The sensitivity, specificity, PPV, and NPV were numerically at least as high as those obtained from CHOP-ROP (Children’s Hospital of Philadelphia–ROP), OMA-ROP (Omaha-ROP), WINROP (weight, insulinlike growth factor 1, neonatal, ROP), and CO-ROP (Colorado-ROP), models requiring more complex postnatal data. Validations of DIGIROP-Birth for 24 to 30 weeks’ GA showed high predictive ability for the model overall (AUC, 0.90 for internal validation, 0.94 for temporal validation, 0.87 for US external validation, and 0.90 for European external validation) by calendar periods and by race/ethnicity. Irrespective of GA, the risk for receiving ROP treatment increased during postnatal weeks 8 through 12 and decreased thereafter. The measures were estimated momentary and cumulative risks, hazard ratios with 95% CIs, area under the receiver operating characteristic curve (hereinafter referred to as AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).Īmong 7609 infants (54.6% boys mean GA, 28.1 weeks mean birth weight, 1119 g), 442 (5.8%) were treated for ROP, including 142 (40.1%) treated of 354 born at less than 24 gestational weeks. The model was validated internally and externally (in US and European cohorts) and compared with 4 published prediction models. In this retrospective cohort study, Swedish National Patient Registry data from infants screened for ROP (born between January 1, 2007, and August 7, 2018) were analyzed with Poisson regression for time-varying data (postnatal age, gestational age, sex, birth weight, and important interactions) to develop an individualized predictive model for ROP treatment (called DIGIROP-Birth ). To create and validate an easy-to-use prediction model using only birth characteristics and to describe a continuous hazard function for ROP treatment. Early individual risk stratification would improve screening timing and efficiency and potentially reduce the risk of blindness. To prevent blindness, repeated infant eye examinations are performed to detect severe retinopathy of prematurity (ROP), yet only a small fraction of those screened need treatment. Further external validation of this protocol would be required. We propose a possible algorithm (TWO-ROP) in appropriate NICUs, with an amendment in screening protocol for this low-risk population to include only an outpatient screening exam within 1 week of discharge, or at 40 weeks if inpatient, to decrease the inpatient ROP screening burden while maintaining safety. Patients meeting one screening criterion had a low rate of ROP (<5%), with no stage 3, zone 1, or plus disease. No cases of stage 3, zone 1 or plus disease were recorded. Mean interval between birth and ROP diagnosis was 36.25 days (range 12 - 75) in group 1, 47 days in group 2 and 23.33 days (range 10 - 39) in group 3 (P =. The number of patients diagnosed with ROP was 20 (4.29%) in group 1, 1 (4.35%) in group 2, and 12 (1.07%) in group 3, P <. Out of 7,520 patients with reported BW and GA, 1,612 (21.4%) patients met the inclusion criteria. Rates of ROP and treatment-warranted ROP were evaluated in group 1 (BW < 1500g and GA ≥ 30weeks), group 2 (BW ≥ 1500g and GA < 30 weeks), and group 3 (BW ≥ 1500g and GA ≥ 30weeks). Single-center study of 9,350 infants screened for ROP from 2009-2019. fPercent * 10000.To assess the rates of retinopathy of prematurity (ROP) and treatment-warranted ROP in a modern set of patients meeting zero or one of the current ROP screening criteria. iCount is not used anywhere in the funcion or any game file (searched with Find in Files function), so ymir maybe changed his mind about that part of common_drop_item.Ībout the drop chance, i found this on the same funcion:ĭWORD dwPct = (DWORD) (d.fPercent * 10000.0f) Ībout the drop chance, i found this on the same funcion: DWORD dwPct = (DWORD) (d.fPercent * 10000.0f) Ĭorrect "DWORD dwPct = (DWORD) (d. Sys_log(1, "CommonItemDrop %d %d %d %u", c.m_iLevelStart, c.m_iLevelEnd, c.m_iPercent, c.m_dwVnum) Sys_err("Cannot open %s", c_pszFileName) įor (int i = 0 i & v = g_vec_pkCommonDropItem This is from server funcion ITEM_MANAGER::ReadCommonDropItemFile.īool ITEM_MANAGER::ReadCommonDropItemFile(const char * c_pszFileName) Case 1: str_to_number(d.iLvStart, szTemp) break Ĭase 2: str_to_number(d.iLvEnd, szTemp) break Ĭase 3: d.fPercent = atof(szTemp) break Ĭase 4: strlcpy(d.szItemName, szTemp, sizeof(d.szItemName)) break Ĭase 5: str_to_number(d.iCount, szTemp) break
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