Tele-medicine controlled hospital at home is associated with better outcomes than hospital stay.

BACKGROUND: Hospital-at-home (HAH) is increasingly becoming an alternative for in-hospital stay in selected clinical scenarios. Nevertheless, there is still a question whether HAH could be a viable option for acutely ill patients, otherwise hospitalized in departments of general-internal medicine. METHODS: This was a retrospective matched study, conducted at a telemedicine controlled HAH department, being part of a tertiary medical center. The objective was to compare clinical outcomes of acutely ill patients (both COVID-19 and non-COVID) admitted to either in-hospital or HAH. Non-COVID patients had one of three acute infectious diseases: urinary tract infections (UTI, either lower or upper), pneumonia, or cellulitis. RESULTS: The analysis involved 159 HAH patients (64 COVID-19 and 95 non-COVID) who were compared to a matched sample of in-hospital patients (192 COVID-19 and 285 non-COVID). The median length-of-hospital stay (LOS) was 2 days shorter in the HAH for both COVID-19 patients (95% CI: 1-3; p = 0.008) and non-COVID patients (95% CI; 1-3; p < 0.001). The readmission rates within 30 days were not significantly different for both COVID-19 patients (Odds Ratio (OR) = 1; 95% CI: 0.49-2.04; p = 1) and non-COVID patients (OR = 0.7; 95% CI; 0.39-1.28; p = 0.25). The differences remained insignificant within one year. The risk of death within 30 days was significantly lower in the HAH group for COVID-19 patients (OR = 0.34; 95% CI: 0.11-0.86; p = 0.018) and non-COVID patients (OR = 0.38; 95% CI: 0.14-0.9; p = 0.019). For one year survival period, the differences were significant for COVID-19 patients (OR = 0.5; 95% CI: 0.31-0.9; p = 0.044) and insignificant for non-COVID patients (OR = 0.63; 95% CI: 0.4-1; p = 0.052). CONCLUSIONS: Care for acutely ill patients in the setting of telemedicine-based hospital at home has the potential to reduce hospitalization length without increasing readmission risk and to reduce both 30 days and one-year mortality rates.

Early Detection of Pulmonary Embolism in a General Patient Population Immediately Upon Hospital Admission Using Machine Learning to Identify New, Unidentified Risk Factors: Model Development Study.

BACKGROUND: Under- or late identification of pulmonary embolism (PE)-a thrombosis of 1 or more pulmonary arteries that seriously threatens patients' lives-is a major challenge confronting modern medicine. OBJECTIVE: We aimed to establish accurate and informative machine learning (ML) models to identify patients at high risk for PE as they are admitted to the hospital, before their initial clinical checkup, by using only the information in their medical records. METHODS: We collected demographics, comorbidities, and medications data for 2568 patients with PE and 52,598 control patients. We focused on data available prior to emergency department admission, as these are the most universally accessible data. We trained an ML random forest algorithm to detect PE at the earliest possible time during a patient's hospitalization-at the time of his or her admission. We developed and applied 2 ML-based methods specifically to address the data imbalance between PE and non-PE patients, which causes misdiagnosis of PE. RESULTS: The resulting models predicted PE based on age, sex, BMI, past clinical PE events, chronic lung disease, past thrombotic events, and usage of anticoagulants, obtaining an 80% geometric mean value for the PE and non-PE classification accuracies. Although on hospital admission only 4% (1942/46,639) of the patients had a diagnosis of PE, we identified 2 clustering schemes comprising subgroups with more than 61% (705/1120 in clustering scheme 1; 427/701 and 340/549 in clustering scheme 2) positive patients for PE. One subgroup in the first clustering scheme included 36% (705/1942) of all patients with PE who were characterized by a definite past PE diagnosis, a 6-fold higher prevalence of deep vein thrombosis, and a 3-fold higher prevalence of pneumonia, compared with patients of the other subgroups in this scheme. In the second clustering scheme, 2 subgroups (1 of only men and 1 of only women) included patients who all had a past PE diagnosis and a relatively high prevalence of pneumonia, and a third subgroup included only those patients with a past diagnosis of pneumonia. CONCLUSIONS: This study established an ML tool for early diagnosis of PE almost immediately upon hospital admission. Despite the highly imbalanced scenario undermining accurate PE prediction and using information available only from the patient's medical history, our models were both accurate and informative, enabling the identification of patients already at high risk for PE upon hospital admission, even before the initial clinical checkup was performed. The fact that we did not restrict our patients to those at high risk for PE according to previously published scales (eg, Wells or revised Genova scores) enabled us to accurately assess the application of ML on raw medical data and identify new, previously unidentified risk factors for PE, such as previous pulmonary disease, in general populations.

Designing for flexibility in hybrid care services: lessons learned from a pilot in an internal medicine unit.

Digital transformation in healthcare during the COVID-19 pandemic led to the development of new hybrid models integrating physical and virtual care. The ability to provide remote care by telemedicine technologies and the need to better manage and control hospitals' occupancy accelerated growth in hospital-at-home programs. The Sheba Medical Center restructured to create Sheba Beyond as the first virtual hospital in Israel. These transformations enabled them to deliver hybrid services in their internal medicine unit by managing inpatient hospital-care with remote home-care based on the patients' medical condition. The hybrid services evolved to integrate care pathways multiplied by the mode of delivery-physical (in person) or virtual (technology enabled)-and the location of care-at the hospital or the patient home. The study examines this home hospitalization program pilot for internal medicine at Sheba Medical Center (MC). The research is based on qualitative semi-structured interviews with Sheba Beyond management, medical staff from the hospital and the Health Maintenance Organization (HMO), Architects, Information Technology (IT), Telemedicine and Medtech organizations. We investigated the implications of the development of hybrid services for the future design of the physical built-environment and the virtual technological platform. Our findings highlight the importance of designing for flexibility in the development of hybrid care services, while leveraging synergies across the built environment and digital platforms to support future models of care. In addition to exploring the potential for scalability in accelerating the flexibility of the healthcare system, we also highlight current barriers in professional, management, logistic and economic healthcare models.

Interpretation of Heart and Lungs Sounds Acquired via Remote, Digital Auscultation Reached Fair-to-Substantial Levels of Consensus among Specialist Physicians.

BACKGROUND: Technological advancement may bridge gaps between long-practiced medical competencies and modern technologies. Such a domain is the application of digital stethoscopes used for physical examination in telemedicine. This study aimed to validate the level of consensus among physicians regarding the interpretation of remote, digital auscultation of heart and lung sounds. METHODS: Seven specialist physicians considered both the technical quality and clinical interpretation of auscultation findings of pre-recorded heart and lung sounds of patients hospitalized in their homes. TytoCareTM system was used as a remote, digital stethoscope. RESULTS: In total, 140 sounds (70 heart and 70 lungs) were presented to seven specialists. The level of agreement was measured using Fleiss' Kappa (FK) variable. Agreement relating to heart sounds reached low-to-moderate consensus: the overall technical quality (FK = 0.199), rhythm regularity (FK = 0.328), presence of murmurs (FK = 0.469), appreciation of sounds as remote (FK = 0.011), and an overall diagnosis as normal or pathologic (FK = 0.304). The interpretation of some of the lung sounds reached a higher consensus: the overall technical quality (FK = 0.169), crepitus (FK = 0.514), wheezing (FK = 0.704), bronchial sounds (FK = 0.034), and an overall diagnosis as normal or pathological (FK = 0.386). Most Fleiss' Kappa values were in the range of "fare consensus", while in the domains of diagnosing lung crepitus and wheezing, the values increased to the "substantial" level. CONCLUSIONS: Bio signals, as recorded auscultations of the heart and lung sounds serving the process of clinical assessment of remotely situated patients, do not achieve a high enough level of agreement between specialized physicians. These findings should serve as a catalyzer for improving the process of telemedicine-attained bio-signals and their clinical interpretation.

Six-Lead Electrocardiography Enables Identification of Rhythm and Conduction Anomalies of Patients in the Telemedicine-Based, Hospital-at-Home Setting: A Prospective Validation Study.

BACKGROUND: The hospital-at-home (HAH) model is a viable alternative for conventional in-hospital stays worldwide. Serum electrolyte abnormalities are common in acute patients, especially in those with many comorbidities. Pathologic changes in cardiac electrophysiology pose a potential risk during HAH stays. Periodical electrocardiogram (ECG) tracing is therefore advised, but few studies have evaluated the accuracy and efficiency of compact, self-activated ECG devices in HAH settings. This study aimed to evaluate the reliability of such a device in comparison with a standard 12-lead ECG. METHODS: We prospectively recruited consecutive patients admitted to the Sheba Beyond Virtual Hospital, in the HAH department, during a 3-month duration. Each patient underwent a 12-lead ECG recording using the legacy device and a consecutive recording by a compact six-lead device. Baseline patient characteristics during hospitalization were collected. The level of agreement between devices was measured by Cohen's kappa coefficient for inter-rater reliability (Ϗ). RESULTS: Fifty patients were included in the study (median age 80 years, IQR 14). In total, 26 (52%) had electrolyte disturbances. Abnormal D-dimer values were observed in 33 (66%) patients, and 12 (24%) patients had elevated troponin values. We found a level of 94.5% raw agreement between devices with regards to nine of the options included in the automatic read-out of the legacy device. The calculated Ϗ was 0.72, classified as a substantial consensus. The rate of raw consensus regarding the ECG intervals' measurement (PR, RR, and QT) was 78.5%, and the calculated Ϗ was 0.42, corresponding to a moderate level of agreement. CONCLUSION: This is the first report to our knowledge regarding the feasibility of using a compact, six-lead ECG device in the setting of an HAH to be safe and bearing satisfying agreement level with a legacy, 12-lead ECG device, enabling quick, accessible arrythmia detection in this setting. Our findings bear a promise to the future development of telemedicine-based hospital-at-home methodology.

Low Alanine-Aminotransferase Blood Activity Is Associated with Increased Mortality in Chronic Lymphocytic Leukemia Patients: A Retrospective Cohort Study of 716 Patients.

BACKGROUND: Chronic lymphocytic leukemia (CLL) is one of the most common hematologic malignancies, especially among elderlies. Several prognostic scores are available that utilize the characteristics of patients' blood counts and cytogenetic anomalies-all are features of the disease rather than of the patient. Addressing the route of personalized rather than precise medicine, we refer to the assessment of patients' status of sarcopenia and frailty. Low alanine aminotransferase (ALT) was already shown to function as a surrogate marker for sarcopenia and frailty. We decided to find a possible correlation between low ALT values and poor prognosis of CLL patients. PATIENTS AND METHODS: This is a retrospective cohort study of CLL patients treated in a large, tertiary medical center, as outpatients or inpatients. Their frailty status was evaluated in a retrospective manner. We defined patients with ALT below 12 IU/L as frail and divided our cohort into two groups including a low ALT level group (ALT < 12) and a normal ALT level group (ALT ≥ 12). RESULTS: Overall, our final analysis included 716 CLL patients, of which 161 (22.5%) had ALT levels lower than 12 IU/L. There was no significant difference in patients' age between the two groups. Patients with the low ALT had a lower hemoglobin concentration (median 10.8 g/dL [IQR = 2.7] vs. 12.2 [IQR = 3.1]; p < 0.001) and a higher proportion of patients were classified as Binet C score [48.4% vs. 31.1%]; p < 0.001). Frail CLL patients' survival was significantly shorter when compared to non-frail patients, in both the univariate [HR = 1.6 [95% confidence interval, CI 1.23, 2.0]; p < 0.01] and multivariate analyses [HR = 1.3 [95% CI 1.0, 1.7]; p = 0.03]. CONCLUSIONS: Sarcopenia and frailty assessment, based on blood ALT measurements, could potentially point out differences in CLL patients' prognoses. Such assessment could serve the purpose of treatment personalization of CLL patients.

Low Alanine Aminotransferase, as a Marker of Sarcopenia and Frailty, Is Associated with Shorter Survival Among Prostate Cancer Patients and Survivors. A Retrospective Cohort Analysis of 4064 Patients.

Background: Sarcopenia is characterized by loss of muscle mass and function and is associated with frailty, a syndrome with higher likelihood of falls, fractures, physical disability, and mortality. Both frailty and sarcopenia are known markers of shorter survival in various cancer patient populations. Low alanine aminotransferase (ALT), reflecting loss of muscle mass (sarcopenia), may be associated with greater frailty and shorter survival in multiple cancers. Objective: To assess the potential association between low ALT and shorter survival among prostate cancer (PCa) patients and survivors. Design setting and participants: This was a retrospective analysis of a historical cohort of PCa patients and survivors. Patients were defined as those still actively receiving PCa treatment, while those no longer receiving such treatment were classified as PCa survivors. Outcome measurements and statistical analysis: ALT data were obtained from results for basic biochemical blood testing carried out for patients on their first hospital admission. Patients were divided into two groups: those with ALT ≥17 IU/l and those with ALT <17 IU/l. Univariate and multivariable analyses were conducted for between-group survival comparisons. Results and limitations: We identified 9489 PCa records. The final study cohort with ALT data available included 4064 patients with ALT <40 IU/l. Of this cohort, 536 patients were actively receiving medical anticancer therapy for PCa. The mean age for the entire cohort was 74.6 yr (standard deviation 9.6) and the median ALT level was 19.28 IU/l; 1676 patients (41%) had low ALT (<17 IU/l). On univariate analysis, low ALT was associated with a 78% increase in mortality risk (95% confidence interval [CI] 1.62-1.97; p < 0.001). A sensitivity analysis of the 536 patients actively receiving medical anticancer treatment revealed that low ALT was associated with a 48% increase in mortality risk (95% CI 1.19-1.85; p = 0.001). In a multivariable model controlled for age, kidney disease, history of cerebrovascular event/transient ischemic attack, and baseline prostate-specific antigen, low ALT was still associated with a 35% increase in mortality risk (95% CI 1.12-1.63; p = 0.001). Limitations include the single-center, retrospective design. Conclusions: Low ALT, which is indicative of sarcopenia and frailty, is associated with shorter survival among PCa patients and survivors and could potentially be used for treatment personalization. Patient summary: We compared survival for prostate cancer patients and survivors according to their blood level of the protein alanine aminotransferase (ALT). Low ALT levels in the general population are associated with loss of muscle mass. We found that in our group of prostate cancer patients and survivors, the risk of death from any cause was higher for those with low ALT levels.

Do low levels of alanine aminotransferase, a baseline marker of sarcopenia and frailty, associate with worse clinical outcomes among hospitalized COVID-19 patients? A Retrospective Cohort Study.

Objectives: COVID-19 geoperdize lives. Not all the risk factors for negative outcomes are known. Sarcopenia and frailty are common, negatively affecting clinical outcomes. Studies have shown that sarcopenia and frailty are associated with worse outcomes. Our objective was to examine whether low ALT (Alanine-aminotranferase), a surrogate marker for sarcopenia, is associated with worse clinical outcomes among hospitalized COVID-19 patients. Methods: We reviewed cases of COVID-19 in a tertiary hospital, during three COVID-19 waves and examined correlations between ALT and mortality using crude, univariate and multivariate analysis for age, gender, hypertension, Chronic obstructive pulmonary disease and Congestive heart failure. Results: 357 patients were included in this analysis. Median age was 69, 54% were males. Median ALT was 19 IU/L. During follow-up, 73 (20%) died. Patients with low ALT were more likely to die (HR 1.82, 95% CI 1.06-3.09, P=0.028). Other predictors for mortality were low albumin, background COPD, dyslipidemia, dementia, and malignancy. The multivariate analysis showed that low ALT was still an independent predictor of poor prognosis (HR 1.7, 95% CI 1.0-2.9, P=0.049). Conclusions: In our analysis of COVID-19 patients, low ALT levels were independently associated with increased risk of mortality, both as standalone and when incorporated into a multivariate analysis.

A blockchain-based computerized network infrastructure for the transparent, immutable calculation and dissemination of quantitative, measurable parameters of academic and medical research publications.

Digital transformation of healthcare systems should rely on decentralized computer networks and take advantage of the unique characteristics of blockchain technology. Decentralization ensures process transparency and data transparency for all relevant stakeholders. These values are essential in the realms of populations' healthcare information communications and processing, control and tracking of medical logistics supply chains, clinical research management, and control of certified healthcare services organizations. Mounting decentralized processes onto a blockchain-based computerized network will endow the values of immutability, improved cybersecurity, and potential for incentivizing stakeholders for relevant, pre-determined activities. One of the most relevant processes that would benefit from a decentralized, blockchain-based architecture is the submission, review, and publishing of scientific manuscripts. Current structures and processes in this world are non-transparent, poorly incentivizing significant stakeholders such as manuscripts' reviewers, and many are potentially corrupted. In this review, we suggest a blockchain-based architecture for such systems and advocate further research and development in several domains of modern healthcare systems-offering medicine to become "the new guy on the block (chain)."

Low ALT, a marker of sarcopenia and frailty, is associated with shortened survival amongst myelodysplastic syndrome patients: A retrospective study.

Myelodysplastic Syndrome (MDS) is a common blood dyscrasia that mainly affects the elderly population. Several prognostic scores are available utilizing blood count variables and cytogenetic abnormalities, targeting the disease rather than the patient. Sarcopenia and frailty are associated with shortened survival rates in various disease states. Low Alanine Aminotransferase (ALT) levels are a marker of lowered muscle mass and frailty status. This study aimed to examine the correlation between low ALT levels and prognosis in MDS patients. This is a retrospective cohort study. We obtained the demographic, clinical, and laboratory data of patients in a tertiary hospital. Univariate and multivariate models were used to investigate the potential relationship between low ALT level and survival. The final study included 831 patients (median age 74.3 years, Interquartile range 65.6-81.8), and 62% were males. The median ALT level was 15 international units (IU)/L and 233 patients (28%) had low ALT levels (<12 IU/L). Univariate analysis showed that low ALT levels were associated with a 25% increase in mortality (95% confidence interval [CI]: 1.05-1.50, P = .014). A multivariate model controlling for age, sex, body mass index, hemoglobin and albumin concentrations, and low ALT levels was still significantly associated with increased mortality (hazard ratio [HR] = 1.25, 95% CI: 1.01-1.56, P = .041). Low ALT levels were associated with increased mortality among patients with MDS. Impact: Using ALT as a frailty metric may allow patient-centered, personalized care in this patient population. A low ALT level reflects the pre-morbid robustness of patients and is not intended to replace disease-centered characteristics.

Hospitalized patients with positive antiphospholipid antibodies who have low complement levels are at increased risk for death-a retrospective cohort study.

PURPOSE: To investigate whether low complement levels can predict worse outcomes in patients hospitalized with positive anti-phospholipid antibodies. METHODS: This was a retrospective cohort study. We obtained demographics, laboratory, and prognostic data of all consecutive patients hospitalized between 2007 and 2021, for whatever reason, with at least one positively abnormal anti-phospholipid antibody, who were also tested for complement levels (C3 or C4). We then compared the rates of long-term mortality, 1-year mortality, deep vein thrombosis, and pulmonary emboli between groups of low complement and normal complement levels. Multivariate analysis was used to control for levels of clinical and laboratory confounders. RESULTS: We identified 32,286 patients tested for anti-phospholipid antibodies. Of those patients, 6800 tested positive for at least one anti-phospholipid antibody and had a documented complement level. Significant higher mortality rates were found in the low complement group, with an odds ratio for mortality (OR 1.93 CI 1.63-2.27 p < .001). Deep vein thrombosis and pulmonary emboli rates were similar. Multivariate analysis confirmed that low complement was an independent predictor for mortality after controlling for age, sex, dyslipidemia, chronic heart failure (CHF), chronic kidney disease (CKD), and anemia. CONCLUSIONS: Our study results indicate that low complement is associated with significantly higher mortality rates in admitted patients with elevated levels of anti-phospholipid antibodies. This finding correlates with recent literature suggesting a vital role for complement activation in anti-phospholipid syndrome.

High Attendance Rate of Family Members During Physician Rounds Is Predictive of Worse Clinical Outcomes: A Historic Cohort Study.

BACKGROUND: The prognosis of long-term clinical outcomes for each patient is of utmost importance. OBJECTIVES: To evaluate the association between rates of family attendance during rounds and long-term outcomes. METHODS: We conducted a historic cohort study. RESULTS: We followed 200 consecutive patients for a median of 19 months. Within the group of patients that had family members present in > 75% of rounds, the 30-day re-hospitalization rate was tenfold higher (P = 0.017). The overall prognosis (including median survival length) of patients who had the highest rates of family attendance (> 75%) was significantly worse compared to patients who had lower rates (P = 0.028). High rates of family attendance were found to correlate with other established risk factors for long-term mortality, including advanced age (r = 0.231, P = 0.001) and in-hospital delirium. CONCLUSIONS: High family attendance during physician rounds in an internal medicine department is associated with worse patient prognosis.

Association between Thrombin Generation and Clinical Characteristics in COVID-19 Patients.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) disease is associated with coagulopathy and an increased risk of thrombosis. An association between thrombin generation (TG) capacity, disease severity, and outcomes has not been well described. METHODS: We assessed the correlation of TG with sequential organ failure assessment (SOFA) and sepsis-induced coagulopathy (SIC) scores and clinical outcomes by analysis of plasma samples obtained from hospitalized COVID-19 patients. RESULTS: 32 patients (68.8% male), whose median age was 69 years, were assessed, of whom only 3 patients did not receive anticoagulant therapy. D-dimers were uniformly increased. During hospitalization, 2 patients suffered thrombosis, 3 experienced bleeding, and 12 died. TG parameters from anticoagulated COVID-19 patients did not significantly differ from the values obtained from non-anticoagulated healthy controls. Patients who received higher than prophylactic doses of anticoagulant therapy had increased lag time (p = 0.003), lower endogenous thrombin potential (ETP) (p = 0.037), and a reduced peak height (p = 0.006). ETP correlated with the SIC score (p = 0.038). None of the TG parameters correlated with the SOFA score or were associated with mortality. CONCLUSION: TG was not associated with disease severity among patients hospitalized with COVID-19. However, a correlation between ETP and the SIC score was noted and deserves attention.

Low Alanine Aminotransferase as a Marker for Sarcopenia and Frailty, Is Associated with Decreased Survival of Bladder Cancer Patients and Survivors-A Retrospective Data Analysis of 3075 Patients.

BACKGROUND: Sarcopenia is characterized by the loss of muscle mass and function and is associated with frailty, a syndrome linked to an increased likelihood of falls, fractures, and physical disability. Both frailty and sarcopenia are recognized as markers for shortened survival in a number of medical conditions and in cancer patient populations. Low alanine aminotransferase (ALT) values, representing low muscle mass (sarcopenia), may be associated with increased frailty and subsequently shortened survival in cancer patients. In the current study, we aimed to assess the potential relationship between low ALT and shorter survival in bladder cancer patients and survivors. PATIENTS AND METHODS: This was a retrospective analysis of bladder cancer patients and survivors, both in and outpatients. We defined patients with sarcopenia as those presenting with ALT < 17 IU/L. RESULTS: A total of 5769 bladder cancer patients' records were identified. After the exclusion of patients with no available ALT values or ALT levels above the upper normal limit, the final study cohort included 3075 patients (mean age 73.2 ± 12 years), of whom 80% were men and 1362 (53% had ALT ≤ 17 IU/L. The mean ALT value of patients within the low ALT group was 11.44 IU/L, while the mean value in the higher ALT level group was 24.32 IU/L (p < 0.001). Patients in the lower ALT group were older (74.7 vs. 71.4 years; p < 0.001), had lower BMI (25.8 vs. 27; p < 0.001), and their hemoglobin values were lower (11.7 vs. 12.6 g/dL; p < 0.001). In a univariate analysis, low ALT levels were associated with a 45% increase in mortality (95% CI 1.31-1.60, p < 0.001). In a multivariate model controlling for age, kidney function, and hemoglobin, low ALT levels were still associated with 22% increased mortality. CONCLUSIONS: Low ALT values, indicative of sarcopenia and frailty, are associated with decreased survival of bladder cancer patients and survivors and could potentially be applied for optimizing individual treatment decisions.

Developing and validating a machine learning prognostic model for alerting to imminent deterioration of hospitalized patients with COVID-19.

Our study was aimed at developing and validating a new approach, embodied in a machine learning-based model, for sequentially monitoring hospitalized COVID-19 patients and directing professional attention to patients whose deterioration is imminent. Model development employed real-world patient data (598 prediction events for 210 patients), internal validation (315 prediction events for 97 patients), and external validation (1373 prediction events for 307 patients). Results show significant divergence in longitudinal values of eight routinely collected blood parameters appearing several days before deterioration. Our model uses these signals to predict the personal likelihood of transition from non-severe to severe status within well-specified short time windows. Internal validation of the model's prediction accuracy showed ROC AUC of 0.8 and 0.79 for prediction scopes of 48 or 96 h, respectively; external validation showed ROC AUC of 0.7 and 0.73 for the same prediction scopes. Results indicate the feasibility of predicting the forthcoming deterioration of non-severe COVID-19 patients by eight routinely collected blood parameters, including neutrophil, lymphocyte, monocyte, and platelets counts, neutrophil-to-lymphocyte ratio, CRP, LDH, and D-dimer. A prospective clinical study and an impact assessment will allow implementation of this model in the clinic to improve care, streamline resources and ease hospital burden by timely focusing the medical attention on potentially deteriorating patients.

Mortality prediction upon hospital admission - the value of clinical assessment: A retrospective, matched cohort study.

Accurate prediction of mortality upon hospital admission is of great value, both for the sake of patients and appropriate resources' allocation. A myriad of assessment tools exists for this purpose. The evidence relating to the comparative value of clinical assessment versus established indexes are scarce. We analyzed the accuracy of a senior physician's clinical assessment in a retrospective cohort of patients in a crude, general patients' population and later on a propensity matched patients' population. In one department of internal medicine in a tertiary hospital, of 9891 admitted patients, 973 (10%) were categorized as prone to death in a 6-months' duration by a senior physician. The risk of death was significantly higher for these patients [73.1% vs 14.1% mortality within 180 days; hazard ratio (HR) = 7.58; confidence intervals (CI) 7.02-8.19, P < .001]. After accounting for multiple, other patients' variables associated with increased risk of mortality, the correlation remained significant (HR = 3.25; CI 2.85-3.71, P < .001). We further performed a propensity matching analysis (a subgroup of 710 patients, subdivided to two groups with 355 patients each): survival rates were as low as 45% for patients categorized as prone to death compared to 78% in patients who weren't categorized as such (P < .001). Reliance on clinical evaluation, done by an experienced senior physician, is an appropriate tool for mortality prediction upon hospital admission, achieving high accuracy rates.

A Biphasic COVID-19 Clinical Course in Anti-CD20 Treated Patients: Case Series and Review of the Literature.

We describe four cases of COVID-19 infection during the Omicron wave, in patients treated with anti-CD20 monoclonal antibodies. All cases follow a similar biphasic clinical course consisting of respiratory deterioration, which occurred a few weeks after convalescence from initial mild to asymptomatic infection. Possible explanations are discussed. LEARNING POINTS: Four cases of COVID-19 infection in anti-CD20 treated patients are described.These cases display a unique biphasic course that was previously undescribed: respiratory deterioration weeks after convalescence.Awareness of such a course and rapid utilisation of bronchoalveolar lavage will lead to quicker diagnosis and more timely, appropriate treatment.

[A RARE COMBINATION OF DELAYED TYPE HYPERSENSITIVITY REACTIONS TO BETA-LACTAMS IN A PATIENT WITH MSSA BACTEREMIA].

INTRODUCTION: A male patient aged 81, with a history of atrial fibrillation, pacemaker implantation and hip replacement was admitted due to pneumonia. Subsequent Methicillin Sensitive Staphylococcus Aureus (MSSA) bacteremia and septic arthritis of his prosthetic joint was diagnosed, and treated with Oxacillin. Two weeks later, an exanthematous rash appeared, involving most of his body surface, evolving to blisters that dried up and led to extensive exfoliation of the skin, consistent with a delayed type hypersensitivity drug reaction. Other possible etiologies for this rash were ruled out. Antibiotic treatment was changed to Cefalexin, assuming that there is no cross reactivity between penicillins and cephalosporins, regarding late drug reactions. Thereafter, the rash subsided, but his renal function deteriorated and interstitial nephritis due to a hypersensitivity reaction to cephalosporin was diagnosed. Hypersensitivity to penicillins and other beta-lactam antibiotics is reported by 10% of the population, only 1/10 of them are verified using standardized allergic testing (1-3). Delayed type hypersensitivity to beta-lactams is more common than immediate type allergy. It evolves days and weeks following exposure to the offending drug. Late responses are classified as type II- IV hypersensitivities, type IV being the most prevalent (4-7). We present a patient who developed two distinct delayed type phenomena to two different beta lactam antibiotics during the same hospitalization. The possibility of a hypersensitivity reaction should rise in the differential diagnosis of the deteriorating patient most notably as such might be life threatening on the one hand, and reversible, after drug withdrawal, on the other hand.

Sarcopenia as Manifested by L3SMI Is Associated with Increased Long-Term Mortality amongst Internal Medicine Patients-A Prospective Cohort Study.

Background: Sarcopenia and Frailty are syndromes that affect the clinical outcomes of patients suffering from a wide range of diseases. The use of Computed Tomography (CT) is well established for Sarcopenia evaluation via estimation of the Skeletal Muscle Index (SMI) at the level of the third lumbar vertebra (L3SMI). Nevertheless, the association of more readily available biomarkers of Sarcopenia and clinical outcomes is desired. Recent studies have associated low Alanine amino-transferase ALT (SGPT) levels with Sarcopenia and frailty. The current study aimed to establish the association between low L3SMI and the aforementioned indices of Sarcopenia, frailty and poor clinical outcomes. Methods: A cohort study of patients admitted to the internal medicine department at a tertiary medical center. Sarcopenia was determined as L3SMI, lower than 53 cm2/m2 in men and 41 cm2/m2 in women. Clinical and mortality data was collected from the medical record. Results: Of the 187 patients recruited (mean age 70.4 ± 9.2, 59% males), 116 (62%) had Sarcopenia, based on L3SMI values. Sarcopenic patients were older, predominantly male, had lower BMI, lower mid-arm muscle circumference (MAMC) and low ALT values upon admission. L3SMI values significantly correlated with age and MAMC among males (R = −0.38, p < 0.001, R = 0.35, p < 0.001, respectively). Sarcopenia was associated with higher, one-year mortality (HR = 2.60, 95% CI 1.06−6.37, p = 0.036) and shorter all-time survival (HR = 2.91, 95% CI 1.35−6.29, p = 0.007). The association with all-time survival remained after adjusting for age and sex (HR = 2.38, 95% CI 1.07−5.29, p = 0.034). Conclusion: As defined by low L3SMI value, Sarcopenia is a poor prognostic factor for the general internal ward patient population. As part of personalized medicine, physicians may benefit from measuring L3SMI value, as indicated by commonly performed CT scans, to objectively assess their patient's risk of suffering from Sarcopenia and frailty-associated complications.