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Applications of Health Data
Published in Disa Lee Choun, Anca Petre, Digital Health and Patient Data, 2023
Aside from using IoT devices, with patients’ health data, the doctors’ data-centric approach for treating patients with no or minimal margin for error involves observing their lifestyle and bringing changes to their health, like patients who are suffering from high blood pressure, asthma, etc. This is a way of personalizing what’s important for the individual. Using a platform that collects and organizes data from laboratory reports, clinical notes, radiology scans, and pathology images helps physicians make more personalized and informed treatment plans.
All Probabilities Are Conditional
Published in Mitchell G. Maltenfort, Camilo Restrepo, Antonia F. Chen, Statistical Reasoning for Surgeons, 2020
Mitchell G. Maltenfort, Camilo Restrepo, Antonia F. Chen
Keep in mind that these sensitivities and specificities calculated in the study are statistical estimates and as such have some margin of error. The standard error for a proportion p estimated from a sample N is sqrt(p*(1 − p)/N), and the 95% confidence interval for the estimate is p ± 1.96 times the standard error. If your study includes 100 patients with the condition (TP + FN) and your observed sensitivity is 0.9 (TP = 90 patients), then the standard error is sqrt (0.9 * 0.1/100) = 0.03, and your confidence interval is 0.84–0.96.
Human Skeletal Remains
Published in Cristoforo Pomara, Vittorio Fineschi, Forensic and Clinical Forensic Autopsy, 2020
Francesco Sessa, Dario Piombino-Mascali, Nicholas Márquez-Grant, Luigi Cipolloni, Cristoforo Pomara
The fact that long bones stand in a linear relation to the overall body length is used to estimate height. There are numerous formulas based on the mathematical model of linear regression, which, by determining primarily the length of intact or fragmented long bones, permits height to be calculated (Duyar and Pelin, 2003; Duyar et al., 2006). It is widely known that formulas of this kind tend to be highly population- and sex-specific. Considering that this kind of evaluation is an estimation, it is correct to give the margin of error or a statistical confidence interval. Another important consideration is that when stature is estimated from a bone, an allowance of 2.5 to 4 cm is added to the calculated stature in order to compensate for the loss of soft tissues (Garmendia et al., 2014; Nath and Badkur, 2017). Different formulae are used to estimate stature, whether from complete bones or fragmentary bones, but the most employed today are those of Trotter and Gleser (1977), although there are a number of other equations (e.g., see Márquez-Grant et al. 2016).
Test–retest reliability of the L-Test in patients with advanced knee osteoarthritis
Published in Physiotherapy Theory and Practice, 2022
Abdurrahman Nalbant, Bayram Unver, Vasfi Karatosun
The reliable and valid measurement of outcome measures is crucial in both research and clinical practice (Dobson et al., 2017). Reliability provides information about how consistent and repeatable the measurements are. It is an essential feature of a meaningful measurement (Gadotti, Vieira, and Magee, 2006). It can be defined as the consistency of a measurement tool. The margin of error that can always be seen in continuous measurements is in accordance with the accepted measurement error. It is important for the effective and practical use of the measuring tool. Reliability should be tested for first in a new measurement tool since it will never be valid if it is not adequately consistent with whatever value it indicates from repeated measurements (Atkinson and Nevill, 1998). There are different types of reliability like test–retest, intra-rater, and inter-rater.
Does lack of brain injury mean lack of cognitive impairment in traumatic spinal cord injury?
Published in The Journal of Spinal Cord Medicine, 2022
Eyal Heled, Keren Tal, Gabi Zeilig
The current conclusions should be considered in light of the study’s limitations. First, the small sample size reduces the power of the study results and increases the margin for error. Second, the SCI group was diverse in terms of time post injury, and while no relationship was found between this variable and the cognitive abilities examined, a more homogenous sample would have methodological advantages. This is also applicable to the wide age range (18–50) of the participants, as cognition is often affected by age. Third, most of the participants in the study were males, making it difficult to generalize results to the entire tSCI population. Finally, other variables that could account for between-group differences were not measured, including medications and comorbidities such as pain or fatigue. Thus, conclusions should be taken cautiously.
Comparison of ventricular repolarization parameters of Covid-19 patients diagnosed with chest CT and RT-PCR
Published in Acta Cardiologica, 2021
Ersin Ibisoglu, Bedrettin Boyraz
QT max (401.29 ± 44.05 ms vs. 375.72 ± 40.32 ms. p < 0.001), QT min (361.38 ± 39.24 ms vs. 346.34 ± 38.88 ms. p = 0.007), JT (287.13 ± 41.75 ms vs. 273.13 ± 39. 63 ms. p = 0.002), cQTd (45.17 ± 23.37 ms vs. 34.92 ± 12.14 ms. p = 0.002), Tp-e (84.00 ± 14.98 ms vs. 73.06 ± 14.49 ms. p < 0.001). Tp-e/QT max (0.210 ± 0.038 vs. 0.195 ± 0.036. p = 0.002). Tp-e/QTc max (0.184 ± 0.032 vs. 0.164 ± 0.033. p < 0.001). Tp-e/JT (0.296 ± 0.056 vs. 0.271 ± 0.057. p = 0.002), Tp- e/JTc (0.259 ± 0.048 vs. 0.227 ± 0.049. p < 0.001) values were much more higher in positive RT-PCR Covid-19 patients. There was no statistical significant difference in both group regarding QRS (92.39 ± 13.85 ms vs. 93.51 ± 13.91 ms. p = 0.41), QTc max (456. 16 ± 41.57 ms vs. 446.51 ± 34.65 ms. p = 0.074), QTc min (410.99 ± 38.73 ms vs. 411.59 ± 33.98 ms. p = 0.90) (QTc >440 ms for men and >460 ms for women or >500 ms), JTc (327.21 ± 40.60 ms vs. 324.14 ± 36.53 ms. p = 0.81). Heart rates (79.07 ± 14.11 bpm vs. 86.79 ± 16.63 bpm. p = 0.01) was much more different in the control group (Table 3). Interobserver variability rate between cardiologists for JT, QT and Tp-e measurements were relatively similar at 2.5, 3.4, and 4.3%. Both cardiologist creating the survey for both groups (patients being taking part of the study and control group) ended with the same margin of error.