Infections and internal medicine patients: Could a comorbidity score predict in-hospital mortality?

Sustainability in Internal Medicine: A Year-Long Ward-Wide Observational Study

Population aging and multimorbidity challenge health system sustainability, but the role of assistance-related variables rather than individual pathophysiological factors in determining patient outcomes is unclear. To identify assistance-related determinants of sustainable hospital healthcare, all patients hospitalised in an Internal Medicine Unit (n = 1073) were enrolled in a prospective year-long observational study and split 2:1 into a training (n = 726) and a validation subset (n = 347). Demographics, comorbidities, provenance setting, estimates of complexity (cumulative illness rating scale, CIRS: total, comorbidity, CIRS-CI, and severity, CIRS-SI subscores) and intensity of care (nine equivalents of manpower score, NEMS) were analysed at individual and Unit levels along with variations in healthcare personnel as determinants of in-hospital mortality, length of stay and nosocomial infections. Advanced age, higher CIRS-SI, end-stage cancer, and the absence of immune-mediated diseases were correlated with higher mortality. Admission from nursing homes or intensive care units, dependency on activity of daily living, community- or hospital-acquired infections, oxygen support and the number of exits from the Unit along with patient/physician ratios were associated with prolonged hospitalisations. Upper gastrointestinal tract disorders, advanced age and higher CIRS-SI were associated with nosocomial infections. In addition to demographic variables and multimorbidity, physician number and assistance context affect hospitalisation outcomes and healthcare sustainability.

Establishment and external validation of a nomogram for predicting 28-day mortality in patients with skull fracture

Background

Skull fracture can lead to significant morbidity and mortality, yet the development of effective predictive tools has remained a challenge. This study aimed to establish and validate a nomogram to evaluate the 28-day mortality risk among patients with skull fracture.

Materials and methods

Data extracted from the Medical Information Mart for Intensive Care (MIMIC) database were utilized as the training set, while data from the eICU Collaborative Research Database were employed as the external validation set. This nomogram was developed using univariate Cox regression, best subset regression (BSR), and the least absolute shrinkage and selection operator (LASSO) methods. Subsequently, backward stepwise multivariable Cox regression was employed to refine predictor selection. Variance inflation factor (VIF), akaike information criterion (AIC), area under the receiver operating characteristic curve (AUC), concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the model's performance.

Results

A total of 1,527 adult patients with skull fracture were enrolled for this analysis. The predictive factors in the final nomogram included age, temperature, serum sodium, mechanical ventilation, vasoactive agent, mannitol, extradural hematoma, loss of consciousness and Glasgow Coma Scale score. The AUC of our nomogram was 0.857, and C-index value was 0.832. After external validation, the model maintained an AUC of 0.853 and a C-index of 0.829. Furthermore, it showed good calibration with a low Brier score of 0.091 in the training set and 0.093 in the external validation set. DCA in both sets revealed that our model was clinically useful.

Conclusion

A nomogram incorporating nine features was constructed, with a good ability in predicting 28-day mortality in patients with skull fracture.

Risk Prediction Models for Hospital Mortality in General Medical Patients: A Systematic Review

Objective

To systematically review contemporary prediction models for hospital mortality developed or validated in general medical patients.

Methods

We screened articles in five databases, from January 1, 2010, through April 7, 2022, and the bibliography of articles selected for final inclusion. We assessed the quality for risk of bias and applicability using the Prediction Model Risk of Bias Assessment Tool (PROBAST) and extracted data using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist. Two investigators independently screened each article, assessed quality, and extracted data.

Results

From 20,424 unique articles, we identified 15 models in 8 studies across 10 countries. The studies included 280,793 general medical patients and 19,923 hospital deaths. Models included 7 early warning scores, 2 comorbidities indices, and 6 combination models. Ten models were studied in all general medical patients (general models) and 7 in general medical patients with infection (infection models). Of the 15 models, 13 were developed using logistic or Poisson regression and 2 using machine learning methods. Also, 4 of 15 models reported on handling of missing values. None of the infection models had high discrimination, whereas 4 of 10 general models had high discrimination (area under curve >0.8). Only 1 model appropriately assessed calibration. All models had high risk of bias; 4 of 10 general models and 5 of 7 infection models had low concern for applicability for general medical patients.

Conclusion

Mortality prediction models for general medical patients were sparse and differed in quality, applicability, and discrimination. These models require hospital-level validation and/or recalibration in general medical patients to guide mortality reduction interventions.

Impact of COVID-19 Pandemic on In-Hospital Mortality in Patients Without SARS-CoV-2 Infection in an Internal Medicine Ward of a Tertiary Care Hospital in Portugal

INTRODUCTION

Despite the emergence of a new worldwide cause of death related to COVID-19, several studies have hypothesized that the international mortality rate attributed to non-COVID-19 causes was significantly higher during the COVID pandemic, questioning whether this excess in mortality is related only to COVID-19 or to the difficulties that the healthcare systems faced during the pandemic. Therefore, understanding the impact of the COVID-19 pandemic on the prognosis of patients without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a major unmet need as this was overshadowed by the overwhelming number of patients with SARS-CoV-2.

METHODS

This is a retrospective, cross-sectional, observational study in the internal medicine non-COVID-19 wards of a tertiary care hospital in Portugal. A total of 2021 patients without SARS-CoV-2 infection admitted between March and May of 2019 and 2020 were included. For each patient, we collected information regarding demographic characteristics, emergency department admission information, hospitalization information, date of discharge or death, health comorbidities, and current medication.

RESULTS

Data from 1013 patients in 2019 and 1008 patients in 2020 was analyzed. The patients' demographic characteristics, health comorbidities, and current medications were distributed in similar patterns in the two studied periods. There was a statistically significant difference in the in-hospital mortality in patients without SARS-CoV-2 infection between 2019 and 2020 (12% vs 17%, p-value < 0.001) and in admission severity in hospitalized patients without SARS-CoV-2 infection between 2019 and 2020 (0.9 vs 0.6, p-value < 0.001).

CONCLUSION

Our work showed a statistically significant increase in in-hospital mortality during the COVID-19 pandemic in patients without SARS-CoV-2 infection, which was not apparently explained by differences in the characteristics of hospitalized patients. As this is one of the first works describing the silent impact of the COVID-19 pandemic in Portugal, we believe it holds an important value in the provision of bases for building up future health policies in case of new COVID-19 outbreaks or other medical emergencies.

A case report of severe Fusobacterium nucleatum sepsis secondary to nephrectomy

Background

Fusobacterium nucleatum (F. nucleatum) is a resident anaerobic bacterium, which in rare cases may invade blood from the head and neck or the digestive tract to cause bacteremia and induce venous thrombosis. F. nucleatum is closely related to abdominal tumors, but it has not been reported in relation to renal tumors. We report herein a possible case.

Case presentation

This patient had kidney cancer with thrombosis in the right renal vein but had no sign of infection. After radical nephrectomy, thrombi formed in his left renal vein, and when removed, severe sepsis occurred. He did not respond to treatment with antibiotics and died, but the blood culture done confirmed that he had F. nucleatum bacteremia.

Conclusion

F. nucleatum may also be associated with kidney cancer, and could cause post-operative renal vein thrombosis, and sepsis or septic shock after thrombectomy.

A 2-year retrospective analysis of the prognostic value of MqSOFA compared to lactate, NEWS and qSOFA in patients with sepsis

Purpose

Sepsis is a life-threating organ dysfunction caused by a dysregulated host response to infection. Being a time-dependent condition, the present study aims to compare a recently established score, i.e., modified quick SOFA (MqSOFA), with other existing tools commonly applied to predict in-hospital mortality.

Methods

All cases of sepsis and septic shock consecutively observed at St. Anna University Hospital of Ferrara, Italy, from January 2017 to December 2018 were included in this study. Each patient was evaluated with MqSOFA, lactate assay, NEWS and qSOFA. Accurate statistical and logistic regression analyses were applied to our database.

Results

A total of 1001 consecutive patients with sepsis/septic shock were retrieved. Among them, 444 were excluded for incomplete details about vital parameters; thus, 556 patients were eligible for the study. Data analysis showed that MqSOFA, NEWS and lactate assay provided a better predictive ability than qSOFA in terms of in-hospital mortality (p < 0.001). Aetiology-based stratification in 5 subgroups demonstrated the superiority of NEWS vs. other tools in predicting fatal outcomes (p = 0.030 respiratory, p = 0.036 urinary, p = 0.044 abdominal, p = 0.047 miscellaneous and p = 0.041 for indeterminate causes). After Bonferroni’s correction, MqSOFA was superior to qSOFA over respiratory (p < 0.001) and urinary (p < 0.001) aetiologies. Age was an independent factor for negative outcomes (p < 0.001).

Conclusions

MqSOFA, NEWS and lactate assay better predicted in-hospital mortality compared to qSOFA. Since sepsis needs a time-dependent assessment, an easier and non-invasive score, i.e., MqSOFA, could be used to establish patients’ outcome in the emergency setting.

Do Sex-Related Differences of Comorbidity Burden and/or In-Hospital Mortality Exist in Cancer Patients? A Retrospective Study in an Internal Medicine Setting

Cancer represents important comorbidity, and data on outcomes are usually derived from selected oncologic units. Our aim was to evaluate possible sex-related differences and factors associated with in-hospital mortality (IHM) in a consecutive cohort of elderly patients with cancer admitted to internal medicine. We included all patients admitted to our department with a diagnosis of cancer during 2018. Based on the International Classification of Diseases, 9th Revision, Clinical Modification, demography, comorbidity burden, and diagnostic procedures were evaluated, with IHM as our outcome. We evaluated 955 subjects with cancer (23.9% of total hospital admissions), 42.9% were males, and the mean age was 76.4 ± 11.4 years. Metastatic cancer was diagnosed in 18.2%. The deceased group had a higher modified Elixhauser Index (17.6 ± 7.7 vs. 14 ± 7.3, p < 0.001), prevalence of cachexia (17.9% vs. 7.2%, p < 0.001), and presence of metastasis (27.8% vs. 16.3%, p = 0.001) than survivors. Females had a higher age (77.4 ± 11.4 vs. 75.5 ± 11.4, p = 0.013), and lower comorbidity (10.2 ± 5.9 vs. 12.0 ± 5.6, p < 0.001) than males. IHM was not significantly different among sex groups, but it was independently associated with cachexia and metastasis only in women. Comorbidities are highly prevalent in patients with cancer admitted to the internal medicine setting and are associated with an increased risk of all-cause mortality, especially in female elderly patients with advanced disease.

Epidemiology, mortality and risk factors for patients with K. pneumoniae bloodstream infections: Clinical impact of carbapenem resistance in a tertiary university teaching hospital of Beijing

BACKGROUND

This study compared the epidemiology of carbapenem-resistant (CRKP) and carbapenem-sensitive (CSKP) K. pneumoniae bloodstream infections (BSIs), and assessed risk factors for 28-day mortality of patients with K. pneumoniae BSIs.

METHODS

A retrospective cohort study was conducted in a 2000-bed tertiary teaching hospital of Beijing between Jan 1st 2013 to Dec 31st, 2019. All patients with K. pneumoniae BSI were identified through the Hospital Information System. The endpoints included incidence rate, mortality and risk factors for mortality of patients with K. pneumoniae BSIs.

RESULTS

496 patients with K. pneumoniae BSIs were included in the analysis, with 108 CRKP BSIs. The incidence rate of K. pneumoniae BSI was 10.6 (CI: 9.7, 11.6) per 100 000 patient-days, with the rate for CRKP BSI was 2.3 (95% CI: 1.9, 2.8). The 28-day mortality was 38.0% for CRKP BSI and 8.8% for CSKP BSI, respectively. Logistic analysis showed, higher Charlson Comorbidity Index score (OR = 1.26, 95%CI 1.12-1.43, p < 0.001), respiratory failure (OR = 2.73, 95%CI1.28-5.84, p = 0.010), renal failure (OR = 4.13, 95%CI1.93-8.83, p < 0.001), septic shock (OR = 8.77, 95%CI3.60-21.32, p < 0.001), mechanical ventilation (OR = 4.41, 95%CI1.59-12.25, p = 0.004) and CRKP infection (OR = 3.04, 95%CI1.28-7.22, p = 0.012) were independently associated with 28-day mortality.

CONCLUSIONS

Considerable incidence rate and remarkable mortality of patients with K. pneumoniae (especially CRKP) BSI was declared in the study. Patient conditions before (higher CCI) and after presentation (respiratory failure, renal failure, septic shock), and healthcare factors (mechanical ventilation and CRKP infection) were independently associated with 28-day mortality. Understanding these risks helps better establishment of infection control strategies.

Predictors of infection after "de novo" cardiac electronic device implantation

BACKGROUND

Cardiac implantable electronic device (CIED) infection is a major complication that increases morbidity and mortality after the procedure. Several infection risk scores have been suggested to identify patients at higher pre-procedural risk of infection OBJECTIVE: this study sought to evaluate rates of infection, potential risk factors and the role of a modified "Shariff" score as predictor of infection in high-risk patients undergoing de novo CIED implantation.

METHODS AND RESULTS

We retrospectively analysed 1391 patients underwent a de novo CIED procedure during the study period. At the median follow-up of 48 months, 20 patients of 1391 (1.4%) developed a CIED-related infective event. In our population, we studied a modified version of the "Shariff" score for only first-time implant patients. At multivariate regression analysis, three factors were independent predictors of infection: previous pocket hematoma [RR 27.2 (8.30-54.02), p = 10^-10], a Shariff Score ≥ 4 [RR 3.20 (1.29-12.59), p= 0.029]. and reintervention for catheter malfunction or dislocation [RR 3.57 (1.2-37.4), p= 0.048].

CONCLUSIONS

a "Shariff" score > 4 is suggested as a predictor of higher risk of infection in patients after de novo device implantation. The use of an infection risk score may help to improve tailored pre-operatory strategies to prevent infection.

Validation and Comparison of a Modified Elixhauser Index for Predicting In-Hospital Mortality in Italian Internal Medicine Wards

Purpose

Burden of comorbidities appears to be related to clinical outcomes in hospitalized patients. Clinical stratification of admitted patients could be obtained calculating a comorbidity score, which represents the simplest way to identify the severity of patients' clinical conditions and a practical approach to assess prevalent comorbidities. Our aim was to validate a modified Elixhauser score for predicting in-hospital mortality (IHM) in internal medicine admissions and to compare it with a different one derived from clinical data previously used in a similar setting, having a good prognostic accuracy.

Patients and Methods

A single-center retrospective study enrolled all patients admitted to internal medicine department between January and June 2016. A modified Elixhauser score was calculated from chart review and administrative data; moreover, a second prognostic index was calculated from chart review only. Comorbidity scores were compared using c-statistic.

Results

We analyzed 1614 individuals without selecting the reason for admission, 224 (13.9%) died during hospital stay. Deceased subjects were older (83.3±9.1 vs 78.4±13.5 years; p<0.001) and had higher burden of comorbidities. The modified Elixhauser score calculated by administrative data and by chart review and the comparator one was 18.13±9.36 vs 24.43±11.27 vs 7.63±3.3, respectively, and the c-statistic was 0.758 (95% CI 0.727-0.790), 0.811 (95% CI 0.782-0.840) and 0.740 (95% CI 0.709-0.771), respectively.

Conclusion

The new modified Elixhauser score showed a similar performance to a previous clinical prognostic index when it was calculated using administrative data; however, its performance improved if calculation was based on chart review.

Gram-negative bloodstream infections and sepsis: risk factors, screening tools and surveillance

INTRODUCTION AND BACKGROUND

Incidence of gram-negative bloodstream infections (GNBSIs) and sepsis are rising in the UK. Healthcare-associated risk factors have been identified that increase the risk of infection and associated mortality. Current research is focused on identifying high-risk patients and improving the methods used for surveillance.

SOURCES OF DATA

Comprehensive literature search of the topic area using PubMed (Medline). Government, professional and societal publications were also reviewed.

AREAS OF AGREEMENT

A range of healthcare-associated risk factors independently associate with the risk of GNBSIs and sepsis.

AREAS OF CONTROVERSY

There are calls to move away from using simple comorbidity scores to predict the risk of sepsis-associated mortality, instead more advanced multimorbidity models should be considered.

GROWING POINTS AND AREAS FOR DEVELOPING RESEARCH

Advanced risk models should be created and evaluated for their ability to predict sepsis-associated mortality. Investigations into the accuracy of NEWS2 to predict sepsis-associated mortality are required.

Acute Kidney Injury and In-Hospital Mortality: A Retrospective Analysis of a Nationwide Administrative Database of Elderly Subjects in Italy

Background: The aim of this study was to investigate the association between acute kidney injury (AKI) and in-hospital mortality (IHM) in a large nationwide cohort of elderly subjects in Italy. Methods: We analyzed the hospitalization data of all patients aged ≥65 years, who were discharged with a diagnosis of AKI, which was identified by the presence of the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM), and extracted from the Italian Health Ministry database (January 2000 to December 2015). Data regarding age, gender, dialysis treatment, and comorbidity, including the development of sepsis, were also collected. Results: We evaluated 760,664 hospitalizations, the mean age was 80.5 ± 7.8 years, males represented 52.2% of the population, and 9% underwent dialysis treatment. IHM was 27.7% (210,661 admissions): Deceased patients were more likely to be older, undergoing dialysis treatment, and to be sicker than the survivors. The population was classified on the basis of tertiles of comorbidity score (the first group 7.48 ± 1.99, the second 13.67 ± 2,04, and third 22.12 ± 4.13). IHM was higher in the third tertile, whilst dialysis-dependent AKI was highest in the first. Dialysis-dependent AKI was associated with an odds ratios (OR) of 2.721; 95% confidence interval (CI) 2.676–2.766; p < 0.001, development of sepsis was associated with an OR of 1.990; 95% CI 1.948–2.033; p < 0.001, the second tertile of comorbidity was associated with an OR of 1.750; 95% CI 1.726–1.774; p < 0.001, and the third tertile of comorbidity was associated with an OR of 2.522; 95% CI 2.486–2.559; p < 0.001. Conclusions: In elderly subjects with AKI discharge codes, IHM is a frequent complication affecting more than a quarter of the investigated population. The increasing burden of comorbidity, dialysis-dependent AKI, and sepsis are the major risk factors.