Rate and risk factors of in-hospital and early post-discharge mortality in patients admitted to an internal medicine ward

Background: We sought to quantify in-hospital and early post-discharge mortality rates in hospitalised patients. Methods: Consecutive adult patients admitted to an internal medicine ward were prospectively enrolled. The rates of in-hospital and 4-month post-discharge mortality and their possible associated sociodemographic and clinical factors (eg Cumulative Illness Rating Scale [CIRS], body mass index [BMI], polypharmacy, Barthel Index) were assessed. Results: 1,451 patients (median age 80 years, IQR 69-86; 53% female) were included. Of these, 93 (6.4%) died in hospital, while 4-month post-discharge mortality was 15.9% (191/1,200). Age and high dependency were associated (p<0.01) with a higher risk of in-hospital (OR 1.04 and 2.15) and 4-month (HR 1.04 and 1.65) mortality, while malnutrition and length of stay were associated (p<0.01) with a higher risk of 4-month mortality (HR 2.13 and 1.59). Conclusions: Several negative prognostic factors for early mortality were found. Interventions addressing dependency and malnutrition could potentially decrease early post-discharge mortality

Resilience is associated with frailty and older age in hospitalised patients

Abstract Background Little is known about resilience in an internal medicine setting. We aimed to assess the relationship between resilience and frailty and other clinical and sociodemographic characteristics in a cohort of prospectively enrolled hospitalised patients. Methods In 2017–2019, we consecutively enrolled patients in our internal medicine wards. We selected all patients who filled in the 25-item Connor-Davidson resilience scale (CD-RISC). Mean resilience was evaluated according to baseline demographic (i.e., age, sex, marital and socioeconomic status) and clinical (i.e., Cumulative Illness Rating Scale [CIRS], Edmonton Frail Scale [EFS], Barthel index, Short Blessed test, length of stay [LOS]) data. A multivariable analysis for assessing factors affecting resilience was fitted. Results Overall, 143 patients (median age 69 years, interquartile range 52–79, 74 females) were included. Resilience was significantly lower in frail (p = 0.010), elderly (p = 0.021), dependent (p = 0.032), and more clinically (p = 0.028) and cognitively compromised patients (p = 0.028), and in those with a low educational status (p = 0.032). No relation between resilience and LOS was noticed (p = 0.597). Frail patients were significantly older (p < 0.001), had a greater disease burden as measured by CIRS comorbidity (p < 0.001) and severity indexes (p < 0.001), were more dependent (p < 0.001), more cognitively impaired (p < 0.001), and displayed a lower educational level (p = 0.011) compared to non-frail patients. At multivariable analysis, frailty (p = 0.022) and dependency (p = 0.031; according to the Barthel index) were associated with lower resilience in the age groups 18–64 and ≥ 65 years, respectively. Conclusions Low resilience was associated with frailty and dependency with an age-dependent fashion. Studies assessing the impact of this finding on important health outcomes are needed. Trial registration Clinical Complexity in Internal Medicine Wards. San MAtteo Complexity Study (SMAC); NCT03439410 . Registered 01/11/2017

Aging underlies heterogeneity between comorbidity and multimorbidity frameworks

Studies exploring differences between comorbidity (i.e., the co-existence of additional diseases with reference to an index condition) and multimorbidity (i.e., the presence of multiple diseases in which no one holds priority) are lacking. In this single-center, observational study conducted in an academic, internal medicine ward, we aimed to evaluate the prevalence of patients with two or more multiple chronic conditions (MCC), comorbidity, or multimorbidity, correlating them with other patients' characteristics. The three categories were compared to the Cumulative Illness Rating Scale (CIRS) comorbidity index, age, gender, polytherapy, 30-day readmission, in-hospital and 30-day mortalities. Overall, 1394 consecutive patients (median age 80 years, IQR 69-86; F:M ratio 1.16:1) were included. Of these, 1341 (96.2%; median age 78 years, IQR 65-84; F:M ratio 1.17:1) had MCC. Fifty-three patients (3.8%) had no MCC, 286 (20.5%) had comorbidity, and 1055 (75.7%) had multimorbidity, showing a statistically significant (p &lt; 0.001) increasing age trend (median age 38 years vs 71 vs 82, respectively) and increasing mean CIRS comorbidity index (1.53 +/- 0.95 vs 2.97 +/- 1.43 vs 4.09 +/- 1.70, respectively). The CIRS comorbidity index was always higher in multimorbid patients, but only in the subgroups 75-84 years and &gt;= 85 years was a significant (p &lt; 0.001) difference (1.24 and 1.36, respectively) noticed. At multivariable analysis, age was always independently associated with in-hospital mortality (p = 0.002), 30-day mortality (p &lt; 0.001), and 30-day readmission (p = 0.037), while comorbidity and multimorbidity were not. We conclude that age determines the most important differences between comorbid and multimorbid patients, as well as major outcomes, in a hospital setting

Clinical complexity and hospital admissions in the December holiday period.

BackgroundChristmas and New Year's holidays are risk factors for hospitalization, but the causes of this "holiday effect" are uncertain. In particular, clinical complexity (CC) has never been assessed in this setting. We therefore sought to determine whether patients admitted to the hospital during the December holiday period had greater CC compared to those admitted during a contiguous non-holiday period.MethodsThis is a prospective, longitudinal study conducted in an academic ward of internal medicine in 2017-2019. Overall, 227 consecutive adult patients were enrolled, including 106 cases (mean age 79.4±12.8 years, 55 females; 15 December-15 January) and 121 controls (mean age 74.3±16.6 years, 56 females; 16 January-16 February). Demographic characteristics, CC, length of stay, and early mortality rate were assessed. Logistic regression analyses for the evaluation of independent correlates of being a holiday case were computed.ResultsCases displayed greater CC (17.7±5.5 vs 15.2±5.9; p = 0.001), with greater impact of socioeconomic (3.51±1.7 vs 2.9±1.7; p = 0.012) and behavioral (2.36±1.6 vs 1.9±1.8; p = 0.01) CC components. Cases were also significantly frailer according to the Edmonton Frail Scale (8.0±2.8 vs 6.4±3.1; pConclusionsPatients hospitalized during the December holiday period had worse health outcomes, and this could be attributable to the grater CC, especially related to socioeconomic (social deprivation, low income) and behavioral factors (inappropriate diet). The evaluation of all CC components could potentially represent a useful tool for a more rational resource allocation over this time of the year

A mid-term follow-up with a lung ultrasonographic score correlates with the severity of COVID-19 acute phase

Lung ultrasound (LUS) has rapidly emerged in COVID-19 diagnosis and for the follow-up during the acute phase. LUS is not yet used routinely in lung damage follow-up after COVID-19 infection. We investigated the correlation between LUS score, and clinical and laboratory parameters of severity of SARS-COV-2 damage during hospitalization and at follow-up visit. Observational retrospective study including all the patients discharged from the COVID-19 wards, who attended the post-COVID outpatient clinic of the IRCCS Policlinico San Matteo in April-June 2020. 115 patients were enrolled. Follow-up visits with LUS score measurements were at a median of 38 days (IQR 28-48) after discharge. LUS scores were associated with the length of hospitalization (p  9 points). We found a significantly higher LUS score at the follow-up in the patients with persistent dyspnea (7.00, IQR 3.00-11.00) when compared to eupnoeic patients (3.00, IQR 0-7.00 p < 0.001). LUS score at follow-up visit correlates with more severe lung disease. These findings support the hypothesis that ultrasound could be a valid tool in the follow-up medium-term COVID-19 lung damage

Mid-term follow-up chest CT findings in recovered COVID-19 patients with residual symptoms

Objectives: More than a year has passed since the initial outbreak of SARS-CoV-2, which caused many hospitalizations worldwide due to COVID-19 pneumonia and its complications. However, there is still a lack of information detailing short- and long-term outcomes of previously hospitalized patients. The purpose of this study is to analyze the most frequent lung CT findings in recovered COVID-19 patients at mid-term follow-ups. Methods: A total of 407 consecutive COVID-19 patients who were admitted to the Fondazione IRCCS Policlinico San Matteo, Pavia and discharged between February 27, 2020, and June 26, 2020 were recruited into this study. Out of these patients, a subset of 108 patients who presented with residual asthenia and dyspnea at discharge, altered spirometric data, positive lung ultrasound and positive chest X-ray was subsequently selected, and was scheduled to undergo a mid-term chest CT study, which was evaluated for specific lung alterations and morphological patterns. Results: The most frequently observed lung CT alterations, in order of frequency, were ground-glass opacities (81%), linear opacities (74%), bronchiolectases (64.81%), and reticular opacities (63.88%). The most common morphological pattern was the non-specific interstitial pneumonia pattern (63.88%). Features consistent with pulmonary fibrosis were observed in 32 patients (29.62%). Conclusions: Our work showed that recovered COVID-19 patients who were hospitalized and who exhibited residual symptoms after discharge had a slow radiological recovery with persistent residual lung alterations. Advances in knowledge: This slow recovery process should be kept in mind when determining the follow-up phases in order to improve the long-term management of patients affected by COVID-19