Background: The long-term effects of COVID-19 remain largely unclear. This study aims to investigate post-acute health consequences and mortality one year after hospital discharge. Methods: All surviving adult patients who were discharged after hospital admission due to acute COVID-19 in the first wave of the pandemic underwent a comprehensive interview. Functional assessment was performed in patients aged over 65. Clinical and hospital records were reviewed and mortality causes assessed. Results: A total of 587 patients with COVID-19 were discharged from hospital, including 266 after hospital admission and 321 from the emergency room. Mortality within the following year occurred in 34/266 (12.8%) and 10/321 (3.1%), respectively, due to causes directly or possibly related to COVID-19 in 20.5% and 25% of patients. Post-COVID-19 syndrome was assessed in 543 patients at one year from discharge. Any clinical complaint was reported by 90.1% of patients who needed hospitalization and 80.4% of those discharged from the emergency room (p = 0.002), with breathlessness (41.6%), tiredness (35.4%), ageusia (30.2%), and anosmia (26.3%) being the most common complaints. Ongoing symptoms attributed to COVID-19 were reported by 66.8% and 49.5% of patients, respectively (p < 0.001). Newly developed COPD, asthma, diabetes, heart failure, and arthritis—as well as worsening of preexisting comorbidities—were found. Conclusions: One-year mortality among survivors of acute COVID-19 was 7.5%. A significant proportion of COVID-19 patients experienced ongoing symptoms at 1 year from onset of the disease.

Background: Risk factors for in-hospital mortality from severe coronavirus disease 2019 (COVID-19) infection have been identified in studies mainly carried out in urban-based teaching hospitals. However, there is little data for rural populations attending community hospitals during the first wave of the pandemic. Methods: A retrospective, single-center cohort study was undertaken among inpatients at a rural community hospital in Spain. Electronic medical records of the 444 patients (56.5% males) admitted due to severe SARS-CoV-2 infection during 26 February 2020–31 May 2020 were reviewed. Results: Mean age was 71.2 ± 14.6 years (rank 22–98), with 69.8% over 65. At least one comorbidity was present in 410 patients (92.3%), with chronic obstructive pulmonary disease (COPD) present in 21.7%. Overall in-hospital mortality was 32%. Multivariate analysis of factors associated with death identified patients’ age (with a cumulative effect per decade), COPD as a comorbidity, and respiratory insufficiency at the point of admission. No additional comorbid conditions proved significant. Among analytical values, increased serum creatinine, LDH > 500 mg/dL, thrombocytopenia (<150 × 109/per L), and lymphopenia (<1000 cells/µL) were all independently associated with mortality during admission. Conclusions: Age remained the major determinant for COVID-19-caused mortality; COPD was the only comorbidity independently associated with in-hospital death, together with respiratory insufficiency and analytical markers at admission.

Multiple prediction models for risk of in-hospital mortality from COVID-19 have been developed, but not applied, to patient cohorts different to those from which they were derived. The MEDLINE, EMBASE, Scopus, and Web of Science (WOS) databases were searched. Risk of bias and applicability were assessed with PROBAST. Nomograms, whose variables were available in a well-defined cohort of 444 patients from our site, were externally validated. Overall, 71 studies, which derived a clinical prediction rule for mortality outcome from COVID-19, were identified. Predictive variables consisted of combinations of patients′ age, chronic conditions, dyspnea/taquipnea, radiographic chest alteration, and analytical values (LDH, CRP, lymphocytes, D-dimer); and markers of respiratory, renal, liver, and myocardial damage, which were mayor predictors in several nomograms. Twenty-five models could be externally validated. Areas under receiver operator curve (AUROC) in predicting mortality ranged from 0.71 to 1 in derivation cohorts; C-index values ranged from 0.823 to 0.970. Overall, 37/71 models provided very-good-to-outstanding test performance. Externally validated nomograms provided lower predictive performances for mortality in their respective derivation cohorts, with the AUROC being 0.654 to 0.806 (poor to acceptable performance). We can conclude that available nomograms were limited in predicting mortality when applied to different populations from which they were derived.