Hospital length of stay for COVID-19 patients: a systematic review and meta-analysis

A Retrospective Claims Data Analysis on the Burden of COVID-19-Related Hospitalization in Adults at High Risk for Severe Disease Progression in Germany

INTRODUCTION

Individuals at increased risk of severe coronavirus disease 2019 (COVID-19) progression have a higher probability of being hospitalized. Nirmatrelvir/ritonavir (NMV/r) is an antiviral drug aiming to prevent severe disease courses. Our study aimed to assess the resource utilization and costs of adults hospitalized for COVID-19 at high risk for severe disease progression.

METHODS

A retrospective study was conducted using German claims data. The presence of high-risk criteria was determined through recorded diagnoses, operations, procedures, and prescriptions. Individuals at high risk for severe COVID-19 progression, primarily hospitalized for COVID-19, required a recorded diagnosis for COVID-19 and additionally a diagnosis of sepsis, pulmonary embolism, acute respiratory failure, pneumonia, or a remdesivir prescription. Patients were grouped by eligibility for NMV/r treatment (eligible, eligible with restrictions, and not eligible). The outcomes of interest were reported for the timeframe of the last dominant virus variant available in the database, i.e., Delta (June 21, 2021 to December 31, 2021).

RESULTS

Of approximately 3.7 million individuals continuously observable in the database, about 60% were identified as being at high risk for severe COVID-19 progression. Among high-risk individuals, 2938 patients were primarily hospitalized for COVID-19 between June 21, 2021, and December 31, 2021, two-thirds of which were suitable for NMV/r treatment (half without restrictions). Advanced age (86.3%) and cardiovascular conditions (83.9%) were the most prevalent of the predefined risk factors. Identified patients stayed, on average, 11.3 days in hospital, with inpatient mortality of 18.9%. These COVID-19-related hospitalizations resulted in mean healthcare costs of €8728.

CONCLUSIONS

This study reflects the economic burden of hospitalized adult individuals with COVID-19 at high risk for severe disease progression from payer's perspective in Germany. Our findings highlight the need to prevent severe disease courses and associated hospitalizations to relieve healthcare systems regarding costs and resource allocation.

Modeling time-varying spatial accessibility to healthcare: A system dynamic approach

Spatial accessibility to healthcare is essential for policymakers to identify health disparities and develop targeted interventions. Current modeling approaches poorly capture temporal dynamics of contributing factors, and few have represented dynamic interactions among these factors. Further, validating current models is hindered by data limitations and methodological challenges. To fill these gaps, I propose a new modeling approach that produces time-varying and empirically validated measures of healthcare accessibility. Specifically, I develop a system dynamic model to represent interplay between population demand and healthcare supply over time. The model simultaneously estimated people's potential accessibility to healthcare and their utilization over time and space, then validated these estimates with actual hospitalization data. To illustrate the model's practical use, a working prototype was constructed to estimate and validate healthcare accessibility by day and by ZIP code in Florida, USA, during a disease outbreak in 2022-23. The results indicate that system dynamic modeling offers a robust framework for monitoring healthcare accessibility fluctuations across regions and time periods, thereby guiding the development of timely and targeted interventions to reduce disparities.

Unveiling pandemic patterns: a detailed analysis of transmission and severity parameters across four COVID-19 waves in Bogotá, Colombia

BACKGROUND

Despite a wealth of data from high-income countries, there is limited information on the distinct epidemiological patterns observed in diverse, densely populated regions within Latin America. This retrospective analysis of COVID-19's four major waves in Bogotá, Colombia, evaluates 1.77 million cases in detail.

METHODS

A comprehensive suite of statistical methods was employed. Transmission dynamics were assessed by estimating the instantaneous reproduction number R ( t ) , while variant-specific transmission advantages were estimated using multinomial logistic regression models. Disease severity was assessed through a suite of indicators: Hospitalisation Case Ratio (HCR), intensive care unit case ratio (ICU-CR), case fatality ratio (CFR), hospitalisation fatality ratio (HFR), and ICU fatality ratio (ICU-FR). Additionally, we analysed the distribution of hospitalisations, ICU admissions, and fatalities by age group and wave. We employed a Bayesian hierarchical model to capture epidemiological delays-such as onset-to-death, hospitalisation, and ICU admission durations to estimate hospital and ICU stay durations.

RESULTS

Our findings reveal substantial variation in R ( t ) , with peaks exceeding 2.5 during the ancestral and Omicron waves. Over the course of the pandemic, we observed a 78% reduction in CFR, underscoring shifts in clinical severity. The third wave, associated with the Mu variant, recorded the highest case and death counts, alongside a decreased CFR, an elevated HFR, and a shift in the most affected age group towards younger populations. In contrast, the fourth wave, driven by the Omicron variant, exhibited the highest reproduction number and the lowest overall severity. This wave was characterised by a significant increase in pediatric hospitalisations. The study reveals a continued decline in the mean durations of hospital and ICU stays across the four waves, with hospital stays decreasing from 10.84 to 7.85 days and ICU stays dropping from 16.2 to 12.4 days.

CONCLUSIONS

This study reveals significant shifts in transmission and severity metrics-including mortality, hospitalisation, and ICU rates and stays-across age groups during Bogotá's four COVID-19 waves. These insights underscore the value of retrospective analyses to understand the pandemic's varied impact and inform public health strategies in diverse urban settings.

Association of COVID-19 with thyroid dysfunction and autoimmune thyroid disease: A retrospective cohort study

Background

Since the end of the COVID-19 pandemic, the potential roles of thyroid-inflammatory derangements in driving or being associated with the prognosis of COVID-19 remain controversial. We aimed to clarify the association between COVID-19 infection and thyroid dysfunction, and highlight the impacts of subsequent autoimmune thyroid disease (AITD) on the prognosis of COVID-19.

Methods

The retrospective, multicenter, cohort study enrolled 2,339 participants with COVID-19 from three hospitals located in the north, middle, and south regions of Shaan Xi Province, China, between December 2022 and July 2023. 464 non-COVID-19 patients within the same period were supplemented, divided into groups with and without AITD. At hospital admission (baseline), 3- and 6-month follow-ups, we presented a dynamic description and correlation analysis of thyroid-inflammatory-autoimmune derangements in patients with AITD.

Results

A total of 2,082 COVID-19 patients diagnosed with AITD and 257 cases without AITD were included in the study, and 464 non-COVID-19 patients were supplemented, dividing into 14 AITD and 450 non-AITD cases. We found that COVID-19 infection was closely associated with thyroid dysfunction (χ 2  = 1518.129, p = 0.000). AITD patients with COVID-19 showed a higher prevalence of symptoms and comorbidities and longer hospital stays at baseline than non-AITD patients with COVID-19 (p = 0.000, p = 0.000, and p = 0.000). The baseline free triiodothyronine (FT3), free thyroxine, and radioactive iodine uptake at 24 h in AITD cases significantly decreased (p = 0.000, p = 0.000, and p = 0.000), while thyroid stimulating hormone, thyroglobulin, reverse triiodothyronine (rT3), and thyroid antibodies varying elevated from the baseline to the follow-up (baseline: p = 0.000, p = 0.000, p = 0.000, p = 0.000, p = 0.000, and p = 0.000; 3-month follow-up: p = 0.000, p = 0.000, p = 0.000, p = 0.000, p = 0.030, and p = 0.000). C-reactive protein, calcitonin, interleukin-6, -8, -10, and tumor necrosis factor-α rose significantly at baseline (p = 0.000, p = 0.000, p = 0.000, p = 0.000, p = 0.000, and p = 0.000) in AITD. Interferon-α and interferon-γ at baseline showed a significant decrease (p = 0.000 and p = 0.000), and remained at low levels after 6 months (p = 0.000 and p = 0.000). FT3 and rT3 were positively and negatively correlated with hospitalization, respectively (r = -0.208 and 0.231; p = 0.000 and p = 0.000). ROC curves showed that FT3 and rT3 had better robustness in predicting severe COVID-19 prognosis (AUC = 0.801 and 0.705). Ordered logistic regression revealed that ORs were 0.370, 0.048, and 0.021 for AITD [(subacute thyroiditis, Grave's disease, and Hashimoto's thyroiditis compared to non-thyroidal illness syndrome (NTIS)] with COVID-19 risk, indicating that NTIS was the predominant risk factor for the severity of COVID-19.

Conclusions

A robust association has been identified, wherein COVID-19 infection is closely associated with thyroid dysfunction, and the subsequent AITD may aggravate the poor prognosis of COVID-19.

Hospital costs of COVID-19, post-COVID-19 condition and other viral pneumonias: a cost comparison analysis

OBJECTIVES

To compare hospital admission costs for coronavirus disease 2019 (COVID-19) cases to hospital admission costs for other viral pneumonia cases in Australia, and to describe hospital admission costs for post-COVID-19 condition.

DESIGN, SETTING, PARTICIPANTS

A cost comparison analysis of hospital admissions due to COVID-19 or other viral pneumonias between 1 January 2020 and 30 June 2021 at Victorian public health acute and subacute services.

MAIN OUTCOME MEASURES

Demographic characteristics, clinical outcomes (including diagnoses, impairment, subacute admission, intensive care unit admissions, ventilation, and length of stay) and cost data (including diagnostic-related groups, and total, direct and indirect costs).

RESULTS

During the study period, 3197 patients were admitted to hospital due to COVID-19 and 15 761 were admitted for other viral pneumonias. Admissions for COVID-19 cost 29% more than admissions for other viral pneumonias. Admissions for COVID-19 requiring intensive care unit admission incurred significantly higher mean costs (A$120 504 or US$90 595) compared with those not requiring intensive care unit admission (A$19 634 or US$14 761). The adjusted cost of admissions related to post-COVID-19 condition was A$11 090 or US$8 337, and these admissions were significantly more likely to be elective. Direct costs accounted for most of the costs for all groups, and admissions for post-COVID-19 condition used less allied health services than other groups.

CONCLUSIONS

Given its recent emergence, cases of acute COVID-19 and post-COVID-19 condition have had a significant additional financial impact on Australian hospitals. Further studies are required to understand long term costs and identify trends over time in the context of increased vaccination rates and subsequent variants of severe acute respiratory syndrome coronavirus 2.

Tracing In-Hospital COVID-19 Outcomes: A Multistate Model Exploration (TRACE)

This study aims to develop and apply multistate models to estimate, forecast, and manage hospital length of stay during the COVID-19 epidemic without using any external packages. Data from Bellvitge University Hospital in Barcelona, Spain, were analyzed, involving 2285 hospitalized COVID-19 patients with moderate to severe conditions. The implemented multistate model includes transition probabilities and risk rates calculated from transitions between defined states, such as admission, ICU transfer, discharge, and death. In addition to examining key factors like age and gender, diabetes, lymphocyte count, comorbidity burden, symptom duration, and different COVID-19 waves were analyzed. Based on the model, patients hospitalized stay an average of 11.90 days before discharge, 2.84 days before moving to the ICU, or 34.21 days before death. ICU patients remain for about 24.08 days, with subsequent stays of 124.30 days before discharge and 35.44 days before death. These results highlight hospital stays' varying durations and trajectories, providing critical insights into patient flow and healthcare resource utilization. Additionally, it can predict ICU peak loads for specific subgroups, aiding in preparedness. Future work will integrate the developed code into the hospital's Health Information System (HIS) following ISO 13606 EHR standards and implement recursive methods to enhance the model's efficiency and accuracy.

The Interplay between Gender and Duration of Hospitalization Modulates Psychiatric Symptom Severity in Subjects with Long COVID-19

Long COVID-19 is characterized by ongoing symptoms or prolonged or long-term complications of SARS-CoV-2 contraction which persist beyond 4 weeks from the initial onset of symptoms. Gender and duration of hospitalization (DH) are key risk factors for developing long COVID-19 syndrome, but their impact and interplay need further study. This research involved 996 long COVID-19 patients, and we compared the levels of general psychopathology, depression, agitated depression, anxiety, and medication use between hospitalized and non-hospitalized males and females. In the hospitalized patients, multivariate regressions assessed the impact of gender, DH, and the interaction of these variables. The females had higher levels of long COVID-19 symptoms, psychotropic drug use, depression, anxiety, and general psychopathology than the males. The non-hospitalized females exhibited more severe agitated depression than the non-hospitalized males. In females, DH was more strongly correlated with the number of psychotropic medications used during long COVID-19. A negative correlation was found between DH and severity of agitated depression in the female patients only. These results highlight that the gender-specific relationship between DH and agitated depression severity should be explored further.

The efficacy of herbal medicines on the length of stay and negative conversion time/rate outcomes in patients with COVID-19: a systematic review

Introduction

In recent years, diverse initiatives have been carried out to control the COVID-19 pandemic, ranging from measures restricting social activities to analyzing drugs and vaccines. Studies on herbal medicines are also increasingly conducted in various countries as an adjuvant therapy or supplement. Therefore, this systematic review aimed to investigate the efficacy of herbal medicines analyzed from various countries through clinical trials with the randomized controlled trial method. The outcomes of Length of Stay (LOS), Negative Conversion Time (NCT), and Negative Conversion Rate (NCR) were the main focus.

Methods

An extensive review of literature spanning from 2019 to 2023 was carried out using well-known databases including PubMed, Scopus, and Cochrane. The search included relevant keywords such as "randomized controlled trial," "COVID-19," and "herbal medicine."

Results

A total of 8 articles were part of the inclusion criteria with outcomes of LOS, NCT, and NCR. In terms of LOS outcomes, all types of herbal medicines showed significant results, such as Persian Medicine Herbal (PM Herbal), Persian Barley Water (PBW), Jingyin Granules (JY granules), Reduning Injection, and Phyllanthus emblica (Amla). However, only JY granules showed significant results in NCR outcome, while JY granules and Reduning Injection showed significant results in reducing NCT.

Conclusion

These findings enrich our understanding of the potential benefits of herbal medicines in influencing LOS, NCR and NCT parameters in COVID-19 patients. Herbal medicines worked to treat COVID-19 through antiviral, anti-inflammatory, and immunomodulatory mechanisms.

Elevated neutrophil-lymphocyte ratio is associated with high rates of ICU mortality, length of stay, and invasive mechanical ventilation in critically ill patients with COVID-19 : NRL and severe COVID-19

Neutrophil and lymphocyte ratio (NLR) has emerged as a complementary marker in intensive care. This study aimed to associate high NLR values with mortality as the primary outcome, and length of stay and need for invasive mechanical ventilation as secondary outcomes, in critically ill patients with COVID-19. A cross-sectional study encompassing 189 critically ill patients with COVID-19 was performed. The receiver operating characteristic curve was used to identify the best NLR cutoff value for ICU mortality (≥ 10.6). An NLR ≥ 10.6, compared with an NLR < 10.6, was associated with higher odds of ICU mortality (odds ratio [OR], 2.77; 95% confidence interval [CI], 1.24-6.18), ICU length of stay ≥ 14 days (OR, 3.56; 95% CI, 1.01-12.5), and need for invasive mechanical ventilation (OR, 5.39; 95% CI, 1.96-14.81) in the fully adjusted model (age, sex, kidney dysfunction, diabetes, obesity, hypertension, deep vein thrombosis, antibiotics, anticoagulants, antivirals, corticoids, neuromuscular blockers, and vasoactive drugs). In conclusion, elevated NLR is associated with high rates of mortality, length of stay, and need for invasive mechanical ventilation in critically ill patients with COVID-19.

Effect of COVID-19 on infections associated with medical devices in critical care

OBJECTIVES

This study explores the hypothesis that COVID-19 patients are at a heightened risk of healthcare-associated infections (HAIs) associated with medical device usage compared to non-COVID-19 patients. Our primary objective was to investigate the correlation between COVID-19 infection in ICU patients and subsequent HAIs following invasive medical device insertion. Additionally, we aim to assess the impact of SARS-CoV-2 infection on onset times concerning specific microorganisms and the type of medical device, providing valuable insights into this intricate relationship in intensive care settings.

METHODOLOGY

A retrospective cohort study was conducted using ICU patient records at our hospital from 2020 to 2022. This investigation entailed evaluating the timing of HAIs while distinguishing between patients with and without SARS-CoV-2 infection. We identified and analyzed the type of isolation and infection attributed to the medical device while controlling for ICU duration and ventilator days using Cox regression.

RESULTS

Our study included 127 patients without SARS-CoV-2 infection and 140 patients with SARS-CoV-2 infection. The findings indicated a higher incidence of HAI caused by various microorganisms associated with any medical device in patients with SARS-CoV-2 (HR = 6.86; 95% CI-95%: 3.26-14.43; p < 0.01). After adjusting for ICU duration and ventilator days, a heightened frequency of HAIs persisted in SARS-CoV-2-infected individuals. However, a detailed examination of HAIs revealed that only ventilation-associated pneumonia (VAP) displayed a significant association (HR = 6.69; 95% CI: 2.59-17.31; p < 0.01). A statistically significant correlation between SARS-CoV-2 infection and the isolation of S. aureus was also observed (p = 0.034). The prevalence of S. aureus infection was notably higher in patients with SARS-CoV-2 (RR = 8.080; 95% CI: 1.052-62.068; p < 0.01).

CONCLUSIONS

The frequency of pathogen isolates in invasive medical devices exhibited an association with SARS-CoV-2 infection. Critically ill patients with SARS-CoV-2 are more prone to developing early-onset VAP than those without SARS-CoV-2 infection.

Neurological Manifestations in Hospitalized Geriatric Patients With COVID-19 at King Abdulaziz Medical City in Jeddah, Western Region, Saudi Arabia From 2020 to 2021: A Cross-Sectional Study

Introduction COVID-19 involvement in the nervous system has been reported in many cases. Viral neuroinvasion has multiple routes of entry. Neurological manifestations of COVID-19 can be divided into ones of the central nervous system (CNS), such as headache, dizziness, altered mental status, ataxia, and seizure, and of the peripheral nervous system (PNS), including ageusia, anosmia, acute illness demyelinating polyneuropathy, and neuralgia. Aim and objectives This study aims to observe and report the neurological manifestations in geriatric patients who were diagnosed with COVID-19 at KAMC-J and report the duration of admission to the in-patient and ICU wards. Methods This was a cross-sectional study conducted on admitted geriatric patients with PCR-confirmed COVID-19 from April 1, 2020 to June 30, 2021 at KAMC-J. Using Raosoft®, the sample size was estimated with a CI of 95% and a 36.4% prevalence of neurological symptoms in COVID-19 patients to be 289. Convenience sampling was used, and the data were collected from BESTCare EMRs. IBM SPSS Statistics for Windows, Version 20 (Released 2011) was used for descriptive and inferential statistical analysis. Results In this study, a total of 290 patients' data were collected, 161 (55.5%) of which were males. In addition, the median age was 71 (Q1-Q3: 65-78) years; furthermore, the median body mass index (BMI) was 30(Q1-Q3: 25-34) kg/m2. In descending order, the most prevalent comorbidities were hypertension (HTN) (70.3%), diabetes mellitus (DM) (68.6%), cardiac disease (42.1%), chronic kidney disease (26.6%), neurological disease (23.6%), cancer malignancy (13.1%), and finally chronic respiratory disease (11.4%). Regarding typical COVID-19 manifestations, 181 patients claimed to have experienced cough (62.4%), dyspnea by 164 (56.7%), fever by 154 (53.5%), fatigue by 93 (32.3%), a reading of anoxia by 68 (23.4%), abdominal pain by 58 (20.0%), diarrhea by 56 (19.4%), and finally throat pain by 19 (6.6%). Manifestations and pathologies of the CNS included headache (25.4%), dizziness (21.5%), impaired consciousness (17.2%), delirium (6.6%), ischemic stroke (4.1%), focal cranial nerve dysfunction (2.8%), seizure (2.8%), intracerebral hemorrhage (ICH) (0.3%), and ataxia (0.3%). Moreover, pathologies of the PNS manifested as taste impairment in 46 patients (15.9%), smell impairment in 33 (11.4%), nerve pain in 7 (24%), visual impairment in 5 (1.7%), Bell's palsy in 2 (0.7%), and Guillain-Barre syndrome in 1 (0.3%). Moreover, the majority of patients who developed an ischemic stroke or ICH, or required admission to the ICU had either DM or HTN. In addition, 17 (25.4%) of the 67 patients admitted to the ICU developed impaired consciousness. All-cause mortality in our study was 31 (10.71%) cases. Conclusion Neurological manifestations of COVID-19 are common and can result in serious complications if not detected and managed early, especially in the elderly. These complications are mostly seen in severely ill patients and may be the only symptoms in COVID-19 patients. In addition, patients' clinical conditions could deteriorate rapidly and result in significant morbidity and mortality. Therefore, a high index of suspicion is required among healthcare providers when dealing with such cases. Moreover, we recommend systematically collecting data on the short- and long-term neurological complications of COVID-19 globally and documenting the functional long-term outcomes after these complications.

Distinct Clinical Presentations and Outcomes of Hospitalized Adults with the SARS-CoV-2 Infection Occurring during the Omicron Variant Surge

The COVID-19 Omicron variant has imposed a tremendous burden on healthcare services. We characterized the types of the Omicron variant-associated hospitalizations and their associations with clinical outcomes. Consecutive adults hospitalized with COVID-19 during the Omicron variant surge period of 1-14 January 2022, were classified into one of three groups based on their clinical presentations on admission: Group 1-primary COVID-19; Group 2-extrapulmonary manifestations of COVID-19; and Group 3-incidental COVID-19. Of the 500 patients who were hospitalized, 51.4% fell into Group 1, 16.4% into Group 2, and 32.2% into Group 3. The patients in Groups 1 and 2 were older, with higher proportions of comorbidities than patients in Group 3. The Group 1 patients had the highest mortality rate (15.6%), followed by Group 2 (8.5%), and Group 3 (0.6%), with adjusted odds ratios (OR) of 22.65 (95% confidence interval [CI], 2.75-239.46; p = 0.004) and 10.95 (95% CI, 1.02-117.28; p = 0.048), respectively, compared to Group 3. Those in Group 1 showed a greater utilization of intensive care services (15.9%), followed by Group 2 (10.9%), and Group 3 (2.5%), with adjusted ORs of 7.95 (95% CI, 2.52-25.08; p < 0.001) and 5.07 (95% CI, 1.34-19.15; p = 0.017), respectively, compared to Group 3. The patients in Groups 1 and 2 had longer hospitalization stays than the patients in Group 3 (p < 0.001 and p = 0.002, respectively). Older age (≥65 years) was an independent factor associated with longer hospital stays (OR = 1.72, 95% CI, 1.07-2.77). These findings can help hospitals prioritize patient care and service planning for future SARS-CoV-2 variants.

Differential in-hospital mortality and intensive care treatment over time: Informing hospital pathways for modelling COVID-19 in South Africa

There are limited published data within sub-Saharan Africa describing hospital pathways of COVID-19 patients hospitalized. These data are crucial for the parameterisation of epidemiological and cost models, and for planning purposes for the region. We evaluated COVID-19 hospital admissions from the South African national hospital surveillance system (DATCOV) during the first three COVID-19 waves between May 2020 and August 2021. We describe probabilities and admission into intensive care units (ICU), mechanical ventilation, death, and lengths of stay (LOS) in non-ICU and ICU care in public and private sectors. A log-binomial model was used to quantify mortality risk, ICU treatment and mechanical ventilation between time periods, adjusting for age, sex, comorbidity, health sector and province. There were 342,700 COVID-19-related hospital admissions during the study period. Risk of ICU admission was 16% lower during wave periods (adjusted risk ratio (aRR) 0.84 [0.82-0.86]) compared to between-wave periods. Mechanical ventilation was more likely during a wave overall (aRR 1.18 [1.13-1.23]), but patterns between waves were inconsistent, while mortality risk in non-ICU and ICU were 39% (aRR 1.39 [1.35-1.43]) and 31% (aRR 1.31 [1.27-1.36]) higher during a wave, compared to between-wave periods, respectively. If patients had had the same probability of death during waves vs between-wave periods, we estimated approximately 24% [19%-30%] of deaths (19,600 [15,200-24,000]) would not have occurred over the study period. LOS differed by age (older patients stayed longer), ward type (ICU stays were longer than non-ICU) and death/recovery outcome (time to death was shorter in non-ICU); however, LOS remained similar between time periods. Healthcare capacity constraints as inferred by wave period have a large impact on in-hospital mortality. It is crucial for modelling health systems strain and budgets to consider how input parameters related to hospitalisation change during and between waves, especially in settings with severely constrained resources.