No abstract available.
Spine* ; Spondylitis, Ankylosing*

A novel bacteriophage, designated as VPP97, that infects the strains of Vibiro parahaemolyticus (hallophilic, Gram-negative bacterium) isolated most commonly from marine environments, has been discovered, and several of its properties have been determined. The plaques were clear and sized 0.6-1.0 mm in diameter. The virion forms a single band on 70% sucrose gradient and p1.50 CsC1 gradient by sucrose gradient centrifugation and CsCI gradient centrifugation respectively. It has a hexagonal head and a relatively long tail, as shown by electron microscopy. Vibrio alginolyticus, Vibrio fluvialis and Vibrio furnissii were also sensitive to this phage It was almost totally inactivated at 70 degree C and at pH below 5 or over 10. The nucleic acid of VPP97 is composed of DNA. The VPP97 had 9 specific structural proteins sized between 21.5 kDa and 97.4 kDa on SDS-PAGE. When V. parahaemolyticus cultures were treated with either phage VPP97 or one of the several antibiotics for 2 hours, the viable number of V. parahaemolyticus treated with the phage VPP97 is lower than that treated with chloramphenicol, erythromycin or penicillin, but not lower than that treated with tetracycline. Mice that have responded to the phage treatment revealed the lower numbers of V. parahaemolyticus in small intestine and less damage on small intestine compared to the untreated mice. Therefore, we suggest that the phage treatment appears effective to the infection by V. parahaemolyticus.
Animals ; Anti-Bacterial Agents ; Bacteriophages* ; Centrifugation ; Chloramphenicol ; DNA ; Electrophoresis, Polyacrylamide Gel ; Erythromycin ; Head ; Hydrogen-Ion Concentration ; Intestine, Small ; Mice ; Microscopy, Electron ; Penicillins ; Sucrose ; Tail ; Tetracycline ; Vibrio alginolyticus ; Vibrio parahaemolyticus* ; Vibrio* ; Virion

BACKGROUND: Although a history of febrile convulsion (FC) is common in epilepsy patients, the preferential associa-tion of febrile convulsion with temporal lobe epilepsy (TLE) is not clear. METHODS:We obtained the FC data from "Paik and Bongsang hospital" epilepsy clinic. We classified epilepsy syndromes into generalized epilepsy (GE), temporal lobe epilepsy (TLE), extratemporal epilepsy (ETLE), unclassified partial and undetermined epilepsy by standardized criteria. The incidence of antecedent FC was evaluated in relation to the epilepsy classifications. We calculated kappa values for inter and intra observer reliability for the classifications of epilepsy syndromes. RESULTS: The agreement of epilepsy classifications were reliable (intra-observer kappa value=0.78, inter-observer kappa value=0.77). Thirteen percent of the studied patients (72/537) had a history of FC and 38% of FC (27/72) were complex types of FC. TLE was more likely to be preceded by FC 25% (42/166) than ETLE 6% (12/189), p<0.05 or GE 13% (12/93), p<0.05 and 85% of complex FC (23/27) preceded TLE. GE however, was more likely to have non-complex FC 100% (12/12) than partial epilepsy 55% (32/58), p<0.05. CONCLUSIONS We therefore conclude and agree that FC should be preferentially associated with TLE.
Classification ; Epilepsies, Partial ; Epilepsy ; Epilepsy, Generalized ; Epilepsy, Temporal Lobe* ; Humans ; Incidence ; Seizures, Febrile* ; Temporal Lobe*

OBJECTIVE: Panic disorder has been suggested to be divided into the respiratory and non-respiratory subtypes in terms of its clinical presentations. The present study aimed to investigate whether there are any differences in treatment response and clinical characteristics between the respiratory and non-respiratory subtypes of panic disorder patients. METHODS: Among the 48 patients those who completed the study, 25 panic disorder patients were classified as the respiratory subtype, whereas 23 panic disorder patients were classified as the non-respiratory subtype. All patients were treated with escitalopram or paroxetine for 12 weeks. We measured clinical and psychological characteristics before and after pharmacotherapy using the Panic Disorder Severity Scale (PDSS), Albany Panic and Phobic Questionnaire (APPQ), Anxiety Sensitivity Index-Revised (ASI-R), State-Trait Anxiety Inventory (STAI-T, STAI-S), Hamilton Anxiety Rating Scale (HAM-A), and Hamilton Depression Rating Scale (HAM-D). RESULTS: The prevalence of the agoraphobia was significantly higher in the respiratory group than the non-respiratory group although there were no differences in gender and medication between the two groups. The respiratory group showed higher scores on the fear of respiratory symptoms of the ASI-R. In addition, after pharmacotherapy, the respiratory group showed more improvement in panic symptoms than the non-respiratory group. CONCLUSION: Panic disorder patients with the respiratory subtype showed more severe clinical presentations, but a greater treatment response to SSRIs than those with non-respiratory subtype. Thus, classification of panic disorder patients as respiratory and non-respiratory subtypes may be useful to predict clinical course and treatment response to SSRIs.
Agoraphobia ; Anxiety ; Citalopram ; Classification ; Depression ; Drug Therapy ; Humans ; Panic ; Panic Disorder* ; Paroxetine ; Prevalence ; Surveys and Questionnaires ; Serotonin Uptake Inhibitors ; Treatment Outcome

Grisel’s syndrome is a non-traumatic atlantoaxial rotatory subluxation for which the underlying mechanism has not yet been identified. It is known to occur following upper respiratory infections, tonsillitis, ear, nose, and throat (ENT) surgeries such as tonsillectomy and adenoidectomy. The diagnosis of Grisel’s syndrome can be made by plain x-ray, CT scanning, and/or MRI scanning. The first choice of treatment is conservative therapy such as bed rest, muscle relaxation, analgesic therapy, antibiotics, and simple traction. While Grisel’s syndrome occurs rarely, delayed treatment may lead to neurological complications or requires surgical treatment. Early diagnosis and treatment are important in preventing fatal outcome. We report the case of a 9-year-old male who developed Grisel’s syndrome after tonsillectomy and adenoidectomy.

Background: The effects of anesthetic techniques on postdural puncture backache (PDPB) have not been specifically evaluated. The purpose of this study was to compare the incidence and severity of PDPB between median and paramedian techniques. Methods: Patients were randomized to receive spinal anesthesia by either a median (Group M, n = 50) or paramedian (Group P, n = 50) approach.We recorded each patient’s personal number of puncture attempts, surgical position, and operation duration. We investigated the incidence and intensity of back pain 1 day, 1 week, and 1, 2, and 3 months postoperatively. Results: The overall incidence of PDPB was higher in the Group M (18/50, 36%) than in the Group P (8/50, 16%) (P =0.023). Twenty-four hours after surgery, 8 patients in Group M and 6 patients in Group P complained of back pain, and the average numeric rating scale (NRS) pain scores showed no evidence of differences. Seven days after the surgery, 16 patients in the Group M and 5 patients in the Group P complained of pain (P = 0.007); their NRS scores did not significantly differ. After 1 month, 5 patients in the Group M and 1 patient in the Group P complained of pain. Only one patient in each group complained of pain after 3 months. Conclusions The results of this study suggest that spinal anesthesia using the paramedian approach reduces the incidence of PDPB during the early postoperative period.

Background: The effects of anesthetic techniques on postdural puncture backache (PDPB) have not been specifically evaluated. The purpose of this study was to compare the incidence and severity of PDPB between median and paramedian techniques. Methods: Patients were randomized to receive spinal anesthesia by either a median (Group M, n = 50) or paramedian (Group P, n = 50) approach.We recorded each patient’s personal number of puncture attempts, surgical position, and operation duration. We investigated the incidence and intensity of back pain 1 day, 1 week, and 1, 2, and 3 months postoperatively. Results: The overall incidence of PDPB was higher in the Group M (18/50, 36%) than in the Group P (8/50, 16%) (P =0.023). Twenty-four hours after surgery, 8 patients in Group M and 6 patients in Group P complained of back pain, and the average numeric rating scale (NRS) pain scores showed no evidence of differences. Seven days after the surgery, 16 patients in the Group M and 5 patients in the Group P complained of pain (P = 0.007); their NRS scores did not significantly differ. After 1 month, 5 patients in the Group M and 1 patient in the Group P complained of pain. Only one patient in each group complained of pain after 3 months. Conclusions The results of this study suggest that spinal anesthesia using the paramedian approach reduces the incidence of PDPB during the early postoperative period.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.

Background: Despite the considerable disease burden due to trauma injury, sufficient effort has not been made for the assessment of nationwide trauma care status in Korea. We explored the feasibility of a diagnosis code-based injury severity measuring method in light of its realworld usage. Methods: We used datasets from the National Emergency Department Information System to calculate the survival risk ratios (SRRs) and the Korean Trauma Data Bank to predict models, respectively. The target cohort was split into training and validation datasets using stratified random sampling in an 8:2 ratio. We established six major mortality prediction models depending on the included parameters: 1) the Trauma and Injury Severity Score (TRISS) (age, sex, original Revised Trauma Score [RTS], Injury Severity Score [ISS]), 2) extended International Classification of Diseases-based Injury Severity Score (ICISS) 1 (age, sex, original RTS, ICISS using international SRRs), 3) extended ICISS 2 (age, sex, original RTS, ICISS using Korean SRRs based on 4-digit diagnosis codes), 4) extended ICISS 3 (age, sex, original RTS, ICISS using Korean SRRs based on full-digit diagnosis codes), 5) extended ICISS 4 (age, sex, modified RTS, and ICISS using Korean SRRs based on 4-digit diagnosis codes), 6) extended ICISS 5 (age, sex, modified RTS, and ICISS using Korean SRRs based on full-digit diagnosis codes). We estimated the model using training datasets and fitted it to the validation datasets. We measured the area under the receiver operating characteristic curve (AUC) for discriminative ability. Overall performance was also evaluated using the Brier score. Results: We observed the feasibility of the extended ICISS models, though their performance was slightly lower than the TRISS model (training cohort, AUC 0.936–0.938 vs. 0.949).Regarding SRR calculation methods, we did not find statistically significant differences.The alternative use of the Alert, Voice, Pain, Unresponsive Scale instead of the Glasgow Coma Scale in the RTS calculation did not degrade model performance. Conclusion The availability of the practical ICISS model was observed based on the model performance. We expect our ICISS model to contribute to strengthening the Korean Trauma Care System by utilizing mortality prediction and severity classification.