Development and derivation of bacteremia prediction model in patients with hepatobiliary infection.

INTRODUCTION: Hepatobiliary infections are common in the emergency department (ED), and the mortality rate for this condition is high. A suitable bacteremia prediction model would support prompt identification of bacteremia and appropriate management of hepatobiliary infections in the ED. Therefore, we attempted to produce a bacteremia prediction model with both internal and external validation for hepatobiliary infections in the ED. METHODS: Patients with hepatobiliary infection were extracted from retrospective cohort databases of two tertiary hospitals from January 2018 to December 2019 and from January 2016 to December 2019, respectively. Independent risk factors were determined using multivariable logistic regression in a developmental cohort. We assigned a weighted value to predictive factors and developed a prediction model, which was validated both internally and externally. We assessed discrimination using the area under the receiver operating characteristics curve (AUC). RESULTS: One hospital cohort of 1568 patients was randomly divided into a developmental group of 927 patients (60%) and an internal validation group of 641 patients (40%), and 736 people from the other hospital cohort were used for external validation. Bacteremia rates were 20.5%, 18.1%, and 23.1% in the developmental, internal, and external validation cohorts, respectively. Nine significant factors were used for predicting bacteremia, including age, three vital signs, and five laboratory tests. After applying our bacteremia prediction rule to the validation cohort, 56.5% and 53.8% of the internal and external validation groups were classified as low-risk bacteremia groups (bacteremia rates: 8.6% and 13.9%, respectively). The AUCs were 0.727 (95% confidence interval [CI]: 0.686-0.767), 0.730 (95% CI: 0.679-0.781), and 0.715 (95% CI: 0.672-0.758) for the developmental, internal, and external validation cohorts, respectively. The sensitivity and specificity for internal validation/external validation was 73.2%/67.6% and 63.0%/60.2%, respectively. CONCLUSION: A bacteremia prediction model for hepatobiliary infection might be useful to predict the risk of bacteremia. It might also reduce the need for blood culture in low-risk patients.

A simple and novel equation to estimate the degree of bleeding in haemorrhagic shock: mathematical derivation and preliminary in vivo validation.

Determining blood loss [100% - RBV (%)] is challenging in the management of haemorrhagic shock. We derived an equation estimating RBV (%) via serial haematocrits (Hct1, Hct2) by fixing infused crystalloid fluid volume (N) as [0.015 × body weight (g)]. Then, we validated it in vivo. Mathematically, the following estimation equation was derived: RBV (%) = 24k / [(Hct1 / Hct2) - 1]. For validation, nonongoing haemorrhagic shock was induced in Sprague-Dawley rats by withdrawing 20.0%-60.0% of their total blood volume (TBV) in 5.0% intervals (n = 9). Hct1 was checked after 10 min and normal saline N cc was infused over 10 min. Hct2 was checked five minutes later. We applied a linear equation to explain RBV (%) with 1 / [(Hct1 / Hct2) - 1]. Seven rats losing 30.0%-60.0% of their TBV suffered shock persistently. For them, RBV (%) was updated as 5.67 / [(Hct1 / Hct2) - 1] + 32.8 (95% confidence interval [CI] of the slope: 3.14-8.21, p = 0.002, R2 = 0.87). On a Bland-Altman plot, the difference between the estimated and actual RBV was 0.00 ± 4.03%; the 95% CIs of the limits of agreements were included within the pre-determined criterion of validation (< 20%). For rats suffering from persistent, non-ongoing haemorrhagic shock, we derived and validated a simple equation estimating RBV (%). This enables the calculation of blood loss via information on serial haematocrits under a fixed N. Clinical validation is required before utilisation for emergency care of haemorrhagic shock.

External validation and update of the early detection rule for severe hyperkalemia among patients with symptomatic bradycardia.

OBJECTIVE: Chon et al. suggested a high prevalence of severe hyperkalemia (serum potassium ≥ 6.0 mEq/L with electrocardiographic [ECG] changes) among patients with symptomatic or extreme bradycardia. Despite the urgent need to detect and treat severe hyperkalemia, serum potassium result may be available too late and is often spuriously high. Meanwhile, the traditional, descriptive ECG findings of severe hyperkalemia have shown unsatisfactory diagnostic powers. To overcome these diagnostic problems, they outlined the following quantitative rules to facilitate its early detection: Maximum precordial T wave ≥ 8.5 mV (2), atrial fibrillation/junctional bradycardia (1), heart rate (HR) ≤ 42/min (1) with (original rule)/without (ECG-only rule) diltiazem medication (2), and diabetes mellitus (1). Here we report on our external validation of these rules and the resulting updates. METHODS: This retrospective, cross-sectional study included all adults with symptomatic (HR ≤ 50/min with syncope/pre-syncope/dizziness, altered mentality, chest pain, dyspnea, general weakness, oliguria, or shock) or extreme (HR ≤ 40/min) bradycardia who visited a university emergency department from 2014 to 2019. After validating the abovementioned rules externally, we selected risk factors of severe hyperkalemia among the ECG findings and easy-to-assess clinical variables by multiple logistic regression analysis. After modelling the updated 'ECG-only' and 'ECG-plus' indices, we internally validated the better of the two by bootstrapping with 1000 iterations. RESULTS: Among 455 symptomatic/extreme bradycardia cases (70.3 ± 13.1 years; 213 females [46.8%]), 70 (15.4%) had severe hyperkalemia. The previous ECG-only rule showed a c-statistic of 0.765 (95% CI: 0.706-0.825), Hosmer-Lemeshow test of p < 0.001, and a calibration slope of 0.719 (95% CI: 0.401-1.04). On updating, the ECG-plus index summing junctional bradycardia/atrial fibrillation (1), maximum precordial T wave≥8.0 mV (2), general weakness as the chief complaint (2), oxygen demand (1), and dialysis (2) outperformed the ECG-only index (c-statistic, 0.832; 95% CI, 0.785-0.880 vs. 0.764; 95% CI, 0.700-0.828; p = 0.011). On bootstrapping, the c-statistic was 0.832 (95% CI: 0.786-0.878). For scores ≥ 3 (positive likelihood ratio ≥ 5.0), the sensitivity and specificity were 0.514 and 0.901, respectively. For scores ≤ 1, negative likelihood ratio was ≤0.2. CONCLUSIONS: Previous rules showed less satisfactory calibration but fair discrimination to detect severe hyperkalemia in patients with symptomatic or extreme bradycardia. We propose the ECG-plus index as the optimum tool to facilitate its early detection.

Optimum chest compression point might be located rightwards to the maximum diameter of the right ventricle: A preliminary, retrospective observational study.

BACKGROUND: Some researchers have reported that applying compression closer to the maximum diameter of the left ventricle (Point_max.LV) is associated with worse clinical outcomes, challenging its traditional position as optimum compression point (Point_optimum). By locating the mid-sternum (the actual compression site) in terms of Point_max.LV and its right ventricular equivalent (Point_max.RV), we aimed to determine its optimum horizontal position associated with increased chances of return of spontaneous circulation (ROSC). METHODS: A retrospective, cross-sectional study was performed at a university hospital from 2014 to 2019 on non-traumatic out-of-hospital cardiac arrest (OHCA) victims who underwent chest computed tomography. On absolute x-axis, we designated the x-coordinate of the mid-sternum (x_mid-sternum) as 0 and leftward direction as positive. Re-defining the x-coordinate of Point_max.RV and Point_max.LV as 0 and 1 interventricular unit (IVU), respectively, we could convert x_mid-sternum to "-x_max.RV/(x_max.LV - x_max.RV) (IVU)." Using multiple logistic regression analysis, we investigated whether this converted x_mid-sternum was associated with clinical outcomes, adjusting core elements of the Utstein template. RESULTS: Among 887 non-traumatic OHCA victims, 124 [64.4 ± 16.7 years, 43 women (34.7%)] were enrolled. Of these, 80 (64.5%) exhibited ROSC. X_mid-sternum ranging from -1.71 to 0.58 (-0.36 ± 0.38) IVU was categorised into quintiles: <-0.60, -0.60 to -0.37, -0.37 to -0.22, -0.22 to -0.07 and ≥-0.07 (reference) IVU. The first quintile was positively associated with ROSC (odds ratio [95% confidence interval], 9.43 [1.44, 63.3]). CONCLUSION: Point_optimum might be located far rightwards to Point_max.RV, challenging the traditional assumption identifying Point_optimum as Point_max.LV.

The Maximum Diameter of the Left Ventricle May Not Be the Optimum Target for Chest Compression During Cardiopulmonary Resuscitation: A Preliminary, Observational Study Challenging the Traditional Assumption.

OBJECTIVE: Researchers have assumed that compressing the point beneath which the left ventricle (LV) diameter is maximum (P_max.LV) would improve cardiopulmonary resuscitation outcomes. Defining the midsternum, the currently recommended location for chest compression, as the reference (x = 0), the lateral deviation (x_max.LV) of personalized P_max.LV has become estimable using posteroanterior chest radiography. The authors investigated whether out-of-hospital cardiac arrest (OHCA) patients, whose x_max.LV was closer to the midsternum and thus had their P_max.LV compressed closer during cardiopulmonary resuscitation, showed better chances of return of spontaneous circulation (ROSC) and survival to discharge. DESIGN: Retrospective, cross-sectional study. SETTING: A university hospital. PARTICIPANTS: Adult OHCA patients with available previous posteroanterior chest radiography. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: For each clinical outcome, multivariable logistic regression was performed, grouping x_max.LV into tertiles and adjusting the variables selected among the core elements of the Utstein template showing possible differences (p > 0.10) in univariate analysis. Odds ratios were presented as OR (95% confidence interval). Among 268 cases (age 64.4 ± 15.8 y, female 89 [33.2%]), 123 (45.9%) achieved ROSC and 40 (14.9%) survival to discharge. Compared with the third tertile of x_max.LV (59 to ∼101 mm), the first (31 to ∼48 mm) and second (48 to ∼59 mm) tertiles, which had a P_max.LV closer to the midsternum, were negatively associated with ROSC (OR 0.502 [0.262-0.960]; p = 0.037 and OR 0.442 [0.233-0.837]; p = 0.012, respectively) and survival to discharge (OR 0.286 [0.080-1.03]; p = 0.055 and OR 0.046 [0.007-0.308]; p = 0.002, respectively). CONCLUSIONS: OHCA patients with a P_max.LV located closer to the midsternum showed worse chances of ROSC and survival to discharge, which challenges the traditional assumption of identifying P_max.LV as the optimum compression point.

Determination of the theoretical personalized optimum chest compression point using anteroposterior chest radiography.

OBJECTIVE: There is a traditional assumption that to maximize stroke volume, the point beneath which the left ventricle (LV) is at its maximum diameter (P_max.LV) should be compressed. Thus, we aimed to derive and validate rules to estimate P_max.LV using anteroposterior chest radiography (chest_AP), which is performed for critically ill patients urgently needing determination of their personalized P_max.LV. METHODS: A retrospective, cross-sectional study was performed with non-cardiac arrest adults who underwent chest_AP within 1 hour of computed tomography (derivation:validation=3:2). On chest_AP, we defined cardiac diameter (CD), distance from right cardiac border to midline (RB), and cardiac height (CH) from the carina to the uppermost point of left hemi-diaphragm. Setting point zero (0, 0) at the midpoint of the xiphisternal joint and designating leftward and upward directions as positive on x- and y-axes, we located P_max.LV (x_max.LV, y_max.LV). The coefficients of the following mathematically inferred rules were sought: x_max.LV=α0*CD-RB; y_max.LV=ß0*CH+γ0 (α0: mean of [x_max.LV+RB]/CD; ß0, γ0: representative coefficient and constant of linear regression model, respectively). RESULTS: Among 360 cases (52.0±18.3 years, 102 females), we derived: x_max.LV=0.643*CD-RB and y_max.LV=55-0.390*CH. This estimated P_max.LV (19±11 mm) was as close as the averaged P_max.LV (19±11 mm, P=0.13) and closer than the three equidistant points representing the current guidelines (67±13, 56±10, and 77±17 mm; all P<0.001) to the reference identified on computed tomography. Thus, our findings were validated. CONCLUSION: Personalized P_max.LV can be estimated using chest_AP. Further studies with actual cardiac arrest victims are needed to verify the safety and effectiveness of the rule.

Optimum Chest Compression Point for Cardiopulmonary Resuscitation in Children Revisited Using a 3D Coordinate System Imposed on CT: A Retrospective, Cross-Sectional Study.

OBJECTIVES: The optimum chest compression site (P_optimum) in children is debated: European Resuscitation Council recommends one finger breadth above the xiphisternal joint, whereas American Heart Association proposes the lower sternal half. Using a coordinate system imposed on CT, we aimed to determine the pediatric P_optimum to maximize stroke volume, the key point for successful cardiopulmonary resuscitation, while minimizing hepatic injury. DESIGN: Retrospective, cross-sectional study. SETTING: University hospital. PATIENTS: Children 1-15 years old who underwent chest CT. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We defined zero point (0, 0) as the center of the xiphisternal joint designating leftward and upward directions of the patients as positive on each axis. P_optimum (x_max. left ventricle, y_max. left ventricle) was defined as the center of the maximum diameter of the left ventricle, whereas P_aorta (x_aorta, y_aorta) as that of the aortic annulus. To compress the left ventricle exclusively, y_max. left ventricle should range above the y coordinate of hepatic dome (y_liver_dome) and below y_aorta. Data were presented as median (interquartile range) and compared among age groups 1.0-5.0, 5.1-10.0, and 10.1-15.0 years using Kruskal-Wallis test. For universal application regardless of age, y coordinates were converted into relative ones with unit of sternal top: 1 unit of sternal top was the y coordinate of the sternal top. A total of 163 patients were enrolled, median age 8.8 year (4.2-14.3 yr). Among age groups, no significant difference was observed in y_max. left ventricle, relative y_max. left ventricle, y_aorta, and y_liver_dome: 1.0 cm (0.1-1.9 cm), 0.10 unit of sternal top (0.01-0.18 unit of sternal top), 0.39 unit of sternal top (0.30-0.47 unit of sternal top), and -0.14 unit of sternal top (-0.25 to -0.03 unit of sternal top), respectively. The probability to compress the left ventricle exclusively was greater than or equal to 96% when placing hand at 0.05-0.20 unit of sternal top. Subgroup analysis demonstrated the following regression equation: x_max. left ventricle (mm) = 0.173 × (height in cm) + 13 (n = 106; p < 0.001; R = 0.278). CONCLUSIONS: Theoretically, pediatric P_optimum is located 1 cm (or 0.1 unit of sternal top) above the xiphisternal joint.

Theoretical personalized optimum chest compression point can be determined using posteroanterior chest radiography.

AIM: Cardiopulmonary resuscitation guidelines suggest the lower sternal half be compressed. However, stroke volume has been assumed to be maximized by compressing the 'point' (P_max.LV) beneath which the left ventricle (LV) is at its maximum diameter. Identifying 'personalized' P_max.LV on computed tomography (CT), we derived and validated rules to estimate P_max.LV using posteroanterior chest radiography (chest_PA). METHODS: A retrospective, cross-sectional study was performed with non-cardiac arrest (CA) adults who underwent chest_PA and CT within 1h (derivation:validation = 3:2). On chest_PA, we defined CD (cardiac diameter), RB (distance from right cardiac border to midline) and CH (cardiac height, from carina to uppermost point of left hemi-diaphragm). Setting P_zero (0, 0) at the midpoint of xiphisternal joint and designating leftward and upward directions as positive on x and y axes, we located P_max.LV (x_max.LV, y_max.LV). Mathematically, followings were inferable: x_max.LV = α0*CD-RB; y_max.LV = ß0*CH + γ0. (α0: mean of (x_max.LV + RB)/CD; ß0, γ0: representative coefficient and constant of linear regression model, respectively). We investigated their feasibility by applying them to in-hospital (IHCA) and out-of-hospital CA (OHCA) adults. RESULTS: Among 266 (57.6 ±â€¯16.4 years, 120 females), followings were derived: x_max.LV = 0.664*CD-RB; y_max.LV = 40 - 0.356*CH. Estimated P_max.LV was closer to the reference than other candidates and thus validated: 15 ±â€¯9 vs 17 ±â€¯10 (averaged P_max.LV, p = 0.025); 76 ±â€¯13, 54 ±â€¯11 and 63 ±â€¯13 mm (3 equidistant points as per guidelines, all p < 0.001). Among IHCA and OHCA patients, 70.7% (106/150) and 38.0% (57/150) had previous chest_PA with measurable parameters to estimate P_max.LV. CONCLUSION: Personalized P_max.LV, which is potentially superior to the lower sternal half and feasible in CA, is estimable with chest_PA.

A Fortified Method to Screen and Detect Left Ventricular Hypertrophy in Asymptomatic Hypertensive Adults: A Korean Retrospective, Cross-Sectional Study.

PURPOSE: Left ventricular (LV) mass is determined by the wall thickness and diameter. LV hypertrophy (LVH), the increase in LV mass, is usually screened with electrocardiography but is often insensitive. We tried to fortify the rule to detect LVH using cardiothoracic ratio (CTR) in chest X-ray and well-known risk factors besides electrocardiography. MATERIALS AND METHODS: This retrospective cross-sectional study included asymptomatic hypertensive individuals aged ≥40 y who underwent voluntary checkups including echocardiography. Independent variables to explain LVH (LV mass index>115 g/m2 for men and >95 g/m2 for women calculated on echocardiography) were chosen among Sokolow-Lyon voltage amplitude (SLVA), CTR and cardiovascular risk factors by multiple logistic regression analysis. The diagnostic rule to detect LVH was made by summing up the rounded-off odds ratio of each independent variable and was validated using bootstrapping method. RESULTS: Among the 789 cases enrolled (202 females (25.6%), mean age 59.6±8.8 y), 168 (21.3%) had LVH. The diagnostic rule summed female, age≥65 y, BMI≥25 kg/m2, SLVA≥35 mm, and CTR≥0.50 (scoring 1 per each). Its c-statistics was 0.700 (95% CI: 0.653, 0.747), significantly higher (p<0.001) than that of SLVA≥35 mm, 0.522 (95% CI: 0.472, 0.572). The sensitivity and specificity of the model were 61.9% and 72.1% for score≥2 and 30.4% and 92.9% for score≥3. The SLVA≥35 mm criteria showed sensitivity of 12.5% and specificity of 91.9%. CONCLUSIONS: The rule to sum up the number of the risk factors of female, age≥65 y, BMI≥25 kg/m2, SLVA≥35 mm, and CTR≥0.50 may be a better diagnostic tool for screening LVH, than the electrocardiography-only criteria, at the score≥2.

The optimum chest compression site with regard to heart failure demonstrated by computed tomography.

BACKGROUND: To determine the optimum chest compression site during cardiopulmonary resuscitation (CPR) with regard to heart failure (HF) by applying three-dimensional (3D) coordinates on computed tomography (CT). METHODS: This retrospective, cross-sectional study involved adults who underwent echocardiography and CT on the same day from 2007 to 2017. Incomplete CT images or information on HF, cardiac medication between echocardiography and CT, or thoracic abnormalities were excluded. Cases were checked whether they had HF through symptom/sign assessment, N-terminal pro-B type natriuretic peptide, and echocardiography. We set the xiphisternal joint's midpoint as the reference (0, 0, 0) to draw a 3D coordinate system, designating leftward, upward, and into-the-thorax directions as positive. The coordinate of the maximum LV diameter's midpoint (P_max.LV) was identified. RESULTS: Enrolled were 148 patients (63.0±15.1 years) with 87 females and 76 HF cases. P_max.LV of HF cases was located more leftwards, lower, and deeper than non-HF cases (5.69±0.98, -1.51±1.67, 5.76±1.09 cm vs. 5.00±0.83, -0.99±1.36, 5.25±0.71 cm, all p<0.05). Fewer HF cases had their LV compressed than non-HF cases (59.2% vs. 77.8%, p=0.025) when being compressed according to the current guidelines. The aorta (vs. LV) was compressed in 85.5% and 81.9% of HF and non-HF cases, respectively, at 3 cm above the xiphisternal joint. At 6cm above the joint, the highest allowable position according to the current guidelines, all victims would have their aorta compressed directly during CPR rather than the LV. CONCLUSIONS: The lowest possible sternum just above the xiphisternal joint should be compressed especially for HF patients during CPR.

Calculation of the Residual Blood Volume after Acute, Non-Ongoing Hemorrhage Using Serial Hematocrit Measurements and the Volume of Isotonic Fluid Infused: Theoretical Hypothesis Generating Study.

Fluid resuscitation, hemostasis, and transfusion is essential in care of hemorrhagic shock. Although estimation of the residual blood volume is crucial, the standard measuring methods are impractical or unsafe. Vital signs, central venous or pulmonary artery pressures are inaccurate. We hypothesized that the residual blood volume for acute, non-ongoing hemorrhage was calculable using serial hematocrit measurements and the volume of isotonic solution infused. Blood volume is the sum of volumes of red blood cells and plasma. For acute, non-ongoing hemorrhage, red blood cell volume would not change. A certain portion of the isotonic fluid would increase plasma volume. Mathematically, we suggest that the residual blood volume after acute, non-ongoing hemorrhage might be calculated as 0·25N/[(Hct1/Hct2)-1], where Hct1 and Hct2 are the initial and subsequent hematocrits, respectively, and N is the volume of isotonic solution infused. In vivo validation and modification is needed before clinical application of this model.

Etiologies of acute undifferentiated fever and clinical prediction of scrub typhus in a non-tropical endemic area.

Scrub typhus usually presents as acute undifferentiated fever. This cross-sectional study included adult patients presenting with acute undifferentiated fever defined as any febrile illness for ≤ 14 days without evidence of localized infection. Scrub typhus cases were defined by an antibody titer of a ≥ fourfold increase in paired sera, a ≥ 1:160 in a single serum using indirect immunofluorescence assay, or a positive result of the immunochromatographic test. Multiple regression analysis identified predictors associated with scrub typhus to develop a prediction rule. Of 250 cases with known etiology of acute undifferentiated fever, influenza (28.0%), hepatitis A (25.2%), and scrub typhus (16.4%) were major causes. A prediction rule for identifying suspected cases of scrub typhus consisted of age ≥ 65 years (two points), recent fieldwork/outdoor activities (one point), onset of illness during an outbreak period (two points), myalgia (one point), and eschar (two points). The c statistic was 0.977 (95% confidence interval = 0.960-0.994). At a cutoff value ≥ 4, the sensitivity and specificity were 92.7% (79.0-98.1%) and 90.9% (86.0-94.3%), respectively. Scrub typhus, the third leading cause of acute undifferentiated fever in our region, can be identified early using the prediction rule.

Severe hyperkalemia can be detected immediately by quantitative electrocardiography and clinical history in patients with symptomatic or extreme bradycardia: a retrospective cross-sectional study.

PURPOSE: Detecting severe hyperkalemia is challenging. We explored its prevalence in symptomatic or extreme bradycardia and devised a diagnostic rule. MATERIALS AND METHODS: This retrospective cross-sectional study included patients with symptomatic (heart rate [HR] ≤ 50/min with dyspnea, chest pain, altered mentality, dizziness/syncope/presyncope, general weakness, oliguria, or shock) or extreme (HR ≤ 40/min) bradycardia at an emergency department for 46 months. Risk factors for severe hyperkalemia were chosen by multiple logistic regression analysis from history (sex, age, comorbidities, and medications), vital signs, and electrocardiography (ECG; maximum precordial T-wave amplitude, PR, and QRS intervals). The derived diagnostic index was validated using bootstrapping method. RESULTS: Among the 169 participants enrolled, 87 (51.5%) were female. The mean (SD) age was 71.2 (12.5) years. Thirty-six (21.3%) had severe hyperkalemia. The diagnostic summed "maximum precordial T ≥ 8.5 mV (2)," "atrial fibrillation/junctional bradycardia (1)," "HR ≤ 42/min (1)," "diltiazem medication (2)," and "diabetes mellitus (1)." The C-statistics were 0.86 (0.80-0.93) and were validated. For scores of 4 or higher, sensitivity was 0.50, specificity was 0.92, and positive likelihood ratio was 6.02. The "ECG-only index," which sums the 3 ECG findings, had a sensitivity of 0.50, specificity of 0.90, and likelihood ratio (+) of 5.10 for scores of 3 or higher. CONCLUSIONS: Severe hyperkalemia is prevalent in symptomatic or extreme bradycardia and detectable by quantitative electrocardiographic parameters and history.

Juvenile first rib fracture caused by morning stretching.

BACKGROUND: First rib fractures are very rare, being primarily associated with external blunt trauma. Related conditions, such as sudden contraction of the neck muscle, stress fractures, and fatigue fractures, have been reported sporadically. These fractures are mostly related to repetitive or explosive physical training. However, anatomical relationships and related injury mechanisms may cause first rib fractures without repetitive sports activity. OBJECTIVE: To present a case of juvenile first rib fracture caused by morning stretching without sports activity. CASE  REPORT: We present a rare case report of juvenile atraumatic first rib fracture. CONCLUSION: Physicians should be aware that even morning stretching with yawning can cause a first rib fracture in children. Awareness is important for early recognition, and proper management is critical for a pain-free return to normal life. An understanding of the mechanism of atraumatic first rib fracture is important.

Calculation of the cardiothoracic ratio from portable anteroposterior chest radiography.

Cardiothoracic ratio (CTR), the ratio of cardiac diameter (CD) to thoracic diameter (TD), is a useful screening method to detect cardiomegaly, but is reliable only on posteroanterior chest radiography (chest PA). We performed this cross-sectional 3-phase study to establish reliable CTR from anteroposterior chest radiography (chest AP). First, CD(Chest PA)/CD(Chest AP) ratios were determined at different radiation distances by manipulating chest computed tomography to simulate chest PA and AP. CD(Chest PA) was inferred from multiplying CD(Chest AP) by this ratio. Incorporating this CD and substituting the most recent TD(Chest PA), we calculated the 'corrected' CTR and compared it with the conventional one in patients who took both the chest radiographies. Finally, its validity was investigated among the critically ill patients who performed portable chest AP. CD(Chest PA)/CD(Chest AP) ratio was {0.00099 × (radiation distance [cm])} + 0.79 (n = 61, r = 1.00, P < 0.001). The corrected CTR was highly correlated with the conventional one (n = 34, difference: 0.00016 ± 0.029; r = 0.92, P < 0.001). It was higher in congestive than non-congestive patients (0.53 ± 0.085; n = 38 vs 0.49 ± 0.061; n = 46, P = 0.006). Its sensitivity and specificity was 61% and 54%. In summary, reliable CTR can be calculated from chest AP with an available previous chest PA. This might help physicians detect congestive cardiomegaly for patients undergoing portable chest AP.