
  20. Li, Y.; Temkin-Greener, H.; Shan, G.; Cai, X. COVID‐19 infections and deaths among Connecticut nursing home residents: Facility correlates. J. Am. Geriatr. Soc. 2020, 68, 1899–1906. [Google Scholar] [CrossRef]
  21. Mehta, H.B.; Li, S.; Goodwin, J.S. Risk factors associated with SARS-CoV-2 infections, hospitalizations and mortality among US nursing homes residents. JAMA Newt. Open 2021, 4, e216315. [Google Scholar] [CrossRef]
  22. Lu, Y.; Jiao, Y.; Graham, D.J.; Wu, Y.; Wang, J.; Menis, M.; Chillarige, Y.; Wernecke, M.; Kelman, J.; Forshee, R.A.; et al. Risk factors for COVID-19 deaths among elderly nursing home medicare beneficiaries in the prevaccine period. J. Infect. Dis. 2021, 225, 567–577. [Google Scholar] [CrossRef]
  23. Philip, K.; Polkey, M.; Hopkinson, N.S.; Steptoe, A.; Fancourt, D. Social isolation, loneliness and physical performance in older-adults: Fixed effects analysis of a cohort study. Sci. Rep. 2020, 10, 13908. [Google Scholar] [CrossRef]
  24. Szczerbinska, K. Could we have done better with COVID-19 in nursing homes? Eur. Geriatr. Med. 2020, 11, 639–643. [Google Scholar] [CrossRef] [PubMed]
  25. Chen, A.T.; Yun, H.; Ryskina, K.L.; Jung, H.Y. Nursing home characteristics associated with resident COVID-19 morbidity in communities with high infection rates. JAMA Netw. Open 2021, 4, e211555. [Google Scholar] [CrossRef] [PubMed]
  26. Cepparulo, A.; Giuriato, L. The residential healthcare for the elderly in Italy: Some considerations for post COVID-19 policies. Eur. J. Health Econ. 2021, 27, 1–15. [Google Scholar] [CrossRef] [PubMed]
  27. Terranova, C.; Terranova, O. COVID-19 and the death of older people in Italy’s rest homes. Is a judicial turmoil the answer? Lancet Psychiatry 2020, 7, e46. [Google Scholar] [CrossRef]
  28. Bui, D.P.; See, I.; Hesse, E.M.; Varela, K.; Harvey, R.R.; August, E.M.; Winquist, A.; Mullins, S.; McBee, S.; Thomasson, E.; et al. Association between CMS quality ratings and COVID-19 outbreaks in nursing homes—West Virginia, March 17—June 11, 2020. Morb. Mortal. Wkly. Rep. 2020, 69, 1300–1304. [Google Scholar] [CrossRef]
  29. Clarke, S.P.; Donaldson, N.E. Nurse Staffing and Patient Care Quality and Safety. In Patient Safety and Quality: An Evidence-Based Handbook for Nurses; Hughes, R.G., Ed.; Agency for Healthcare Research and Quality (US): Rockville, MD, USA, 2008; Chapter 25. [Google Scholar]
  30. Gazzetta Ufficiale della Repubblica. Raccomandazioni ad Interim sui Gruppi Target della Vaccinazione Anti SARS-CoV-2/COVID-19. Available online: https://www.gazzettaufficiale.it/eli/id/2021/03/24/21A01802/sg (accessed on 15 November 2021).
  31. Rapporto ISS COVID-19, n. 16/2021. Vaccinazione Contro COVID-19 nelle Comunità Residenziali in Italia: Priorità e Modalità di Implementazione ad Interim. Available online: https://www.iss.it/rapporti-covid-19/-/asset_publisher/btw1J82wtYzH/content/rapporto-iss-covid-19-n.-16-2021-vaccinazione-contro-covid-19-nelle-comunit%25C3%25A0-residenziali-in-italia-priorit%25C3%25A0-e-modalit%25C3%25A0-di-implementazione-ad-interim.-versione-dell-8-luglio-2021-1 (accessed on 15 November 2021).
  32. Impatto dell’Epidemia COVID-19 sulla Mortalità Totale della Popolazione Residente Primo Trimestre. 2020. Available online: https://www.istat.it/it/files//2020/05/Rapporto_Istat_ISS.pdf (accessed on 10 November 2021).
  33. Bhaskaran, K.; Bacon, S.; Evans, S.J.W.; Bates, C.J.; Rentsch, C.T.; MacKenna, B.; Tomlinson, L.; Walker, A.J.; Schultze, A.; Morton, C.E.; et al. Factors associated with deaths due to COVID-19 versus other causes: Population-based cohort analysis of UK primary care data and linked national death registrations within the Open Safely platform. Lancet Reg. Health Eur. 2021, 6, 100109. [Google Scholar] [CrossRef]
  34. Mehra, M.R.; Desai, S.S.; Kuy, S.; Henry, T.D.; Patel, A.N. Cardiovascular disease, drug therapy and mortality in COVID-19. N. Engl. J. Med. 2020, 382, 2582. [Google Scholar] [CrossRef]
  35. Lippi, G.; Henry, B.M. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir. Med. 2020, 167, 105941. [Google Scholar] [CrossRef]
  36. Grippo, F.; Navarra, S.; Orsi, C.; Manno, V.; Grande, E.; Crialesi, R.; Frova, L.; Marchetti, S.; Pappagallo, M.; Simeoni, S.; et al. The role of COVID-19 in the death of SARS-CoV-2-positive patients: A study based on death certificates. J. Clin. Med. 2020, 9, 3459. [Google Scholar] [CrossRef]
  37. Slater, T.A.; Straw, S.; Drozd, M.; Kamalathasan, S.; Cowley, A.; Witte, K.K. Dying “due to” or “with” COVID-19: A cause of death analysis in hospitalized patients. Clin. Med. 2020, 5, 189–190. [Google Scholar] [CrossRef]
  38. World Health Organization. International Guidelines for Certification and Classification (Coding) of COVID-19 as Cause of Death. 2020. Available online: https://www.who.int/classifications/icd/Guidelines_Cause_of_Death_COVID-19-20200420-EN.pdf (accessed on 20 November 2021).
  39. Gruppo di Lavoro Sovrintendenza Sanitaria Centrale—INAIL ISTAT. Rapporto ISS COVID-19 n. 49/2020. COVID-19: Rapporto ad Interim su Definizione, Certificazione e Classificazione delle Cause di Morte. 2020. Available online: https://www.iss.it/documents/20126/0/Rapporto+ISS+COVID-19++49_2020+%281%29.pdf/9378da12-76ae-f51f-9666-14c7c2078a17?t=1592583825077 (accessed on 8 June 2020).
  40. Pomara, C.; Volti, G.L.; Cappello, F. COVID-19 deaths: Are we sure it is pneumonia? Please autopsy, autopsy, autopsy! J. Clin. Med. 2020, 9, 1259. [Google Scholar] [CrossRef] [PubMed]
  41. Baj, J.; Ciesielka, M.; Buszewicz, G.; Maciejewski, R.; Budzyńska, B.; Listos, P.; Teresiński, G. COVID-19 in the autopsy room–requirements, safety, recommendations and pathological findings. Forensic. Sci. Med. Pathol. 2021, 17, 101–113. [Google Scholar] [CrossRef] [PubMed]
  42. Hanley, B.; Lucas, S.B.; Youd, E.; Swift, B.; Osbornm, M. Autopsy in suspected COVID-19 cases. Clin. Pathol. 2020, 73, 239–242. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Caramaschi, S.; Kapp, M.E.; Miller, S.E.; Eisenberg, R.; Johnson, J.; Epperly, G.; Maiorana, A.; Silvestri, G.; Giannico, G.A. Histopathological findings and clinic-pathologic correlation in COVID-19: A systematic review. Mod. Pathol. 2021, 34, 1614–1633. [Google Scholar] [CrossRef] [PubMed]
  44. Barton, L.M.; Duval, E.J.; Stroberg, E.; Ghosh, S.; Mukhopadhyay, S. COVID-19 Autopsies, Oklahoma, USA. Am. J. Clin. Pathol. 2020, 153, 725–733. [Google Scholar] [CrossRef] [Green Version]
  45. Salerno, M.; Sessa, F.; Piscopo, A.; Montana, A.; Torrisi, M.; Patanè, F.; Murabito, P.; Li Volti, G.; Pomara, C. No autopsies on COVID-19 deaths: A missed opportunity and the lockdown of science. J. Clin. Med. 2020, 9, 1472. [Google Scholar] [CrossRef]
  46. D’Errico, S.; Zanon, M.; Montanaro, M.; Radaelli, D.; Sessa, F.; Di Mizio, G.; Montana, A.; Corrao, S.; Salerno, M.; Pomara, C. More than pneumonia: Distinctive features of SARS-CoV-2 infection. From autopsy findings to clinical implications: A systematic review. Microorganisms 2020, 8, 1642. [Google Scholar] [CrossRef]
  47. Giorgetti, A.; Orazietti, V.; Busardò, F.P.; Pirani, F.; Giorgetti, R. Died with or Died of? Development and Testing of a SARS-CoV-2 Significance Score to Assess the Role of COVID-19 in the Deaths of Affected Patients. Diagnostics 2021, 11, 190. [Google Scholar] [CrossRef]
  48. Edler, C.; Schroder, A.S.; Aepfelbacher, M.; Fitzek, A.; Heinemann, A.; Heinrich, F.; Klein, A.; Langenwalder, F.; Lütgehetmann, M.; Meißner, K.; et al. Dying with SARS-CoV-2 infection. An autopsy study of the first consecutive 80 cases in Hamburg, Germany. Int. J. Legal Med. 2020, 134, 1275–1284. [Google Scholar] [CrossRef]
  49. Youd, E.; Moore, L. COVID-19 autopsy in people who died in community settings: The first series. J. Clin. Pathol. 2020, 73, 840–844. [Google Scholar] [CrossRef]
  50. Elezkurtaj, S.; Greuel, S.; Ihlow, J.; Michaelis, E.G.; Bischoff, P.; Kunze, C.A.; Sinn, B.V.; Gerhold, M.; Hauptmann, K.; Ingold-Heppner, B.; et al. Causes of Death and Comorbidities in Patients with COVID-19. Sci. Rep. 2021, 11, 4263. [Google Scholar] [CrossRef] [PubMed]
  51. Ventura, F.; Molinelli, A.; Barranco, R. COVID-19-related deaths in residential care homes for elderly: The situation in Italy. J. For. Leg. Med. 2021, 80, 102179. [Google Scholar] [CrossRef] [PubMed]
  52. World Health Organization. Infection Prevention and Control for the Safe Management of a Dead Body in the Context of COVID-19. 2020. Available online: https://www.who.int/publications/i/item/infection-prevention-and-control-for-the-safe-management-of-a-dead-body-in-the-context-of-covid-19-interim-guidance (accessed on 15 November 2021).
  53. Miller, J.M.; Astles, R.; Baszler, T.; Chapin, K.; Carey, R.; Garcia, L.; Gray, L.; Larone, D.; Pentella, M.; Pollock, A.; et al. Guidelines for Safe Work Practices in Human and Animal Medical Diagnostic Laboratories. Recommendations of a CDC-Convened, Biosafety Blue Ribbon Panel. MMWR Surveill. Summ. 2012, 61, 1–102. [Google Scholar]
  54. Centers for Disease Control and Prevention. Collection and Submission of Postmortem Specimens from Deceased Persons with Known or Suspected COVID-19, March 2020. Available online: https://www.cdc.gov/coronavirus/2019-ncov/hcp/guidance-postmortem-specimens.html (accessed on 15 November 2021).
  55. Fineschi, V.; Aprile, A.; Aquila, I.; Arcangeli, M.; Asmundo, A.; Bacci, M.; Cingolani, M.; Cipolloni, L.; D’Errico, S.; de Casamassimi, I.; et al. Italian Society of Anatomical Pathology and Cytology (SIAPEC). Management of the corpse with suspect, probable or confirmed COVID-19 respiratory infection—Italian interim recommendations for personnel potentially exposed to material from corpses, including body fluids, in morgue structures and during autopsy practice. Pathologica 2020, 112, 64–77. [Google Scholar] [CrossRef]
  56. Plenzig, S.; Holz, F.; Bojkova, D.; Kettner, M.; Cinatl, J.; Verhoff, M.A.; Birngruber, C.G.; Ciesek, S.; Rabenau, H.F. Detection and infectivity of SARS-CoV-2 in exhumated corpses. Int. J. Leg. Med. 2021, 135, 2531–2536. [Google Scholar] [CrossRef] [PubMed]
  57. Li, Q.; Guan, X.; Wu, P.; Wang, X.; Zhou, L.; Tong, Y.; Ren, R.; Leung, K.S.M.; Lau, E.H.Y.; Wong, J.Y.; et al. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. N. Engl. J. Med. 2020, 13, 1199–1207. [Google Scholar] [CrossRef] [PubMed]
  58. Greenfield, S.; Blanco, D.M.; Elashoff, R.M.; Aronow, H.U. Development and testing of a new index of comorbidity. Clin. Res. 1987, 35, 346–352. [Google Scholar]
  59. Rozzini, R.; Frisoni, G.B.; Ferrucci, L.; Barbisoni, P.; Sabatini, T.; Ranieri, P.; Guralnik, J.M.; Trabucchi, M. Geriatric Index of Comorbidity: Validation and comparison with other measures of comorbidity. Age Ageing 2002, 31, 277–285. [Google Scholar] [CrossRef] [Green Version]
  60. Sahu, K.K.; Mishra, A.K.; Martin, K.; Chastain, I. COVID-19 and clinical mimics. Correct diagnosis is the key to appropriate therapy. Monaldi Arch. Chest Dis. 2020, 90, 246–247. [Google Scholar] [CrossRef]
  61. Nilsson, L.; Andersson, C.; Sjodahl, R. COVID-19 as the sole cause of death is uncommon in frail home healthcare individuals: A population-based study. BMC Geriatr. 2021, 21, 262. [Google Scholar] [CrossRef]
  62. Eliezer, M.; Hautefort, C.; Hamel, A.L.; Verillaud, B.; Herman, P.; Houdart, E.; Eloit, C. Sudden and complete olfactory loss function as a possible symptom of COVID-19. JAMA Otolaryngol. Head Neck Surg. 2020, 146, 674–675. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  63. Carsana, L.; Sonzogni, A.; Nasr, A.; Rossi, R.S.; Pellegrinelli, A.; Zerbi, P.; Rech, R.; Colombo, R.; Antinori, S.; Corbellino, M.; et al. Pulmonary post-mortem findings in a series of COVID-19 cases from northern Italy: A two-centre descriptive study. Lancet Infect. Dis. 2020, 20, 1135–1140. [Google Scholar] [CrossRef]
  64. Su, H.; Yang, M.; Wan, C.; Yi, L.X.; Tang, F.; Zhu, H.Y.; Yi, F.; Yang, H.C.; Fogo, A.B.; Nie, X.; et al. Renal histopathological analysis of 26 postmortem findings of patients with COVID-19 in China. Kidney Int. 2020, 98, 219–227. [Google Scholar] [CrossRef] [PubMed]
  65. Menter, T.; Haslbauer, J.D.; Nienhold, R.; Savic, S.; Hopfer, H.; Deigendesch, N.; Frank, S.; Turek, D.; Willi, N.; Pargger, H.; et al. Postmortem examination of COVID-19 patients reveals diffuse alveolar damage with severe capillary congestion and variegated findings in lungs and other organs suggesting vascular dysfunction. Histopathology 2020, 77, 198–209. [Google Scholar] [CrossRef] [PubMed]
  66. Bryce, C.; Grimes, Z.; Pujadas, E.; Ahuja, S.; Beasley, M.B.; Albrecht, R.; Hernandez, T.; Stock, A.; Zhao, Z.; Al Rasheed, M.; et al. Pathophysiology of SARS-CoV-2: Targeting of endothelial cells renders a complex disease with thrombotic microangiopathy and aberrant immune response. The Mount Sinai COVID-19 autopsy experience. Mod. Pathol. 2021, 34, 1456–1467. [Google Scholar] [CrossRef]
  67. Remmelink, M.; de Mendonça, R.; D’Haene, N.; de Clercq, S.; Verocq, C.; Lebrun, L.; Lavis, F.; Racu, M.L.; Trépant, A.L.; Maris, C.; et al. Unspecific post-mortem findings despite multiorgan viral spread in COVID-19 patients. Crit. Care 2020, 24, 495. [Google Scholar] [CrossRef]
  68. Gálvez-Barrón, C.; Arroyo-Huidobro, M.; Miňarro, A.; Añaños, G.; Chamero, A.; Martín, M.; Gris, C.; Avalos, J.L.; Capielo, A.M.; Ventosa, E.; et al. COVID-19: Clinical Presentation and Prognostic Factors of Severe Disease and Mortality in the Oldest-Old Population: A Cohort Study. Gerontology 2022, 68, 30–43. [Google Scholar] [CrossRef]
  69. Guo, Y.; Liu, X.; Deng, M.; Liu, P.; Li, F.; Xie, N.; Pang, Y.; Zhang, X.; Luo, W.; Peng, Y.; et al. Epidemiology of COVID-19 in older person, Wuhan China. Age Ageing 2020, 49, 706–712. [Google Scholar] [CrossRef]
  70. Falasca, L.; Nardacci, R.; Colombo, D.; Lalle, E.; Di Caro, A.; Nicastri, E.; Antinori, A.; Petrosillo, N.; Marchioni, L.; Biava, G.; et al. Postmortem Findings in Italian Patients With COVID- 19: A Descriptive Full Autopsy Study of Cases with and Without Comorbidities. J. Infect. Dis. 2020, 222, 1807–1815. [Google Scholar] [CrossRef]
  71. Maiese, A.; Manetti, A.C.; La Russa, R.; Di Paolo, M.; Turillazzi, E.; Frati, P.; Fineschi, V. Autopsy findings in COVID-19-related deaths: A literature review. Forensic. Sci. Med. 2021, 17, 279–296. [Google Scholar] [CrossRef]
  72. Singanayagam, A.; Patel, M.; Charlett, A.; Bernal, J.L.; Saliba, V.; Ellis, J.; Ladhani, S.; Zambon, M.; Gopal, R. Duration of infectiousness and correlation with RT-PCR cycle threshold values in cases of COVID-19, England, January to May 2020. Euro. Surveill. 2020, 25, 2001483. [Google Scholar] [CrossRef] [PubMed]
  73. Skok, K.; Stelzl, E.; Trauner, M.; Kessler, H.H.; Lax, S.F. Post-mortem viral dynamics and tropism in COVID-19 patients in correlation with organ damage. Virchows Arch. 2021, 478, 343–353. [Google Scholar] [CrossRef] [PubMed]
  74. Servadei, F.; Mauriello, S.; Scimeca, M.; Caggiano, B.; Ciotti, M.; Anemona, L.; Montanaro, M.; Giacobbi, E.; Treglia, M.; Bernardini, S.; et al. Persistence of SARS-CoV-2 Viral RNA in nasopharyngeal swabs after death: An observational study. Microorganisms 2021, 9, 800. [Google Scholar] [CrossRef] [PubMed]
  75. Basso, C.; Calabrese, F.; Sbaraglia, M.; Del Vecchio, C.; Carretta, G.; Saieva, A.; Donato, D.; Flor, L.; Crisanti, A.; Dei Tos, A.P. Feasibility of post-mortem examination in the era of COVID-19 pandemic: The experience of a Northeast Italy University Hospital. Virchows Archiv. 2020, 477, 341–347. [Google Scholar] [CrossRef]
  76. Musso, N.; Falzone, L.; Stracquadanio, S.; Bongiorno, D.; Salerno, M.; Esposito, M.; Sessa, F.; Libra, M.; Stefani, S.; Pomara, C. Post-Mortem Detection of SARS-CoV-2 RNA in Long-Buried Lung Samples. Diagnostics 2021, 11, 1158. [Google Scholar] [CrossRef]
  77. Rockwood, K.; Song, X.; MacKnight, C.; Bergman, H.; Hogan, D.B.; McDowell, I.; Mitnitski, A. A global clinical measure of fitness and frailty in elderly people. CMAJ 2005, 173, 489–495. [Google Scholar] [CrossRef] [Green Version]
  78. Zekrya, D.; Loures Valle, B.H.; Lardi, C.; Graf, C.; Michel, J.P.; Gold, G.; Krause, K.H.; Herrmann, F.R. Geriatrics index of comorbidity was the most accurate predictor of death in geriatric hospital among six comorbidity scores. J. Clin. Epidemiol. 2010, 63, 1036–1044. [Google Scholar] [CrossRef]
Table 1. Definition of COVID-19-related death according to the Italian Istituto Superiore di Sanità (ISS).
Table 1. Definition of COVID-19-related death according to the Italian Istituto Superiore di Sanità (ISS).
Strenght of CausationCriteria #1Criteria #2Criteria #3Criteria #4
CertainThe death occurred in a COVID-19 case (confirmed)Clinical (fever, cough, dyspnoea, dizziness, etc.) and radiological features of COVID-19 infectionNo other plausible cause of death other than COVID-19 infectionLack of wellbeing among COVID-19 infection and the death
ProbableThe death occurred in a COVID-19 case (probable)Clinical (fever, cough, dyspnoea, dizziness, etc.) and radiological features of COVID-19 infectionNo other plausible cause of death other than COVID-19 infectionLack of wellbeing among COVID-19 infection and the death
Possible (suspect)The death occurred in a COVID-19 case (suspect)Clinical (fever, cough, dyspnoea, dizziness, etc.) and radiological features of COVID-19 infectionNo other plausible cause of death other than COVID-19 infectionLack of wellbeing among COVID-19 infection and the death
Table 2. Number of comorbidities and Geriatric Index of Comorbidity (GIC).
Table 2. Number of comorbidities and Geriatric Index of Comorbidity (GIC).
Comorbidities (n)Residents (%)
0–2
3–4
5–6
>7
15
44
39
2
Geriatric Index of Comorbidity (GIC)
Class I0
Class II2
Class III20
Class IV78
Table 3. Distribution of swab results and Ct range.
Table 3. Distribution of swab results and Ct range.
NasopharingealOropharingealTrachealRight BronchusLeft BronchusRectal
Positive (n/%)24/58.5%25/61%26/63.4%28/68.3%25/61%4/10%
Negative (n/%)17/41.5%16/39%15/36.6%13/31.7%16/39%37/90%
Ct range15.47–37.1117.64–36.3518.08–35.4519.69–36.716.65–36.5632.62–35.72
Ct < 23,99 (highly positive)9148790
Ct 24–33,99 (moderately positive)1491616112
Ct > 34 (weakly positive)122552
Table 4. Strength of causation between COVID-19 infection and death.
Table 4. Strength of causation between COVID-19 infection and death.
Strength of Causation of COVID-19 InfectionCharacteristics%
High (relevant to death)≥1 positive post mortem swab, signs of diffuse alveolar damage (DAD), with or without bacterial pneumonia, regardless of GIC class12%
Intermediate (contributing to death)≥1 positive post mortem swab, moderate signs of COVID-19 infection (e.g., interstitial lymphocytic infiltrates, type II pneumocyte hyperplasia, microthrombosis) with bacterial pneumonia and GIC class < IV10%
Low
(weakly related with death)
≥1 positive post mortem swab, moderate or no signs of COVID-19 infection (e.g., interstitial lymphocytic infiltrates, type II pneumocyte hyperplasia, microthrombosis), with or without bacterial pneumonia and GIC class IV59%
None
(unrelated with death)
certain alternative cause of death, regardless of the outcome of the swab19%
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Zanon, M.; Peruch, M.; Concato, M.; Moreschi, C.; Pizzolitto, S.; Radaelli, D.; D’Errico, S. Spread of COVID-19 Infection in Long-Term Care Facilities of Trieste (Italy) during the Pre-Vaccination Era, Integrating Findings of 41 Forensic Autopsies with Geriatric Comorbidity Index as a Valid Option for the Assessment of Strength of Causation. Vaccines 2022, 10, 774. https://doi.org/10.3390/vaccines10050774

AMA Style

Zanon M, Peruch M, Concato M, Moreschi C, Pizzolitto S, Radaelli D, D’Errico S. Spread of COVID-19 Infection in Long-Term Care Facilities of Trieste (Italy) during the Pre-Vaccination Era, Integrating Findings of 41 Forensic Autopsies with Geriatric Comorbidity Index as a Valid Option for the Assessment of Strength of Causation. Vaccines. 2022; 10(5):774. https://doi.org/10.3390/vaccines10050774

Chicago/Turabian Style

Zanon, Martina, Michela Peruch, Monica Concato, Carlo Moreschi, Stefano Pizzolitto, Davide Radaelli, and Stefano D’Errico. 2022. "Spread of COVID-19 Infection in Long-Term Care Facilities of Trieste (Italy) during the Pre-Vaccination Era, Integrating Findings of 41 Forensic Autopsies with Geriatric Comorbidity Index as a Valid Option for the Assessment of Strength of Causation" Vaccines 10, no. 5: 774. https://doi.org/10.3390/vaccines10050774

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop