BACKGROUND The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection.The determinants of mortality on a global scale c...BACKGROUND The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection.The determinants of mortality on a global scale cannot be fully understood due to lack of information.AIM To identify key factors that may explain the variability in case lethality across countries.METHODS We identified 21 Potential risk factors for coronavirus disease 2019(COVID-19)case fatality rate for all the countries with available data.We examined univariate relationships of each variable with case fatality rate(CFR),and all independent variables to identify candidate variables for our final multiple model.Multiple regression analysis technique was used to assess the strength of relationship.RESULTS The mean of COVID-19 mortality was 1.52±1.72%.There was a statistically significant inverse correlation between health expenditure,and number of computed tomography scanners per 1 million with CFR,and significant direct correlation was found between literacy,and air pollution with CFR.This final model can predict approximately 97%of the changes in CFR.CONCLUSION The current study recommends some new predictors explaining affect mortality rate.Thus,it could help decision-makers develop health policies to fight COVID-19.展开更多
Kikuchi-Fujimoto disease(KFD), also known as histiocytic necrotizing lymphadenitis, is an uncommon condition, typically characterized by lymphadenopathy and fevers. It usually has a benign course; however, it may prog...Kikuchi-Fujimoto disease(KFD), also known as histiocytic necrotizing lymphadenitis, is an uncommon condition, typically characterized by lymphadenopathy and fevers. It usually has a benign course; however, it may progress to fatality in extremely rare occasions. The diagnosis is made via lymph node biopsy and histopathology. Our patient was a young female who presented with shortness of breath, fever, and malaise. Physical examination revealed significant cervical and axillary lymphadenopathy. Chest X-ray displayed multilobar pneumonia. She required intubation and mechanical ventilation for progressive respiratory distress. Histopathology of lymph nodes demonstrated variable involvement of patchy areas of necrosis within the paracortex composed of karyorrhectic debris with abundant histiocytes consistent with KFD. After initial stabilization, the patient's condition quickly deteriorated with acute anemia, thrombocytopenia and elevated prothrombin time, partial prothrombin time, and D-dimer levels. Disseminated intravascular coagulopathy(DIC) ensued resulting in the patient's fatality. DIC in KFD is not well understood, but it is an important cause of mortality in patients with aggressive disease.展开更多
Objectives: Causes and risk factors that result in fatal road traffic accident have not been described at the national level in Guinea yet. The goal of this study is to explore the causes and risk factors related to f...Objectives: Causes and risk factors that result in fatal road traffic accident have not been described at the national level in Guinea yet. The goal of this study is to explore the causes and risk factors related to fatal road traffic accident, identified most vulnerable road users, and inform the road traffic prevention policy in Guinea. Methods: We made a retrospective descriptive analysis based on national fatal road traffic accident data from the Department of Health Information at the Guinean Ministry of Health for year 2011. Results: In 2011, road traffic accident was responsible for an aggregate number of 1655 deaths with an overall death rate of 15.3 per 100,000 population. Male experienced more than twice the risk of death from road traffic accidents (21.9 deaths per 100,000 population) compared with female (9.0 deaths per 100,000 population). While taking the population as a whole, the highest death rate was found among the middle aged in 35 - 49 age group accounting for (29.7 deaths per 100,000 population), followed successively by young adults age group 25 - 34 years (24.6 deaths per 100,000 population), and the middle aged in 50 - 64 age group (22.9 deaths per 100,000 population). Principally, occupants, motorcyclists and pedestrians sustained considerable burden of deaths respectively (9.2;2.9;2.2 per 100,000 population). In re-gional setting, the highest death rate was found in Upper Guinea (19.5 per 100,000 population), followed by Forest Guinea (18.7 per 100,000 population) and Middle Guinea (16.8 per 100,000 population). A large proportion of male was killed as motorcyclist than female while high per-centage of female died as occupant than male for all age group. The regional distribution showed that when a remarkable number of occupant death were observed in Upper and Forest Guinea, more people died as pedestrian and pedal cyclist in Conakry. Conclusions: This study demonstrated that most of the deaths were among occupants, motorcyclists and pedestrians, and the productive workforce aged 25 - 49 years. It was found that majority of the deaths happened in Upper Guinea followed by Forest Guinea. Improvement of roads design, strict enforcement of road safety laws and raising the awareness of general public about the causes and risks factors of road traffic accident through various channels are highly required which will promote economic growth in the local communities and then help people escape the poverty trap.展开更多
We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartmen...We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.展开更多
To estimate the aggressivity of vehicles in frontal crashes, national highway traffic safety administration (NHTSA) has introduced the driver fatality ratio, DFR, for different vehicle-to-vehicle categories. The DFR p...To estimate the aggressivity of vehicles in frontal crashes, national highway traffic safety administration (NHTSA) has introduced the driver fatality ratio, DFR, for different vehicle-to-vehicle categories. The DFR proposed by NHTSA is based on the actual crash statistical data, which makes it difficult to evaluate for other vehicle categories newly introduced to the market, as they do not have sufficient crash statistics. A finite element (FE) methodology is proposed in this study based on computational reconstruction of crashes and some objective measures to predict the relative risk of DFR associated with any vehicle-to-vehicle crash. The suggested objective measures include the ratios of maximum intrusion in the passenger compartments of the vehicles in crash, and the transmitted peak deceleration of the vehicles’ center of gravity, which are identified as the main influencing parameters on occupant injury. The suitability of the proposed method is established for a range of bullet light truck and van (LTV) categories against a small target passenger car with published data by NHTSA. A mathematical relation between the objective measures and DFR is then developed. The methodology is then extended to predict the relative risk of DFR for a crossover category vehicle, a light pick-up truck, and a mid-size car in crash against a small size passenger car. It is observed that the ratio of intrusions produces a reasonable estimate for the DFR, and that it can be utilized in predicting the relative risk of fatality ratios in head-on collisions. The FE methodology proposed in this study can be utilized in design process of a vehicle to reduce the aggressivity of the vehicle and to increase the on-road fleet compatibility in order to reduce the occupant injury out- come.展开更多
Objective:To identify the febrile characteristics and clinical presentations associated with fatality in hospitalized adult patients with dengue virus(DENV)infections.Methods:A total of 289 adult hospitalized patients...Objective:To identify the febrile characteristics and clinical presentations associated with fatality in hospitalized adult patients with dengue virus(DENV)infections.Methods:A total of 289 adult hospitalized patients with laboratoryconfirmed DENV infections were examined,of which 22 were fatal and 267 were non-fatal.A comparison of the clinical and laboratory characteristics was retrospectively conducted of the deceased and surviving individuals.Multivariate logistic regression and receiver operating characteristic curve analysis were performed to identify predictors of fatality.Results:Fatal patients exhibited significantly more comorbidities,particularly renal and cardiac comorbidities,and they were,in general,older than control individuals(P<0.0001).The results of logistic regression analysis showed that febrile duration of less than four days before arriving in the Emergency Department(OR=5.34;95%CI:1.39–20.6),episode of hypotension in the Emergency Department(OR=6.95;95%CI:2.40–20.1),and comorbidity with congestive heart failure(OR=11.26;95%CI:2.31–54.79)were all significantly associated with inpatient fatality due to DENV infection.The ROC curve analysis indicated that the final prognostic model yielded an area under the curve of 0.87(95%CI:0.79–0.97)for fatality.Conclusions:The aforementioned clinical findings may help clinicians predict fatality among adult inpatients with DENV infection.展开更多
Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fata...Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fatality rate(IFR).We investigated the association between meteorological factors(temperature,humidity,solar irradiance,pressure,wind,precipitation,cloud coverage)and IFR across Spanish provinces(n=52)during the first wave of the pandemic(weeks 10–16 of 2020).Methods We estimated IFR as excess deaths(the gap between observed and expected deaths,considering COVID-19-unrelated deaths prevented by lockdown measures)divided by the number of infections(SARS-CoV-2 seropositive individuals plus excess deaths)and conducted Spearman correlations between meteorological factors and IFR across the provinces.Results We estimated 2,418,250 infections and 43,237 deaths.The IFR was 0.03%in<50-year-old,0.22%in 50–59-year-old,0.9%in 60–69-year-old,3.3%in 70–79-year-old,12.6%in 80–89-year-old,and26.5%in≥90-year-old.We did not find statistically significant relationships between meteorological factors and adjusted IFR.However,we found strong relationships between low temperature and unadjusted IFR,likely due to Spain’s colder provinces’aging population.Conclusion The association between meteorological factors and adjusted COVID-19 IFR is unclear.Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.展开更多
Objective: To predict the daily incidence and fatality rates based on long short-term memory(LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran.Methods: To predict the daily incidence and fatality...Objective: To predict the daily incidence and fatality rates based on long short-term memory(LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran.Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other.Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females(49.7%), and 25 586 were males(50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively;for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.展开更多
Objective: Pedestrian safety is considered as one of the greatest concerns, especially for developing countries. In the year of 2015, about 48% pedestrian accidents with 56% fatalities occurred at mid-blocks in Beijin...Objective: Pedestrian safety is considered as one of the greatest concerns, especially for developing countries. In the year of 2015, about 48% pedestrian accidents with 56% fatalities occurred at mid-blocks in Beijing. Since the high frequency and fatality risk, this study focused on pedestrian accidents taking place at mid-blocks and aimed at identifying significant factors. Methods: Based on total 10,948 crash records, a binary logit model was established to explore the impact of various factors on the probability of pedestrian’s death. Furthermore, first-degree interaction effects were introduced into the basic model. The Hosmer-Lemeshow goodness-of-fit test was used to assess the model performance. Odds ratio was calculated for categorical variables to compare significant accident conditions with the conference level. Variables within consideration in this study included weather, area type, road type, speed limit, pedestrian location, lighting condition, vehicle type, pedestrian gender and pedestrian age. Results: The calibration results of the model show that the increased fatality chances of an accident at mid-blocks are associated with normal weather, rural area, two-way divided road, crossing elsewhere in carriageway, darkness (especially for no street lighting), light vehicle, large vehicle and male pedestrian. With road speed limit increasing by 10 km/h, the probability of death accordingly increases by 46%. Older victims have higher chances of being killed in a crash. Moreover, three interaction effects are found significant: rural area and two-way divided, rural area and crossing elsewhere as well as speed limit and pedestrian age. Conclusions: This study has analyzed police accident data and identified factors significant to the death probability of pedestrians in accidents occurred at mid-blocks. Recommendations and improving measures were proposed correspondingly. Behaviors of different road users at mid-blocks should be taken into account in the future research.展开更多
<strong>Importance:</strong> Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbr...<strong>Importance:</strong> Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbreak was reported in Wuhan, China during December 2019. It is thus important to make cross-country comparison of the relevant rates and understand the socio-demographic risk factors. <strong>Methods: </strong>This is a record based retrospective cohort study. <strong>Table 1</strong> was extracted from <a href="https://www.worldometers.info/coronavirus/" target="_blank">https://www.worldometers.info/coronavirus/</a> and from the Corona virus resource center (<strong>Table 2</strong>, <strong>Figures 1-3</strong>), Johns Hopkins University. Data for <strong>Table 1</strong> includes all countries which reported >1000 cases and <strong>Table 2</strong> includes 20 countries reporting the largest number of deaths. The estimation of CFR, RR and PR of the infection, and disease pattern across geographical clusters in the world is presented. <strong>Results:</strong> From <strong>Table 1</strong>, we could infer that as on 4<sup>th</sup> May 2020, COVID-19 has rapidly spread world-wide with total infections of 3,566,423 and mortality of 248,291. The maximum morbidity is in USA with 1,188,122 cases and 68,598 deaths (CFR 5.77%, RR 15% and PR 16.51%), while Spain is at the second position with 247,122 cases and 25,264 deaths (CFR 13.71%, RR 38.75%, PR 9.78%). <strong>Table 2</strong> depicts the scenario as on 8<sup>th</sup> October 2020, where-in the highest number of confirmed cases occurred in US followed by India and Brazil (cases per million population: 23,080, 5007 & 23,872 respectively). For deaths per million population: US recorded 647, while India and Brazil recorded 77 and 708 respectively. <strong>Conclusion:</strong> Studying the distribution of relevant rates across different geographical clusters plays a major role for measuring the disease burden, which in-turn enables implementation of appropriate public healthcare measures.展开更多
Coronavirus disease 2019 (COVID-19) has spread to 72 countries by the time of writing this report on 4th March 2020[1].On 20th February 2020,the first two confirmed deaths from COVID-19were reported in Iran.Till 4th M...Coronavirus disease 2019 (COVID-19) has spread to 72 countries by the time of writing this report on 4th March 2020[1].On 20th February 2020,the first two confirmed deaths from COVID-19were reported in Iran.Till 4th March 2020,2 922 confirmed and92 death cases have also been reported till 4th March 2020 in Iran(Figure 1)[1].A key question that remains unanswered or controversial among the public,media,and researchers is the exact COVID-19 case fatality rate (CFR) in Iran.Why does the CFR in Iran appear to be higher compared to the rest of the world until now?Or why the fatality rate is high at the beginning of the epidemic in Iran?展开更多
Background:During the course of an epidemic of a potentially fatal disease,it is difficult to accurately estimate the case fatality rate(CFR)because many calculation methods do not account for the delay between case c...Background:During the course of an epidemic of a potentially fatal disease,it is difficult to accurately estimate the case fatality rate(CFR)because many calculation methods do not account for the delay between case confirmation and disease outcome.Taking the coronavirus disease-2019(COVID-19)as an example,this study aimed to develop a new method for CFR calculation while the pandemic was ongoing.Methods:We developed a new method for CFR calculation based on the following formula:number of deaths divided by the number of cases T days before,where T is the average delay between case confirmation and disease outcome.An objective law was found using simulated data that states if the hypothesized T is equal to the true T,the calculated real-time CFR remains constant;whereas if the hypothesized T is greater(or smaller)than the true T,the real-time CFR will gradually decrease(or increase)as the days progress until it approaches the true CFR.Results:Based on the discovered law,it was estimated that the true CFR of COVID-19 at the initial stage of the pandemic in China,excluding Hubei Province,was 0.8%;and in Hubei Province,it was 6.6%.The calculated CFRs predicted the death count with almost complete accuracy.Conclusions:The method could be used for the accurate calculation of the true CFR during a pandemic,instead of waiting until the end of the pandemic,whether the pandemic is under control or not.It could provide those involved in outbreak control a clear view of the timeliness of case confirmations.展开更多
While surveillance can identify changes in COVID-19 transmission patterns over time and space,sections of the population at risk,and the efficacy of public health measures,reported cases of COVID-19 are generally unde...While surveillance can identify changes in COVID-19 transmission patterns over time and space,sections of the population at risk,and the efficacy of public health measures,reported cases of COVID-19 are generally understood to only capture a subset of the actual number of cases.Our primary objective was to estimate the percentage of cases reported in the general community,considered as those that occurred outside of long-term care facilities(LTCFs),in specific provinces and Canada as a whole.We applied a methodology using the delay-adjusted case fatality ratio(CFR)to all cases and deaths,as well as those representing the general community.Our second objective was to assess whether the assumed CFR(mean=1.38%)was appropriate for calculating underestimation of cases in Canada.Estimates were developed for the period from March 11th,2020 to September 16th,2020.Estimates of the percentage of cases reported(PrCR)and CFR varied spatially and temporally across Canada.For the majority of provinces,and for Canada as a whole,the PrCR increased through the early stages of the pandemic.The estimated PrCR in general community settings for all of Canada increased from 18.1%to 69.0%throughout the entire study period.Estimates were greater when considering only those data from outside of LTCFs.The estimated upper bound CFR in general community settings for all of Canada decreased from 9.07%on March 11th,2020 to 2.00%on September 16th,2020.Therefore,the true CFR in the general community in Canada was likely less than 2%on September 16th.According to our analysis,some provinces,such as Alberta,Manitoba,Newfoundland and Labrador,Nova Scotia,and Saskatchewan reported a greater percentage of cases as of September 16th,compared to British Columbia,Ontario,and Quebec.This could be due to differences in testing rates and criteria,demographics,socioeconomic factors,race,and access to healthcare among the provinces.Further investigation into these factors could reveal differences among provinces that could partially explain the variation in estimates of PrCR and CFR identified in our study.The estimates provide context to the summative state of the pandemic in Canada,and can be improved as knowledge of COVID-19 reporting rates and disease characteristics are advanced.展开更多
Background:Early severity estimates of coronavirus disease 2019(COVID-19)are critically needed to assess the potential impact of the on going pandemic in differe nt demographic groups.Here we estimate the real-time de...Background:Early severity estimates of coronavirus disease 2019(COVID-19)are critically needed to assess the potential impact of the on going pandemic in differe nt demographic groups.Here we estimate the real-time delayadjusted case fatality rate across nine age groups by gender in Chile,the country with the highest testing rate for COVID-19 in Latin America.Methods:We used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31,2020.We used a robust likelihood function and a delay distribution to estimate real-time delay-adjusted case-fatality risk and estimate model parameters using a Monte Carlo Markov Chain in a Bayesian framework.展开更多
The case fatality ratio(CFR)is one of the key measurements to evaluate the clinical severity of infectious diseases.The CFR may vary due to change in factors that affect the mortality risk.In this study,we developed a...The case fatality ratio(CFR)is one of the key measurements to evaluate the clinical severity of infectious diseases.The CFR may vary due to change in factors that affect the mortality risk.In this study,we developed a simple likelihood-based framework to estimate the instantaneous CFR of infectious diseases.We used the publicly available COVID-19 surveillance data in Canada for demonstration.We estimated the mean fatality ratio of reported COVID-19 cases(rCFR)in Canada was estimated at 6.9%(95%CI:4.5e10.6).We emphasize the extensive implementation of the constructed instantaneous CFR that is to identify the key determinants affecting the mortality risk.展开更多
BACKGROUND Most species of aconite contain highly toxic aconitines,the oral ingestion of which can be fatal,primarily because they cause ventricular arrhythmias.We describe a case of severe aconite poisoning that was ...BACKGROUND Most species of aconite contain highly toxic aconitines,the oral ingestion of which can be fatal,primarily because they cause ventricular arrhythmias.We describe a case of severe aconite poisoning that was successfully treated through venoarterial extracorporeal membrane oxygenation(VA-ECMO)and in which detailed toxicological analyses of the aconite roots and biological samples were performed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).CASE SUMMARY A 23-year-old male presented to the emergency room with circulatory collapse and ventricular arrhythmia after ingesting approximately half of a root labeled,“Aconitum japonicum Thunb”.Two hours after arrival,VA-ECMO was initiated as circulatory collapse became refractory to antiarrhythmics and vasopressors.Nine hours after arrival,an electrocardiogram revealed a return to sinus rhythm.The patient was weaned off VA-ECMO and the ventilator on hospital days 3 and 5,respectively.On hospital day 15,he was transferred to a psychiatric hospital.The other half of the root and his biological samples were toxicologically analyzed using LC-MS/MS,revealing 244.3 mg/kg of aconitine and 24.7 mg/kg of mesaconitine in the root.Serum on admission contained 1.50 ng/mL of aconitine.Beyond hospital day 2,neither were detected.Urine on admission showed 149.09 ng/mL of aconitine and 3.59 ng/mL of mesaconitine,but these rapidly decreased after hospital day 3.CONCLUSION The key to saving the life of a patient with severe aconite poisoning is to introduce VA-ECMO as soon as possible.展开更多
The evidence for the effects of environmental factors on COVID-19 case fatality remains controversial,and it is crucial to understand the role of preventable environmental factors in driving COVID-19 fatality.We thus ...The evidence for the effects of environmental factors on COVID-19 case fatality remains controversial,and it is crucial to understand the role of preventable environmental factors in driving COVID-19 fatality.We thus conducted a nationwide cohort study to estimate the effects of environmental factors(temperature,particulate matter[PM2.5,PM10],sulfur dioxide[SO2],nitrogen dioxide[NO2],and ozone[O3])on COVID-19 case fatality.A total of 71,808 confirmed COVID-19 cases were identified and followed up for their vital status through April 25,2020.Exposures to ambient air pollution and temperature were estimated by linking the city-and county-level monitoring data to the residential community of each participant.For each participant,two windows were defined:the period from symptom onset to diagnosis(exposure window I)and the period from diagnosis date to date of death/recovery or end of the study period(exposure window II).Cox proportional hazards models were used to estimate the associations between these environmental factors and COVID-19 case fatality.COVID-19 case fatality increased in association with environmental factors for the two exposure windows.For example,each 10 mg/m^(3) increase in PM2.5,PM10,O3,and NO2 in window I was associated with a hazard ratio of 1.11(95%CI 1.09,1.13),1.10(95%CI 1.08,1.13),1.09(95 CI 1.03,1.14),and 1.27(95%CI 1.19,1.35)for COVID-19 fatality,respectively.A significant effect was also observed for low temperature,with a hazard ratio of 1.03(95%CI 1.01,1.04)for COVID-19 case fatality per 1C decrease.Subgroup analysis indicated that these effects were stronger in the elderly,as well as in those with mild symptoms and living in Wuhan or Hubei.Overall,the sensitivity analyses also yielded consistent estimates.Short-term exposure to ambient air pollution and low temperature during the illness would play a nonnegligible part in causing case fatality due to COVID-19.Reduced exposures to high concentrations of PM2.5,PM10,O3,SO2,and NO2 and low temperature would help improve the prognosis and reduce public health burden.展开更多
Introduction: Data on mortality in acute kidney injury (AKI) derives from high-income countries where AKI is hospital-acquired and occurs in elderly patients with a high burden of cardiovascular disease. In sub-Sahara...Introduction: Data on mortality in acute kidney injury (AKI) derives from high-income countries where AKI is hospital-acquired and occurs in elderly patients with a high burden of cardiovascular disease. In sub-Saharan Africa (SSA), AKI is community-acquired occurring in healthy young adults. We aimed to identify predictors of fatal outcomes in patients with AKI in two tertiary hospitals in Cameroon. Methods: Medical records of adults with confirmed AKI, from January 2018 to March 2020 were retrieved. The outcomes of interest were in-hospital deaths and presumed causes of death. We used multiple logistic regressions modeling to identify predictors of death. The study was approved by the ethics boards of both hospitals. Values were considered significant for a p-value of 0.05. Results: We included 285 patient records (37.2% females). The mean (SD) age was 50.1 (19.0) years. Hypertension (n = 97, 34.0%), organ failure (n = 88, 30.9%), and diabetes (n = 60, 21.1%) were the main comorbidities. The majority of patients had community-acquired AKI (78.6%, n = 224), were KDIGO stage 3 (88.8%, n = 253), and needed dialysis (52.6%, n = 150). Up to 16.7% (n = 25) did not receive what was needed. The in-hospital mortality rate was 29.1% (n = 83). Lack of access to dialysis (OR = 27.8;CI: 5.2 - 149.3, p = 0.001), hypotension (OR = 11.8;CI: 1.3 - 24.8;p = 0.001) and ICU admission (OR = 5.7;CI: 1.3 - 24.8, p = 0.001) were predictors of mortality. The presence of co-morbidities or underlying diseases (n = 46, 55%) were the main causes of death. Conclusions: In-hospital AKI mortality is high, as in other low- and middle-income economies. Lack of access to dialysis and the severity of the underlying illness are major predictors of death.展开更多
文摘BACKGROUND The spread of the severe acute respiratory syndrome coronavirus 2 outbreak worldwide has caused concern regarding the mortality rate caused by the infection.The determinants of mortality on a global scale cannot be fully understood due to lack of information.AIM To identify key factors that may explain the variability in case lethality across countries.METHODS We identified 21 Potential risk factors for coronavirus disease 2019(COVID-19)case fatality rate for all the countries with available data.We examined univariate relationships of each variable with case fatality rate(CFR),and all independent variables to identify candidate variables for our final multiple model.Multiple regression analysis technique was used to assess the strength of relationship.RESULTS The mean of COVID-19 mortality was 1.52±1.72%.There was a statistically significant inverse correlation between health expenditure,and number of computed tomography scanners per 1 million with CFR,and significant direct correlation was found between literacy,and air pollution with CFR.This final model can predict approximately 97%of the changes in CFR.CONCLUSION The current study recommends some new predictors explaining affect mortality rate.Thus,it could help decision-makers develop health policies to fight COVID-19.
文摘Kikuchi-Fujimoto disease(KFD), also known as histiocytic necrotizing lymphadenitis, is an uncommon condition, typically characterized by lymphadenopathy and fevers. It usually has a benign course; however, it may progress to fatality in extremely rare occasions. The diagnosis is made via lymph node biopsy and histopathology. Our patient was a young female who presented with shortness of breath, fever, and malaise. Physical examination revealed significant cervical and axillary lymphadenopathy. Chest X-ray displayed multilobar pneumonia. She required intubation and mechanical ventilation for progressive respiratory distress. Histopathology of lymph nodes demonstrated variable involvement of patchy areas of necrosis within the paracortex composed of karyorrhectic debris with abundant histiocytes consistent with KFD. After initial stabilization, the patient's condition quickly deteriorated with acute anemia, thrombocytopenia and elevated prothrombin time, partial prothrombin time, and D-dimer levels. Disseminated intravascular coagulopathy(DIC) ensued resulting in the patient's fatality. DIC in KFD is not well understood, but it is an important cause of mortality in patients with aggressive disease.
文摘Objectives: Causes and risk factors that result in fatal road traffic accident have not been described at the national level in Guinea yet. The goal of this study is to explore the causes and risk factors related to fatal road traffic accident, identified most vulnerable road users, and inform the road traffic prevention policy in Guinea. Methods: We made a retrospective descriptive analysis based on national fatal road traffic accident data from the Department of Health Information at the Guinean Ministry of Health for year 2011. Results: In 2011, road traffic accident was responsible for an aggregate number of 1655 deaths with an overall death rate of 15.3 per 100,000 population. Male experienced more than twice the risk of death from road traffic accidents (21.9 deaths per 100,000 population) compared with female (9.0 deaths per 100,000 population). While taking the population as a whole, the highest death rate was found among the middle aged in 35 - 49 age group accounting for (29.7 deaths per 100,000 population), followed successively by young adults age group 25 - 34 years (24.6 deaths per 100,000 population), and the middle aged in 50 - 64 age group (22.9 deaths per 100,000 population). Principally, occupants, motorcyclists and pedestrians sustained considerable burden of deaths respectively (9.2;2.9;2.2 per 100,000 population). In re-gional setting, the highest death rate was found in Upper Guinea (19.5 per 100,000 population), followed by Forest Guinea (18.7 per 100,000 population) and Middle Guinea (16.8 per 100,000 population). A large proportion of male was killed as motorcyclist than female while high per-centage of female died as occupant than male for all age group. The regional distribution showed that when a remarkable number of occupant death were observed in Upper and Forest Guinea, more people died as pedestrian and pedal cyclist in Conakry. Conclusions: This study demonstrated that most of the deaths were among occupants, motorcyclists and pedestrians, and the productive workforce aged 25 - 49 years. It was found that majority of the deaths happened in Upper Guinea followed by Forest Guinea. Improvement of roads design, strict enforcement of road safety laws and raising the awareness of general public about the causes and risks factors of road traffic accident through various channels are highly required which will promote economic growth in the local communities and then help people escape the poverty trap.
基金The work has been supported by a grant received from the Ministry of Education,Government of India under the Scheme for the Promotion of Academic and Research Collaboration(SPARC)(ID:SPARC/2019/1396).
文摘We have proposed a new mathematical method,the SEIHCRD model,which has an excellent potential to predict the incidence of COVID-19 diseases.Our proposed SEIHCRD model is an extension of the SEIR model.Three-compartments have added death,hospitalized,and critical,which improves the basic understanding of disease spread and results.We have studiedCOVID-19 cases of six countries,where the impact of this disease in the highest are Brazil,India,Italy,Spain,the United Kingdom,and the United States.After estimating model parameters based on available clinical data,the modelwill propagate and forecast dynamic evolution.Themodel calculates the Basic reproduction number over time using logistic regression and the Case fatality rate based on the selected countries’age-category scenario.Themodel calculates two types of Case fatality rate one is CFR daily,and the other is total CFR.The proposed model estimates the approximate time when the disease is at its peak and the approximate time when death cases rarely occur and calculate how much hospital beds and ICU beds will be needed in the peak days of infection.The SEIHCRD model outperforms the classic ARXmodel and the ARIMA model.RMSE,MAPE,andRsquaredmatrices are used to evaluate results and are graphically represented using Taylor and Target diagrams.The result shows RMSE has improved by 56%–74%,and MAPE has a 53%–89%improvement in prediction accuracy.
文摘To estimate the aggressivity of vehicles in frontal crashes, national highway traffic safety administration (NHTSA) has introduced the driver fatality ratio, DFR, for different vehicle-to-vehicle categories. The DFR proposed by NHTSA is based on the actual crash statistical data, which makes it difficult to evaluate for other vehicle categories newly introduced to the market, as they do not have sufficient crash statistics. A finite element (FE) methodology is proposed in this study based on computational reconstruction of crashes and some objective measures to predict the relative risk of DFR associated with any vehicle-to-vehicle crash. The suggested objective measures include the ratios of maximum intrusion in the passenger compartments of the vehicles in crash, and the transmitted peak deceleration of the vehicles’ center of gravity, which are identified as the main influencing parameters on occupant injury. The suitability of the proposed method is established for a range of bullet light truck and van (LTV) categories against a small target passenger car with published data by NHTSA. A mathematical relation between the objective measures and DFR is then developed. The methodology is then extended to predict the relative risk of DFR for a crossover category vehicle, a light pick-up truck, and a mid-size car in crash against a small size passenger car. It is observed that the ratio of intrusions produces a reasonable estimate for the DFR, and that it can be utilized in predicting the relative risk of fatality ratios in head-on collisions. The FE methodology proposed in this study can be utilized in design process of a vehicle to reduce the aggressivity of the vehicle and to increase the on-road fleet compatibility in order to reduce the occupant injury out- come.
基金supported by National Cheng Kung University Hospital(NCKUH-10505033)
文摘Objective:To identify the febrile characteristics and clinical presentations associated with fatality in hospitalized adult patients with dengue virus(DENV)infections.Methods:A total of 289 adult hospitalized patients with laboratoryconfirmed DENV infections were examined,of which 22 were fatal and 267 were non-fatal.A comparison of the clinical and laboratory characteristics was retrospectively conducted of the deceased and surviving individuals.Multivariate logistic regression and receiver operating characteristic curve analysis were performed to identify predictors of fatality.Results:Fatal patients exhibited significantly more comorbidities,particularly renal and cardiac comorbidities,and they were,in general,older than control individuals(P<0.0001).The results of logistic regression analysis showed that febrile duration of less than four days before arriving in the Emergency Department(OR=5.34;95%CI:1.39–20.6),episode of hypotension in the Emergency Department(OR=6.95;95%CI:2.40–20.1),and comorbidity with congestive heart failure(OR=11.26;95%CI:2.31–54.79)were all significantly associated with inpatient fatality due to DENV infection.The ROC curve analysis indicated that the final prognostic model yielded an area under the curve of 0.87(95%CI:0.79–0.97)for fatality.Conclusions:The aforementioned clinical findings may help clinicians predict fatality among adult inpatients with DENV infection.
文摘Objective Previous studies have shown that meteorological factors may increase COVID-19 mortality,likely due to the increased transmission of the virus.However,this could also be related to an increased infection fatality rate(IFR).We investigated the association between meteorological factors(temperature,humidity,solar irradiance,pressure,wind,precipitation,cloud coverage)and IFR across Spanish provinces(n=52)during the first wave of the pandemic(weeks 10–16 of 2020).Methods We estimated IFR as excess deaths(the gap between observed and expected deaths,considering COVID-19-unrelated deaths prevented by lockdown measures)divided by the number of infections(SARS-CoV-2 seropositive individuals plus excess deaths)and conducted Spearman correlations between meteorological factors and IFR across the provinces.Results We estimated 2,418,250 infections and 43,237 deaths.The IFR was 0.03%in<50-year-old,0.22%in 50–59-year-old,0.9%in 60–69-year-old,3.3%in 70–79-year-old,12.6%in 80–89-year-old,and26.5%in≥90-year-old.We did not find statistically significant relationships between meteorological factors and adjusted IFR.However,we found strong relationships between low temperature and unadjusted IFR,likely due to Spain’s colder provinces’aging population.Conclusion The association between meteorological factors and adjusted COVID-19 IFR is unclear.Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.
文摘Objective: To predict the daily incidence and fatality rates based on long short-term memory(LSTM) in 4 age groups of COVID-19 patients in Mazandaran Province, Iran.Methods: To predict the daily incidence and fatality rates by age groups, this epidemiological study was conducted based on the LSTM model. All data of COVID-19 disease were collected daily for training the LSTM model from February 22, 2020 to April 10, 2021 in the Mazandaran University of Medical Sciences. We defined 4 age groups, i.e., patients under 29, between 30 and 49, between 50 and 59, and over 60 years old. Then, LSTM models were applied to predict the trend of daily incidence and fatality rates from 14 to 40 days in different age groups. The results of different methods were compared with each other.Results: This study evaluated 5 0826 patients and 5 109 deaths with COVID-19 daily in 20 cities of Mazandaran Province. Among the patients, 25 240 were females(49.7%), and 25 586 were males(50.3%). The predicted daily incidence rates on April 11, 2021 were 91.76, 155.84, 150.03, and 325.99 per 100 000 people, respectively;for the fourteenth day April 24, 2021, the predicted daily incidence rates were 35.91, 92.90, 83.74, and 225.68 in each group per 100 000 people. Furthermore, the predicted average daily incidence rates in 40 days for the 4 age groups were 34.25, 95.68, 76.43, and 210.80 per 100 000 people, and the daily fatality rates were 8.38, 4.18, 3.40, 22.53 per 100 000 people according to the established LSTM model. The findings demonstrated the daily incidence and fatality rates of 417.16 and 38.49 per 100 000 people for all age groups over the next 40 days. Conclusions: The results highlighted the proper performance of the LSTM model for predicting the daily incidence and fatality rates. It can clarify the path of spread or decline of the COVID-19 outbreak and the priority of vaccination in age groups.
文摘Objective: Pedestrian safety is considered as one of the greatest concerns, especially for developing countries. In the year of 2015, about 48% pedestrian accidents with 56% fatalities occurred at mid-blocks in Beijing. Since the high frequency and fatality risk, this study focused on pedestrian accidents taking place at mid-blocks and aimed at identifying significant factors. Methods: Based on total 10,948 crash records, a binary logit model was established to explore the impact of various factors on the probability of pedestrian’s death. Furthermore, first-degree interaction effects were introduced into the basic model. The Hosmer-Lemeshow goodness-of-fit test was used to assess the model performance. Odds ratio was calculated for categorical variables to compare significant accident conditions with the conference level. Variables within consideration in this study included weather, area type, road type, speed limit, pedestrian location, lighting condition, vehicle type, pedestrian gender and pedestrian age. Results: The calibration results of the model show that the increased fatality chances of an accident at mid-blocks are associated with normal weather, rural area, two-way divided road, crossing elsewhere in carriageway, darkness (especially for no street lighting), light vehicle, large vehicle and male pedestrian. With road speed limit increasing by 10 km/h, the probability of death accordingly increases by 46%. Older victims have higher chances of being killed in a crash. Moreover, three interaction effects are found significant: rural area and two-way divided, rural area and crossing elsewhere as well as speed limit and pedestrian age. Conclusions: This study has analyzed police accident data and identified factors significant to the death probability of pedestrians in accidents occurred at mid-blocks. Recommendations and improving measures were proposed correspondingly. Behaviors of different road users at mid-blocks should be taken into account in the future research.
文摘<strong>Importance:</strong> Corona virus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pandemic claiming millions of lives since the first outbreak was reported in Wuhan, China during December 2019. It is thus important to make cross-country comparison of the relevant rates and understand the socio-demographic risk factors. <strong>Methods: </strong>This is a record based retrospective cohort study. <strong>Table 1</strong> was extracted from <a href="https://www.worldometers.info/coronavirus/" target="_blank">https://www.worldometers.info/coronavirus/</a> and from the Corona virus resource center (<strong>Table 2</strong>, <strong>Figures 1-3</strong>), Johns Hopkins University. Data for <strong>Table 1</strong> includes all countries which reported >1000 cases and <strong>Table 2</strong> includes 20 countries reporting the largest number of deaths. The estimation of CFR, RR and PR of the infection, and disease pattern across geographical clusters in the world is presented. <strong>Results:</strong> From <strong>Table 1</strong>, we could infer that as on 4<sup>th</sup> May 2020, COVID-19 has rapidly spread world-wide with total infections of 3,566,423 and mortality of 248,291. The maximum morbidity is in USA with 1,188,122 cases and 68,598 deaths (CFR 5.77%, RR 15% and PR 16.51%), while Spain is at the second position with 247,122 cases and 25,264 deaths (CFR 13.71%, RR 38.75%, PR 9.78%). <strong>Table 2</strong> depicts the scenario as on 8<sup>th</sup> October 2020, where-in the highest number of confirmed cases occurred in US followed by India and Brazil (cases per million population: 23,080, 5007 & 23,872 respectively). For deaths per million population: US recorded 647, while India and Brazil recorded 77 and 708 respectively. <strong>Conclusion:</strong> Studying the distribution of relevant rates across different geographical clusters plays a major role for measuring the disease burden, which in-turn enables implementation of appropriate public healthcare measures.
基金the research deputy of Jahrom University of Medical Sciences for financial support and confirmation of the project(Project identification code IR.JUMS.REC.1398.120)
文摘Coronavirus disease 2019 (COVID-19) has spread to 72 countries by the time of writing this report on 4th March 2020[1].On 20th February 2020,the first two confirmed deaths from COVID-19were reported in Iran.Till 4th March 2020,2 922 confirmed and92 death cases have also been reported till 4th March 2020 in Iran(Figure 1)[1].A key question that remains unanswered or controversial among the public,media,and researchers is the exact COVID-19 case fatality rate (CFR) in Iran.Why does the CFR in Iran appear to be higher compared to the rest of the world until now?Or why the fatality rate is high at the beginning of the epidemic in Iran?
文摘Background:During the course of an epidemic of a potentially fatal disease,it is difficult to accurately estimate the case fatality rate(CFR)because many calculation methods do not account for the delay between case confirmation and disease outcome.Taking the coronavirus disease-2019(COVID-19)as an example,this study aimed to develop a new method for CFR calculation while the pandemic was ongoing.Methods:We developed a new method for CFR calculation based on the following formula:number of deaths divided by the number of cases T days before,where T is the average delay between case confirmation and disease outcome.An objective law was found using simulated data that states if the hypothesized T is equal to the true T,the calculated real-time CFR remains constant;whereas if the hypothesized T is greater(or smaller)than the true T,the real-time CFR will gradually decrease(or increase)as the days progress until it approaches the true CFR.Results:Based on the discovered law,it was estimated that the true CFR of COVID-19 at the initial stage of the pandemic in China,excluding Hubei Province,was 0.8%;and in Hubei Province,it was 6.6%.The calculated CFRs predicted the death count with almost complete accuracy.Conclusions:The method could be used for the accurate calculation of the true CFR during a pandemic,instead of waiting until the end of the pandemic,whether the pandemic is under control or not.It could provide those involved in outbreak control a clear view of the timeliness of case confirmations.
基金This work was funded by the Public Health Agency of Canada.
文摘While surveillance can identify changes in COVID-19 transmission patterns over time and space,sections of the population at risk,and the efficacy of public health measures,reported cases of COVID-19 are generally understood to only capture a subset of the actual number of cases.Our primary objective was to estimate the percentage of cases reported in the general community,considered as those that occurred outside of long-term care facilities(LTCFs),in specific provinces and Canada as a whole.We applied a methodology using the delay-adjusted case fatality ratio(CFR)to all cases and deaths,as well as those representing the general community.Our second objective was to assess whether the assumed CFR(mean=1.38%)was appropriate for calculating underestimation of cases in Canada.Estimates were developed for the period from March 11th,2020 to September 16th,2020.Estimates of the percentage of cases reported(PrCR)and CFR varied spatially and temporally across Canada.For the majority of provinces,and for Canada as a whole,the PrCR increased through the early stages of the pandemic.The estimated PrCR in general community settings for all of Canada increased from 18.1%to 69.0%throughout the entire study period.Estimates were greater when considering only those data from outside of LTCFs.The estimated upper bound CFR in general community settings for all of Canada decreased from 9.07%on March 11th,2020 to 2.00%on September 16th,2020.Therefore,the true CFR in the general community in Canada was likely less than 2%on September 16th.According to our analysis,some provinces,such as Alberta,Manitoba,Newfoundland and Labrador,Nova Scotia,and Saskatchewan reported a greater percentage of cases as of September 16th,compared to British Columbia,Ontario,and Quebec.This could be due to differences in testing rates and criteria,demographics,socioeconomic factors,race,and access to healthcare among the provinces.Further investigation into these factors could reveal differences among provinces that could partially explain the variation in estimates of PrCR and CFR identified in our study.The estimates provide context to the summative state of the pandemic in Canada,and can be improved as knowledge of COVID-19 reporting rates and disease characteristics are advanced.
文摘Background:Early severity estimates of coronavirus disease 2019(COVID-19)are critically needed to assess the potential impact of the on going pandemic in differe nt demographic groups.Here we estimate the real-time delayadjusted case fatality rate across nine age groups by gender in Chile,the country with the highest testing rate for COVID-19 in Latin America.Methods:We used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31,2020.We used a robust likelihood function and a delay distribution to estimate real-time delay-adjusted case-fatality risk and estimate model parameters using a Monte Carlo Markov Chain in a Bayesian framework.
文摘The case fatality ratio(CFR)is one of the key measurements to evaluate the clinical severity of infectious diseases.The CFR may vary due to change in factors that affect the mortality risk.In this study,we developed a simple likelihood-based framework to estimate the instantaneous CFR of infectious diseases.We used the publicly available COVID-19 surveillance data in Canada for demonstration.We estimated the mean fatality ratio of reported COVID-19 cases(rCFR)in Canada was estimated at 6.9%(95%CI:4.5e10.6).We emphasize the extensive implementation of the constructed instantaneous CFR that is to identify the key determinants affecting the mortality risk.
文摘BACKGROUND Most species of aconite contain highly toxic aconitines,the oral ingestion of which can be fatal,primarily because they cause ventricular arrhythmias.We describe a case of severe aconite poisoning that was successfully treated through venoarterial extracorporeal membrane oxygenation(VA-ECMO)and in which detailed toxicological analyses of the aconite roots and biological samples were performed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).CASE SUMMARY A 23-year-old male presented to the emergency room with circulatory collapse and ventricular arrhythmia after ingesting approximately half of a root labeled,“Aconitum japonicum Thunb”.Two hours after arrival,VA-ECMO was initiated as circulatory collapse became refractory to antiarrhythmics and vasopressors.Nine hours after arrival,an electrocardiogram revealed a return to sinus rhythm.The patient was weaned off VA-ECMO and the ventilator on hospital days 3 and 5,respectively.On hospital day 15,he was transferred to a psychiatric hospital.The other half of the root and his biological samples were toxicologically analyzed using LC-MS/MS,revealing 244.3 mg/kg of aconitine and 24.7 mg/kg of mesaconitine in the root.Serum on admission contained 1.50 ng/mL of aconitine.Beyond hospital day 2,neither were detected.Urine on admission showed 149.09 ng/mL of aconitine and 3.59 ng/mL of mesaconitine,but these rapidly decreased after hospital day 3.CONCLUSION The key to saving the life of a patient with severe aconite poisoning is to introduce VA-ECMO as soon as possible.
基金This study was supported by the National Natural Science Foundation of China(82041021 and 42041001)the Bill&Melinda Gates Foundation(INV-006371)the General Program of the State Key Laboratory of Infectious Disease Prevention and Control of China(2020SKLID201).
文摘The evidence for the effects of environmental factors on COVID-19 case fatality remains controversial,and it is crucial to understand the role of preventable environmental factors in driving COVID-19 fatality.We thus conducted a nationwide cohort study to estimate the effects of environmental factors(temperature,particulate matter[PM2.5,PM10],sulfur dioxide[SO2],nitrogen dioxide[NO2],and ozone[O3])on COVID-19 case fatality.A total of 71,808 confirmed COVID-19 cases were identified and followed up for their vital status through April 25,2020.Exposures to ambient air pollution and temperature were estimated by linking the city-and county-level monitoring data to the residential community of each participant.For each participant,two windows were defined:the period from symptom onset to diagnosis(exposure window I)and the period from diagnosis date to date of death/recovery or end of the study period(exposure window II).Cox proportional hazards models were used to estimate the associations between these environmental factors and COVID-19 case fatality.COVID-19 case fatality increased in association with environmental factors for the two exposure windows.For example,each 10 mg/m^(3) increase in PM2.5,PM10,O3,and NO2 in window I was associated with a hazard ratio of 1.11(95%CI 1.09,1.13),1.10(95%CI 1.08,1.13),1.09(95 CI 1.03,1.14),and 1.27(95%CI 1.19,1.35)for COVID-19 fatality,respectively.A significant effect was also observed for low temperature,with a hazard ratio of 1.03(95%CI 1.01,1.04)for COVID-19 case fatality per 1C decrease.Subgroup analysis indicated that these effects were stronger in the elderly,as well as in those with mild symptoms and living in Wuhan or Hubei.Overall,the sensitivity analyses also yielded consistent estimates.Short-term exposure to ambient air pollution and low temperature during the illness would play a nonnegligible part in causing case fatality due to COVID-19.Reduced exposures to high concentrations of PM2.5,PM10,O3,SO2,and NO2 and low temperature would help improve the prognosis and reduce public health burden.
文摘Introduction: Data on mortality in acute kidney injury (AKI) derives from high-income countries where AKI is hospital-acquired and occurs in elderly patients with a high burden of cardiovascular disease. In sub-Saharan Africa (SSA), AKI is community-acquired occurring in healthy young adults. We aimed to identify predictors of fatal outcomes in patients with AKI in two tertiary hospitals in Cameroon. Methods: Medical records of adults with confirmed AKI, from January 2018 to March 2020 were retrieved. The outcomes of interest were in-hospital deaths and presumed causes of death. We used multiple logistic regressions modeling to identify predictors of death. The study was approved by the ethics boards of both hospitals. Values were considered significant for a p-value of 0.05. Results: We included 285 patient records (37.2% females). The mean (SD) age was 50.1 (19.0) years. Hypertension (n = 97, 34.0%), organ failure (n = 88, 30.9%), and diabetes (n = 60, 21.1%) were the main comorbidities. The majority of patients had community-acquired AKI (78.6%, n = 224), were KDIGO stage 3 (88.8%, n = 253), and needed dialysis (52.6%, n = 150). Up to 16.7% (n = 25) did not receive what was needed. The in-hospital mortality rate was 29.1% (n = 83). Lack of access to dialysis (OR = 27.8;CI: 5.2 - 149.3, p = 0.001), hypotension (OR = 11.8;CI: 1.3 - 24.8;p = 0.001) and ICU admission (OR = 5.7;CI: 1.3 - 24.8, p = 0.001) were predictors of mortality. The presence of co-morbidities or underlying diseases (n = 46, 55%) were the main causes of death. Conclusions: In-hospital AKI mortality is high, as in other low- and middle-income economies. Lack of access to dialysis and the severity of the underlying illness are major predictors of death.
