The rising healthcare demand during COVID-19 outbreak may endanger patients and forces hospital to plan for future needs. Predictive analyses were conducted to monitor hospital resources at one of the gazetted COVID-19 hospitals in Malaysia. Simultaneously, a real-time observation on patient’s volume was conducted to understand the actual trend of healthcare resource utilisations. All the projections were directly compared to the actual number of patients in-care. This predictive study was done at University Malaya Medical Centre (UMMC) using various sources of data. The projections revealed a steady increase in the number of cumulative cases until April 2020 followed by an exponential increase in the number of cumulative positive cases in Malaysia. When a comparison between the projection and actual data was done, it was found that the initial projections estimated a range that is 50% to 70% higher during the first three phases of Movement Control Order (MCO) compared to the actual number of COVID-19 patients at UMMC. Subsequent projections were done by using recent estimations from the national database and it was estimated that the number of patients treated will be less than 10 each day up until the end of May 2020. The accuracy of this estimation is 95% when compared to the actual number of COVID-19 patients in care. In conclusion, the practice of continuous projections and real-time observation through predictive analysis using mathematical calculations and algorithms is one of the useful tools to facilitate hospital management to allocate adequate resource allocations.
COVID-19

INTRODUCTIONCephalic index (CI), the ratio of head breadth to head length, is widely used to categorise human populations. The aim of this study was to access the impact of anthropometric measurements on the CI of male Japanese university students.

METHODSThis study included 1,215 male university students from Tokyo and Kyoto, selected using convenient sampling. Multiple regression analysis was used to determine the effect of anthropometric measurements on CI.

RESULTSThe variance inflation factor (VIF) showed no evidence of a multicollinearity problem among independent variables. The coefficients of the regression line demonstrated a significant positive relationship between CI and minimum frontal breadth (p < 0.01), bizygomatic breadth (p < 0.01) and head height (p < 0.05), and a negative relationship between CI and morphological facial height (p < 0.01) and head circumference (p < 0.01). Moreover, the coefficient and odds ratio of logistic regression analysis showed a greater likelihood for minimum frontal breadth (p < 0.01) and bizygomatic breadth (p < 0.01) to predict round-headedness, and morphological facial height (p < 0.05) and head circumference (p < 0.01) to predict long-headedness. Stepwise regression analysis revealed bizygomatic breadth, head circumference, minimum frontal breadth, head height and morphological facial height to be the best predictor craniofacial measurements with respect to CI.

CONCLUSIONThe results suggest that most of the variables considered in this study appear to influence the CI of adult male Japanese students.

Adolescent ; Adult ; Body Height ; Cephalometry ; methods ; Cross-Sectional Studies ; Head ; anatomy & histology ; Humans ; Japan ; Male ; Reference Values ; Regression Analysis ; Students ; Universities ; Young Adult

Any medical diagnosis should take a multimodal approach, especially those involving tumour-like conditions, as entities that mimic neoplasms have overlapping features and may present detrimental outcomes if they are underdiagnosed. These case reports present diagnostic pitfalls resulting from overdependence on a single diagnostic parameter for three musculoskeletal neoplasm mimics: brown tumour (BT) that was mistaken for giant cell tumour (GCT), methicillin-resistant Staphylococcus aureus osteomyelitis mistaken for osteosarcoma and a pseudoaneurysm mistaken for a soft tissue sarcoma. Literature reviews revealed five reports of BT simulating GCT, four reports of osteomyelitis mimicking osteosarcoma and five reports of a pseudoaneurysm imitating a soft tissue sarcoma. Our findings highlight the therapeutic dilemmas that arise with musculoskeletal mimics, as well as the importance of thorough investigation to distinguish mimickers from true neoplasms.
Adult ; Aneurysm, False ; diagnosis ; Biopsy ; Bone Diseases ; diagnosis ; Bone Diseases, Metabolic ; diagnosis ; Bone Neoplasms ; diagnosis ; Cell Proliferation ; Diagnosis, Differential ; Diagnostic Errors ; prevention & control ; Female ; Giant Cell Tumors ; diagnosis ; Humans ; Hyperparathyroidism ; complications ; Leukocytosis ; diagnosis ; Male ; Methicillin-Resistant Staphylococcus aureus ; Middle Aged ; Neoplasms ; diagnosis ; microbiology ; Osteomyelitis ; diagnosis ; microbiology ; Osteosarcoma ; diagnosis ; Sarcoma ; diagnosis ; Soft Tissue Neoplasms ; diagnosis ; Tibia ; pathology

The sudden surge in the number of healthcare utilizations compels the hospital to plan for its future needs. Several time-series projections of Covid-19 were conducted to forecast the disease burden and resources utilization through simple predictive analytics. The projections revealed a rapid increase in the number of cases and patient in care at the hospital. It was estimated that the number of patients in care to range from 62 to 81 and 89 to 121 patients daily in the second and third phase of movement control order respectively. It was estimated that more than 100,000 plastic aprons, 80,000 sterile and non-sterile isolation gowns, 40,000 masks N95 and face shields, 30,000 gloves and nearly 17,000 bottles of hand sanitizers are needed until late May. Hence, a simple mathematical algorithm is a helpful tool to manage hospital resources during the pandemic.
COVID-19