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Background: Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus, we developed a unique ARC prediction model for a Japanese mixed intensive care unit (ICU) population and compared it with existing models. Methods: This retrospective study enrolled a mixed ICU population in Japan from January 2019 and June 2022. The primary outcome was the development and validation of a model to predict ARC onset based on baseline information at ICU admission. Patients admitted until May 2021 were included in the training set, and external validation was performed on patients admitted thereafter. A multivariate logistic regression model was used to develop an integer-based predictive scoring system for ARC. The new model (the JPNARC score) was externally validated along with the ARC and Augmented Renal Clearance in Trauma Intensive Care (ARCTIC) scores. Results: A total of 2,592 critically ill patients were enrolled initially, with 651 patients finally included after excluding 1,941 patients. The training and validation datasets comprised 456 and 195 patients, respectively. Multivariate analysis was performed to develop the JPNARC score, which incorporated age, sex, serum creatinine, and diagnosis upon ICU admission (trauma or central nervous system disease). The JPNARC score had a larger area under the receiver operating characteristic curve than the ARC and ARCTIC scores in the validation dataset (0.832, 0.633, and 0.740, respectively). Conclusions: An integer-based scoring system was developed to predict ARC onset in a critically ill Japanese population and showed high predictive performance. New models designed to predict the often-unrecognized ARC phenomenon may aid in the decision-making process for upward drug dosage modifications, especially in resource- and labor-limited settings. [ABSTRACT FROM AUTHOR]

Background: The incidence of esophageal adenocarcinoma has recently increased in Asia, including Japan. A system to identify individuals at high risk for Barrett's esophagus (BE), a pre-cancerous condition of esophageal adenocarcinoma, among the general population is needed to perform endoscopic surveillance appropriately. We therefore developed risk prediction scores for BE at health checkups in Japan. Methods: 4128 consecutive health checkup examinees were retrospectively enrolled from October 2021 to March 2022. A prediction score for BE was developed based on the linear transformation of β-regression coefficients in a multivariable regression model incorporating BE predictors. Internal validation was performed by evaluating discrimination and calibration of the prediction model. Results: Three prediction scores corresponding to BE based on its length were developed: all lengths, ≥ 1 cm, ≥ 2 cm. All scores were internally validated, and the model calibration was excellent. The performance of the prediction models was better for longer BE, with a c-statistic of 0.70 for BE ≥ 2 cm, than for shorter values. The prediction score for BE ≥ 2 cm yielded sensitivity and specificity of 52.9% and 78.6% in high-risk subjects and 91.2% and 29.3% in intermediate- or high-risk subjects, respectively. Conclusions: This prediction score can potentially increase the endoscopic detection of BE by identifying potentially high-risk individuals from the general population. This is the first report on developing a prediction score for BE that may suit the Japanese population. [ABSTRACT FROM AUTHOR]

Background: Juvenile strokes (< 55 years) account for about 15% of all ischemic strokes. Structured data on clinical outcome in those patients are sparse. Here, we aimed to fill this gap by systematically collecting relevant data and modeling a juvenile stroke prediction score for the 3-month functional outcome. Methods: We retrospectively integrated and analyzed clinical and outcome data of juvenile stroke and TIA patients treated at the LMU University Hospital, LMU Munich, Munich. Good outcome was defined as a modified Rankin Scale of 0–2 or return to baseline of function. We analyzed candidate predictors and developed a predictive model. Predictive abilities were inspected using Area Under the ROC curve (AUROC) and visual representation of the calibration. The model was validated internally. Results: 346 patients were included in the analysis. We observed a good outcome in n = 293 patients (84.7%). The prediction model for an unfavourable outcome had an AUROC of 89.1% (95% CI 83.3–93.1%). The model includes age NIHSS, ASPECTS, blood glucose and type of vessel occlusion as predictors for the individual patient outcome. Conclusions: Here, we introduce the highly accurate PREDICT-score for the 3-month outcome after juvenile stroke derived from clinical routine data. The PREDICT-score might be helpful in guiding individual patient decisions and designing future studies but needs further prospective validation which is already planned. Trial registration The study has been registered at https://drks.de (DRKS00024407) on March 31, 2022. [ABSTRACT FROM AUTHOR]

Abstract Background Augmented renal clearance (ARC) decreases the therapeutic concentration of drugs excreted by the kidneys in critically ill patients. Several ARC prediction models have been developed and validated; however, their usefulness in Japan has not been comprehensively investigated. Thus, we developed a unique ARC prediction model for a Japanese mixed intensive care unit (ICU) population and compared it with existing models. Methods This retrospective study enrolled a mixed ICU population in Japan from January 2019 and June 2022. The primary outcome was the development and validation of a model to predict ARC onset based on baseline information at ICU admission. Patients admitted until May 2021 were included in the training set, and external validation was performed on patients admitted thereafter. A multivariate logistic regression model was used to develop an integer-based predictive scoring system for ARC. The new model (the JPNARC score) was externally validated along with the ARC and Augmented Renal Clearance in Trauma Intensive Care (ARCTIC) scores. Results A total of 2,592 critically ill patients were enrolled initially, with 651 patients finally included after excluding 1,941 patients. The training and validation datasets comprised 456 and 195 patients, respectively. Multivariate analysis was performed to develop the JPNARC score, which incorporated age, sex, serum creatinine, and diagnosis upon ICU admission (trauma or central nervous system disease). The JPNARC score had a larger area under the receiver operating characteristic curve than the ARC and ARCTIC scores in the validation dataset (0.832, 0.633, and 0.740, respectively). Conclusions An integer-based scoring system was developed to predict ARC onset in a critically ill Japanese population and showed high predictive performance. New models designed to predict the often-unrecognized ARC phenomenon may aid in the decision-making process for upward drug dosage modifications, especially in resource- and labor-limited settings.

Abstract Background Sepsis is a leading cause of death and serious illness that requires early recognition and therapeutic management to improve survival. The quick-SOFA score helps in its recognition, but its diagnostic performance is insufficient. To develop a score that can rapidly identify a community acquired septic situation at risk of clinical complications in patients consulting the emergency department (ED). Methods We conducted a monocentric, prospective cohort study in the emergency department of a university hospital between March 2016 and August 2018 (NCT03280992). All patients admitted to the emergency department for a suspicion of a community-acquired infection were included. Predictor variables of progression to septic shock or death within the first 90 days were selected using backward stepwise multivariable logistic regression to develop a clinical score. Receiver operating characteristic (ROC) curves were constructed to determine the discriminating power of the area under the curve (AUC). We also determined the threshold of our score that optimized the performance required for a sepsis-worsening score. We have compared our score with the NEWS-2 and qSOFA scores. Results Among the 21,826 patients admitted to the ED, 796 patients were suspected of having community-acquired infection and 461 met the sepsis criteria; therefore, these patients were included in the analysis. The median [interquartile range] age was 72 [54–84] years, 248 (54%) were males, and 244 (53%) had respiratory symptoms. The clinical score ranged from 0 to 90 and included 8 variables with an area under the ROC curve of 0.85 (confidence interval [CI] 95% 0.81–0.89). A cut-off of 26 yields a sensitivity of 88% (CI 95% 0.79–0.93), a specificity of 62% (CI 95% 57–67), and a negative predictive value of 95% (CI 95% 91–97). The area under the ROC curve for our score was 0.85 (95% CI, 0.81–0.89) versus 0.73 (95% CI, 0.68–0.78) for qSOFA and 0.66 (95% CI, 0.60–0.72) for NEWS-2. Conclusions Our study provides an accurate clinical score for identifying septic patients consulting the ED early at risk of worsening disease. This score could be implemented at admission.

Background: Sepsis is a leading cause of death and serious illness that requires early recognition and therapeutic management to improve survival. The quick-SOFA score helps in its recognition, but its diagnostic performance is insufficient. To develop a score that can rapidly identify a community acquired septic situation at risk of clinical complications in patients consulting the emergency department (ED). Methods: We conducted a monocentric, prospective cohort study in the emergency department of a university hospital between March 2016 and August 2018 (NCT03280992). All patients admitted to the emergency department for a suspicion of a community-acquired infection were included. Predictor variables of progression to septic shock or death within the first 90 days were selected using backward stepwise multivariable logistic regression to develop a clinical score. Receiver operating characteristic (ROC) curves were constructed to determine the discriminating power of the area under the curve (AUC). We also determined the threshold of our score that optimized the performance required for a sepsis-worsening score. We have compared our score with the NEWS-2 and qSOFA scores. Results: Among the 21,826 patients admitted to the ED, 796 patients were suspected of having community-acquired infection and 461 met the sepsis criteria; therefore, these patients were included in the analysis. The median [interquartile range] age was 72 [54–84] years, 248 (54%) were males, and 244 (53%) had respiratory symptoms. The clinical score ranged from 0 to 90 and included 8 variables with an area under the ROC curve of 0.85 (confidence interval [CI] 95% 0.81–0.89). A cut-off of 26 yields a sensitivity of 88% (CI 95% 0.79–0.93), a specificity of 62% (CI 95% 57–67), and a negative predictive value of 95% (CI 95% 91–97). The area under the ROC curve for our score was 0.85 (95% CI, 0.81–0.89) versus 0.73 (95% CI, 0.68–0.78) for qSOFA and 0.66 (95% CI, 0.60–0.72) for NEWS-2. Conclusions: Our study provides an accurate clinical score for identifying septic patients consulting the ED early at risk of worsening disease. This score could be implemented at admission. [ABSTRACT FROM AUTHOR]

Despite the effectiveness of the retrograde approach for chronic total occlusion (CTO) lesions, there are no standardized tools to predict the success of retrograde percutaneous coronary intervention (PCI). The aim of this study was to develop a prediction tool to identify CTO lesions that will achieve successful retrograde PCI. This study evaluated data from 2,374 patients who underwent primary retrograde CTO-PCI and were enrolled in the Japanese CTO-PCI Expert Registry between January 2016 and December 2022 (NCT01889459). All observations were randomly assigned to the derivation and validation cohorts at a 2:1 ratio. The prediction score for guidewire failure in retrograde CTO-PCI was determined by assigning 1 point for each factor and summing all accrued points. The JR-CTO score (moderate–severe calcification, tortuosity, Werner collateral connection grade ≤1, and nonseptal collateral channel) demonstrated a C-statistic for guidewire failure of 0.72 (95% CI: 0.67-0.76) and 0.71 (95% CI: 0.64-0.77) in the derivation and validation cohorts, respectively. Patients with lower scores had higher guidewire and technical success rates and decreased guidewire crossing time and procedural time (P < 0.01). The JR-CTO (Japanese Retrograde Chronic Total Occlusion) score, a simple 4-item score that predicts successful guidewire crossing in patients undergoing retrograde CTO-PCI, has the potential to support clinical decision-making for the retrograde approach. [Display omitted] [ABSTRACT FROM AUTHOR]

Aim: We aimed to develop a risk score to calculate a person's individual risk for a severe COVID-19 course (POINTED score) to support prioritization of especially vulnerable patients for a (booster) vaccination. Subject and methods: This cohort study was based on German claims data and included 623,363 individuals with a COVID-19 diagnosis in 2020. The outcome was COVID-19 related treatment in an intensive care unit, mechanical ventilation, or death after a COVID-19 infection. Data were split into a training and a test sample. Poisson regression models with robust standard errors including 35 predefined risk factors were calculated. Coefficients were rescaled with a min–max normalization to derive numeric score values between 0 and 20 for each risk factor. The scores' discriminatory ability was evaluated by calculating the area under the curve (AUC). Results: Besides age, down syndrome and hematologic cancer with therapy, immunosuppressive therapy, and other neurological conditions were the risk factors with the highest risk for a severe COVID-19 course. The AUC of the POINTED score was 0.889, indicating very good predictive validity. Conclusion: The POINTED score is a valid tool to calculate a person's risk for a severe COVID-19 course. [ABSTRACT FROM AUTHOR]

Background: A previous study has shown that the lactate/albumin*age (LAA) score is useful for predicting mortality in patients with sepsis admitted to the ICU. We aimed to evaluate the clinical significance of the LAA score in patients with sepsis who presented to the emergency department (ED) Methods: This retrospective observational study used data from the Korean Shock Society Registry collected between January 2017 and December 2021. The prognostic performance of the LAA score for predicting the 28-day mortality was evaluated. Lactate and albumin levels were measured immediately after arrival to the ED. Results: Of the 5346 patients with sepsis, data from 3240 were analyzed. The area under the receiver operating characteristic curve (AUROC) of the LAA score (0.737, 95 % confidence interval (CI) 0.716–0.757), was higher than that of lactate (0.699, 95 % CI 0.677–0.720, p

Abstract Background Cellulitis is defined as a bacterial infection of the skin and subcutaneous tissue that can cause multiple complications, such as sepsis and necrotizing fasciitis. In extreme cases, it may lead to multiorgan failure and death. We sought to analyze the clinical factors that contribute to the development of complicated disease, including demographics, clinical presentation, initial vital signs, and laboratory studies. Methods Our study is a retrospective cohort study carried out in a university-based tertiary care hospital in Bangkok, Thailand. Adult patients who presented with cellulitis from January 1, 2018, to December 31, 2022, were evaluated for eligibility and inclusion in this study. All related variables for both outcomes, bacteremia and necrotizing fasciitis, were gathered from electronic medical records and analyzed using multivariable logistic regression analysis. Results Of the 1,560 visits to this hospital, 47 cases reported at least one complication, with bacteremia noted in 27 visits (1.73%) and necrotizing fasciitis in 20 visits (1.27%). From the multivariable logistic regression analysis, six variables emerge as predictors of cellulitis complications. These are: Age ≥ 65 years, Body Mass Index ≥ 30 kg/m2, diabetes mellitus, body temperature ≥ 38 °C, systolic blood pressure ≤ 100 mmHg, and involvement of lower extremities. The predictive score was developed from these factors and was named the Ramathibodi Necrotizing Fasciitis/Bacteremia (RAMA-NFB) Prediction Score. Our predictive score has an accuracy of 82.93% (95% CI, 0.77–0.89). Patients in the high-risk group (RAMA NFB score > 6) have a likelihood ratio of 8.75 (95% CI, 4.41–18.12; p

Abstract Background Most sepsis patients could potentially experience advantageous outcomes from targeted medical intervention, such as fluid resuscitation, antibiotic administration, respiratory support, and nursing care, promptly upon arrival at the emergency department (ED). Several scoring systems have been devised to predict hospital outcomes in sepsis patients, including the Sequential Organ Failure Assessment (SOFA) score. In contrast to prior research, our study introduces the novel approach of utilizing the National Early Warning Score 2 (NEWS2) as a means of assessing treatment efficacy and disease progression during an ED stay for sepsis. Objectives To evaluate the sepsis prognosis and effectiveness of treatment administered during ED admission in reducing overall hospital mortality rates resulting from sepsis, as measured by the NEWS2. Methods The present investigation was conducted at a medical center from 1997 to 2020. The NEWS2 was calculated for patients with sepsis who were admitted to the ED in a consecutive manner. The computation was based on the initial and final parameters that were obtained during their stay in the ED. The alteration in the NEWS2 from the initial to the final measurements was utilized to evaluate the benefit of ED management to the hospital outcome of sepsis. Univariate and multivariate Cox regression analyses were performed, encompassing all clinically significant variables, to evaluate the adjusted hazard ratio (HR) for total hospital mortality in sepsis patients with reduced severity, measured by NEWS2 score difference, with a 95% confidence interval (adjusted HR with 95% CI). The study employed Kaplan-Meier analysis with a Log-rank test to assess variations in overall hospital mortality rates between two groups: the “improvement (reduced NEWS2)” and “non-improvement (no change or increased NEWS2)” groups. Results The present investigation recruited a cohort of 11,011 individuals who experienced the first occurrence of sepsis as the primary diagnosis while hospitalized. The mean age of the improvement and non-improvement groups were 69.57 (± 16.19) and 68.82 (± 16.63) years, respectively. The mean SOFA score of the improvement and non-improvement groups were of no remarkable difference, 9.7 (± 3.39) and 9.8 (± 3.38) years, respectively. The total hospital mortality for sepsis was 42.92% (4,727/11,011). Following treatment by the prevailing guidelines at that time, a total of 5,598 out of 11,011 patients (50.88%) demonstrated improvement in the NEWS2, while the remaining 5,403 patients (49.12%) did not. The improvement group had a total hospital mortality rate of 38.51%, while the non-improvement group had a higher rate of 47.58%. The non-improvement group exhibited a lower prevalence of comorbidities such as congestive heart failure, cerebral vascular disease, and renal disease. The non-improvement group exhibited a lower Charlson comorbidity index score [4.73 (± 3.34)] compared to the improvement group [4.82 (± 3.38)] The group that underwent improvement exhibited a comparatively lower incidence of septic shock development in contrast to the non-improvement group (51.13% versus 54.34%, P

Abstract Background Bloodstream infections (BSI) are highly prevalent in hospitalized patients requiring intensive care. They are among the most serious infections and are highly associated with sepsis or septic shock, which can lead to prolonged hospital stays and high healthcare costs. This study aimed at establishing an easy-to-use nomogram for predicting the prognosis of patients with BSI. Methods In retrospective study, records of patients with BSI admitted to the intensive care unit (ICU) over the period from Jan 1st 2016 to Dec 31st 2021 were included. We used data from two different China hospitals as development cohort and validation cohort respectively. The demographic and clinical data of patients were collected. Based on all baseline data, k-means algorithm was applied to discover the groups of BSI phenotypes with different prognostic outcomes, which was confirmed by Kaplan-Meier analysis and compared using log-rank tests. Univariate Cox regression analyses were used to estimate the risk of clusters. Random forest was used to identified discriminative predictors in clusters, which were utilized to construct nomogram based on multivariable logistic regression in the discovery cohort. For easy clinical applications, we developed a bloodstream infections clustering (BSIC) score according to the nomogram. The results were validated in the validation cohort over a similar period. Results A total of 360 patients in the discovery cohort and 310 patients in the validation cohort were included in statistical analyses. Based on baseline variables, two distinct clusters with differing prognostic outcomes were identified in the discovery cohort. Population in cluster 1 was 211 with a ICU mortality of 17.1%, while population in cluster 2 was 149 with an ICU mortality of 41.6% (p

Background: Cellulitis is defined as a bacterial infection of the skin and subcutaneous tissue that can cause multiple complications, such as sepsis and necrotizing fasciitis. In extreme cases, it may lead to multiorgan failure and death. We sought to analyze the clinical factors that contribute to the development of complicated disease, including demographics, clinical presentation, initial vital signs, and laboratory studies. Methods: Our study is a retrospective cohort study carried out in a university-based tertiary care hospital in Bangkok, Thailand. Adult patients who presented with cellulitis from January 1, 2018, to December 31, 2022, were evaluated for eligibility and inclusion in this study. All related variables for both outcomes, bacteremia and necrotizing fasciitis, were gathered from electronic medical records and analyzed using multivariable logistic regression analysis. Results: Of the 1,560 visits to this hospital, 47 cases reported at least one complication, with bacteremia noted in 27 visits (1.73%) and necrotizing fasciitis in 20 visits (1.27%). From the multivariable logistic regression analysis, six variables emerge as predictors of cellulitis complications. These are: Age ≥ 65 years, Body Mass Index ≥ 30 kg/m2, diabetes mellitus, body temperature ≥ 38 °C, systolic blood pressure ≤ 100 mmHg, and involvement of lower extremities. The predictive score was developed from these factors and was named the Ramathibodi Necrotizing Fasciitis/Bacteremia (RAMA-NFB) Prediction Score. Our predictive score has an accuracy of 82.93% (95% CI, 0.77–0.89). Patients in the high-risk group (RAMA NFB score > 6) have a likelihood ratio of 8.75 (95% CI, 4.41–18.12; p < 0.001) times to develop complications of cellulitis. Conclusion: In our study, the RAMA-NFB Prediction Score predicts complications of necrotizing fasciitis and bacteremia in adult patients who present with cellulitis. External validation of this predictive score is still needed for further practical application. [ABSTRACT FROM AUTHOR]

Background: Most sepsis patients could potentially experience advantageous outcomes from targeted medical intervention, such as fluid resuscitation, antibiotic administration, respiratory support, and nursing care, promptly upon arrival at the emergency department (ED). Several scoring systems have been devised to predict hospital outcomes in sepsis patients, including the Sequential Organ Failure Assessment (SOFA) score. In contrast to prior research, our study introduces the novel approach of utilizing the National Early Warning Score 2 (NEWS2) as a means of assessing treatment efficacy and disease progression during an ED stay for sepsis. Objectives: To evaluate the sepsis prognosis and effectiveness of treatment administered during ED admission in reducing overall hospital mortality rates resulting from sepsis, as measured by the NEWS2. Methods: The present investigation was conducted at a medical center from 1997 to 2020. The NEWS2 was calculated for patients with sepsis who were admitted to the ED in a consecutive manner. The computation was based on the initial and final parameters that were obtained during their stay in the ED. The alteration in the NEWS2 from the initial to the final measurements was utilized to evaluate the benefit of ED management to the hospital outcome of sepsis. Univariate and multivariate Cox regression analyses were performed, encompassing all clinically significant variables, to evaluate the adjusted hazard ratio (HR) for total hospital mortality in sepsis patients with reduced severity, measured by NEWS2 score difference, with a 95% confidence interval (adjusted HR with 95% CI). The study employed Kaplan-Meier analysis with a Log-rank test to assess variations in overall hospital mortality rates between two groups: the "improvement (reduced NEWS2)" and "non-improvement (no change or increased NEWS2)" groups. Results: The present investigation recruited a cohort of 11,011 individuals who experienced the first occurrence of sepsis as the primary diagnosis while hospitalized. The mean age of the improvement and non-improvement groups were 69.57 (± 16.19) and 68.82 (± 16.63) years, respectively. The mean SOFA score of the improvement and non-improvement groups were of no remarkable difference, 9.7 (± 3.39) and 9.8 (± 3.38) years, respectively. The total hospital mortality for sepsis was 42.92% (4,727/11,011). Following treatment by the prevailing guidelines at that time, a total of 5,598 out of 11,011 patients (50.88%) demonstrated improvement in the NEWS2, while the remaining 5,403 patients (49.12%) did not. The improvement group had a total hospital mortality rate of 38.51%, while the non-improvement group had a higher rate of 47.58%. The non-improvement group exhibited a lower prevalence of comorbidities such as congestive heart failure, cerebral vascular disease, and renal disease. The non-improvement group exhibited a lower Charlson comorbidity index score [4.73 (± 3.34)] compared to the improvement group [4.82 (± 3.38)] The group that underwent improvement exhibited a comparatively lower incidence of septic shock development in contrast to the non-improvement group (51.13% versus 54.34%, P < 0.001). The improvement group saw a total of 2,150 patients, which represents 38.41% of the overall sample size of 5,598, transition from the higher-risk to the medium-risk category. A total of 2,741 individuals, representing 48.96% of the sample size of 5,598 patients, exhibited a reduction in severity score only without risk category alteration. Out of the 5,403 patients (the non-improvement group) included in the study, 78.57% (4,245) demonstrated no alteration in the NEWS2. Conversely, 21.43% (1,158) of patients exhibited an escalation in severity score. The Cox regression analysis demonstrated that the implementation of interventions aimed at reducing the NEWS2 during a patient's stay in the ED had a significant positive impact on the outcome, as evidenced by the adjusted HRs of 0.889 (95% CI = 0.808, 0.978) and 0.891 (95% CI = 0.810, 0.981), respectively. The results obtained from the Kaplan-Meier analysis indicated that the survival rate of the improvement group was significantly higher than that of the non-improvement group (P < 0.001) in the hospitalization period. Conclusion: The present study demonstrated that 50.88% of sepsis patients obtained improvement in ED, ascertained by means of the NEWS2 scoring system. The practical dynamics of NEWS2 could be utilized to depict such intricacies clearly. The findings also literally supported the importance of ED management in the comprehensive course of sepsis treatment in reducing the total hospital mortality rate. [ABSTRACT FROM AUTHOR]

Background: Bloodstream infections (BSI) are highly prevalent in hospitalized patients requiring intensive care. They are among the most serious infections and are highly associated with sepsis or septic shock, which can lead to prolonged hospital stays and high healthcare costs. This study aimed at establishing an easy-to-use nomogram for predicting the prognosis of patients with BSI. Methods: In retrospective study, records of patients with BSI admitted to the intensive care unit (ICU) over the period from Jan 1st 2016 to Dec 31st 2021 were included. We used data from two different China hospitals as development cohort and validation cohort respectively. The demographic and clinical data of patients were collected. Based on all baseline data, k-means algorithm was applied to discover the groups of BSI phenotypes with different prognostic outcomes, which was confirmed by Kaplan-Meier analysis and compared using log-rank tests. Univariate Cox regression analyses were used to estimate the risk of clusters. Random forest was used to identified discriminative predictors in clusters, which were utilized to construct nomogram based on multivariable logistic regression in the discovery cohort. For easy clinical applications, we developed a bloodstream infections clustering (BSIC) score according to the nomogram. The results were validated in the validation cohort over a similar period. Results: A total of 360 patients in the discovery cohort and 310 patients in the validation cohort were included in statistical analyses. Based on baseline variables, two distinct clusters with differing prognostic outcomes were identified in the discovery cohort. Population in cluster 1 was 211 with a ICU mortality of 17.1%, while population in cluster 2 was 149 with an ICU mortality of 41.6% (p < 0.001). The survival analysis also revealed a higher risk of death for cluster 2 when compared with cluster 1 (hazard ratio: 2.31 [95% CI, 1.53 to 3.51], p < 0.001), which was confirmed in validation cohort. Four independent predictors (vasoconstrictor use before BSI, mechanical ventilation (MV) before BSI, Deep vein catheterization (DVC) before BSI, and antibiotic use before BSI) were identified and used to develop a nomogram. The nomogram and BSIC score showed good discrimination with AUC of 0.96. Conclusion: The developed score has potential applications in the identification of high-risk critically ill BSI patients. [ABSTRACT FROM AUTHOR]

Introduction: Sepsis is a significant and common cause of death and burden among critically ill patients, which has increasing incidence and mortality in adults over 60 and advanced age. This study aimed to develop an easy-to-use clinical tool for assessing 28-day mortality risk in older sepsis patients upon their initial assessment in the emergency department (ED). Method: A retrospective cohort study was conducted using electronic medical records of older (≥60 years) ED patients with suspected sepsis from August 1, 2018, to December 31, 2018. A new prediction score was formulated based on the logistic coefficients of clinical predictors through multivariable regression analyses. Then, the score's screening performance was evaluated and compared to existing scoring systems; Systemic Inflammatory Response Syndrome (SIRS), quick Sequential Organ Failure Assessment (qSOFA), National early warning score (NEWS), and The Ramathibodi early warning score (REWS); using receiver operating characteristic curve analysis (AuROC). Result: The study included 599 patients with the mean age of 77.13 (range: 60-101) years (56.43% male) and an overall 28-day mortality rate of 7.01%. The newly developed prediction score had seven independent predictors of 28-day mortality: malignancy, dependent status, heart rate, respiratory rate, oxygen saturation, consciousness, and lactate, which demonstrated excellent discriminative ability (AuROC: 0.87, 95% confidence interval (CI): 0.82 - 0.92), significantly outperforming SIRS (AuROC: 0.62), qSOFA (AuROC: 0.72), NEWS (AuROC: 0.74), and REWS (AuROC: 0.71), all with p-values

SARS-CoV-2 respiratory infection is associated with significant morbidity and mortality in hospitalized patients. We aimed to assess the risk factors for hospital mortality in non-vaccinated patients during the 2021 spring wave in the Czech Republic. A total of 991 patients hospitalized between January 2021 and March 2021 with a PCR-confirmed SARS-CoV-2 acute respiratory infection in two university hospitals and five rural hospitals were included in this analysis. After excluding patients with unknown outcomes, 790 patients entered the final analyses. Out of 790 patients included in the analysis, 282/790 (35.7%) patients died in the hospital; 162/790 (20.5) were male and 120/790 (15.2%) were female. There were 141/790 (18%) patients with mild, 461/790 (58.3%) with moderate, and 187/790 (23.7%) with severe courses of the disease based mainly on the oxygenation status. The best-performing multivariate regression model contains only two predictors—age and the patient’s state; both predictors were rendered significant (p < 0.0001). Both age and disease state are very significant predictors of hospital mortality. An increase in age by 10 years raises the risk of hospital mortality by a factor of 2.5, and a unit increase in the oxygenation status raises the risk of hospital mortality by a factor of 20.

Incisional hernia (IH) manifests in 10%–15% of abdominal surgeries and patients at elevated risk of this complication should be identified for prophylactic intervention. This study aimed to externally validate the Penn hernia risk calculator. The Ramathibodi abdominal surgery cohort was constructed by linking relevant hospital databases from 2010 to 2021. Penn hernia risk scores were calculated according to the original model which was externally validated using a seven-step approach. An updated model which included four additional predictor variables (i.e., age, immunosuppressive medication, ostomy reversal, and transfusion) added to those of the three original predictors (i.e., body mass index, chronic liver disease, and open surgery) was also evaluated. The area under the receiver operating characteristic curve (AUC) was estimated, and calibration performance was compared using the Hosmer–Lemeshow goodness-of-fit method for the observed/expected (O/E) ratio. A total of 12,155 abdominal operations were assessed. The original Penn model yielded fair discrimination with an AUC (95% confidence interval (CI)) of 0.645 (0.607, 0.683). The updated model that included the additional predictor variables achieved an acceptable AUC (95% CI) of 0.733 (0.698, 0.768) with the O/E ratio of 0.968 (0.848, 1.088). The updated model achieved improved discrimination and calibration performance, and should be considered for the identification of high-risk patients for further hernia prevention strategy. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 respiratory infection is associated with significant morbidity and mortality in hospitalized patients. We aimed to assess the risk factors for hospital mortality in non-vaccinated patients during the 2021 spring wave in the Czech Republic. A total of 991 patients hospitalized between January 2021 and March 2021 with a PCR-confirmed SARS-CoV-2 acute respiratory infection in two university hospitals and five rural hospitals were included in this analysis. After excluding patients with unknown outcomes, 790 patients entered the final analyses. Out of 790 patients included in the analysis, 282/790 (35.7%) patients died in the hospital; 162/790 (20.5) were male and 120/790 (15.2%) were female. There were 141/790 (18%) patients with mild, 461/790 (58.3%) with moderate, and 187/790 (23.7%) with severe courses of the disease based mainly on the oxygenation status. The best-performing multivariate regression model contains only two predictors—age and the patient's state; both predictors were rendered significant (p < 0.0001). Both age and disease state are very significant predictors of hospital mortality. An increase in age by 10 years raises the risk of hospital mortality by a factor of 2.5, and a unit increase in the oxygenation status raises the risk of hospital mortality by a factor of 20. [ABSTRACT FROM AUTHOR]

Aim: To develop and validate a novel weighted score integrating multisystem laboratory and clinical variables to predict poor 3‐month outcome (mRS score of 3–6) in acute ischemic stroke (AIS) patients with intravenous thrombolysis (IVT) therapy. Methods: We retrospectively analyzed data from Trial of Revascularization Treatment for Acute Ischemic Stroke study. The Supra‐Blan2t score was derived using the data on age, the National Institutes of Health Stroke Scale score, history of atrial fibrillation, blood sugar level, neutrophil count, direct bilirubin level, platelet–lymphocyte ratio, and TnI level in the derivation cohort of 433 patients, and validated in a cohort of 525 patients. Furthermore, we compared the performance of the Supra‐Blan2t score with DRAGON, TURN, and SPAN‐100 scores. Results: The discrimination capacity in the derivation and validation cohorts was good for poor 3‐month outcome (the area under the curve was 0.821 and 0.843, respectively). The cumulative incidence of poor 3‐month outcome significantly increased across risk categories in the derivation (low‐risk, 9.2%; medium‐risk, 17.4%; and high‐risk, 58.8%) and validation cohorts (12.7%, 36.5%, and 73.6%, respectively). The performance of the Supra‐Blan2t score was similar to or superior to DRAGON, TURN, and SPAN‐100 scores. Conclusion: The Supra‐Blan2t score, based on easily available multisystem laboratory and clinical variables, reliably predicted poor 3‐month functional outcome in AIS patients treated with IVT therapy featuring good calibration and discrimination. [ABSTRACT FROM AUTHOR]

Background: One of the unmet therapeutic needs in the treatment of multiple sclerosis (MS) is to prevent the accumulation of irreversible disability. Formulating standardized predictors of conversion in the secondary progressive phase of the relapsing-remitting MS (RRMS) should be a step toward solving this problem. Objective: To develop a reliable score, a predictor of physical disability worsening and secondary progression in patients with RRMS. Materials and Methods: Seventy-four patients with RRMS were observed retrospectively for 15 years. Clinical and demographic parameters were analyzed with respect to the time of reaching Expanded Disability Status Scale (EDSS) 4 and/or EDSS 6, as well as EDSS at the end of 15 years. Results: Almost half of the patients observed (47%) reached irreversible disability (EDSS ≥4.0) and - developed secondary progression (EDSS 6.0). The statistically significant variables selected were age at onset of MS, sex, type (afferent, efferent, and combined), and number of symptoms during the first and second attacks. Based on this selection, a predictive score for the course of the disease was formed. It has a sensitivity of 86%, specificity of 89%, positive predictive value of 85%, and negative predictive value of 81%. Conclusion: The proposed predictive score can be applied as a complementary tool in the choice of appropriate therapeutic approach at the early stages of MS, which can help avoid disability overtime. [ABSTRACT FROM AUTHOR]

IntroductionCasirivimab and imdevimab (CAS/IMV) are two non-competing, high-affinity human IgG1 anti-SARS-CoV-2 monoclonal antibodies, that showed a survival benefit in seronegative hospitalized patients with COVID-19. This study aimed to estimate the day-28 risk of mechanical ventilation (MV) and death in individuals hospitalized for severe COVID-19 pneumonia and receiving CAS/IMV. Additionally, it aimed to identify variables measured at the time of hospital admission that could predict these outcomes and derive a prediction algorithm.MethodsThis is a retrospective, observational cohort study conducted in 12 hospitals in Italy. Adult patients who were consecutively hospitalized from November 2021 to February 2022 receiving CAS/IMV were included. A multivariable logistic regression model was used to identify predictors of MV or death by day 28 from treatment initiation, and β-coefficients from the model were used to develop a risk score that was derived by means of leave-one-out internal cross-validation (CV), external CV, and calibration. Secondary outcome was mortality.ResultsA total of 480 hospitalized patients in the training set and 157 patients in the test set were included. By day 28, 36 participants (8%) underwent MV and 28 died (6%) for a total of 58 participants (12%) experiencing the composite primary endpoint. In multivariable analysis, four factors [age, PaO2/FiO2 ratio, lactate dehydrogenase (LDH), and platelets] were independently associated with the risk of MV/death and were used to generate the proposed risk score. The accuracy of the score in the area under the curve (AUC) was 0.80 and 0.77 in internal validation and test for the composite endpoint and 0.87 and 0.86 for death, respectively. The model also appeared to be well calibrated with the raw data.ConclusionThe mortality risk reported in our study was lower than that previously reported. Although CAS/IMV is no longer used, our score might help in identifying which patients are not likely to benefit from monoclonal antibodies and may require alternative interventions.

Abstract Background Predictors of ICU-acquired pulmonary aspergillosis (IPA) are not well-established in critically ill patients with ventilator-associated pneumonia (VAP), making IPA commonly misdiagnosed and anti-fungal therapy delayed. We aimed to develop a clinical score for prediction of IPA among patients with VAP. Methods Mechanically ventilated patients who developed VAP in 4 ICUs in Bretagne, Western France, were included. The score was constructed in a learning cohort, based on predictors of IPA in logistic regression model, and validated in a validation cohort. Results Among 1636 mechanically ventilated patients, 215 developed VAP but only 39 developed IPA (4 possible and 35 probable/putative) (18%). Most cases (31/39) were documented through a positive broncho-alveolar sample culture. Independent predictors of IPA were immunodepression (including onco-hematological disorder, immunomodulatory treatment, solid organ transplant, neutropenia

Min Li,1,2,&ast; Binlong Zhang,3,&ast; Jiangbo Xie,4 Ran Meng,1,2 Xunming Ji2,5 1Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Beijing Institute for Brain Disorders, Capital Medical University, Beijing, People’s Republic of China; 3Department of Acupuncture, Moxibustion, and Neurology, Guang’anmen Hospital, Chinese Academy of Chinese Medical Sciences, Beijing, People’s Republic of China; 4Department of Neurology, Weifang Traditional Chinese Hospital, Weifang, Shandong, People’s Republic of China; 5Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Ran Meng, Department of Neurology, Xuanwu Hospital, Capital Medical University, 45 Changchun Road, Xicheng District, Beijing, 100053, People’s Republic of China, Tel +86-13693080599, Email ranmeng2011@126.com Xunming Ji, Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, 45 Changchun Road, Xicheng District, Beijing, 100053, People’s Republic of China, Tel +86-13911077166, Email jixm@ccmu.edu.cnBackground: Although numerous prognostic markers for cerebral venous thrombosis (CVT) have been reported, inconsistencies exist in their predictive values, leading to contradictory forecasts. This study was designed to develop a comprehensive clinical outcome prediction score for Chinese patients with CVT, integrating key prognostic markers to furnish an overall prognosis.Methods: Participants were selected from the CCC cohort, a multicenter study encompassing 26 tertiary hospitals across mainland China. Between January 2021 and May 2022, 170 patients with CVT were prospectively recruited. Potential prognostic markers were extracted from the CCC database and subsequently analyzed.Results: Age, diastolic blood pressure (DBP), neutrophil-to-lymphocyte ratio (NLR), and neuron-specific enolase (NSE) emerged as significant prognostic markers for CVT after a multivariate logistic analysis. Specific cut-off values were identified: Age > 27.5 years, DBP > 79.5 mmHg, NLR > 6.6, and NSE > 16.5 ng/mL. The points assigned were: one each for age and NSE level, two for DBP, and three for NLR, based on the adjusted odds ratio. A positive correlation was found between the baseline CVT outcome score and the mRS at six months’ follow-up. A CVT outcome score of 3.5 served as an effective cut-off value for predicting CVT clinical outcomes. Further analysis revealed that patients with CVT outcome scores > 3 exhibited significantly higher mRS scores than those with scores ≤ 3.Conclusion: This study led to the development of the CVT outcome score, consisting of age, DBP, NLR, and NSE level, specifically for Chinese patients with CVT. The baseline CVT outcome score positively correlated with the mRS score at the six-month follow-up. A CVT outcome score of > 3 serves as a reliable indicator to identify patients at a higher risk of unfavorable clinical outcomes. These patients may benefit from additional care and early interventions to avert potential deterioration.Keywords: clinical outcome, prognosis, cerebral venous thrombosis, prediction score, validation

Background: Spinal metastases can impair mobility, worsening the Karnofsky Performance Status (KPS). Surgery for spinal metastases has the potential to improve KPS and extend prognosis, but it is crucial to recognize the elevated risk of perioperative complications. Therefore, the development of a new scoring system to accurately predict perioperative complications in spinal metastatic surgery is essential. Methods: We conducted a retrospective observational study with 86 patients who underwent surgical intervention for spinal metastases. Patients were divided into two groups based on the presence or absence of perioperative complications within 14 days after surgery. Various factors related to perioperative complications were assessed through univariate and multivariate analyses. We established a clinical prognostic scoring system called the Perioperative Complications following Metastatic Spinal Surgery (PERCOM) score and evaluated its precision using receiver operating characteristic (ROC) analysis. Results: Five variables (age, KPS, primary prostate cancer, Albumin, and Hemoglobin) identified in the univariate analysis were assigned binary values of 0 or 1. The PERCOM score was then calculated for each patient by summing the individual points, ranging from 0 to 5. The optimal threshold determined by ROC curve analysis for the PERCOM score was 2 points, with a sensitivity of 86 % and a specificity of 56 %. Conclusions: The composite PERCOM score effectively predicted perioperative complications in spinal metastasis surgery. To further validate its precision, a prospective multicenter study is needed.

Background and objectivePost-stroke delirium (PSD) is a common complication in acute stroke patients, and guidelines recommend routine screening and various preventive and treatment measures. However, there is a substantial lack of standardized approaches in diagnostic and therapeutic management of PSD. Here, we aimed to develop a new pragmatic and easily assessable screening tool to predict PSD based on early parameters, which are already integral to acute stroke diagnostics.MethodsWe enrolled acute stroke patients admitted to our stroke unit or intensive care unit and developed the scoring system using retrospective single-center patient data. The Confusion Assessment Method for the Intensive Care Unit was used for prospective score validation. Logistic regression models were employed to analyze the association of early clinical and paraclinical parameters with PSD development.ResultsN = 525 patients (median age: 76 years; 45.7% female) were enrolled, with 29.7% developing PSD during hospitalization. The resulting score comprises 6 items, including medical history, clinical examination findings, and non-contrast computed tomography results at admission. Scores range from −15 to +15 points, with higher values indicating a higher likelihood of PSD, ranging from 4% to 79%. The accuracy was 0.85, and the area under the curve was 0.89.ConclusionThe new RAPID (Risk Assessment and PredIction of Delirium in acute stroke patients)-score shows high accuracy in predicting PSD among acute stroke patients and offers precise odds of PSD for each corresponding score value, utilizing routine early clinical and paraclinical parameters. It can identify high-risk populations for clinical study interventions and may be suitable to guide prophylactic PSD measures.

Gestational diabetes (GDM) is a frequent complication during pregnancy. We aimed to develop a score to predict future insulin dependency in gestational diabetes (GDM). Data from 1611 patients from Charité Berlins gestational diabetes clinic from 2015 to 2022 were utilized. A stepwise backwards regression, including patient characteristics obtained at the initial presentation, was performed. Predictors examined included age, fasting blood glucose level, blood glucose levels one and two hours after oral glucose tolerance test, pre-pregnancy BMI, number of previous pregnancies and births, and fetal sex. The ideal cutoff value between high and low risk for insulin dependency was assessed and the score was internally validated. There were 1249 (77.5%) women diagnosed with dietary GDM and 362 (22.5%) were diagnosed with insulin-dependent GDM. The CHarité AssessmeNt of GEstational Diabetes (CHANGED) Score achieved an area under the curve of 0.77 (95% confidence interval 0.75–0.80; 0.75 in internal validation). The optimal cutoff value was calculated at a score value of 9 (72% sensitivity, 69% specificity). We developed an easily applicable tool to accurately predict insulin dependency in gestational diabetes. The CHANGED Score is routinely available and can potentially improve maternal and fetal outcomes. [ABSTRACT FROM AUTHOR]

Background: Predictors of ICU-acquired pulmonary aspergillosis (IPA) are not well-established in critically ill patients with ventilator-associated pneumonia (VAP), making IPA commonly misdiagnosed and anti-fungal therapy delayed. We aimed to develop a clinical score for prediction of IPA among patients with VAP. Methods: Mechanically ventilated patients who developed VAP in 4 ICUs in Bretagne, Western France, were included. The score was constructed in a learning cohort, based on predictors of IPA in logistic regression model, and validated in a validation cohort. Results: Among 1636 mechanically ventilated patients, 215 developed VAP but only 39 developed IPA (4 possible and 35 probable/putative) (18%). Most cases (31/39) were documented through a positive broncho-alveolar sample culture. Independent predictors of IPA were immunodepression (including onco-hematological disorder, immunomodulatory treatment, solid organ transplant, neutropenia < 0.5G/L and high-dose steroids ≥ 1 mg/kg/day of prednisolone equivalent) (p = 0.001; score = 1 point) and lymphocyte count at admission < 0.8 G/L (p = 0.019; score = 1 point). Operational values of the predictive score in the learning/validation cohort were 50%/52% sensitivity and 90%/87% specificity, respectively, for high PiPa score (score = 2) and 94%/91% sensitivity and 44%/46% specificity, respectively, for moderate PiPa score (score = 1). Finally, the AUC for the prediction of IPA was 0.783 in the learning cohort and 0.770 in the validation cohort. Conclusions: We evaluated a clinical score with good predictive value which may help to predict IPA in patient with VAP. External validation will be needed to confirm our preliminary findings. [ABSTRACT FROM AUTHOR]

RATIONALE: Acute pancreatitis (AP) is a serious acute abdominal disease. AP is often referred to as an unpredictable illness, which can take a mild to severe (fatal) course. AIMS OF THE STUDY: 1) To identify clinical parameters that are significantly related to the clinical course of acute pancreatitis. 2) To compile a scoring system enabling the severity of AP to be predicted when the patient is first admitted to hospital. METHODS: Analysis of available publications and clinical guidance, and retrospective analysis of data on patients hospitalised with AP at our clinic enable us to identify clinical details and laboratory results recorded at the time of patients’ admission to hospital that are related to the subsequent severity of the disease. For the purposes of statistical analysis, the sample of patients was divided into two groups: group A (mild AP, without local or organ complications), group B (moderately severe and severe AP with local and/or organ complications). PATIENT GROUPS AND RESULTS: In total, between 01.01.2013 and 30.06.2022, 312 patients with acute pancreatitis were allocated to the retrospective-prospective study sample. 74 % (231/312) of these patients were allocated to group A and 26 % (81/312) were allocated to group B. Univariate analysis of the data collected on the patient sample identifi ed 5 parameters that are statistically signifi cantly associated with the severity of the clinical course of the disease. Presence of SIRS on admission (A vs B, Odds ratio 10.787, 95% CI 5.09-22.85, p < 0.0001), diabetes mellitus type 2 in case history (A vs B, Odds ratio 7.703, 95% CI 3.04-19.51, p < 0.0001), hypocalcaemia on admission (A vs B, Odds ratio 8.288, 95% CI 3.84-17.88, p < 0.0001), urea concentration > 8 mmol/l (A vs B, Odds ratio 4.227, 95% CI 1.79-10.00, p = 0.0010) and venous lactate concentration > 2 mmol/l (A vs B, Odds ratio 3.293, 95% CI 1.59-6.82, p = 0.0013). In order to develop a scoring system, each of these parameters was allocated a points value based on its Odds ratio (OR): presence of SIRS 3 points, hypocalcaemia 3 points, diabetes mellitus type 2 in case history 2 points, urea concentration > 8 mmol/l 1 point and lactate concentration > 2 mmol/l 1 point. The authors refer to their scoring system as The Acute Pancreatitis Admission Score (APAS). The accuracy of APAS was modelled for various cut off values. Across the whole sample, we ascertained that an APAS ≥ 4 points predicts moderately severe or severe AP with a sensitivity of 81 % (95% CI: 71 – 89 %) and specifi city of 87 % (95 CI: 81 – 91 %). The positive predictive value (PPV) of APAS ≥ 4 is 0.68, while its negative predictive value (NPV) is 0.93 and accuracy 0.85 (95% CI 0.81 – 0.89). CONCLUSION: In this study we identify signifi cant simple clinical and laboratory parameters that are commonly tested as part of an initial examination when admitting a patient with AP to hospital. Having identifi ed these parameters we are able to establish a simple scoring system that is able to predict the severity of the course of AP at the moment of hospitalisation (Tab. 5, Fig. 2, Ref. 27). [ABSTRACT FROM AUTHOR]

Objectives: The aims of this study were to develop and validate 2 simple scores for stratification of the risks of (1) any fragility (AF) and (2) major osteoporotic fracture (MOF) in type 2 diabetes (T2D) patients; we also compared the performance of these scores with that of the Fracture Risk Assessment Tool (FRAX) and its adjustments. Design and methods: In this longitudinal cohort study, 1855 patients with T2D were enrolled from January 2015 to August 2019. Cox proportional hazard regression was used to model the 5-year risk of AF and MOF. These scores were internally validated using a bootstrap resampling method of 1000. Results: During a median follow-up of 5 years, 119 (6.42%) cases of AF and 92 (4.96%) cases of MOFs were identified. Both the concordance index (C-index) and calibration plots indicated improved identification performance using the newly established scores. Furthermore, these scores also showed improved outcomes regarding the decision curve analysis (DCA) and area under the curve (AUC) compared to the widely used FRAX and its derivatives. More importantly, these scores successfully separated T2D patients into risk groups according to significant differences in fracture incidence. Conclusions: These novel scores enable simple and reliable fracture risk stratification in T2D patients. Future work is needed to validate these findings in external cohort(s). [ABSTRACT FROM AUTHOR]

Objectives: Risk prediction scores are important for early diagnosis and treatment of diseases. Diabetic peripheral neuropathy (DPN) is a common complication of type 2 diabetes, but the early diagnosis is challenging. This study developed a risk prediction model for DPN based on modifiable risk factors. Materials and Methods: The study included 315 type 2 diabetes patients with and without DPN. Demographic, biochemical, and diagnostic data were collected. Multinomial logistic regression analysis was used to identify independent risk factors for DPN. Results: Hemoglobin% and total red blood cells were identified as independent risk factors for DPN, used to develop a risk prediction score. Conclusion: The risk prediction score developed in this study can be used by physicians to quickly assess a patient's risk of DPN and select appropriate therapeutic options. Routine monitoring of modifiable risk factors can improve DPN prognosis. Patients stratified by risk scores can better understand their risk and seek appropriate care. [ABSTRACT FROM AUTHOR]

Simple Summary: This review explores hemoptysis in cancer patients. It delves into risk factors, epidemiology and clinical consequences. The need for a mortality prediction score for cancer patients with hemoptysis-related variables is needed, and this tool could aid in risk assessment, optimize the control of bleeding with critical care, implement tracheobronchial or vascular interventions, and guide treatment planning. Managing hemoptysis in cancer patients requires addressing the underlying cause and providing supportive care for improved quality of life. Hemoptysis in cancer patients can occur for various reasons, including infections, tumors, blood vessel abnormalities and inflammatory conditions. The degree of hemoptysis is commonly classified according to the quantity of blood expelled. However, volume-based definitions may not accurately reflect the clinical impact of bleeding. This review explores a more comprehensive approach to evaluating hemoptysis by considering its risk factors, epidemiology and clinical consequences. In particular, this review provides insight into the risk factors, identifies mortality rates associated with hemoptysis in cancer patients and highlights the need for developing a mortality prediction score specific for cancer patients. The use of hemoptysis-related variables may help stratify patients into risk categories; optimize the control of bleeding with critical care; implement the use of tracheobronchial or vascular interventions; and aid in treatment planning. Effective management of hemoptysis in cancer patients must address the underlying cause while also providing supportive care to improve patients' quality of life. [ABSTRACT FROM AUTHOR]

The authors aimed to develop a simple prediction score to help identify patients at high risk of low-cardiac-output syndrome after adult cardiac surgery. A single-center, retrospective, observational study. At a tertiary hospital. Adult patients who underwent on-pump cardiac surgery between April 2016 and March 2021. None. Among the 2,806 patients retained for final analyses, 355 (12.7%) developed low-cardiac-output syndrome. Using a stepwise backward variable selection procedure applied to a multivariate logistic regression, a prediction model, including 8 risk factors, could be identified—preoperative left ventricular ejection fraction, glomerular filtration rate <60 mL/min according to the Cockcroft formula or preoperative dialysis, combined surgery, nonelective surgery, mitral valve surgery for mitral valve regurgitation, history of extracardiac arteriopathy, preoperative hemoglobin <13 g/dL, and New York Heart Association functional class III or IV. A clinical prediction score was derived from the regression coefficients. The model had a good discriminative ability, with an area under the receiver operating characteristics curve of 0.8 (95% CI: 077-0.84). Using a threshold value of 5, the score had a 68% sensitivity, 79% specificity, a positive-predictive value of 33%, and a negative-predictive value of 94%. These results were validated on a validation sample using the bootstrap resampling technique. The authors developed a clinical score to facilitate the prediction of low- cardiac-output syndrome after adult cardiac surgery. This could help tailor patient management by contributing to the early identification of those at high risk of postoperative low cardiac output. [ABSTRACT FROM AUTHOR]

Abstract Background Prediction of difficult laparoscopic cholecystectomy may help in making necessary arrangements for optimal intraoperative requirements and postoperative care. This study was conducted to examine the factors associated with and outcomes of difficult laparoscopic cholecystectomy performed at the Bhutan's largest hospital in 2020. Methods This was a cross‐sectional study with a convenience sampling method. Data on clinical features, ultrasonography and intraoperative factors of patients who underwent laparoscopic cholecystectomy were extracted from their medical records, investigation reports and intraoperative surgery note. Difficult laparoscopic cholecystectomy was defined on the basis of the duration of the surgery, injury to bile duct or artery, or conversion to open cholecystectomy. Data were double entered and validated in EpiData 3.1 and analysed in STATA 13.0. Results Data from 134 patients were extracted. The mean age of the sample was 43 (±SD 13) years. “Difficult laparoscopic cholecystectomy” was reported in 83 patients (62%) and easy laparoscopic cholecystectomy in 51 patients (38%). Those patients having simple adhesions up to the body of the gall bladder were 1.6 times more likely to encounter difficult laparoscopic cholecystectomy (adjusted PR = 1.60, 95% CI 1.04–2.48, p = 0.034). The majority did not have any post‐operative complications (130 cases, 97%). The indications of laparoscopic cholecystectomy were symptomatic gall stone disease (129, 96%), acalculous cholecystitis (2, 1%) and gall bladder polyp (3, 2%). Conclusions The proportion of difficult laparoscopic cholecystectomy is high, but the rates of post‐operative complications were minimal with no mortality or injury to bile duct or arteries.

Introduction: The success of diabetes prevention based on early treatment depends on high-quality screening. This study compared the diagnostic properties of currently recommended screening strategies against alternative score-based rules to identify those at high risk of developing diabetes. Methods: The study used data from ELSA-Brasil, a contemporary cohort followed up for a mean (standard deviation) of 7.4 (0.54) years, to develop risk functions with logistic regression to predict incident diabetes based on socioeconomic, lifestyle, clinical, and laboratory variables. We compared the predictive capacity of these functions against traditional pre-diabetes cutoffs of fasting plasma glucose (FPG), 2-h plasma glucose (2hPG), and glycated hemoglobin (HbA1c) alone or combined with recommended screening questionnaires. Results: Presenting FPG > 100 mg/dl predicted 76.6% of future cases of diabetes in the cohort at the cost of labeling 40.6% of the sample as high risk. If FPG testing was performed only in those with a positive American Diabetes Association (ADA) questionnaire, labeling was reduced to 12.2%, but only 33% of future cases were identified. Scores using continuously expressed clinical and laboratory variables produced a better balance between detecting more cases and labeling fewer false positives. They consistently outperformed strategies based on categorical cutoffs. For example, a score composed of both clinical and laboratory data, calibrated to detect a risk of future diabetes ≥20%, predicted 54% of future diabetes cases, labeled only 15.3% as high risk, and, compared to the FPG ≥ 100 mg/dl strategy, nearly doubled the probability of future diabetes among screen positives. Discussion: Currently recommended screening strategies are inferior to alternatives based on continuous clinical and laboratory variables. [ABSTRACT FROM AUTHOR]

Background: Delayed treatment leads to increased mortality in critically ill patients with invasive pulmonary aspergillosis (IPA). We aimed to develop and validate a prediction score based on novel biomarkers and clinical risk factors to identify IPA in immunocompetent patients in the intensive care unit (ICU). Methods: A retrospective study was conducted to collect medical information and novel biomarkers upon ICU admission. Risk factors adopted for the final prediction score were identified using multivariate logistic regression analysis. Results: We retrospectively collected 1841 critical ill patients between January 2018 and August 2022. Patients with IPA had higher C‐reactive protein‐to‐albumin ratio (CAR), neutrophil‐to‐lymphocyte ratio, systemic immune‐inflammation index and lower prognostic nutritional index (PNI). Chronic obstructive pulmonary disease (COPD), continuous renal replacement therapy (CRRT), high dose of corticosteroids, broad‐spectrum antibiotics, blood galactomannan (GM) positivity and high CAR were independent risk factors for IPA and were entered into the final prediction score. The score had good discrimination, with the area under receiver operating characteristic curve of 0.816 and 0.780 for the training and validation cohorts, respectively, and good calibration. Conclusion: A score based on six clinical and novel immunological biomarkers showed promising predictive value for antifungal treatment in immunocompetent ICU patients. [ABSTRACT FROM AUTHOR]

As the population worldwide is aging, the need for surgery in elderly patients with neurotrauma is increasing. The aim of this study was to compare the outcome of elderly patients undergoing surgery for neurotrauma with younger patients and to identify the risk factors for mortality. We retrospectively analyzed consecutive patients undergoing craniotomy or craniectomy for neurotrauma at our institution from 2012 to 2019. Patients were divided into two groups (≥70 years or <70 years) and compared. The primary outcome was the 30-day mortality rate. Potential risk factors for 30-day mortality were assessed in a uni- and multivariate regression model for both age groups, forming the basis of a 30-day mortality prediction score. We included 163 consecutive patients (average age 57.98 ± 19.87 years); 54 patients were ≥70 years. Patients ≥70 years showed a significantly better median preoperative Glasgow Coma Scale (GCS) score compared with young patients (P < 0.001), and fewer pupil asymmetry (P = 0.001), despite having a higher Marshall score (P = 0.07) at admission. Multivariate regression analysis identified low pre- and postoperative GCS scores and the lack of prompt postoperative prophylactic low-molecular-weight heparin treatment as risk factors for 30-day mortality. Our score showed moderate accuracy in predicting 30-day mortality with an area under the curve of 0.76. Elderly patients after neurotrauma present with a better GCS at admission despite having more severe radiographic injuries. Mortality and favorable outcome rates are comparable between the age groups. [ABSTRACT FROM AUTHOR]

Background In the absence of bacteriologic confirmation to diagnose tuberculosis (TB) in children, it is suggested that treatment should be initiated when sufficient clinical evidence of disease is available. However, it is unclear what clinical evidence is sufficient to make this decision. To identify children who would benefit from rapid initiation of TB treatment, we developed 2 clinical prediction tools. Methods We conducted a secondary analysis of a prospective intensified TB patient–finding intervention conducted in Pakistan in 2014–2016. TB disease was determined through either bacteriologic confirmation or a clinical diagnosis. We derived 2 tools: 1 uses classification and regression tree (CART) analysis to develop decision trees, while the second uses multivariable logistic regression to calculate a risk score. Results Of the 5162 and 5074 children included in the CART and prediction score, respectively, 1417 (27.5%) and 1365 (26.9%) were eligible for TB treatment. CART identified abnormal chest radiographs and family history of TB as the most important predictors (area under the receiver operating characteristic curve [AUC], 0.949). The final prediction score model included age group (0–4, 5–9, 10–14), weight <5th percentile, cough, fever, weight loss, chest radiograph suggestive of TB disease, and family history of TB; the identified best cutoff score was 9 (AUC, 0.985%). Conclusions Use of clinical evidence was sufficient to accurately identify children who would benefit from treatment initiation. Our tools performed well compared with existing algorithms, though these results need to be externally validated before operationalization. [ABSTRACT FROM AUTHOR]

The etiology of OT is largely unknown. Any predisposition to rotation of the infundibulopelvic ligament and utero-ovarian ligament should be considered a possible etiology. Information with respect to ovarian torsion (OT) among pregnant is underreported and based on small studies. We aim to compare characteristics of confirmed OT to laparoscopies performed for the indication of suspected OT, in which no OT was found among pregnant women. This is a retrospective case–control study. We included pregnant women who underwent laparoscopy for a suspected OT between March 2011 and August 2020. Pregnant women with confirmed OT (torsion group) were compared to those without (no torsion group). There were 169 women with suspected OT. OT was confirmed in 140 (82.8%) women. There was higher proportion of assisted reproductive technology (ART) gestation in the torsion group [76 (54.3%) vs. 5 (17.2%), p < 0.001]. The rate of pregnant approaching evaluation within 8 h of symptoms onset was higher in the torsion group [57 (40.7%) vs. 2 (6.9%), p < 0.001]. The mean visual analogue score (VAS) was higher in the torsion group (8.5 vs. 7.1, p = 0.002). The mean pulse was lower in the torsion group (79 vs. 88 bpm, p < 0.001). From sonographic characteristics examined, the following was higher in the torsion group; mean maximal size of the ovary (70 mm in the torsion group vs. 54 mm in the no torsion group, p = 0.011). In a multivariable logistic regression analysis, number of hours of symptoms was negatively associated with AT [aOR, 95% CI 0.95 (0.91–0.98)] and pulse was negatively associated with OT [aOR, 95% CI 0.78 (0.63–0.95)]. Among the 29 cases in which no OT was found during laparoscopy, the following findings were noted: 16 (55.2%) no abnormality at all, 5 (17.2%) functional ovarian cyst, 2 (6.9%) mature teratoma and 6 cases of peritoneal adhesions (20.7%). The time from pain onset to approaching evaluation and women's pulse should be considered and acknowledged in the evaluation of OT during pregnancy. [ABSTRACT FROM AUTHOR]

Severe COVID-19 infections are at high risk of causing thromboembolic events (TEEs). However, the usual exams may be unavailable or unreliable in predicting the risk of TEEs at admission or during hospitalization. We performed a retrospective analysis of two centers (n = 124 patients) including severe COVID-19 patients to determine the specific risk factors of TEEs in SARS-CoV-2 infection at admission and during stays at the intensive care unit (ICU). We used stepwise regression to create two composite scores in order to predict TEEs in the first 48 h (H0–H48) and during the first 15 days (D1–D15) in ICU. We then evaluated the performance of our scores in our cohort. During the period H0–H48, patients with a TEE diagnosis had higher D-Dimers and ferritin values at day 1 (D1) and day 3 (D3) and a greater drop in fibrinogen between D1 and D3 compared with patients without TEEs. Over the period D1-D15, patients with a diagnosis of a TEE showed a more marked drop in fibrinogen and had higher D-Dimers and lactate dehydrogenase (LDH) values at D1 and D3. Based on ROC analysis, the COVID-related acute lung and deep vein thrombosis (CALT) 1 score, calculated at D1, had a diagnostic performance for TEEs at H0–H48, estimated using an area under the curve (AUC) of 0.85 (CI95%: 0.76–0.93, p < 10−3). The CALT 2 score, calculated at D3, predicted the occurrence of TEEs over the period D1-D15 with an estimated AUC of 0.85 (CI95%: 0.77–0.93, p < 10−3). These two scores were used as the basis for the development of the CALT protocol, a tool to assist in the decision to use anticoagulation during severe SARS-CoV-2 infections. The CALT scores showed good performances in predicting the risk of TEEs in severe COVID-19 patients at admission and during ICU stays. They could, therefore, be used as a decision support protocol on whether or not to initiate therapeutic anticoagulation. [ABSTRACT FROM AUTHOR]

PurposeThe purpose of this study was to identify risk factors for developing a subsequent contralateral slipped capital femoral epiphysis (SCFE) and provide a prediction score to quantify risk of subsequent slip at the time of initial presentation.MethodsThis retrospective study included patients that presented with a unilateral SCFE between 2006 and 2017. Chart and radiographic review were performed to collect demographic, clinical and radiographic risk factors. Descriptive statistics, univariate analyses and multivariate regression analysis were used to compare risk factors between patients that did or did not develop a subsequent contralateral SCFE.ResultsThis study included 183 patients and 33 patients (18%) developed a subsequent contralateral SCFE. Younger age at time of initial presentation, lower modified Oxford Score and smaller difference in epiphyseal-diaphyseal angle between both sides during index presentation were significant predictors of subsequent contralateral SCFE. Specifically, age ≤ 11 years, modified Oxford Score ≤ 20 and difference in epiphyseal-diaphyseal angle of ≤ 21° between both hips were predictive of a contralateral slip (Area Under the Curve = 0.78; p < 0.05). The presence of each risk factor increased the risk of subsequent contralateral SCFE and having all three risk factors increased the risk to 73%.ConclusionThere is a significant risk of subsequent contralateral SCFE in patients with unilateral SCFE, and predictive risk factors include younger age, lower modified Oxford Score and smaller difference in epiphyseal-diaphyseal angle between the affected and unaffected hips.Level of evidenceLevel III.

Abstract Background Although of high individual and socioeconomic relevance, a reliable prediction model for the prognosis of juvenile stroke (18–55 years) is missing. Therefore, the study presented in this protocol aims to prospectively validate the discriminatory power of a prediction score for the 3 months functional outcome after juvenile stroke or transient ischemic attack (TIA) that has been derived from an independent retrospective study using standard clinical workup data. Methods PREDICT-Juvenile-Stroke is a multi-centre (n = 4) prospective observational cohort study collecting standard clinical workup data and data on treatment success at 3 months after acute ischemic stroke or TIA that aims to validate a new prediction score for juvenile stroke. The prediction score has been developed upon single center retrospective analysis of 340 juvenile stroke patients. The score determines the patient’s individual probability for treatment success defined by a modified Rankin Scale (mRS) 0–2 or return to pre-stroke baseline mRS 3 months after stroke or TIA. This probability will be compared to the observed clinical outcome at 3 months using the area under the receiver operating characteristic curve. The primary endpoint is to validate the clinical potential of the new prediction score for a favourable outcome 3 months after juvenile stroke or TIA. Secondary outcomes are to determine to what extent predictive factors in juvenile stroke or TIA patients differ from those in older patients and to determine the predictive accuracy of the juvenile stroke prediction score on other clinical and paraclinical endpoints. A minimum of 430 juvenile patients (

Background: The recurrence rate of ischemic symptoms after coronary artery bypass grafting (CABG) is increasing in recent years. How to prevent and treat saphenous vein graft disease (SVGD [symptomatic ⩾50% stenosis in at least one Saphenous vein graft]) has been a clinical challenge to date. Different pathogenesis may exist in SVGD of different periods. There are currently few available scores for estimating the risk of SVGD after one year post CABG. Objective: We sought to develop and validate a simple predictive clinical risk score for SVGD with recurring ischemia after one year post CABG. Methods and Results: This was a cross-sectional study and the results were validated using bootstrap resampling on a separate cohort. A nomogram and risk scoring system were developed based on retrospective data from a training cohort of 606 consecutive patients with recurring ischemia >1 year after CABG. Logistic regression model was used to find the predictive factors and to build a nomogram. To assess the generalization, models were validated using bootstrap resampling and an external cross-sectional study of 187 consecutive patients in four other hospitals. In multivariable analysis of the primary cohort, native lesion vessel number, SVG age, recurring ischemia type, very low-density lipoprotein level, and left ventricular end-diastolic diameter were independent predictors. A summary risk score was derived from nomogram, with a cut-off value of 15. In internal and external validation, the C-index was 0.86 and 0.82, indicating good discrimination. The calibration curve for probability of SVGD showed optimal agreement between actual observations and risk score prediction. Conclusion: A simple-to-use risk scoring system based on five easily variables was developed and validated to predict the risk of SVGD among patients who recurring ischemia after one year post CABG. This score may be useful for providing patients with individualized estimates of SVGD risk. [ABSTRACT FROM AUTHOR]

Aim: The aim of the study was to examine the predictive value of inflammatory markers for chorioamnionitis and funisitis in extremely low gestational age neonates. Methods: According to the Redline histopathological classification, extremely low gestational age neonates were classified into: (1) maternal inflammatory response ≤1 or ≥2, based on inflammatory findings of the placenta and (2) foetal inflammatory response ≤1 or ≥2, based on inflammatory findings of the umbilical cord. On admission and 12–36 h postnatally, procalcitonin and high‐sensitivity C‐reactive protein levels and white blood cell and neutrophil counts were compared. For both maternal and foetal inflammatory responses ≥2, the predictive value of each inflammatory marker was calculated. Results: On admission, procalcitonin had the best predictive value for maternal and foetal inflammatory response ≥2. The maternal inflammatory response ≥2 prediction score includes procalcitonin level on admission, high‐sensitivity C‐reactive protein level and white blood cell count at 12–36 h postnatally. Foetal inflammatory response ≥2 prediction score includes procalcitonin level and white blood cell count on admission and 12–36 h postnatally. The sensitivities were 96.4% and 96.3%, respectively. Conclusion: Procalcitonin, high‐sensitivity C‐reactive protein levels and white blood cell count provide highly sensitive prediction scores for chorioamnionitis and funisitis in extremely low gestational age neonates. [ABSTRACT FROM AUTHOR]

IntroductionThe success of diabetes prevention based on early treatment depends on high-quality screening. This study compared the diagnostic properties of currently recommended screening strategies against alternative score-based rules to identify those at high risk of developing diabetes.MethodsThe study used data from ELSA-Brasil, a contemporary cohort followed up for a mean (standard deviation) of 7.4 (0.54) years, to develop risk functions with logistic regression to predict incident diabetes based on socioeconomic, lifestyle, clinical, and laboratory variables. We compared the predictive capacity of these functions against traditional pre-diabetes cutoffs of fasting plasma glucose (FPG), 2-h plasma glucose (2hPG), and glycated hemoglobin (HbA1c) alone or combined with recommended screening questionnaires.ResultsPresenting FPG > 100 mg/dl predicted 76.6% of future cases of diabetes in the cohort at the cost of labeling 40.6% of the sample as high risk. If FPG testing was performed only in those with a positive American Diabetes Association (ADA) questionnaire, labeling was reduced to 12.2%, but only 33% of future cases were identified. Scores using continuously expressed clinical and laboratory variables produced a better balance between detecting more cases and labeling fewer false positives. They consistently outperformed strategies based on categorical cutoffs. For example, a score composed of both clinical and laboratory data, calibrated to detect a risk of future diabetes ≥20%, predicted 54% of future diabetes cases, labeled only 15.3% as high risk, and, compared to the FPG ≥ 100 mg/dl strategy, nearly doubled the probability of future diabetes among screen positives.DiscussionCurrently recommended screening strategies are inferior to alternatives based on continuous clinical and laboratory variables.

Abstract Background The hospital management of patients diagnosed with COVID-19 can be hampered by heterogeneous characteristics at entry into the emergency department. We aimed to identify demographic, clinical and laboratory parameters associated with higher risks of hospitalisation, oxygen support, admission to intensive care and death, to build a risk score for clinical decision making at presentation to the emergency department. Methods We carried out a retrospective study using linked administrative data and laboratory parameters available in the initial phase of the pandemic at the emergency department of the regional reference hospital of Pescara, Abruzzo, Italy, March–June 2020. Logistic regression and Cox modelling were used to identify independent predictors for risk stratification. Validation was carried out collecting data from an extended timeframe covering other variants of concern, including Alpha (December 2020–January 2021) and Delta/Omicron (January–March 2022). Results Several clinical and laboratory parameters were significantly associated to the outcomes of interest, independently from age and gender. The strongest predictors were: for hospitalisation, monocyte distribution width ≥ 22 (4.09; 2.21–7.72) and diabetes (OR = 3.04; 1.09–9.84); for oxygen support: saturation

Wijittra Liengswangwong, Pacharaporn Preechakul, Chaiyaporn Yuksen, Chetsadakon Jenpanitpong, Welawat Tienpratarn, Sorawich Watcharakitpaisan Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, ThailandCorrespondence: Chaiyaporn Yuksen, Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, 10400, Thailand, Email chaipool0634@hotmail.comBackground: In Thailand, most primary care hospitals cannot measure serum lipase and amylase; no 24 hours computed tomography and magnetic resonance imaging available, and no on-call gastroenterologists. Thus, acute pancreatitis cannot be diagnosed based on the established diagnostic criteria that require this information. The resultant delayed management increases morbidity and mortality. This study was performed to create a clinical prediction score for early diagnosis of acute pancreatitis in emergency departments without requiring a computed tomography scan or laboratory measurement to assist in the initial diagnosis, treatment, or referral.Methods: Patients with suspected acute pancreatitis who had available data regarding lipase and amylase measurements and visited the emergency department from June 2019 to August 2020 were retrospectively analyzed. The baseline predictive factors were compared between patients with and without acute pancreatitis according to the 2012 revised Atlanta classification. Multivariable logistic regression was used to explore potential predictive factors and develop a clinical prediction score for the diagnosis of acute pancreatitis.Results: A total of 506 eligible patients, 84 (16%) had acute pancreatitis. The PRE-PAN score [area under the receiver operating characteristics curve, 0.88; 95% confidence interval (CI), 0.84– 0.93] included six factors: alcohol drinking, epigastric pain, pain radiating to the back, persistent pain, nausea or vomiting, and the pain score. A score of > 7.5 points suggested a high probability of acute pancreatitis [positive likelihood ratio, 6.80 (95% CI, 4.75– 9.34; p < 0.001); sensitivity, 66.7% (95% CI, 54.6– 77.3); specificity, 90.2% (95% CI, 86.6– 93.1); positive predictive value, 58.5% (95% CI, 47.1– 69.3);, 92.9% (95% CI, 89.6– 95.4)].Conclusion: A PRE-PAN risk score is a screening tool for predicting acute pancreatitis without using the lipase concentration or radiological findings. A high predictive score, especially > 7.5, suggests a high probability of acute pancreatitis.Keywords: prediction score, prediction model, clinical diagnostic score, acute pancreatitis

Abstract Background Critically-ill Covid-19 patients require extensive resources which can overburden a healthcare system already under strain due to a pandemic. A good disease severity prediction score can help allocate resources to where they are needed most. Objectives We developed a Covid-19 Severity Assessment Score (CoSAS) to predict those patients likely to suffer from mortalities within 28 days of hospital admission. We also compared this score to Quick Sequential Organ Failure Assessment (qSOFA) in adults. Methods CoSAS includes the following 10 components: Age, gender, Clinical Frailty Score, number of comorbidities, Ferritin level, D-dimer level, neutrophil/lymphocyte ratio, C-reactive Protein levels, systolic blood pressure and oxygen saturation. Our study was a single center study with data collected via chart review and phone calls. 309 patients were included in the study. Results CoSAS proved to be a good score to predict Covid-19 mortality with an Area under the Curve (AUC) of 0.78. It also proved better than qSOFA (AUC of 0.70). More studies are needed to externally validate CoSAS. Conclusion CoSAS is an accurate score to predict Covid-19 mortality in the Pakistani population.

Sorravit Savatmongkorngul, Panrikan Pitakwong, Pungkava Sricharoen, Chaiyaporn Yuksen, Chetsadakon Jenpanitpong, Sorawich Watcharakitpaisan Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, ThailandCorrespondence: Chaiyaporn Yuksen, Department of Emergency Medicine, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, 10400, Thailand, Email chaipool0634@hotmail.comObjective: Difficult laryngoscopy is associated with difficult intubation, an increasing number of endotracheal intubation attempts, and adverse events. Clinical prediction of difficult airways in an emergency setting was limited in sensitivity and specificity. This study developed a new model for predicting difficult laryngoscopy in the emergency department.Methods: This retrospective cohort study was conducted using an exploratory model at the Emergency Medicine of Ramathibodi Hospital. The study was conducted from June 2018 to July 2020. The eligibility criteria were an age of ≥ 15 years who undergo intubation in the emergency department. Difficult laryngoscopy was defined as a Cormack–Lehane grade 3 and above. The predictive model and score were developed by multivariable logistic regression analysis.Results: A total of 617 patients met the eligibility criteria; 83 (13.45%) had difficult laryngoscopy. Five independent factors were predictive of difficult laryngoscopy. Significant factors were M: limited mouth opening, O: presence of obstructed airway, N: poor neck mobility, T: large tongue, and H: short hypo-mental distance. The difficult laryngoscopy score had an accuracy of 89%. A score of > 4 increased the likelihood ratio of difficult laryngoscopy by 7.62 times.Conclusion: The MONTH Difficult Laryngoscopy Score of > 4 was associated with difficult laryngoscopy.Keywords: difficult laryngoscopy, prediction score, emergency department intubation